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Diffstat (limited to 'latest/_deserializer_8cpp_source.html')
| -rw-r--r-- | latest/_deserializer_8cpp_source.html | 7316 |
1 files changed, 3690 insertions, 3626 deletions
diff --git a/latest/_deserializer_8cpp_source.html b/latest/_deserializer_8cpp_source.html index 0f173b462d..f449f2ee4f 100644 --- a/latest/_deserializer_8cpp_source.html +++ b/latest/_deserializer_8cpp_source.html @@ -36,7 +36,7 @@ <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 15rem; margin-top: .5rem; margin-left 13px"/> <td id="projectalign" style="padding-left: 0.9em;"> <div id="projectname"> -  <span id="projectnumber">24.02</span> +  <span id="projectnumber">24.05</span> </div> </td> </tr> @@ -97,7 +97,7 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i </div><!--header--> <div class="contents"> <a href="_deserializer_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div> -<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017,2019-2023 Arm Ltd and Contributors. All rights reserved.</span></div> +<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017,2019-2024 Arm Ltd and Contributors. All rights reserved.</span></div> <div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div> <div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div> <div class="line"><a name="l00005"></a><span class="lineno"> 5</span>  </div> @@ -363,1594 +363,1594 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  m_ParserFunctions[Layer_ResizeLayer] = &DeserializerImpl::ParseResize;</div> <div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  m_ParserFunctions[Layer_ReverseV2Layer] = &DeserializerImpl::ParseReverseV2;</div> <div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  m_ParserFunctions[Layer_RsqrtLayer] = &DeserializerImpl::ParseRsqrt;</div> -<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  m_ParserFunctions[Layer_ShapeLayer] = &DeserializerImpl::ParseShape;</div> -<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  m_ParserFunctions[Layer_SliceLayer] = &DeserializerImpl::ParseSlice;</div> -<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  m_ParserFunctions[Layer_SoftmaxLayer] = &DeserializerImpl::ParseSoftmax;</div> -<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  m_ParserFunctions[Layer_SpaceToBatchNdLayer] = &DeserializerImpl::ParseSpaceToBatchNd;</div> -<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  m_ParserFunctions[Layer_SpaceToDepthLayer] = &DeserializerImpl::ParseSpaceToDepth;</div> -<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  m_ParserFunctions[Layer_SplitterLayer] = &DeserializerImpl::ParseSplitter;</div> -<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  m_ParserFunctions[Layer_StackLayer] = &DeserializerImpl::ParseStack;</div> -<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  m_ParserFunctions[Layer_StandInLayer] = &DeserializerImpl::ParseStandIn;</div> -<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  m_ParserFunctions[Layer_StridedSliceLayer] = &DeserializerImpl::ParseStridedSlice;</div> -<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  m_ParserFunctions[Layer_SubtractionLayer] = &DeserializerImpl::ParseSubtraction;</div> -<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  m_ParserFunctions[Layer_SwitchLayer] = &DeserializerImpl::ParseSwitch;</div> -<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  m_ParserFunctions[Layer_TileLayer] = &DeserializerImpl::ParseTile;</div> -<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  m_ParserFunctions[Layer_TransposeConvolution2dLayer] = &DeserializerImpl::ParseTransposeConvolution2d;</div> -<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  m_ParserFunctions[Layer_TransposeLayer] = &DeserializerImpl::ParseTranspose;</div> -<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  m_ParserFunctions[Layer_UnidirectionalSequenceLstmLayer] = &DeserializerImpl::ParseUnidirectionalSequenceLstm;</div> -<div class="line"><a name="l00283"></a><span class="lineno"> 283</span> }</div> -<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  </div> -<div class="line"><a name="l00285"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ab3dff510bec873d3e4ffe5cdfa71f1cd"> 285</a></span> <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ab3dff510bec873d3e4ffe5cdfa71f1cd">IDeserializer::DeserializerImpl::GetBaseLayer</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l00286"></a><span class="lineno"> 286</span> {</div> -<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keyword">auto</span> layerType = graphPtr->layers()->Get(layerIndex)->layer_type();</div> -<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  </div> -<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordflow">switch</span>(layerType)</div> -<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  {</div> -<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keywordflow">case</span> Layer::Layer_AbsLayer:</div> -<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_AbsLayer()->base();</div> -<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keywordflow">case</span> Layer::Layer_ActivationLayer:</div> -<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ActivationLayer()->base();</div> -<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordflow">case</span> Layer::Layer_AdditionLayer:</div> -<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base();</div> -<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keywordflow">case</span> Layer::Layer_ArgMinMaxLayer:</div> -<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ArgMinMaxLayer()->base();</div> -<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordflow">case</span> Layer::Layer_BatchMatMulLayer:</div> -<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_BatchMatMulLayer()->base();</div> -<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordflow">case</span> Layer::Layer_BatchToSpaceNdLayer:</div> -<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->base();</div> -<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordflow">case</span> Layer::Layer_BatchNormalizationLayer:</div> -<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_BatchNormalizationLayer()->base();</div> -<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">case</span> Layer::Layer_CastLayer:</div> -<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_CastLayer()->base();</div> -<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keywordflow">case</span> Layer::Layer_ChannelShuffleLayer:</div> -<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ChannelShuffleLayer()->base();</div> -<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordflow">case</span> Layer::Layer_ComparisonLayer:</div> -<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ComparisonLayer()->base();</div> -<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordflow">case</span> Layer::Layer_ConcatLayer:</div> -<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ConcatLayer()->base();</div> -<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keywordflow">case</span> Layer::Layer_ConstantLayer:</div> -<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ConstantLayer()->base();</div> -<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keywordflow">case</span> Layer::Layer_Convolution2dLayer:</div> -<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Convolution2dLayer()->base();</div> -<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keywordflow">case</span> Layer::Layer_Convolution3dLayer:</div> -<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Convolution3dLayer()->base();</div> -<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">case</span> Layer::Layer_DepthToSpaceLayer:</div> -<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DepthToSpaceLayer()->base();</div> -<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keywordflow">case</span> Layer::Layer_DepthwiseConvolution2dLayer:</div> -<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer()->base();</div> -<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordflow">case</span> Layer::Layer_DequantizeLayer:</div> -<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DequantizeLayer()->base();</div> -<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordflow">case</span> Layer::Layer_DetectionPostProcessLayer:</div> -<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DetectionPostProcessLayer()->base();</div> -<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordflow">case</span> Layer::Layer_DivisionLayer:</div> -<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DivisionLayer()->base();</div> -<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">case</span> Layer::Layer_EqualLayer:</div> -<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_EqualLayer()->base();</div> -<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="keywordflow">case</span> Layer::Layer_ElementwiseBinaryLayer:</div> -<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ElementwiseBinaryLayer()->base();</div> -<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordflow">case</span> Layer::Layer_ElementwiseUnaryLayer:</div> -<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ElementwiseUnaryLayer()->base();</div> -<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordflow">case</span> Layer::Layer_FullyConnectedLayer:</div> -<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_FullyConnectedLayer()->base();</div> -<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="keywordflow">case</span> Layer::Layer_FillLayer:</div> -<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_FillLayer()->base();</div> -<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordflow">case</span> Layer::Layer_FloorLayer:</div> -<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_FloorLayer()->base();</div> -<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keywordflow">case</span> Layer::Layer_GatherLayer:</div> -<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_GatherLayer()->base();</div> -<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">case</span> Layer::Layer_GatherNdLayer:</div> -<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_GatherNdLayer()->base();</div> -<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="keywordflow">case</span> Layer::Layer_GreaterLayer:</div> -<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_GreaterLayer()->base();</div> -<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keywordflow">case</span> Layer::Layer_InputLayer:</div> -<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->base();</div> -<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordflow">case</span> Layer::Layer_InstanceNormalizationLayer:</div> -<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_InstanceNormalizationLayer()->base();</div> -<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="keywordflow">case</span> Layer::Layer_L2NormalizationLayer:</div> -<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_L2NormalizationLayer()->base();</div> -<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keywordflow">case</span> Layer::Layer_LogicalBinaryLayer:</div> -<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_LogicalBinaryLayer()->base();</div> -<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="keywordflow">case</span> Layer::Layer_LogSoftmaxLayer:</div> -<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->base();</div> -<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="keywordflow">case</span> Layer::Layer_LstmLayer:</div> -<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_LstmLayer()->base();</div> -<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="keywordflow">case</span> Layer::Layer_MeanLayer:</div> -<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MeanLayer()->base();</div> -<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keywordflow">case</span> Layer::Layer_MinimumLayer:</div> -<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MinimumLayer()->base();</div> -<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">case</span> Layer::Layer_MaximumLayer:</div> -<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MaximumLayer()->base();</div> -<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="keywordflow">case</span> Layer::Layer_MergeLayer:</div> -<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MergeLayer()->base();</div> -<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="keywordflow">case</span> Layer::Layer_MergerLayer:</div> -<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MergerLayer()->base();</div> -<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keywordflow">case</span> Layer::Layer_MultiplicationLayer:</div> -<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MultiplicationLayer()->base();</div> -<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordflow">case</span> Layer::Layer_NormalizationLayer:</div> -<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->base();</div> -<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keywordflow">case</span> Layer::Layer_OutputLayer:</div> -<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->base();</div> -<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordflow">case</span> Layer::Layer_PadLayer:</div> -<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_PadLayer()->base();</div> -<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="keywordflow">case</span> Layer::Layer_PermuteLayer:</div> -<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_PermuteLayer()->base();</div> -<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="keywordflow">case</span> Layer::Layer_Pooling2dLayer:</div> -<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->base();</div> -<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keywordflow">case</span> Layer::Layer_Pooling3dLayer:</div> -<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Pooling3dLayer()->base();</div> -<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keywordflow">case</span> Layer::Layer_PreluLayer:</div> -<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_PreluLayer()->base();</div> -<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordflow">case</span> Layer::Layer_QLstmLayer:</div> -<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_QLstmLayer()->base();</div> -<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">case</span> Layer::Layer_QuantizeLayer:</div> -<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_QuantizeLayer()->base();</div> -<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keywordflow">case</span> Layer::Layer_QuantizedLstmLayer:</div> -<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_QuantizedLstmLayer()->base();</div> -<div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="keywordflow">case</span> Layer::Layer_RankLayer:</div> -<div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_RankLayer()->base();</div> -<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="keywordflow">case</span> Layer::Layer_ReduceLayer:</div> -<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ReduceLayer()->base();</div> -<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keywordflow">case</span> Layer::Layer_ReshapeLayer:</div> -<div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->base();</div> -<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keywordflow">case</span> Layer::Layer_ResizeBilinearLayer:</div> -<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ResizeBilinearLayer()->base();</div> -<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keywordflow">case</span> Layer::Layer_ResizeLayer:</div> -<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ResizeLayer()->base();</div> -<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keywordflow">case</span> Layer::Layer_ReverseV2Layer:</div> -<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ReverseV2Layer()->base();</div> -<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <span class="keywordflow">case</span> Layer::Layer_RsqrtLayer:</div> -<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_RsqrtLayer()->base();</div> -<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="keywordflow">case</span> Layer::Layer_ShapeLayer:</div> -<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ShapeLayer()->base();</div> -<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="keywordflow">case</span> Layer::Layer_SliceLayer:</div> -<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SliceLayer()->base();</div> -<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <span class="keywordflow">case</span> Layer::Layer_SoftmaxLayer:</div> -<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->base();</div> -<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <span class="keywordflow">case</span> Layer::Layer_SpaceToBatchNdLayer:</div> -<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->base();</div> -<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <span class="keywordflow">case</span> Layer::Layer_SpaceToDepthLayer:</div> -<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToDepthLayer()->base();</div> -<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keywordflow">case</span> Layer::Layer_SplitterLayer:</div> -<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SplitterLayer()->base();</div> -<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keywordflow">case</span> Layer::Layer_StackLayer:</div> -<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_StackLayer()->base();</div> -<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <span class="keywordflow">case</span> Layer::Layer_StandInLayer:</div> -<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_StandInLayer()->base();</div> -<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="keywordflow">case</span> Layer::Layer_StridedSliceLayer:</div> -<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_StridedSliceLayer()->base();</div> -<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordflow">case</span> Layer::Layer_SubtractionLayer:</div> -<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SubtractionLayer()->base();</div> -<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  <span class="keywordflow">case</span> Layer::Layer_SwitchLayer:</div> -<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SwitchLayer()->base();</div> -<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <span class="keywordflow">case</span> Layer::Layer_TileLayer:</div> -<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_TileLayer()->base();</div> -<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="keywordflow">case</span> Layer::Layer_TransposeConvolution2dLayer:</div> -<div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_TransposeConvolution2dLayer()->base();</div> -<div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <span class="keywordflow">case</span> Layer::Layer_TransposeLayer:</div> -<div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_TransposeLayer()->base();</div> -<div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keywordflow">case</span> Layer::Layer_UnidirectionalSequenceLstmLayer:</div> -<div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_UnidirectionalSequenceLstmLayer()->base();</div> -<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="keywordflow">case</span> Layer::Layer_NONE:</div> -<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Layer type {} not recognized"</span>, layerType));</div> -<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  }</div> -<div class="line"><a name="l00439"></a><span class="lineno"> 439</span> }</div> -<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  </div> -<div class="line"><a name="l00441"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af2e5b4595b6abc056779ecd12bd271c2"> 441</a></span> std::string <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af2e5b4595b6abc056779ecd12bd271c2">IDeserializer::DeserializerImpl::GetLayerName</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index)</div> -<div class="line"><a name="l00442"></a><span class="lineno"> 442</span> {</div> -<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="keyword">auto</span> layer = GetBaseLayer(graph, index);</div> -<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  assert(layer);</div> -<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="keywordflow">return</span> layer->layerName()->str();</div> -<div class="line"><a name="l00446"></a><span class="lineno"> 446</span> }</div> -<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  </div> -<div class="line"><a name="l00448"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#afcc87bf0e20779861dd5d01a4bedcda9"> 448</a></span> int32_t <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#afcc87bf0e20779861dd5d01a4bedcda9">IDeserializer::DeserializerImpl::GetBindingLayerInfo</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l00449"></a><span class="lineno"> 449</span> {</div> -<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <span class="keyword">auto</span> layerType = graphPtr->layers()->Get(layerIndex)->layer_type();</div> -<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  </div> -<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="keywordflow">if</span> (layerType == Layer::Layer_InputLayer)</div> -<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  {</div> -<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->layerBindingId();</div> -<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  }</div> -<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> ( layerType == Layer::Layer_OutputLayer )</div> -<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  {</div> -<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->layerBindingId();</div> -<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  }</div> -<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <span class="keywordflow">return</span> 0;</div> -<div class="line"><a name="l00461"></a><span class="lineno"> 461</span> }</div> -<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  </div> -<div class="line"><a name="l00463"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829"> 463</a></span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(<a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnnSerializer::DataLayout</a> dataLayout)</div> -<div class="line"><a name="l00464"></a><span class="lineno"> 464</span> {</div> -<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="keywordflow">switch</span> (dataLayout)</div> -<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  {</div> -<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NHWC:</div> -<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div> -<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NDHWC:</div> -<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a4dd0194b114cbf51da5b3a72569863ef">armnn::DataLayout::NDHWC</a>;</div> -<div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NCDHW:</div> -<div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015">armnn::DataLayout::NCDHW</a>;</div> -<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NCHW:</div> -<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div> -<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  }</div> -<div class="line"><a name="l00477"></a><span class="lineno"> 477</span> }</div> -<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  </div> -<div class="line"><a name="l00479"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a2ee1264a9803ff8dc1323a26f1f4c986"> 479</a></span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a> <a class="code" href="namespacearmnn_deserializer.html#a2ee1264a9803ff8dc1323a26f1f4c986">ToActivationFunction</a>(<a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9ea">armnnSerializer::ActivationFunction</a> <span class="keyword">function</span>)</div> -<div class="line"><a name="l00480"></a><span class="lineno"> 480</span> {</div> -<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <span class="keywordflow">switch</span> (<span class="keyword">function</span>)</div> -<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  {</div> -<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Sigmoid:</div> -<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a>;</div> -<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_TanH:</div> -<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e">armnn::ActivationFunction::TanH</a>;</div> -<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Linear:</div> -<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b">armnn::ActivationFunction::Linear</a>;</div> -<div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_ReLu:</div> -<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559">armnn::ActivationFunction::ReLu</a>;</div> -<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_BoundedReLu:</div> -<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a>;</div> -<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_LeakyReLu:</div> -<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaacb7667f5ec2f6e8a5943b781ba6c2735">armnn::ActivationFunction::LeakyReLu</a>;</div> -<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Abs:</div> -<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::ActivationFunction::Abs</a>;</div> -<div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Sqrt:</div> -<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::ActivationFunction::Sqrt</a>;</div> -<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Square:</div> -<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaceb46ca115d05c51aa5a16a8867c3304">armnn::ActivationFunction::Square</a>;</div> -<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Elu:</div> -<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaed67cf7d54c570e4c4891800f085f41d">armnn::ActivationFunction::Elu</a>;</div> -<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_HardSwish:</div> -<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa0877e5b3fbe9d7569df6399609ed0186">armnn::ActivationFunction::HardSwish</a>;</div> -<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Gelu:</div> -<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaf48cca1c6deaa6a1c34e4ee46954cf0b">armnn::ActivationFunction::Gelu</a>;</div> -<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a>;</div> -<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  }</div> -<div class="line"><a name="l00510"></a><span class="lineno"> 510</span> }</div> -<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  </div> -<div class="line"><a name="l00512"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a8fb47fe218330370a5c9c066ac1571ea"> 512</a></span> <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeae">armnn::ArgMinMaxFunction</a> <a class="code" href="namespacearmnn_deserializer.html#a8fb47fe218330370a5c9c066ac1571ea">ToArgMinMaxFunction</a>(<a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeae">armnnSerializer::ArgMinMaxFunction</a> <span class="keyword">function</span>)</div> -<div class="line"><a name="l00513"></a><span class="lineno"> 513</span> {</div> -<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="keywordflow">switch</span> (<span class="keyword">function</span>)</div> -<div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  {</div> -<div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <span class="keywordflow">case</span> armnnSerializer::ArgMinMaxFunction::ArgMinMaxFunction_Max:</div> -<div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::ArgMinMaxFunction::Max</a>;</div> -<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="keywordflow">case</span> armnnSerializer::ArgMinMaxFunction::ArgMinMaxFunction_Min:</div> -<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea78d811e98514cd165dda532286610fd2">armnn::ArgMinMaxFunction::Min</a>;</div> -<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  }</div> -<div class="line"><a name="l00522"></a><span class="lineno"> 522</span> }</div> -<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  </div> -<div class="line"><a name="l00524"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a28f896fb78cdf6607b61c196c98b2570"> 524</a></span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58c">armnn::ComparisonOperation</a> <a class="code" href="namespacearmnn_deserializer.html#a28f896fb78cdf6607b61c196c98b2570">ToComparisonOperation</a>(<a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58c">armnnSerializer::ComparisonOperation</a> operation)</div> -<div class="line"><a name="l00525"></a><span class="lineno"> 525</span> {</div> -<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  <span class="keywordflow">switch</span> (operation)</div> -<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  {</div> -<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_Equal:</div> -<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">armnn::ComparisonOperation::Equal</a>;</div> -<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_Greater:</div> -<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">armnn::ComparisonOperation::Greater</a>;</div> -<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_GreaterOrEqual:</div> -<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca6f2f0aefb3d22da0f3839453add5f937">armnn::ComparisonOperation::GreaterOrEqual</a>;</div> -<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_Less:</div> -<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca1cfdf0e8d0c87a228c1f40d9bee7888b">armnn::ComparisonOperation::Less</a>;</div> -<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_LessOrEqual:</div> -<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58caa4cbdbb6070a5abb35fc95ecf1e22c14">armnn::ComparisonOperation::LessOrEqual</a>;</div> -<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_NotEqual:</div> -<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96">armnn::ComparisonOperation::NotEqual</a>;</div> -<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  }</div> -<div class="line"><a name="l00542"></a><span class="lineno"> 542</span> }</div> -<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  </div> -<div class="line"><a name="l00544"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#afa869143574c5885c6ad75f5a6f0333d"> 544</a></span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0">armnn::ReduceOperation</a> <a class="code" href="namespacearmnn_deserializer.html#afa869143574c5885c6ad75f5a6f0333d">ToReduceOperation</a>(<a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0">armnnSerializer::ReduceOperation</a> operation)</div> -<div class="line"><a name="l00545"></a><span class="lineno"> 545</span> {</div> -<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="keywordflow">switch</span> (operation)</div> -<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  {</div> -<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Sum:</div> -<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0aa0ec87054b5e5b7847d0d8780a01a3d5">armnn::ReduceOperation::Sum</a>;</div> -<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Max:</div> -<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a6a061313d22e51e0f25b7cd4dc065233">armnn::ReduceOperation::Max</a>;</div> -<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Mean:</div> -<div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a3d6c9ac08ada31c184094bbc67afe00d">armnn::ReduceOperation::Mean</a>;</div> -<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Min:</div> -<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a78d811e98514cd165dda532286610fd2">armnn::ReduceOperation::Min</a>;</div> -<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Prod:</div> -<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a362a33c23b08e4a32a4ec53fbb82cccd">armnn::ReduceOperation::Prod</a>;</div> -<div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0aa0ec87054b5e5b7847d0d8780a01a3d5">armnn::ReduceOperation::Sum</a>;</div> -<div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  }</div> -<div class="line"><a name="l00561"></a><span class="lineno"> 561</span> }</div> -<div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  </div> -<div class="line"><a name="l00563"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a2ccbea2c0078ba1d34c2ac48a8bdd342"> 563</a></span> <a class="code" href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379e">armnn::LogicalBinaryOperation</a> <a class="code" href="namespacearmnn_deserializer.html#a2ccbea2c0078ba1d34c2ac48a8bdd342">ToLogicalBinaryOperation</a>(<a class="code" href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379e">armnnSerializer::LogicalBinaryOperation</a> operation)</div> -<div class="line"><a name="l00564"></a><span class="lineno"> 564</span> {</div> -<div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <span class="keywordflow">switch</span> (operation)</div> -<div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  {</div> -<div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="keywordflow">case</span> armnnSerializer::LogicalBinaryOperation::LogicalBinaryOperation_LogicalAnd:</div> -<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379ea103aa83df42877d5f9baeafdbf620b55">armnn::LogicalBinaryOperation::LogicalAnd</a>;</div> -<div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <span class="keywordflow">case</span> armnnSerializer::LogicalBinaryOperation::LogicalBinaryOperation_LogicalOr:</div> -<div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379ea74ce78827b02c650a20b149765388247">armnn::LogicalBinaryOperation::LogicalOr</a>;</div> -<div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Logical Binary operation unknown"</span>);</div> -<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  }</div> -<div class="line"><a name="l00574"></a><span class="lineno"> 574</span> }</div> -<div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  </div> -<div class="line"><a name="l00576"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a3bb16a8c4f68fd2dfde128f1dc623571"> 576</a></span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047">armnn::BinaryOperation</a> <a class="code" href="namespacearmnn_deserializer.html#a3bb16a8c4f68fd2dfde128f1dc623571">ToElementwiseBinaryOperation</a>(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047">armnnSerializer::BinaryOperation</a> operation)</div> -<div class="line"><a name="l00577"></a><span class="lineno"> 577</span> {</div> -<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <span class="keywordflow">switch</span> (operation)</div> -<div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  {</div> -<div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Add:</div> -<div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aec211f7c20af43e742bf2570c3cb84f9">armnn::BinaryOperation::Add</a>;</div> -<div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Div:</div> -<div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a43d11850893d2fe84a1e618121c1cc0a">armnn::BinaryOperation::Div</a>;</div> -<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Maximum:</div> -<div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a8321e79c278ec510f63675c040594892">armnn::BinaryOperation::Maximum</a>;</div> -<div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Minimum:</div> -<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aa1d0ec6d56f8833a078b5a7ac4caf2d4">armnn::BinaryOperation::Minimum</a>;</div> -<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Mul:</div> -<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a62b6d55816cf737bfc6f42e60df1a3f2">armnn::BinaryOperation::Mul</a>;</div> -<div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Sub:</div> -<div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047ae80155eceb940c89e2de63ad05868db2">armnn::BinaryOperation::Sub</a>;</div> -<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_SqDiff:</div> -<div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a2d17ea57d7f86acde5c60cef8e123a53">armnn::BinaryOperation::SqDiff</a>;</div> -<div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Power:</div> -<div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047add4fe0cc913f704600b97d1f5dd285de">armnn::BinaryOperation::Power</a>;</div> -<div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Binary operation unknown"</span>);</div> -<div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  }</div> -<div class="line"><a name="l00599"></a><span class="lineno"> 599</span> }</div> -<div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  </div> -<div class="line"><a name="l00601"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a9c11dfb7a73226061b83ecd995b91582"> 601</a></span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8">armnn::UnaryOperation</a> <a class="code" href="namespacearmnn_deserializer.html#a9c11dfb7a73226061b83ecd995b91582">ToElementwiseUnaryOperation</a>(<a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8">armnnSerializer::UnaryOperation</a> operation)</div> -<div class="line"><a name="l00602"></a><span class="lineno"> 602</span> {</div> -<div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <span class="keywordflow">switch</span> (operation)</div> -<div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  {</div> -<div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Abs:</div> -<div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a1e34af023adeb7d5f484f8eb4b9826b6">armnn::UnaryOperation::Abs</a>;</div> -<div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Ceil:</div> -<div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8ab95a01ffffa8fcdd2a9af961937c097c">armnn::UnaryOperation::Ceil</a>;</div> -<div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Rsqrt:</div> -<div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4">armnn::UnaryOperation::Rsqrt</a>;</div> -<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Sqrt:</div> -<div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8aae77f3ad25595e35b327334d89410054">armnn::UnaryOperation::Sqrt</a>;</div> -<div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Exp:</div> -<div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8acad39a154bffb61175f674d6eefaf6d0">armnn::UnaryOperation::Exp</a>;</div> -<div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Neg:</div> -<div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8afb278fa5defd7e699fcbc930c3e76ccd">armnn::UnaryOperation::Neg</a>;</div> -<div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_LogicalNot:</div> -<div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a2a25ebd8c909241e3f7818389b804ecc">armnn::UnaryOperation::LogicalNot</a>;</div> -<div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Log:</div> -<div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8ace0be71e33226e4c1db2bcea5959f16b">armnn::UnaryOperation::Log</a>;</div> -<div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Sin:</div> -<div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a0986d137604183312e6d3599578bc6cd">armnn::UnaryOperation::Sin</a>;</div> -<div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Unary operation unknown"</span>);</div> -<div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  }</div> -<div class="line"><a name="l00626"></a><span class="lineno"> 626</span> }</div> -<div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  </div> -<div class="line"><a name="l00628"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#ac33cddeda1d847c4a17d679ea1dab6be"> 628</a></span> <a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91">armnn::PaddingMode</a> <a class="code" href="namespacearmnn_deserializer.html#ac33cddeda1d847c4a17d679ea1dab6be">ToPaddingMode</a>(<a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91">armnnSerializer::PaddingMode</a> paddingMode)</div> -<div class="line"><a name="l00629"></a><span class="lineno"> 629</span> {</div> -<div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  <span class="keywordflow">switch</span> (paddingMode)</div> -<div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  {</div> -<div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  <span class="keywordflow">case</span> armnnSerializer::PaddingMode::PaddingMode_Reflect:</div> -<div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91a74de3e45e4491e956e8dc18d841d9b00">armnn::PaddingMode::Reflect</a>;</div> -<div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  <span class="keywordflow">case</span> armnnSerializer::PaddingMode::PaddingMode_Symmetric:</div> -<div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91af334649ef5e5d0ffe200751d07012626">armnn::PaddingMode::Symmetric</a>;</div> -<div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91acb17869fe51048b5a5c4c6106551a255">armnn::PaddingMode::Constant</a>;</div> -<div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  }</div> -<div class="line"><a name="l00639"></a><span class="lineno"> 639</span> }</div> -<div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  </div> -<div class="line"><a name="l00641"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a8b51e137fab21d758b965c6c6e3b02f3"> 641</a></span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4">armnn::ResizeMethod</a> <a class="code" href="namespacearmnn_deserializer.html#a8b51e137fab21d758b965c6c6e3b02f3">ToResizeMethod</a>(<a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4">armnnSerializer::ResizeMethod</a> method)</div> -<div class="line"><a name="l00642"></a><span class="lineno"> 642</span> {</div> -<div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  <span class="keywordflow">switch</span> (method)</div> -<div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  {</div> -<div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  <span class="keywordflow">case</span> armnnSerializer::ResizeMethod_NearestNeighbor:</div> -<div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a>;</div> -<div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  <span class="keywordflow">case</span> armnnSerializer::ResizeMethod_Bilinear:</div> -<div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a>;</div> -<div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a>;</div> -<div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  }</div> -<div class="line"><a name="l00652"></a><span class="lineno"> 652</span> }</div> -<div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  </div> -<div class="line"><a name="l00654"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2"> 654</a></span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(<a class="code" href="namespacearmnn_deserializer.html#a80888061963ddd18e87105807a035d9a">TensorRawPtr</a> tensorPtr)</div> -<div class="line"><a name="l00655"></a><span class="lineno"> 655</span> {</div> -<div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> type;</div> -<div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <a class="code" href="_deserializer_8cpp.html#ae38d96fe05581ea025713b3e781c5a43">CHECK_TENSOR_PTR</a>(tensorPtr);</div> -<div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  </div> -<div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  <span class="keywordflow">switch</span> (tensorPtr->dataType())</div> -<div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  {</div> -<div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  <span class="keywordflow">case</span> DataType_QAsymmS8:</div> -<div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>;</div> -<div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  <span class="keywordflow">case</span> DataType_QSymmS8:</div> -<div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a>;</div> -<div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <span class="keywordflow">case</span> DataType_QuantisedAsymm8:</div> -<div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  <span class="keywordflow">case</span> DataType_QAsymmU8:</div> -<div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>;</div> -<div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  <span class="keywordflow">case</span> DataType_QSymmS16:</div> -<div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  <span class="keywordflow">case</span> DataType_QuantisedSymm16:</div> -<div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>;</div> -<div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <span class="keywordflow">case</span> DataType_Signed32:</div> -<div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>;</div> -<div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  <span class="keywordflow">case</span> DataType_Signed64:</div> -<div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d">armnn::DataType::Signed64</a>;</div> -<div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  <span class="keywordflow">case</span> DataType_Float32:</div> -<div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>;</div> -<div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  <span class="keywordflow">case</span> DataType_Float16:</div> -<div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>;</div> -<div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  <span class="keywordflow">case</span> DataType_Boolean:</div> -<div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a>;</div> -<div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  {</div> -<div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <a class="code" href="structarmnn_1_1_check_location.html">CheckLocation</a> location = <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Unsupported data type {0} = {1}. {2}"</span>,</div> -<div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  tensorPtr->dataType(),</div> -<div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  EnumNameDataType(tensorPtr->dataType()),</div> -<div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  location.<a class="code" href="structarmnn_1_1_check_location.html#a5e3562cda960da001597e7dd5679b140">AsString</a>()));</div> -<div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  }</div> -<div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  }</div> -<div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  </div> -<div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <span class="keywordtype">float</span> quantizationScale = tensorPtr->quantizationScale();</div> -<div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  int32_t quantizationOffset = tensorPtr->quantizationOffset();</div> -<div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  </div> -<div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <span class="keywordflow">if</span> (tensorPtr->dimensionality() == <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(Dimensionality::Scalar))</div> -<div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  {</div> -<div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>{<a class="code" href="namespacearmnn.html#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">armnn::Dimensionality::Scalar</a>},</div> -<div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  type,</div> -<div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  quantizationScale,</div> -<div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  quantizationOffset);</div> -<div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  }</div> -<div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (tensorPtr->dimensionality() == <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(Dimensionality::NotSpecified))</div> -<div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  {</div> -<div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> result(<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>{Dimensionality::NotSpecified},</div> -<div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  type,</div> -<div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  quantizationScale,</div> -<div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  quantizationOffset);</div> -<div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <span class="keywordflow">return</span> result;</div> -<div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  }</div> -<div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  </div> -<div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  <span class="keyword">auto</span> dimensions = tensorPtr->dimensions();</div> -<div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size = dimensions->size();</div> -<div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  std::vector<unsigned int> outputDims(dimensions->begin(), dimensions->begin() + size);</div> -<div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <span class="keywordtype">bool</span> dimensionsSpecificity[<a class="code" href="namespacearmnn.html#abdcd184ed3bd648bb31d385040cafd5d">armnn::MaxNumOfTensorDimensions</a>];</div> -<div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  std::fill_n(dimensionsSpecificity, <a class="code" href="namespacearmnn.html#abdcd184ed3bd648bb31d385040cafd5d">armnn::MaxNumOfTensorDimensions</a>, <span class="keyword">true</span>);</div> -<div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  <span class="comment">// For backwards compatibility check if the dimensionSpecificity vector is present first.</span></div> -<div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  <span class="comment">// The default is to have dimensionSpecificity set to all true's anyway.</span></div> -<div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  <span class="keywordflow">if</span> (tensorPtr->dimensionSpecificity() != <span class="keyword">nullptr</span>)</div> -<div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  {</div> -<div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  <span class="keyword">auto</span> dimensionSpecificity = tensorPtr->dimensionSpecificity();</div> -<div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  size = dimensionSpecificity->size();</div> -<div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < size; ++i)</div> -<div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  {</div> -<div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  dimensionsSpecificity[i] = dimensionSpecificity->Get(i);</div> -<div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  }</div> -<div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  }</div> -<div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  <span class="comment">// Construct a TensorShape</span></div> -<div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> shape(size, outputDims.data(), dimensionsSpecificity);</div> -<div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  </div> -<div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  <span class="keyword">auto</span> quantizationScales = tensorPtr->quantizationScales();</div> -<div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  <span class="keywordflow">if</span> (quantizationScales)</div> -<div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  {</div> -<div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationScalesSize = quantizationScales->size();</div> -<div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  std::vector<float> scales(quantizationScales->begin(), quantizationScales->begin() + quantizationScalesSize);</div> -<div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim = tensorPtr->quantizationDim();</div> -<div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> result(shape,</div> -<div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  type,</div> -<div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  scales,</div> -<div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  quantizationDim);</div> -<div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <span class="keywordflow">return</span> result;</div> -<div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  }</div> -<div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  </div> -<div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  <span class="comment">// two statements (on purpose) for easier debugging:</span></div> -<div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> result(shape,</div> -<div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  type,</div> -<div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  quantizationScale,</div> -<div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  quantizationOffset);</div> -<div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  </div> -<div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  <span class="keywordflow">return</span> result;</div> -<div class="line"><a name="l00758"></a><span class="lineno"> 758</span> }</div> +<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  m_ParserFunctions[Layer_ScatterNdLayer] = &DeserializerImpl::ParseScatterNd;</div> +<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  m_ParserFunctions[Layer_ShapeLayer] = &DeserializerImpl::ParseShape;</div> +<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  m_ParserFunctions[Layer_SliceLayer] = &DeserializerImpl::ParseSlice;</div> +<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  m_ParserFunctions[Layer_SoftmaxLayer] = &DeserializerImpl::ParseSoftmax;</div> +<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  m_ParserFunctions[Layer_SpaceToBatchNdLayer] = &DeserializerImpl::ParseSpaceToBatchNd;</div> +<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  m_ParserFunctions[Layer_SpaceToDepthLayer] = &DeserializerImpl::ParseSpaceToDepth;</div> +<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  m_ParserFunctions[Layer_SplitterLayer] = &DeserializerImpl::ParseSplitter;</div> +<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  m_ParserFunctions[Layer_StackLayer] = &DeserializerImpl::ParseStack;</div> +<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  m_ParserFunctions[Layer_StandInLayer] = &DeserializerImpl::ParseStandIn;</div> +<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  m_ParserFunctions[Layer_StridedSliceLayer] = &DeserializerImpl::ParseStridedSlice;</div> +<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  m_ParserFunctions[Layer_SubtractionLayer] = &DeserializerImpl::ParseSubtraction;</div> +<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  m_ParserFunctions[Layer_SwitchLayer] = &DeserializerImpl::ParseSwitch;</div> +<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  m_ParserFunctions[Layer_TileLayer] = &DeserializerImpl::ParseTile;</div> +<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  m_ParserFunctions[Layer_TransposeConvolution2dLayer] = &DeserializerImpl::ParseTransposeConvolution2d;</div> +<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  m_ParserFunctions[Layer_TransposeLayer] = &DeserializerImpl::ParseTranspose;</div> +<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  m_ParserFunctions[Layer_UnidirectionalSequenceLstmLayer] = &DeserializerImpl::ParseUnidirectionalSequenceLstm;</div> +<div class="line"><a name="l00284"></a><span class="lineno"> 284</span> }</div> +<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  </div> +<div class="line"><a name="l00286"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ab3dff510bec873d3e4ffe5cdfa71f1cd"> 286</a></span> <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ab3dff510bec873d3e4ffe5cdfa71f1cd">IDeserializer::DeserializerImpl::GetBaseLayer</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l00287"></a><span class="lineno"> 287</span> {</div> +<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="keyword">auto</span> layerType = graphPtr->layers()->Get(layerIndex)->layer_type();</div> +<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  </div> +<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keywordflow">switch</span>(layerType)</div> +<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  {</div> +<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordflow">case</span> Layer::Layer_AbsLayer:</div> +<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_AbsLayer()->base();</div> +<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keywordflow">case</span> Layer::Layer_ActivationLayer:</div> +<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ActivationLayer()->base();</div> +<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keywordflow">case</span> Layer::Layer_AdditionLayer:</div> +<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base();</div> +<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordflow">case</span> Layer::Layer_ArgMinMaxLayer:</div> +<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ArgMinMaxLayer()->base();</div> +<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keywordflow">case</span> Layer::Layer_BatchMatMulLayer:</div> +<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_BatchMatMulLayer()->base();</div> +<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keywordflow">case</span> Layer::Layer_BatchToSpaceNdLayer:</div> +<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->base();</div> +<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordflow">case</span> Layer::Layer_BatchNormalizationLayer:</div> +<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_BatchNormalizationLayer()->base();</div> +<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordflow">case</span> Layer::Layer_CastLayer:</div> +<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_CastLayer()->base();</div> +<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keywordflow">case</span> Layer::Layer_ChannelShuffleLayer:</div> +<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ChannelShuffleLayer()->base();</div> +<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordflow">case</span> Layer::Layer_ComparisonLayer:</div> +<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ComparisonLayer()->base();</div> +<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keywordflow">case</span> Layer::Layer_ConcatLayer:</div> +<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ConcatLayer()->base();</div> +<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordflow">case</span> Layer::Layer_ConstantLayer:</div> +<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ConstantLayer()->base();</div> +<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">case</span> Layer::Layer_Convolution2dLayer:</div> +<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Convolution2dLayer()->base();</div> +<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="keywordflow">case</span> Layer::Layer_Convolution3dLayer:</div> +<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Convolution3dLayer()->base();</div> +<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keywordflow">case</span> Layer::Layer_DepthToSpaceLayer:</div> +<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DepthToSpaceLayer()->base();</div> +<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordflow">case</span> Layer::Layer_DepthwiseConvolution2dLayer:</div> +<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer()->base();</div> +<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordflow">case</span> Layer::Layer_DequantizeLayer:</div> +<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DequantizeLayer()->base();</div> +<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keywordflow">case</span> Layer::Layer_DetectionPostProcessLayer:</div> +<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DetectionPostProcessLayer()->base();</div> +<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordflow">case</span> Layer::Layer_DivisionLayer:</div> +<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DivisionLayer()->base();</div> +<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="keywordflow">case</span> Layer::Layer_EqualLayer:</div> +<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_EqualLayer()->base();</div> +<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordflow">case</span> Layer::Layer_ElementwiseBinaryLayer:</div> +<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ElementwiseBinaryLayer()->base();</div> +<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">case</span> Layer::Layer_ElementwiseUnaryLayer:</div> +<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ElementwiseUnaryLayer()->base();</div> +<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keywordflow">case</span> Layer::Layer_FullyConnectedLayer:</div> +<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_FullyConnectedLayer()->base();</div> +<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">case</span> Layer::Layer_FillLayer:</div> +<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_FillLayer()->base();</div> +<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">case</span> Layer::Layer_FloorLayer:</div> +<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_FloorLayer()->base();</div> +<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">case</span> Layer::Layer_GatherLayer:</div> +<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_GatherLayer()->base();</div> +<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="keywordflow">case</span> Layer::Layer_GatherNdLayer:</div> +<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_GatherNdLayer()->base();</div> +<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keywordflow">case</span> Layer::Layer_GreaterLayer:</div> +<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_GreaterLayer()->base();</div> +<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordflow">case</span> Layer::Layer_InputLayer:</div> +<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->base();</div> +<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">case</span> Layer::Layer_InstanceNormalizationLayer:</div> +<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_InstanceNormalizationLayer()->base();</div> +<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keywordflow">case</span> Layer::Layer_L2NormalizationLayer:</div> +<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_L2NormalizationLayer()->base();</div> +<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordflow">case</span> Layer::Layer_LogicalBinaryLayer:</div> +<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_LogicalBinaryLayer()->base();</div> +<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keywordflow">case</span> Layer::Layer_LogSoftmaxLayer:</div> +<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->base();</div> +<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">case</span> Layer::Layer_LstmLayer:</div> +<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_LstmLayer()->base();</div> +<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">case</span> Layer::Layer_MeanLayer:</div> +<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MeanLayer()->base();</div> +<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">case</span> Layer::Layer_MinimumLayer:</div> +<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MinimumLayer()->base();</div> +<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keywordflow">case</span> Layer::Layer_MaximumLayer:</div> +<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MaximumLayer()->base();</div> +<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keywordflow">case</span> Layer::Layer_MergeLayer:</div> +<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MergeLayer()->base();</div> +<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="keywordflow">case</span> Layer::Layer_MergerLayer:</div> +<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MergerLayer()->base();</div> +<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keywordflow">case</span> Layer::Layer_MultiplicationLayer:</div> +<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MultiplicationLayer()->base();</div> +<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keywordflow">case</span> Layer::Layer_NormalizationLayer:</div> +<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->base();</div> +<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordflow">case</span> Layer::Layer_OutputLayer:</div> +<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->base();</div> +<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordflow">case</span> Layer::Layer_PadLayer:</div> +<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_PadLayer()->base();</div> +<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keywordflow">case</span> Layer::Layer_PermuteLayer:</div> +<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_PermuteLayer()->base();</div> +<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keywordflow">case</span> Layer::Layer_Pooling2dLayer:</div> +<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->base();</div> +<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <span class="keywordflow">case</span> Layer::Layer_Pooling3dLayer:</div> +<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Pooling3dLayer()->base();</div> +<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="keywordflow">case</span> Layer::Layer_PreluLayer:</div> +<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_PreluLayer()->base();</div> +<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keywordflow">case</span> Layer::Layer_QLstmLayer:</div> +<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_QLstmLayer()->base();</div> +<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordflow">case</span> Layer::Layer_QuantizeLayer:</div> +<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_QuantizeLayer()->base();</div> +<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keywordflow">case</span> Layer::Layer_QuantizedLstmLayer:</div> +<div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_QuantizedLstmLayer()->base();</div> +<div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="keywordflow">case</span> Layer::Layer_RankLayer:</div> +<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_RankLayer()->base();</div> +<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="keywordflow">case</span> Layer::Layer_ReduceLayer:</div> +<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ReduceLayer()->base();</div> +<div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="keywordflow">case</span> Layer::Layer_ReshapeLayer:</div> +<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->base();</div> +<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keywordflow">case</span> Layer::Layer_ResizeBilinearLayer:</div> +<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ResizeBilinearLayer()->base();</div> +<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keywordflow">case</span> Layer::Layer_ResizeLayer:</div> +<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ResizeLayer()->base();</div> +<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keywordflow">case</span> Layer::Layer_ReverseV2Layer:</div> +<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ReverseV2Layer()->base();</div> +<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="keywordflow">case</span> Layer::Layer_RsqrtLayer:</div> +<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_RsqrtLayer()->base();</div> +<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  <span class="keywordflow">case</span> Layer::Layer_ScatterNdLayer:</div> +<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ScatterNdLayer()->base();</div> +<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keywordflow">case</span> Layer::Layer_ShapeLayer:</div> +<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ShapeLayer()->base();</div> +<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="keywordflow">case</span> Layer::Layer_SliceLayer:</div> +<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SliceLayer()->base();</div> +<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="keywordflow">case</span> Layer::Layer_SoftmaxLayer:</div> +<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->base();</div> +<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <span class="keywordflow">case</span> Layer::Layer_SpaceToBatchNdLayer:</div> +<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->base();</div> +<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keywordflow">case</span> Layer::Layer_SpaceToDepthLayer:</div> +<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToDepthLayer()->base();</div> +<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <span class="keywordflow">case</span> Layer::Layer_SplitterLayer:</div> +<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SplitterLayer()->base();</div> +<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keywordflow">case</span> Layer::Layer_StackLayer:</div> +<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_StackLayer()->base();</div> +<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keywordflow">case</span> Layer::Layer_StandInLayer:</div> +<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_StandInLayer()->base();</div> +<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="keywordflow">case</span> Layer::Layer_StridedSliceLayer:</div> +<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_StridedSliceLayer()->base();</div> +<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  <span class="keywordflow">case</span> Layer::Layer_SubtractionLayer:</div> +<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SubtractionLayer()->base();</div> +<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <span class="keywordflow">case</span> Layer::Layer_SwitchLayer:</div> +<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SwitchLayer()->base();</div> +<div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="keywordflow">case</span> Layer::Layer_TileLayer:</div> +<div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_TileLayer()->base();</div> +<div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <span class="keywordflow">case</span> Layer::Layer_TransposeConvolution2dLayer:</div> +<div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_TransposeConvolution2dLayer()->base();</div> +<div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="keywordflow">case</span> Layer::Layer_TransposeLayer:</div> +<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_TransposeLayer()->base();</div> +<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <span class="keywordflow">case</span> Layer::Layer_UnidirectionalSequenceLstmLayer:</div> +<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_UnidirectionalSequenceLstmLayer()->base();</div> +<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <span class="keywordflow">case</span> Layer::Layer_NONE:</div> +<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Layer type {} not recognized"</span>, layerType));</div> +<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  }</div> +<div class="line"><a name="l00442"></a><span class="lineno"> 442</span> }</div> +<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  </div> +<div class="line"><a name="l00444"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af2e5b4595b6abc056779ecd12bd271c2"> 444</a></span> std::string <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af2e5b4595b6abc056779ecd12bd271c2">IDeserializer::DeserializerImpl::GetLayerName</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index)</div> +<div class="line"><a name="l00445"></a><span class="lineno"> 445</span> {</div> +<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="keyword">auto</span> layer = GetBaseLayer(graph, index);</div> +<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  assert(layer);</div> +<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <span class="keywordflow">return</span> layer->layerName()->str();</div> +<div class="line"><a name="l00449"></a><span class="lineno"> 449</span> }</div> +<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  </div> +<div class="line"><a name="l00451"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#afcc87bf0e20779861dd5d01a4bedcda9"> 451</a></span> int32_t <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#afcc87bf0e20779861dd5d01a4bedcda9">IDeserializer::DeserializerImpl::GetBindingLayerInfo</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l00452"></a><span class="lineno"> 452</span> {</div> +<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="keyword">auto</span> layerType = graphPtr->layers()->Get(layerIndex)->layer_type();</div> +<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  </div> +<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <span class="keywordflow">if</span> (layerType == Layer::Layer_InputLayer)</div> +<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  {</div> +<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->layerBindingId();</div> +<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  }</div> +<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> ( layerType == Layer::Layer_OutputLayer )</div> +<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  {</div> +<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->layerBindingId();</div> +<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  }</div> +<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keywordflow">return</span> 0;</div> +<div class="line"><a name="l00464"></a><span class="lineno"> 464</span> }</div> +<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  </div> +<div class="line"><a name="l00466"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829"> 466</a></span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(<a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnnSerializer::DataLayout</a> dataLayout)</div> +<div class="line"><a name="l00467"></a><span class="lineno"> 467</span> {</div> +<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  <span class="keywordflow">switch</span> (dataLayout)</div> +<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  {</div> +<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NHWC:</div> +<div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div> +<div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NDHWC:</div> +<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a4dd0194b114cbf51da5b3a72569863ef">armnn::DataLayout::NDHWC</a>;</div> +<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NCDHW:</div> +<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015">armnn::DataLayout::NCDHW</a>;</div> +<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NCHW:</div> +<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div> +<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  }</div> +<div class="line"><a name="l00480"></a><span class="lineno"> 480</span> }</div> +<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  </div> +<div class="line"><a name="l00482"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a2ee1264a9803ff8dc1323a26f1f4c986"> 482</a></span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a> <a class="code" href="namespacearmnn_deserializer.html#a2ee1264a9803ff8dc1323a26f1f4c986">ToActivationFunction</a>(<a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9ea">armnnSerializer::ActivationFunction</a> <span class="keyword">function</span>)</div> +<div class="line"><a name="l00483"></a><span class="lineno"> 483</span> {</div> +<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keywordflow">switch</span> (<span class="keyword">function</span>)</div> +<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  {</div> +<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Sigmoid:</div> +<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a>;</div> +<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_TanH:</div> +<div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e">armnn::ActivationFunction::TanH</a>;</div> +<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Linear:</div> +<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b">armnn::ActivationFunction::Linear</a>;</div> +<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_ReLu:</div> +<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559">armnn::ActivationFunction::ReLu</a>;</div> +<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_BoundedReLu:</div> +<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a>;</div> +<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_LeakyReLu:</div> +<div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaacb7667f5ec2f6e8a5943b781ba6c2735">armnn::ActivationFunction::LeakyReLu</a>;</div> +<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Abs:</div> +<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::ActivationFunction::Abs</a>;</div> +<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Sqrt:</div> +<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::ActivationFunction::Sqrt</a>;</div> +<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Square:</div> +<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaceb46ca115d05c51aa5a16a8867c3304">armnn::ActivationFunction::Square</a>;</div> +<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Elu:</div> +<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaed67cf7d54c570e4c4891800f085f41d">armnn::ActivationFunction::Elu</a>;</div> +<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_HardSwish:</div> +<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa0877e5b3fbe9d7569df6399609ed0186">armnn::ActivationFunction::HardSwish</a>;</div> +<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Gelu:</div> +<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaf48cca1c6deaa6a1c34e4ee46954cf0b">armnn::ActivationFunction::Gelu</a>;</div> +<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a>;</div> +<div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  }</div> +<div class="line"><a name="l00513"></a><span class="lineno"> 513</span> }</div> +<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  </div> +<div class="line"><a name="l00515"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a8fb47fe218330370a5c9c066ac1571ea"> 515</a></span> <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeae">armnn::ArgMinMaxFunction</a> <a class="code" href="namespacearmnn_deserializer.html#a8fb47fe218330370a5c9c066ac1571ea">ToArgMinMaxFunction</a>(<a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeae">armnnSerializer::ArgMinMaxFunction</a> <span class="keyword">function</span>)</div> +<div class="line"><a name="l00516"></a><span class="lineno"> 516</span> {</div> +<div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="keywordflow">switch</span> (<span class="keyword">function</span>)</div> +<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  {</div> +<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="keywordflow">case</span> armnnSerializer::ArgMinMaxFunction::ArgMinMaxFunction_Max:</div> +<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::ArgMinMaxFunction::Max</a>;</div> +<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <span class="keywordflow">case</span> armnnSerializer::ArgMinMaxFunction::ArgMinMaxFunction_Min:</div> +<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea78d811e98514cd165dda532286610fd2">armnn::ArgMinMaxFunction::Min</a>;</div> +<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  }</div> +<div class="line"><a name="l00525"></a><span class="lineno"> 525</span> }</div> +<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  </div> +<div class="line"><a name="l00527"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#ada48fd59da09885ff0c4273b303c28f5"> 527</a></span> <a class="code" href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4a">armnn::ScatterNdFunction</a> <a class="code" href="namespacearmnn_deserializer.html#ada48fd59da09885ff0c4273b303c28f5">ToScatterNdFunction</a>(<a class="code" href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4a">armnnSerializer::ScatterNdFunction</a> <span class="keyword">function</span>)</div> +<div class="line"><a name="l00528"></a><span class="lineno"> 528</span> {</div> +<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <span class="keywordflow">switch</span> (<span class="keyword">function</span>)</div> +<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  {</div> +<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  <span class="keywordflow">case</span> armnnSerializer::ScatterNdFunction_Update:</div> +<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aa06933067aafd48425d67bcb01bba5cb6">armnn::ScatterNdFunction::Update</a>;</div> +<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keywordflow">case</span> armnnSerializer::ScatterNdFunction_Add:</div> +<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aaec211f7c20af43e742bf2570c3cb84f9">armnn::ScatterNdFunction::Add</a>;</div> +<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  <span class="keywordflow">case</span> armnnSerializer::ScatterNdFunction_Sub:</div> +<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aae80155eceb940c89e2de63ad05868db2">armnn::ScatterNdFunction::Sub</a>;</div> +<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  <span class="keywordflow">case</span> armnnSerializer::ScatterNdFunction_Max:</div> +<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aa6a061313d22e51e0f25b7cd4dc065233">armnn::ScatterNdFunction::Max</a>;</div> +<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  <span class="keywordflow">case</span> armnnSerializer::ScatterNdFunction_Min:</div> +<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aa78d811e98514cd165dda532286610fd2">armnn::ScatterNdFunction::Min</a>;</div> +<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aa06933067aafd48425d67bcb01bba5cb6">armnn::ScatterNdFunction::Update</a>;</div> +<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  }</div> +<div class="line"><a name="l00544"></a><span class="lineno"> 544</span> }</div> +<div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  </div> +<div class="line"><a name="l00546"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a28f896fb78cdf6607b61c196c98b2570"> 546</a></span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58c">armnn::ComparisonOperation</a> <a class="code" href="namespacearmnn_deserializer.html#a28f896fb78cdf6607b61c196c98b2570">ToComparisonOperation</a>(<a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58c">armnnSerializer::ComparisonOperation</a> operation)</div> +<div class="line"><a name="l00547"></a><span class="lineno"> 547</span> {</div> +<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <span class="keywordflow">switch</span> (operation)</div> +<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  {</div> +<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_Equal:</div> +<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">armnn::ComparisonOperation::Equal</a>;</div> +<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_Greater:</div> +<div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">armnn::ComparisonOperation::Greater</a>;</div> +<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_GreaterOrEqual:</div> +<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca6f2f0aefb3d22da0f3839453add5f937">armnn::ComparisonOperation::GreaterOrEqual</a>;</div> +<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_Less:</div> +<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca1cfdf0e8d0c87a228c1f40d9bee7888b">armnn::ComparisonOperation::Less</a>;</div> +<div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_LessOrEqual:</div> +<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58caa4cbdbb6070a5abb35fc95ecf1e22c14">armnn::ComparisonOperation::LessOrEqual</a>;</div> +<div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_NotEqual:</div> +<div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96">armnn::ComparisonOperation::NotEqual</a>;</div> +<div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  }</div> +<div class="line"><a name="l00564"></a><span class="lineno"> 564</span> }</div> +<div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  </div> +<div class="line"><a name="l00566"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#afa869143574c5885c6ad75f5a6f0333d"> 566</a></span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0">armnn::ReduceOperation</a> <a class="code" href="namespacearmnn_deserializer.html#afa869143574c5885c6ad75f5a6f0333d">ToReduceOperation</a>(<a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0">armnnSerializer::ReduceOperation</a> operation)</div> +<div class="line"><a name="l00567"></a><span class="lineno"> 567</span> {</div> +<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <span class="keywordflow">switch</span> (operation)</div> +<div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  {</div> +<div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Sum:</div> +<div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0aa0ec87054b5e5b7847d0d8780a01a3d5">armnn::ReduceOperation::Sum</a>;</div> +<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Max:</div> +<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a6a061313d22e51e0f25b7cd4dc065233">armnn::ReduceOperation::Max</a>;</div> +<div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Mean:</div> +<div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a3d6c9ac08ada31c184094bbc67afe00d">armnn::ReduceOperation::Mean</a>;</div> +<div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Min:</div> +<div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a78d811e98514cd165dda532286610fd2">armnn::ReduceOperation::Min</a>;</div> +<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <span class="keywordflow">case</span> armnnSerializer::ReduceOperation::ReduceOperation_Prod:</div> +<div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a362a33c23b08e4a32a4ec53fbb82cccd">armnn::ReduceOperation::Prod</a>;</div> +<div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0aa0ec87054b5e5b7847d0d8780a01a3d5">armnn::ReduceOperation::Sum</a>;</div> +<div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  }</div> +<div class="line"><a name="l00583"></a><span class="lineno"> 583</span> }</div> +<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  </div> +<div class="line"><a name="l00585"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a2ccbea2c0078ba1d34c2ac48a8bdd342"> 585</a></span> <a class="code" href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379e">armnn::LogicalBinaryOperation</a> <a class="code" href="namespacearmnn_deserializer.html#a2ccbea2c0078ba1d34c2ac48a8bdd342">ToLogicalBinaryOperation</a>(<a class="code" href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379e">armnnSerializer::LogicalBinaryOperation</a> operation)</div> +<div class="line"><a name="l00586"></a><span class="lineno"> 586</span> {</div> +<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  <span class="keywordflow">switch</span> (operation)</div> +<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  {</div> +<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="keywordflow">case</span> armnnSerializer::LogicalBinaryOperation::LogicalBinaryOperation_LogicalAnd:</div> +<div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379ea103aa83df42877d5f9baeafdbf620b55">armnn::LogicalBinaryOperation::LogicalAnd</a>;</div> +<div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <span class="keywordflow">case</span> armnnSerializer::LogicalBinaryOperation::LogicalBinaryOperation_LogicalOr:</div> +<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379ea74ce78827b02c650a20b149765388247">armnn::LogicalBinaryOperation::LogicalOr</a>;</div> +<div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Logical Binary operation unknown"</span>);</div> +<div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  }</div> +<div class="line"><a name="l00596"></a><span class="lineno"> 596</span> }</div> +<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  </div> +<div class="line"><a name="l00598"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a3bb16a8c4f68fd2dfde128f1dc623571"> 598</a></span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047">armnn::BinaryOperation</a> <a class="code" href="namespacearmnn_deserializer.html#a3bb16a8c4f68fd2dfde128f1dc623571">ToElementwiseBinaryOperation</a>(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047">armnnSerializer::BinaryOperation</a> operation)</div> +<div class="line"><a name="l00599"></a><span class="lineno"> 599</span> {</div> +<div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keywordflow">switch</span> (operation)</div> +<div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  {</div> +<div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Add:</div> +<div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aec211f7c20af43e742bf2570c3cb84f9">armnn::BinaryOperation::Add</a>;</div> +<div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Div:</div> +<div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a43d11850893d2fe84a1e618121c1cc0a">armnn::BinaryOperation::Div</a>;</div> +<div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Maximum:</div> +<div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a8321e79c278ec510f63675c040594892">armnn::BinaryOperation::Maximum</a>;</div> +<div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Minimum:</div> +<div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aa1d0ec6d56f8833a078b5a7ac4caf2d4">armnn::BinaryOperation::Minimum</a>;</div> +<div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Mul:</div> +<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a62b6d55816cf737bfc6f42e60df1a3f2">armnn::BinaryOperation::Mul</a>;</div> +<div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Sub:</div> +<div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047ae80155eceb940c89e2de63ad05868db2">armnn::BinaryOperation::Sub</a>;</div> +<div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_SqDiff:</div> +<div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a2d17ea57d7f86acde5c60cef8e123a53">armnn::BinaryOperation::SqDiff</a>;</div> +<div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="keywordflow">case</span> armnnSerializer::BinaryOperation::BinaryOperation_Power:</div> +<div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047add4fe0cc913f704600b97d1f5dd285de">armnn::BinaryOperation::Power</a>;</div> +<div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Binary operation unknown"</span>);</div> +<div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  }</div> +<div class="line"><a name="l00621"></a><span class="lineno"> 621</span> }</div> +<div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  </div> +<div class="line"><a name="l00623"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a9c11dfb7a73226061b83ecd995b91582"> 623</a></span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8">armnn::UnaryOperation</a> <a class="code" href="namespacearmnn_deserializer.html#a9c11dfb7a73226061b83ecd995b91582">ToElementwiseUnaryOperation</a>(<a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8">armnnSerializer::UnaryOperation</a> operation)</div> +<div class="line"><a name="l00624"></a><span class="lineno"> 624</span> {</div> +<div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  <span class="keywordflow">switch</span> (operation)</div> +<div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  {</div> +<div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Abs:</div> +<div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a1e34af023adeb7d5f484f8eb4b9826b6">armnn::UnaryOperation::Abs</a>;</div> +<div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Ceil:</div> +<div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8ab95a01ffffa8fcdd2a9af961937c097c">armnn::UnaryOperation::Ceil</a>;</div> +<div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Rsqrt:</div> +<div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4">armnn::UnaryOperation::Rsqrt</a>;</div> +<div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Sqrt:</div> +<div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8aae77f3ad25595e35b327334d89410054">armnn::UnaryOperation::Sqrt</a>;</div> +<div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Exp:</div> +<div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8acad39a154bffb61175f674d6eefaf6d0">armnn::UnaryOperation::Exp</a>;</div> +<div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Neg:</div> +<div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8afb278fa5defd7e699fcbc930c3e76ccd">armnn::UnaryOperation::Neg</a>;</div> +<div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_LogicalNot:</div> +<div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a2a25ebd8c909241e3f7818389b804ecc">armnn::UnaryOperation::LogicalNot</a>;</div> +<div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Log:</div> +<div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8ace0be71e33226e4c1db2bcea5959f16b">armnn::UnaryOperation::Log</a>;</div> +<div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Sin:</div> +<div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a0986d137604183312e6d3599578bc6cd">armnn::UnaryOperation::Sin</a>;</div> +<div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Unary operation unknown"</span>);</div> +<div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  }</div> +<div class="line"><a name="l00648"></a><span class="lineno"> 648</span> }</div> +<div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  </div> +<div class="line"><a name="l00650"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#ac33cddeda1d847c4a17d679ea1dab6be"> 650</a></span> <a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91">armnn::PaddingMode</a> <a class="code" href="namespacearmnn_deserializer.html#ac33cddeda1d847c4a17d679ea1dab6be">ToPaddingMode</a>(<a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91">armnnSerializer::PaddingMode</a> paddingMode)</div> +<div class="line"><a name="l00651"></a><span class="lineno"> 651</span> {</div> +<div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  <span class="keywordflow">switch</span> (paddingMode)</div> +<div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  {</div> +<div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  <span class="keywordflow">case</span> armnnSerializer::PaddingMode::PaddingMode_Reflect:</div> +<div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91a74de3e45e4491e956e8dc18d841d9b00">armnn::PaddingMode::Reflect</a>;</div> +<div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <span class="keywordflow">case</span> armnnSerializer::PaddingMode::PaddingMode_Symmetric:</div> +<div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91af334649ef5e5d0ffe200751d07012626">armnn::PaddingMode::Symmetric</a>;</div> +<div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91acb17869fe51048b5a5c4c6106551a255">armnn::PaddingMode::Constant</a>;</div> +<div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  }</div> +<div class="line"><a name="l00661"></a><span class="lineno"> 661</span> }</div> +<div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  </div> +<div class="line"><a name="l00663"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a8b51e137fab21d758b965c6c6e3b02f3"> 663</a></span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4">armnn::ResizeMethod</a> <a class="code" href="namespacearmnn_deserializer.html#a8b51e137fab21d758b965c6c6e3b02f3">ToResizeMethod</a>(<a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4">armnnSerializer::ResizeMethod</a> method)</div> +<div class="line"><a name="l00664"></a><span class="lineno"> 664</span> {</div> +<div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  <span class="keywordflow">switch</span> (method)</div> +<div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  {</div> +<div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <span class="keywordflow">case</span> armnnSerializer::ResizeMethod_NearestNeighbor:</div> +<div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a>;</div> +<div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  <span class="keywordflow">case</span> armnnSerializer::ResizeMethod_Bilinear:</div> +<div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a>;</div> +<div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a>;</div> +<div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  }</div> +<div class="line"><a name="l00674"></a><span class="lineno"> 674</span> }</div> +<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  </div> +<div class="line"><a name="l00676"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2"> 676</a></span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(<a class="code" href="namespacearmnn_deserializer.html#a80888061963ddd18e87105807a035d9a">TensorRawPtr</a> tensorPtr)</div> +<div class="line"><a name="l00677"></a><span class="lineno"> 677</span> {</div> +<div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> type;</div> +<div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  <a class="code" href="_deserializer_8cpp.html#ae38d96fe05581ea025713b3e781c5a43">CHECK_TENSOR_PTR</a>(tensorPtr);</div> +<div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  </div> +<div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  <span class="keywordflow">switch</span> (tensorPtr->dataType())</div> +<div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  {</div> +<div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  <span class="keywordflow">case</span> DataType_QAsymmS8:</div> +<div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>;</div> +<div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  <span class="keywordflow">case</span> DataType_QSymmS8:</div> +<div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a>;</div> +<div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  <span class="keywordflow">case</span> DataType_QuantisedAsymm8:</div> +<div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <span class="keywordflow">case</span> DataType_QAsymmU8:</div> +<div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>;</div> +<div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  <span class="keywordflow">case</span> DataType_QSymmS16:</div> +<div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  <span class="keywordflow">case</span> DataType_QuantisedSymm16:</div> +<div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>;</div> +<div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <span class="keywordflow">case</span> DataType_Signed32:</div> +<div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>;</div> +<div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <span class="keywordflow">case</span> DataType_Signed64:</div> +<div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d">armnn::DataType::Signed64</a>;</div> +<div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <span class="keywordflow">case</span> DataType_Float32:</div> +<div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>;</div> +<div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  <span class="keywordflow">case</span> DataType_Float16:</div> +<div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>;</div> +<div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <span class="keywordflow">case</span> DataType_Boolean:</div> +<div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  type = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a>;</div> +<div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  {</div> +<div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <a class="code" href="structarmnn_1_1_check_location.html">CheckLocation</a> location = <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Unsupported data type {0} = {1}. {2}"</span>,</div> +<div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  tensorPtr->dataType(),</div> +<div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  EnumNameDataType(tensorPtr->dataType()),</div> +<div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  location.<a class="code" href="structarmnn_1_1_check_location.html#a5e3562cda960da001597e7dd5679b140">AsString</a>()));</div> +<div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  }</div> +<div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  }</div> +<div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  </div> +<div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <span class="keywordtype">float</span> quantizationScale = tensorPtr->quantizationScale();</div> +<div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  int32_t quantizationOffset = tensorPtr->quantizationOffset();</div> +<div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  </div> +<div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  <span class="keywordflow">if</span> (tensorPtr->dimensionality() == <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(Dimensionality::Scalar))</div> +<div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  {</div> +<div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>{<a class="code" href="namespacearmnn.html#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">armnn::Dimensionality::Scalar</a>},</div> +<div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  type,</div> +<div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  quantizationScale,</div> +<div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  quantizationOffset);</div> +<div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  }</div> +<div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (tensorPtr->dimensionality() == <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(Dimensionality::NotSpecified))</div> +<div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  {</div> +<div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> result(<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>{Dimensionality::NotSpecified},</div> +<div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  type,</div> +<div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  quantizationScale,</div> +<div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  quantizationOffset);</div> +<div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  <span class="keywordflow">return</span> result;</div> +<div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  }</div> +<div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  </div> +<div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <span class="keyword">auto</span> dimensions = tensorPtr->dimensions();</div> +<div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size = dimensions->size();</div> +<div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  std::vector<unsigned int> outputDims(dimensions->begin(), dimensions->begin() + size);</div> +<div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <span class="keywordtype">bool</span> dimensionsSpecificity[<a class="code" href="namespacearmnn.html#abdcd184ed3bd648bb31d385040cafd5d">armnn::MaxNumOfTensorDimensions</a>];</div> +<div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  std::fill_n(dimensionsSpecificity, <a class="code" href="namespacearmnn.html#abdcd184ed3bd648bb31d385040cafd5d">armnn::MaxNumOfTensorDimensions</a>, <span class="keyword">true</span>);</div> +<div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <span class="comment">// For backwards compatibility check if the dimensionSpecificity vector is present first.</span></div> +<div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  <span class="comment">// The default is to have dimensionSpecificity set to all true's anyway.</span></div> +<div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <span class="keywordflow">if</span> (tensorPtr->dimensionSpecificity() != <span class="keyword">nullptr</span>)</div> +<div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  {</div> +<div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  <span class="keyword">auto</span> dimensionSpecificity = tensorPtr->dimensionSpecificity();</div> +<div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  size = dimensionSpecificity->size();</div> +<div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < size; ++i)</div> +<div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  {</div> +<div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  dimensionsSpecificity[i] = dimensionSpecificity->Get(i);</div> +<div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  }</div> +<div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  }</div> +<div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  <span class="comment">// Construct a TensorShape</span></div> +<div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> shape(size, outputDims.data(), dimensionsSpecificity);</div> <div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  </div> -<div class="line"><a name="l00760"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da"> 760</a></span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(<a class="code" href="namespacearmnn_deserializer.html#a68b76ee033fdd629404369171c3d4f90">ConstTensorRawPtr</a> constTensorPtr)</div> -<div class="line"><a name="l00761"></a><span class="lineno"> 761</span> {</div> -<div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  <a class="code" href="_deserializer_8cpp.html#a637ba180b64a3cd1a4f83d048a030772">CHECK_CONST_TENSOR_PTR</a>(constTensorPtr);</div> -<div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> tensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(constTensorPtr->info());</div> -<div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">SetConstant</a>();</div> -<div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  </div> -<div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  <span class="keywordflow">switch</span> (constTensorPtr->data_type())</div> -<div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  {</div> -<div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  <span class="keywordflow">case</span> ConstTensorData_ByteData:</div> -<div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  {</div> -<div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  <span class="keyword">auto</span> byteData = constTensorPtr->data_as_ByteData()->data();</div> -<div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  <a class="code" href="_deserializer_8cpp.html#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(byteData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div> -<div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a>(tensorInfo, byteData->data());</div> -<div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  }</div> -<div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  <span class="keywordflow">case</span> ConstTensorData_ShortData:</div> -<div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  {</div> -<div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <span class="keyword">auto</span> shortData = constTensorPtr->data_as_ShortData()->data();</div> -<div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <a class="code" href="_deserializer_8cpp.html#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(shortData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div> -<div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a>(tensorInfo, shortData->data());</div> -<div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  }</div> -<div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  <span class="keywordflow">case</span> ConstTensorData_IntData:</div> -<div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  {</div> -<div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  <span class="keyword">auto</span> intData = constTensorPtr->data_as_IntData()->data();</div> -<div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  <a class="code" href="_deserializer_8cpp.html#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(intData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div> -<div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a>(tensorInfo, intData->data());</div> -<div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  }</div> -<div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  <span class="keywordflow">case</span> ConstTensorData_LongData:</div> -<div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  {</div> -<div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <span class="keyword">auto</span> longData = constTensorPtr->data_as_LongData()->data();</div> -<div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  <a class="code" href="_deserializer_8cpp.html#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(longData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div> -<div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a>(tensorInfo, longData->data());</div> -<div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  }</div> -<div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  {</div> -<div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <a class="code" href="structarmnn_1_1_check_location.html">CheckLocation</a> location = <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Unsupported data type {0} = {1}. {2}"</span>,</div> -<div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  constTensorPtr->data_type(),</div> -<div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  EnumNameConstTensorData(constTensorPtr->data_type()),</div> -<div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  location.<a class="code" href="structarmnn_1_1_check_location.html#a5e3562cda960da001597e7dd5679b140">AsString</a>()));</div> -<div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  }</div> -<div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  }</div> -<div class="line"><a name="l00801"></a><span class="lineno"> 801</span> }</div> -<div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  </div> -<div class="line"><a name="l00803"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac337f5478049cba1da222da655be49cc"> 803</a></span> <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac337f5478049cba1da222da655be49cc">IDeserializer::DeserializerImpl::GetInputs</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l00804"></a><span class="lineno"> 804</span> {</div> -<div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graphPtr, 0, layerIndex);</div> -<div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <span class="keyword">auto</span> layer = GetBaseLayer(graphPtr, layerIndex);</div> -<div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& numInputs = layer->inputSlots()->size();</div> -<div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  </div> -<div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> result(numInputs);</div> -<div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  </div> -<div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<numInputs; ++i)</div> -<div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  {</div> -<div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <span class="keyword">auto</span> inputId = <a class="code" href="_verification_helpers_8hpp.html#aaef93dc9a69f51b59f3cdd0ff0165927">CHECKED_NON_NEGATIVE</a>(<span class="keyword">static_cast<</span>int32_t<span class="keyword">></span></div> -<div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  (layer->inputSlots()->Get(i)->connection()->sourceLayerIndex()));</div> -<div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  result[i] = GetBaseLayer(graphPtr, inputId)->outputSlots()->Get(0)->tensorInfo();</div> -<div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  }</div> -<div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  <span class="keywordflow">return</span> result;</div> -<div class="line"><a name="l00818"></a><span class="lineno"> 818</span> }</div> -<div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  </div> -<div class="line"><a name="l00820"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a9069127d4430d97fe0f2c53fb2c32ab9"> 820</a></span> <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a9069127d4430d97fe0f2c53fb2c32ab9">IDeserializer::DeserializerImpl::GetOutputs</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l00821"></a><span class="lineno"> 821</span> {</div> -<div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graphPtr, 0, layerIndex);</div> -<div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  <span class="keyword">auto</span> layer = GetBaseLayer(graphPtr, layerIndex);</div> -<div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& numOutputs = layer->outputSlots()->size();</div> -<div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  </div> -<div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> result(numOutputs);</div> -<div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  </div> -<div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<numOutputs; ++i)</div> -<div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  {</div> -<div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  result[i] = layer->outputSlots()->Get(i)->tensorInfo();</div> -<div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  }</div> -<div class="line"><a name="l00832"></a><span class="lineno"> 832</span>  <span class="keywordflow">return</span> result;</div> -<div class="line"><a name="l00833"></a><span class="lineno"> 833</span> }</div> -<div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  </div> -<div class="line"><a name="l00835"></a><span class="lineno"> 835</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseUnsupportedLayer(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l00836"></a><span class="lineno"> 836</span> {</div> -<div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layerName = GetBaseLayer(graph, layerIndex)->layerName()->c_str();</div> -<div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Layer not supported. layerIndex: {0} "</span></div> -<div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  <span class="stringliteral">"layerName: {1} / {2}"</span>,</div> -<div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  layerIndex,</div> -<div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  layerName,</div> -<div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l00844"></a><span class="lineno"> 844</span> }</div> -<div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  </div> -<div class="line"><a name="l00846"></a><span class="lineno"> 846</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ResetParser()</div> -<div class="line"><a name="l00847"></a><span class="lineno"> 847</span> {</div> -<div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  m_Network = <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a>(<span class="keyword">nullptr</span>, <span class="keyword">nullptr</span>);</div> -<div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  m_InputBindings.clear();</div> -<div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  m_OutputBindings.clear();</div> -<div class="line"><a name="l00851"></a><span class="lineno"> 851</span> }</div> -<div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  </div> -<div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  </div> -<div class="line"><a name="l00854"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a32a96909bc8a8ee9076bd4d5c1028301"> 854</a></span> <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a32a96909bc8a8ee9076bd4d5c1028301">IDeserializer::DeserializerImpl::CreateNetworkFromBinary</a>(<span class="keyword">const</span> std::vector<uint8_t>& binaryContent)</div> -<div class="line"><a name="l00855"></a><span class="lineno"> 855</span> {</div> -<div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  ResetParser();</div> -<div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph = LoadGraphFromBinary(binaryContent.data(), binaryContent.size());</div> -<div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  <span class="keywordflow">return</span> CreateNetworkFromGraph(graph);</div> -<div class="line"><a name="l00859"></a><span class="lineno"> 859</span> }</div> -<div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  </div> -<div class="line"><a name="l00861"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#aa83e3be25485ec6d6e5a2b21f8201a59"> 861</a></span> <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a32a96909bc8a8ee9076bd4d5c1028301">IDeserializer::DeserializerImpl::CreateNetworkFromBinary</a>(std::istream& binaryContent)</div> -<div class="line"><a name="l00862"></a><span class="lineno"> 862</span> {</div> -<div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  ResetParser();</div> -<div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <span class="keywordflow">if</span> (binaryContent.fail()) {</div> -<div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) << (std::string(<span class="stringliteral">"Cannot read input"</span>));</div> -<div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unable to read Input stream data"</span>);</div> -<div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  }</div> -<div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  binaryContent.seekg(0, std::ios::end);</div> -<div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  <span class="keyword">const</span> std::streamoff size = binaryContent.tellg();</div> -<div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  std::vector<char> content(<span class="keyword">static_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(size));</div> -<div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  binaryContent.seekg(0);</div> -<div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  binaryContent.read(content.data(), <span class="keyword">static_cast<</span>std::streamsize<span class="keyword">></span>(size));</div> -<div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph = LoadGraphFromBinary(<span class="keyword">reinterpret_cast<</span>uint8_t*<span class="keyword">></span>(content.data()), <span class="keyword">static_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(size));</div> -<div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  <span class="keywordflow">return</span> CreateNetworkFromGraph(graph);</div> -<div class="line"><a name="l00875"></a><span class="lineno"> 875</span> }</div> -<div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  </div> -<div class="line"><a name="l00877"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a0bab2006e8fafc4a7fd02efa536f2828"> 877</a></span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a0bab2006e8fafc4a7fd02efa536f2828">IDeserializer::DeserializerImpl::LoadGraphFromBinary</a>(<span class="keyword">const</span> uint8_t* binaryContent, <span class="keywordtype">size_t</span> len)</div> -<div class="line"><a name="l00878"></a><span class="lineno"> 878</span> {</div> -<div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  <span class="keywordflow">if</span> (binaryContent == <span class="keyword">nullptr</span>)</div> -<div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  {</div> -<div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(fmt::format(<span class="stringliteral">"Invalid (null) binary content {}"</span>,</div> -<div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  }</div> -<div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  flatbuffers::Verifier verifier(binaryContent, len);</div> -<div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  <span class="keywordflow">if</span> (verifier.VerifyBuffer<SerializedGraph>() == <span class="keyword">false</span>)</div> -<div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  {</div> -<div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Buffer doesn't conform to the expected Armnn "</span></div> -<div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  <span class="stringliteral">"flatbuffers format. size:{0} {1}"</span>,</div> -<div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  len,</div> -<div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  }</div> -<div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  <span class="keywordflow">return</span> GetSerializedGraph(binaryContent);</div> -<div class="line"><a name="l00893"></a><span class="lineno"> 893</span> }</div> -<div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  </div> -<div class="line"><a name="l00895"></a><span class="lineno"> 895</span> <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> IDeserializer::DeserializerImpl::CreateNetworkFromGraph(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div> -<div class="line"><a name="l00896"></a><span class="lineno"> 896</span> {</div> -<div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  <span class="keywordflow">if</span> (graph == <span class="keyword">nullptr</span>)</div> -<div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  {</div> -<div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"CreateNetworkFromGraph: graph pointer is null"</span>);</div> -<div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  }</div> -<div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  m_Network = INetwork::Create();</div> -<div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex = 0;</div> -<div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="keywordflow">for</span> (AnyLayer <span class="keyword">const</span>* layer : *graph->layers())</div> -<div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  {</div> -<div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  <span class="keywordflow">if</span> (layer->layer_type() != Layer_InputLayer &&</div> -<div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  layer->layer_type() != Layer_OutputLayer)</div> -<div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  {</div> -<div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  <span class="comment">// lookup and call the parser function</span></div> -<div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  <span class="keyword">auto</span>& parserFunction = m_ParserFunctions[layer->layer_type()];</div> -<div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  (this->*parserFunction)(graph, layerIndex);</div> -<div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  }</div> -<div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  ++layerIndex;</div> +<div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  <span class="keyword">auto</span> quantizationScales = tensorPtr->quantizationScales();</div> +<div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  <span class="keywordflow">if</span> (quantizationScales)</div> +<div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  {</div> +<div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationScalesSize = quantizationScales->size();</div> +<div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  std::vector<float> scales(quantizationScales->begin(), quantizationScales->begin() + quantizationScalesSize);</div> +<div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim = tensorPtr->quantizationDim();</div> +<div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> result(shape,</div> +<div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  type,</div> +<div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  scales,</div> +<div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  quantizationDim);</div> +<div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  <span class="keywordflow">return</span> result;</div> +<div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  }</div> +<div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  </div> +<div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  <span class="comment">// two statements (on purpose) for easier debugging:</span></div> +<div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> result(shape,</div> +<div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  type,</div> +<div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  quantizationScale,</div> +<div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  quantizationOffset);</div> +<div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  </div> +<div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  <span class="keywordflow">return</span> result;</div> +<div class="line"><a name="l00780"></a><span class="lineno"> 780</span> }</div> +<div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  </div> +<div class="line"><a name="l00782"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da"> 782</a></span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(<a class="code" href="namespacearmnn_deserializer.html#a68b76ee033fdd629404369171c3d4f90">ConstTensorRawPtr</a> constTensorPtr)</div> +<div class="line"><a name="l00783"></a><span class="lineno"> 783</span> {</div> +<div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <a class="code" href="_deserializer_8cpp.html#a637ba180b64a3cd1a4f83d048a030772">CHECK_CONST_TENSOR_PTR</a>(constTensorPtr);</div> +<div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> tensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(constTensorPtr->info());</div> +<div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">SetConstant</a>();</div> +<div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  </div> +<div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <span class="keywordflow">switch</span> (constTensorPtr->data_type())</div> +<div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  {</div> +<div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <span class="keywordflow">case</span> ConstTensorData_ByteData:</div> +<div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  {</div> +<div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <span class="keyword">auto</span> byteData = constTensorPtr->data_as_ByteData()->data();</div> +<div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  <a class="code" href="_deserializer_8cpp.html#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(byteData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div> +<div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a>(tensorInfo, byteData->data());</div> +<div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  }</div> +<div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <span class="keywordflow">case</span> ConstTensorData_ShortData:</div> +<div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  {</div> +<div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <span class="keyword">auto</span> shortData = constTensorPtr->data_as_ShortData()->data();</div> +<div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  <a class="code" href="_deserializer_8cpp.html#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(shortData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div> +<div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a>(tensorInfo, shortData->data());</div> +<div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  }</div> +<div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <span class="keywordflow">case</span> ConstTensorData_IntData:</div> +<div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  {</div> +<div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  <span class="keyword">auto</span> intData = constTensorPtr->data_as_IntData()->data();</div> +<div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <a class="code" href="_deserializer_8cpp.html#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(intData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div> +<div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a>(tensorInfo, intData->data());</div> +<div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  }</div> +<div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <span class="keywordflow">case</span> ConstTensorData_LongData:</div> +<div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  {</div> +<div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <span class="keyword">auto</span> longData = constTensorPtr->data_as_LongData()->data();</div> +<div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <a class="code" href="_deserializer_8cpp.html#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(longData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div> +<div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a>(tensorInfo, longData->data());</div> +<div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  }</div> +<div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  {</div> +<div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  <a class="code" href="structarmnn_1_1_check_location.html">CheckLocation</a> location = <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Unsupported data type {0} = {1}. {2}"</span>,</div> +<div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  constTensorPtr->data_type(),</div> +<div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  EnumNameConstTensorData(constTensorPtr->data_type()),</div> +<div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  location.<a class="code" href="structarmnn_1_1_check_location.html#a5e3562cda960da001597e7dd5679b140">AsString</a>()));</div> +<div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  }</div> +<div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  }</div> +<div class="line"><a name="l00823"></a><span class="lineno"> 823</span> }</div> +<div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  </div> +<div class="line"><a name="l00825"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac337f5478049cba1da222da655be49cc"> 825</a></span> <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac337f5478049cba1da222da655be49cc">IDeserializer::DeserializerImpl::GetInputs</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l00826"></a><span class="lineno"> 826</span> {</div> +<div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graphPtr, 0, layerIndex);</div> +<div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  <span class="keyword">auto</span> layer = GetBaseLayer(graphPtr, layerIndex);</div> +<div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& numInputs = layer->inputSlots()->size();</div> +<div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  </div> +<div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> result(numInputs);</div> +<div class="line"><a name="l00832"></a><span class="lineno"> 832</span>  </div> +<div class="line"><a name="l00833"></a><span class="lineno"> 833</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<numInputs; ++i)</div> +<div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  {</div> +<div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  <span class="keyword">auto</span> inputId = <a class="code" href="_verification_helpers_8hpp.html#aaef93dc9a69f51b59f3cdd0ff0165927">CHECKED_NON_NEGATIVE</a>(<span class="keyword">static_cast<</span>int32_t<span class="keyword">></span></div> +<div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  (layer->inputSlots()->Get(i)->connection()->sourceLayerIndex()));</div> +<div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  result[i] = GetBaseLayer(graphPtr, inputId)->outputSlots()->Get(0)->tensorInfo();</div> +<div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  }</div> +<div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  <span class="keywordflow">return</span> result;</div> +<div class="line"><a name="l00840"></a><span class="lineno"> 840</span> }</div> +<div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  </div> +<div class="line"><a name="l00842"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a9069127d4430d97fe0f2c53fb2c32ab9"> 842</a></span> <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a9069127d4430d97fe0f2c53fb2c32ab9">IDeserializer::DeserializerImpl::GetOutputs</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l00843"></a><span class="lineno"> 843</span> {</div> +<div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graphPtr, 0, layerIndex);</div> +<div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  <span class="keyword">auto</span> layer = GetBaseLayer(graphPtr, layerIndex);</div> +<div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& numOutputs = layer->outputSlots()->size();</div> +<div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  </div> +<div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> result(numOutputs);</div> +<div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  </div> +<div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<numOutputs; ++i)</div> +<div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  {</div> +<div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  result[i] = layer->outputSlots()->Get(i)->tensorInfo();</div> +<div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  }</div> +<div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  <span class="keywordflow">return</span> result;</div> +<div class="line"><a name="l00855"></a><span class="lineno"> 855</span> }</div> +<div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  </div> +<div class="line"><a name="l00857"></a><span class="lineno"> 857</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseUnsupportedLayer(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l00858"></a><span class="lineno"> 858</span> {</div> +<div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layerName = GetBaseLayer(graph, layerIndex)->layerName()->c_str();</div> +<div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Layer not supported. layerIndex: {0} "</span></div> +<div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <span class="stringliteral">"layerName: {1} / {2}"</span>,</div> +<div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  layerIndex,</div> +<div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  layerName,</div> +<div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l00866"></a><span class="lineno"> 866</span> }</div> +<div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  </div> +<div class="line"><a name="l00868"></a><span class="lineno"> 868</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ResetParser()</div> +<div class="line"><a name="l00869"></a><span class="lineno"> 869</span> {</div> +<div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  m_Network = <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a>(<span class="keyword">nullptr</span>, <span class="keyword">nullptr</span>);</div> +<div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  m_InputBindings.clear();</div> +<div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  m_OutputBindings.clear();</div> +<div class="line"><a name="l00873"></a><span class="lineno"> 873</span> }</div> +<div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  </div> +<div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  </div> +<div class="line"><a name="l00876"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a32a96909bc8a8ee9076bd4d5c1028301"> 876</a></span> <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a32a96909bc8a8ee9076bd4d5c1028301">IDeserializer::DeserializerImpl::CreateNetworkFromBinary</a>(<span class="keyword">const</span> std::vector<uint8_t>& binaryContent)</div> +<div class="line"><a name="l00877"></a><span class="lineno"> 877</span> {</div> +<div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  ResetParser();</div> +<div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph = LoadGraphFromBinary(binaryContent.data(), binaryContent.size());</div> +<div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  <span class="keywordflow">return</span> CreateNetworkFromGraph(graph);</div> +<div class="line"><a name="l00881"></a><span class="lineno"> 881</span> }</div> +<div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  </div> +<div class="line"><a name="l00883"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#aa83e3be25485ec6d6e5a2b21f8201a59"> 883</a></span> <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a32a96909bc8a8ee9076bd4d5c1028301">IDeserializer::DeserializerImpl::CreateNetworkFromBinary</a>(std::istream& binaryContent)</div> +<div class="line"><a name="l00884"></a><span class="lineno"> 884</span> {</div> +<div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  ResetParser();</div> +<div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  <span class="keywordflow">if</span> (binaryContent.fail()) {</div> +<div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) << (std::string(<span class="stringliteral">"Cannot read input"</span>));</div> +<div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unable to read Input stream data"</span>);</div> +<div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  }</div> +<div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  binaryContent.seekg(0, std::ios::end);</div> +<div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  <span class="keyword">const</span> std::streamoff size = binaryContent.tellg();</div> +<div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  std::vector<char> content(<span class="keyword">static_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(size));</div> +<div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  binaryContent.seekg(0);</div> +<div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  binaryContent.read(content.data(), <span class="keyword">static_cast<</span>std::streamsize<span class="keyword">></span>(size));</div> +<div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph = LoadGraphFromBinary(<span class="keyword">reinterpret_cast<</span>uint8_t*<span class="keyword">></span>(content.data()), <span class="keyword">static_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(size));</div> +<div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  <span class="keywordflow">return</span> CreateNetworkFromGraph(graph);</div> +<div class="line"><a name="l00897"></a><span class="lineno"> 897</span> }</div> +<div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  </div> +<div class="line"><a name="l00899"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a0bab2006e8fafc4a7fd02efa536f2828"> 899</a></span> <a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a0bab2006e8fafc4a7fd02efa536f2828">IDeserializer::DeserializerImpl::LoadGraphFromBinary</a>(<span class="keyword">const</span> uint8_t* binaryContent, <span class="keywordtype">size_t</span> len)</div> +<div class="line"><a name="l00900"></a><span class="lineno"> 900</span> {</div> +<div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  <span class="keywordflow">if</span> (binaryContent == <span class="keyword">nullptr</span>)</div> +<div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  {</div> +<div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(fmt::format(<span class="stringliteral">"Invalid (null) binary content {}"</span>,</div> +<div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  }</div> +<div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  flatbuffers::Verifier verifier(binaryContent, len);</div> +<div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  <span class="keywordflow">if</span> (verifier.VerifyBuffer<SerializedGraph>() == <span class="keyword">false</span>)</div> +<div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  {</div> +<div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Buffer doesn't conform to the expected Armnn "</span></div> +<div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  <span class="stringliteral">"flatbuffers format. size:{0} {1}"</span>,</div> +<div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  len,</div> +<div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> <div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  }</div> -<div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  </div> -<div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  SetupInputLayers(graph);</div> -<div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  SetupOutputLayers(graph);</div> -<div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  </div> -<div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  <span class="comment">// establish the connections from the layer outputs to the inputs of the subsequent layers</span></div> -<div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& graphIt : m_GraphConnections)</div> +<div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  <span class="keywordflow">return</span> GetSerializedGraph(binaryContent);</div> +<div class="line"><a name="l00915"></a><span class="lineno"> 915</span> }</div> +<div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  </div> +<div class="line"><a name="l00917"></a><span class="lineno"> 917</span> <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> IDeserializer::DeserializerImpl::CreateNetworkFromGraph(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div> +<div class="line"><a name="l00918"></a><span class="lineno"> 918</span> {</div> +<div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  <span class="keywordflow">if</span> (graph == <span class="keyword">nullptr</span>)</div> <div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  {</div> -<div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  Connections& connections = graphIt.second;</div> -<div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& outputIt : connections.outputSlots)</div> -<div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  {</div> -<div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSlotIndex = outputIt.first;</div> -<div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  <a class="code" href="classarmnn_1_1_i_output_slot.html">IOutputSlot</a>* outputSlot = outputIt.second;</div> -<div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  <span class="keywordflow">if</span> (connections.inputSlots.find(outputSlotIndex) != connections.inputSlots.end())</div> -<div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  {</div> -<div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <span class="keywordflow">for</span> (<a class="code" href="classarmnn_1_1_i_input_slot.html">IInputSlot</a>* inputSlot : connections.inputSlots[outputSlotIndex])</div> -<div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  {</div> -<div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  outputSlot-><a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(*inputSlot);</div> -<div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  }</div> -<div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  }</div> +<div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"CreateNetworkFromGraph: graph pointer is null"</span>);</div> +<div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  }</div> +<div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  m_Network = INetwork::Create();</div> +<div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex = 0;</div> +<div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  <span class="keywordflow">for</span> (AnyLayer <span class="keyword">const</span>* layer : *graph->layers())</div> +<div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  {</div> +<div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  <span class="keywordflow">if</span> (layer->layer_type() != Layer_InputLayer &&</div> +<div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  layer->layer_type() != Layer_OutputLayer)</div> +<div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  {</div> +<div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  <span class="comment">// lookup and call the parser function</span></div> +<div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  <span class="keyword">auto</span>& parserFunction = m_ParserFunctions[layer->layer_type()];</div> +<div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  (this->*parserFunction)(graph, layerIndex);</div> <div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  }</div> -<div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  }</div> -<div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  </div> -<div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  <span class="keywordflow">return</span> std::move(m_Network);</div> -<div class="line"><a name="l00937"></a><span class="lineno"> 937</span> }</div> -<div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  </div> -<div class="line"><a name="l00939"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a5de68e32eabd643f55a35f288ba10294"> 939</a></span> <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html">BindingPointInfo</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a5de68e32eabd643f55a35f288ba10294">IDeserializer::DeserializerImpl::GetNetworkInputBindingInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex,</div> -<div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="keyword">const</span> std::string& name)<span class="keyword"> const</span></div> -<div class="line"><a name="l00941"></a><span class="lineno"> 941</span> <span class="keyword"></span>{</div> -<div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> -<div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> inputBinding : m_InputBindings)</div> -<div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  {</div> -<div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  <span class="keywordflow">if</span> (inputBinding.first == name)</div> -<div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  {</div> -<div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <span class="keywordflow">return</span> inputBinding.second;</div> -<div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  }</div> -<div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  }</div> -<div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"No input binding found for layer:{0} / {1}"</span>,</div> -<div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  name,</div> -<div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l00953"></a><span class="lineno"> 953</span> }</div> -<div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  </div> -<div class="line"><a name="l00955"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a2f66de823cd61765a40407fee754655e"> 955</a></span> <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html">BindingPointInfo</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a2f66de823cd61765a40407fee754655e">IDeserializer::DeserializerImpl::GetNetworkOutputBindingInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex,</div> -<div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  <span class="keyword">const</span> std::string& name)<span class="keyword"> const</span></div> -<div class="line"><a name="l00957"></a><span class="lineno"> 957</span> <span class="keyword"></span>{</div> -<div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> -<div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> outputBinding : m_OutputBindings)</div> -<div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  {</div> -<div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  <span class="keywordflow">if</span> (outputBinding.first == name)</div> -<div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  {</div> -<div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  <span class="keywordflow">return</span> outputBinding.second;</div> -<div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  }</div> -<div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  }</div> -<div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"No output binding found for layer:{0} / {1}"</span>,</div> -<div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  name,</div> -<div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l00969"></a><span class="lineno"> 969</span> }</div> -<div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  </div> -<div class="line"><a name="l00971"></a><span class="lineno"> 971</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> IDeserializer::DeserializerImpl::GetInputLayerInVector(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">int</span> targetId)</div> -<div class="line"><a name="l00972"></a><span class="lineno"> 972</span> {</div> -<div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < graph->layers()->size(); i++)</div> -<div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  {</div> -<div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <span class="keyword">auto</span> layer = graph->layers()->Get(i);</div> -<div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  <span class="keywordflow">if</span> (layer->layer_type() == Layer::Layer_InputLayer)</div> -<div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  {</div> -<div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <span class="keyword">auto</span> layerBindingId = layer->layer_as_InputLayer()->base()->layerBindingId();</div> -<div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  <span class="keywordflow">if</span> (layerBindingId == targetId)</div> -<div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  {</div> -<div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  <span class="keywordflow">return</span> i;</div> -<div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  }</div> -<div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  }</div> -<div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  }</div> -<div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Input layer with given layerBindingId not found"</span>);</div> -<div class="line"><a name="l00986"></a><span class="lineno"> 986</span> }</div> -<div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  </div> -<div class="line"><a name="l00988"></a><span class="lineno"> 988</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> IDeserializer::DeserializerImpl::GetOutputLayerInVector(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">int</span> targetId)</div> -<div class="line"><a name="l00989"></a><span class="lineno"> 989</span> {</div> -<div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < graph->layers()->size(); i++)</div> -<div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  {</div> -<div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  <span class="keyword">auto</span> layer = graph->layers()->Get(i);</div> -<div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  <span class="keywordflow">if</span> (layer->layer_type() == Layer::Layer_OutputLayer)</div> -<div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  {</div> -<div class="line"><a name="l00995"></a><span class="lineno"> 995</span>  <span class="keyword">auto</span> layerBindingId = layer->layer_as_OutputLayer()->base()->layerBindingId();</div> -<div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  <span class="keywordflow">if</span> (layerBindingId == targetId)</div> -<div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  {</div> -<div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  <span class="keywordflow">return</span> i;</div> -<div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  }</div> -<div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  }</div> -<div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  }</div> -<div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Output layer with given layerBindingId not found"</span>);</div> -<div class="line"><a name="l01003"></a><span class="lineno"> 1003</span> }</div> -<div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>  </div> -<div class="line"><a name="l01005"></a><span class="lineno"> 1005</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> IDeserializer::DeserializerImpl::GetLayerIndexInVector(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> targetIndex)</div> -<div class="line"><a name="l01006"></a><span class="lineno"> 1006</span> {</div> -<div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < graph->layers()->size(); i++)</div> -<div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  {</div> -<div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> layer = GetBaseLayer(graph, i);</div> -<div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  <span class="keywordflow">if</span> (layer->index() == targetIndex)</div> -<div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>  {</div> -<div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  <span class="keywordflow">return</span> i;</div> -<div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  }</div> -<div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  }</div> -<div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Layer with given index not found"</span>);</div> -<div class="line"><a name="l01016"></a><span class="lineno"> 1016</span> }</div> -<div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  </div> -<div class="line"><a name="l01018"></a><span class="lineno"> 1018</span> IDeserializer::DeserializerImpl::FeatureVersions IDeserializer::DeserializerImpl::GetFeatureVersions(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div> -<div class="line"><a name="l01019"></a><span class="lineno"> 1019</span> {</div> -<div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>  IDeserializer::DeserializerImpl::FeatureVersions versions;</div> -<div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  </div> -<div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  <span class="keywordflow">if</span> (graph->featureVersions())</div> -<div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>  {</div> -<div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>  versions.m_BindingIdScheme = graph->featureVersions()->bindingIdsScheme();</div> -<div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>  versions.m_WeightsLayoutScheme = graph->featureVersions()->weightsLayoutScheme();</div> -<div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>  versions.m_ConstTensorsAsInputs = graph->featureVersions()->constantTensorsAsInputs();</div> -<div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  }</div> -<div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>  </div> -<div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  <span class="keywordflow">return</span> versions;</div> -<div class="line"><a name="l01030"></a><span class="lineno"> 1030</span> }</div> -<div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  </div> -<div class="line"><a name="l01032"></a><span class="lineno"> 1032</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::SetupInputLayers(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div> -<div class="line"><a name="l01033"></a><span class="lineno"> 1033</span> {</div> -<div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>  <a class="code" href="_deserializer_8cpp.html#ab90eef134463f7b44cd4c9cfb2529825">CHECK_GRAPH</a>(graph, 0);</div> -<div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = graph->inputIds()->size();</div> -<div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>  m_InputBindings.clear();</div> -<div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  m_InputBindings.reserve(numInputs);</div> -<div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  </div> -<div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputs; i++)</div> -<div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>  {</div> -<div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputLayerIndex = 0xFFFFFFFF;</div> -<div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  <span class="keywordflow">if</span> (GetFeatureVersions(graph).m_BindingIdScheme == 0)</div> -<div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  {</div> -<div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputId = armnn::numeric_cast<unsigned int>(graph->inputIds()->Get(i));</div> -<div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>  inputLayerIndex = GetLayerIndexInVector(graph, inputId);</div> -<div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>  }</div> -<div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  {</div> -<div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> inputId = graph->inputIds()->Get(i);</div> -<div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  inputLayerIndex = GetInputLayerInVector(graph, inputId);</div> -<div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>  }</div> -<div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>  </div> -<div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = GetBaseLayer(graph, inputLayerIndex);</div> -<div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>  </div> -<div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>  <span class="comment">// GetBindingLayerInfo expect the index to be index in the vector not index property on each layer base</span></div> -<div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = GetBindingLayerInfo(graph, inputLayerIndex);</div> -<div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  <span class="keywordflow">if</span> (baseLayer->layerName()->c_str() == <span class="keyword">nullptr</span>)</div> -<div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>  {</div> -<div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Input with layer index [{0}] has no name"</span>, inputLayerIndex));</div> -<div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  }</div> -<div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  </div> -<div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* inputLayer =</div> -<div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>  m_Network->AddInputLayer(bindingId, baseLayer->layerName()->c_str());</div> -<div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  </div> -<div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& tensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(baseLayer->outputSlots()->Get(0)->tensorInfo());</div> -<div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  inputLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div> -<div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  RegisterOutputSlots(graph, inputLayerIndex, inputLayer);</div> -<div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  </div> -<div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  <a class="code" href="namespacearmnn.html#a280670a263dc4fd40491f6d0a2737f44">BindingPointInfo</a> bindingInfo = {bindingId, tensorInfo};</div> -<div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>  m_InputBindings.push_back(std::make_pair(baseLayer->layerName()->c_str(), bindingInfo));</div> -<div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  }</div> -<div class="line"><a name="l01072"></a><span class="lineno"> 1072</span> }</div> -<div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  </div> -<div class="line"><a name="l01074"></a><span class="lineno"> 1074</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::SetupOutputLayers(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div> -<div class="line"><a name="l01075"></a><span class="lineno"> 1075</span> {</div> -<div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>  <a class="code" href="_deserializer_8cpp.html#ab90eef134463f7b44cd4c9cfb2529825">CHECK_GRAPH</a>(graph, 0);</div> -<div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputs = graph->outputIds()->size();</div> -<div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>  m_OutputBindings.clear();</div> -<div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  m_OutputBindings.reserve(numOutputs);</div> -<div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>  </div> -<div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numOutputs; i++)</div> -<div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>  {</div> -<div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputLayerIndex = 0xFFFFFFFF;</div> -<div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>  <span class="keywordflow">if</span> (GetFeatureVersions(graph).m_BindingIdScheme == 0)</div> -<div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>  {</div> -<div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputId = armnn::numeric_cast<unsigned int>(graph->outputIds()->Get(i));</div> -<div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>  outputLayerIndex = GetLayerIndexInVector(graph, outputId);</div> -<div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>  }</div> -<div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>  {</div> -<div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> outputId = graph->outputIds()->Get(i);</div> -<div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>  outputLayerIndex = GetOutputLayerInVector(graph, outputId);</div> -<div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>  }</div> -<div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  </div> -<div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = GetBaseLayer(graph, outputLayerIndex);</div> -<div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  </div> -<div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>  <span class="comment">// GetBindingLayerInfo expect the index to be index in the vector not index property on each layer base</span></div> -<div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = GetBindingLayerInfo(graph, outputLayerIndex);</div> -<div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>  <span class="keywordflow">if</span> (baseLayer->layerName()->c_str() == <span class="keyword">nullptr</span>)</div> -<div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  {</div> -<div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Output with layer index [{0}] has no name"</span>, outputLayerIndex));</div> -<div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>  }</div> -<div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  </div> -<div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* outputLayer =</div> -<div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  m_Network->AddOutputLayer(bindingId, baseLayer->layerName()->c_str());</div> -<div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  </div> -<div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  RegisterInputSlots(graph, outputLayerIndex, outputLayer);</div> -<div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> sourceLayerIndex =</div> -<div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>  GetLayerIndexInVector(graph, baseLayer->inputSlots()->Get(0)->connection()->sourceLayerIndex());</div> -<div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSlotIndex =</div> -<div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  GetLayerIndexInVector(graph, baseLayer->inputSlots()->Get(0)->connection()->outputSlotIndex());</div> -<div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> sourceBaseLayer = GetBaseLayer(graph, sourceLayerIndex);</div> -<div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& tensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(</div> -<div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  sourceBaseLayer->outputSlots()->Get(outputSlotIndex)->tensorInfo());</div> -<div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>  <a class="code" href="namespacearmnn.html#a280670a263dc4fd40491f6d0a2737f44">BindingPointInfo</a> bindingInfo = {bindingId, tensorInfo};</div> -<div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>  m_OutputBindings.push_back(std::make_pair(baseLayer->layerName()->c_str(), bindingInfo));</div> -<div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>  }</div> -<div class="line"><a name="l01118"></a><span class="lineno"> 1118</span> }</div> -<div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  </div> -<div class="line"><a name="l01120"></a><span class="lineno"> 1120</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::RegisterOutputSlots(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph,</div> -<div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>  uint32_t layerIndex,</div> -<div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer)</div> -<div class="line"><a name="l01123"></a><span class="lineno"> 1123</span> {</div> -<div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>  <span class="keywordflow">if</span> (layer == <span class="keyword">nullptr</span>)</div> -<div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  {</div> -<div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(</div> -<div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  <span class="stringliteral">"RegisterOutputSlots: pointer to layer with index [{0}] is null"</span>, layerIndex));</div> -<div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>  }</div> -<div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = GetBaseLayer(graph, layerIndex);</div> -<div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>  <span class="keywordflow">if</span> (baseLayer->outputSlots()->size() != layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>())</div> -<div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>  {</div> -<div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The number of outputslots ({0}) does not match the number expected ({1})"</span></div> -<div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>  <span class="stringliteral">" for layer index: {2} {3}"</span>,</div> -<div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>  baseLayer->outputSlots()->size(),</div> -<div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>(),</div> -<div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>  layerIndex,</div> -<div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  ++layerIndex;</div> +<div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  }</div> +<div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  </div> +<div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  SetupInputLayers(graph);</div> +<div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  SetupOutputLayers(graph);</div> +<div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  </div> +<div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="comment">// establish the connections from the layer outputs to the inputs of the subsequent layers</span></div> +<div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& graphIt : m_GraphConnections)</div> +<div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  {</div> +<div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  Connections& connections = graphIt.second;</div> +<div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& outputIt : connections.outputSlots)</div> +<div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  {</div> +<div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSlotIndex = outputIt.first;</div> +<div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <a class="code" href="classarmnn_1_1_i_output_slot.html">IOutputSlot</a>* outputSlot = outputIt.second;</div> +<div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  <span class="keywordflow">if</span> (connections.inputSlots.find(outputSlotIndex) != connections.inputSlots.end())</div> +<div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  {</div> +<div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  <span class="keywordflow">for</span> (<a class="code" href="classarmnn_1_1_i_input_slot.html">IInputSlot</a>* inputSlot : connections.inputSlots[outputSlotIndex])</div> +<div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  {</div> +<div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  outputSlot-><a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(*inputSlot);</div> +<div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  }</div> +<div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  }</div> +<div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  }</div> +<div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  }</div> +<div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  </div> +<div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  <span class="keywordflow">return</span> std::move(m_Network);</div> +<div class="line"><a name="l00959"></a><span class="lineno"> 959</span> }</div> +<div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  </div> +<div class="line"><a name="l00961"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a5de68e32eabd643f55a35f288ba10294"> 961</a></span> <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html">BindingPointInfo</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a5de68e32eabd643f55a35f288ba10294">IDeserializer::DeserializerImpl::GetNetworkInputBindingInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex,</div> +<div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  <span class="keyword">const</span> std::string& name)<span class="keyword"> const</span></div> +<div class="line"><a name="l00963"></a><span class="lineno"> 963</span> <span class="keyword"></span>{</div> +<div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> +<div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> inputBinding : m_InputBindings)</div> +<div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  {</div> +<div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  <span class="keywordflow">if</span> (inputBinding.first == name)</div> +<div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  {</div> +<div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  <span class="keywordflow">return</span> inputBinding.second;</div> +<div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  }</div> +<div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  }</div> +<div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"No input binding found for layer:{0} / {1}"</span>,</div> +<div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  name,</div> +<div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l00975"></a><span class="lineno"> 975</span> }</div> +<div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  </div> +<div class="line"><a name="l00977"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a2f66de823cd61765a40407fee754655e"> 977</a></span> <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html">BindingPointInfo</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a2f66de823cd61765a40407fee754655e">IDeserializer::DeserializerImpl::GetNetworkOutputBindingInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex,</div> +<div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <span class="keyword">const</span> std::string& name)<span class="keyword"> const</span></div> +<div class="line"><a name="l00979"></a><span class="lineno"> 979</span> <span class="keyword"></span>{</div> +<div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> +<div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> outputBinding : m_OutputBindings)</div> +<div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  {</div> +<div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  <span class="keywordflow">if</span> (outputBinding.first == name)</div> +<div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  {</div> +<div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  <span class="keywordflow">return</span> outputBinding.second;</div> +<div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  }</div> +<div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  }</div> +<div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"No output binding found for layer:{0} / {1}"</span>,</div> +<div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  name,</div> +<div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l00991"></a><span class="lineno"> 991</span> }</div> +<div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  </div> +<div class="line"><a name="l00993"></a><span class="lineno"> 993</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> IDeserializer::DeserializerImpl::GetInputLayerInVector(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">int</span> targetId)</div> +<div class="line"><a name="l00994"></a><span class="lineno"> 994</span> {</div> +<div class="line"><a name="l00995"></a><span class="lineno"> 995</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < graph->layers()->size(); i++)</div> +<div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  {</div> +<div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  <span class="keyword">auto</span> layer = graph->layers()->Get(i);</div> +<div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  <span class="keywordflow">if</span> (layer->layer_type() == Layer::Layer_InputLayer)</div> +<div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  {</div> +<div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  <span class="keyword">auto</span> layerBindingId = layer->layer_as_InputLayer()->base()->layerBindingId();</div> +<div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  <span class="keywordflow">if</span> (layerBindingId == targetId)</div> +<div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  {</div> +<div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>  <span class="keywordflow">return</span> i;</div> +<div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>  }</div> +<div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  }</div> +<div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  }</div> +<div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Input layer with given layerBindingId not found"</span>);</div> +<div class="line"><a name="l01008"></a><span class="lineno"> 1008</span> }</div> +<div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  </div> +<div class="line"><a name="l01010"></a><span class="lineno"> 1010</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> IDeserializer::DeserializerImpl::GetOutputLayerInVector(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">int</span> targetId)</div> +<div class="line"><a name="l01011"></a><span class="lineno"> 1011</span> {</div> +<div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < graph->layers()->size(); i++)</div> +<div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  {</div> +<div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  <span class="keyword">auto</span> layer = graph->layers()->Get(i);</div> +<div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  <span class="keywordflow">if</span> (layer->layer_type() == Layer::Layer_OutputLayer)</div> +<div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  {</div> +<div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  <span class="keyword">auto</span> layerBindingId = layer->layer_as_OutputLayer()->base()->layerBindingId();</div> +<div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  <span class="keywordflow">if</span> (layerBindingId == targetId)</div> +<div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  {</div> +<div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>  <span class="keywordflow">return</span> i;</div> +<div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  }</div> +<div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  }</div> +<div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>  }</div> +<div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Output layer with given layerBindingId not found"</span>);</div> +<div class="line"><a name="l01025"></a><span class="lineno"> 1025</span> }</div> +<div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>  </div> +<div class="line"><a name="l01027"></a><span class="lineno"> 1027</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> IDeserializer::DeserializerImpl::GetLayerIndexInVector(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> targetIndex)</div> +<div class="line"><a name="l01028"></a><span class="lineno"> 1028</span> {</div> +<div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < graph->layers()->size(); i++)</div> +<div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>  {</div> +<div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> layer = GetBaseLayer(graph, i);</div> +<div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  <span class="keywordflow">if</span> (layer->index() == targetIndex)</div> +<div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>  {</div> +<div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>  <span class="keywordflow">return</span> i;</div> +<div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>  }</div> +<div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>  }</div> +<div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Layer with given index not found"</span>);</div> +<div class="line"><a name="l01038"></a><span class="lineno"> 1038</span> }</div> +<div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  </div> +<div class="line"><a name="l01040"></a><span class="lineno"> 1040</span> IDeserializer::DeserializerImpl::FeatureVersions IDeserializer::DeserializerImpl::GetFeatureVersions(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div> +<div class="line"><a name="l01041"></a><span class="lineno"> 1041</span> {</div> +<div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  IDeserializer::DeserializerImpl::FeatureVersions versions;</div> +<div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  </div> +<div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  <span class="keywordflow">if</span> (graph->featureVersions())</div> +<div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>  {</div> +<div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>  versions.m_BindingIdScheme = graph->featureVersions()->bindingIdsScheme();</div> +<div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  versions.m_WeightsLayoutScheme = graph->featureVersions()->weightsLayoutScheme();</div> +<div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  versions.m_ConstTensorsAsInputs = graph->featureVersions()->constantTensorsAsInputs();</div> +<div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  }</div> +<div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  </div> +<div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>  <span class="keywordflow">return</span> versions;</div> +<div class="line"><a name="l01052"></a><span class="lineno"> 1052</span> }</div> +<div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  </div> +<div class="line"><a name="l01054"></a><span class="lineno"> 1054</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::SetupInputLayers(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div> +<div class="line"><a name="l01055"></a><span class="lineno"> 1055</span> {</div> +<div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>  <a class="code" href="_deserializer_8cpp.html#ab90eef134463f7b44cd4c9cfb2529825">CHECK_GRAPH</a>(graph, 0);</div> +<div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = graph->inputIds()->size();</div> +<div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>  m_InputBindings.clear();</div> +<div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  m_InputBindings.reserve(numInputs);</div> +<div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  </div> +<div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputs; i++)</div> +<div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>  {</div> +<div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputLayerIndex = 0xFFFFFFFF;</div> +<div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  <span class="keywordflow">if</span> (GetFeatureVersions(graph).m_BindingIdScheme == 0)</div> +<div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  {</div> +<div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputId = armnn::numeric_cast<unsigned int>(graph->inputIds()->Get(i));</div> +<div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  inputLayerIndex = GetLayerIndexInVector(graph, inputId);</div> +<div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  }</div> +<div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>  {</div> +<div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> inputId = graph->inputIds()->Get(i);</div> +<div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>  inputLayerIndex = GetInputLayerInVector(graph, inputId);</div> +<div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  }</div> +<div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  </div> +<div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = GetBaseLayer(graph, inputLayerIndex);</div> +<div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>  </div> +<div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  <span class="comment">// GetBindingLayerInfo expect the index to be index in the vector not index property on each layer base</span></div> +<div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = GetBindingLayerInfo(graph, inputLayerIndex);</div> +<div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  <span class="keywordflow">if</span> (baseLayer->layerName()->c_str() == <span class="keyword">nullptr</span>)</div> +<div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>  {</div> +<div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Input with layer index [{0}] has no name"</span>, inputLayerIndex));</div> +<div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>  }</div> +<div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>  </div> +<div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* inputLayer =</div> +<div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>  m_Network->AddInputLayer(bindingId, baseLayer->layerName()->c_str());</div> +<div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>  </div> +<div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& tensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(baseLayer->outputSlots()->Get(0)->tensorInfo());</div> +<div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>  inputLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div> +<div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>  RegisterOutputSlots(graph, inputLayerIndex, inputLayer);</div> +<div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>  </div> +<div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>  <a class="code" href="namespacearmnn.html#a280670a263dc4fd40491f6d0a2737f44">BindingPointInfo</a> bindingInfo = {bindingId, tensorInfo};</div> +<div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>  m_InputBindings.push_back(std::make_pair(baseLayer->layerName()->c_str(), bindingInfo));</div> +<div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>  }</div> +<div class="line"><a name="l01094"></a><span class="lineno"> 1094</span> }</div> +<div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  </div> +<div class="line"><a name="l01096"></a><span class="lineno"> 1096</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::SetupOutputLayers(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div> +<div class="line"><a name="l01097"></a><span class="lineno"> 1097</span> {</div> +<div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  <a class="code" href="_deserializer_8cpp.html#ab90eef134463f7b44cd4c9cfb2529825">CHECK_GRAPH</a>(graph, 0);</div> +<div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputs = graph->outputIds()->size();</div> +<div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  m_OutputBindings.clear();</div> +<div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>  m_OutputBindings.reserve(numOutputs);</div> +<div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>  </div> +<div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numOutputs; i++)</div> +<div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  {</div> +<div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputLayerIndex = 0xFFFFFFFF;</div> +<div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  <span class="keywordflow">if</span> (GetFeatureVersions(graph).m_BindingIdScheme == 0)</div> +<div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  {</div> +<div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputId = armnn::numeric_cast<unsigned int>(graph->outputIds()->Get(i));</div> +<div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>  outputLayerIndex = GetLayerIndexInVector(graph, outputId);</div> +<div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  }</div> +<div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  {</div> +<div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> outputId = graph->outputIds()->Get(i);</div> +<div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  outputLayerIndex = GetOutputLayerInVector(graph, outputId);</div> +<div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>  }</div> +<div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>  </div> +<div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = GetBaseLayer(graph, outputLayerIndex);</div> +<div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  </div> +<div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  <span class="comment">// GetBindingLayerInfo expect the index to be index in the vector not index property on each layer base</span></div> +<div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = GetBindingLayerInfo(graph, outputLayerIndex);</div> +<div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>  <span class="keywordflow">if</span> (baseLayer->layerName()->c_str() == <span class="keyword">nullptr</span>)</div> +<div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>  {</div> +<div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Output with layer index [{0}] has no name"</span>, outputLayerIndex));</div> +<div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>  }</div> +<div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  </div> +<div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* outputLayer =</div> +<div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  m_Network->AddOutputLayer(bindingId, baseLayer->layerName()->c_str());</div> +<div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>  </div> +<div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  RegisterInputSlots(graph, outputLayerIndex, outputLayer);</div> +<div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> sourceLayerIndex =</div> +<div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>  GetLayerIndexInVector(graph, baseLayer->inputSlots()->Get(0)->connection()->sourceLayerIndex());</div> +<div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSlotIndex =</div> +<div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>  GetLayerIndexInVector(graph, baseLayer->inputSlots()->Get(0)->connection()->outputSlotIndex());</div> +<div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> sourceBaseLayer = GetBaseLayer(graph, sourceLayerIndex);</div> +<div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& tensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(</div> +<div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>  sourceBaseLayer->outputSlots()->Get(outputSlotIndex)->tensorInfo());</div> +<div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>  <a class="code" href="namespacearmnn.html#a280670a263dc4fd40491f6d0a2737f44">BindingPointInfo</a> bindingInfo = {bindingId, tensorInfo};</div> +<div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>  m_OutputBindings.push_back(std::make_pair(baseLayer->layerName()->c_str(), bindingInfo));</div> <div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>  }</div> -<div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  </div> -<div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>(); ++i)</div> -<div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  {</div> -<div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> slotIndex = baseLayer->outputSlots()->Get(i)->index();</div> -<div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>  <a class="code" href="classarmnn_1_1_i_output_slot.html">armnn::IOutputSlot</a>* outputSlot = &(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(slotIndex));</div> -<div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>  <span class="comment">// layerIndex is not necessarily the same as baseLayer->index(). The latter is needed here</span></div> -<div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>  RegisterOutputSlotOfConnection(baseLayer->index(), slotIndex, outputSlot);</div> -<div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>  }</div> -<div class="line"><a name="l01148"></a><span class="lineno"> 1148</span> }</div> -<div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  </div> -<div class="line"><a name="l01150"></a><span class="lineno"> 1150</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::RegisterInputSlots(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph,</div> -<div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>  uint32_t layerIndex,</div> -<div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer,</div> -<div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>  std::vector<unsigned int> ignoreSlots)</div> -<div class="line"><a name="l01154"></a><span class="lineno"> 1154</span> {</div> -<div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>  <span class="keywordflow">if</span> (layer == <span class="keyword">nullptr</span>)</div> -<div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>  {</div> -<div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(</div> -<div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  <span class="stringliteral">"RegisterInputSlots: pointer to layer with index [{0}] is null"</span>, layerIndex));</div> -<div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  }</div> -<div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = GetBaseLayer(graph, layerIndex);</div> +<div class="line"><a name="l01140"></a><span class="lineno"> 1140</span> }</div> +<div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>  </div> +<div class="line"><a name="l01142"></a><span class="lineno"> 1142</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::RegisterOutputSlots(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph,</div> +<div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>  uint32_t layerIndex,</div> +<div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer)</div> +<div class="line"><a name="l01145"></a><span class="lineno"> 1145</span> {</div> +<div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>  <span class="keywordflow">if</span> (layer == <span class="keyword">nullptr</span>)</div> +<div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>  {</div> +<div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(</div> +<div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  <span class="stringliteral">"RegisterOutputSlots: pointer to layer with index [{0}] is null"</span>, layerIndex));</div> +<div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>  }</div> +<div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = GetBaseLayer(graph, layerIndex);</div> +<div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>  <span class="keywordflow">if</span> (baseLayer->outputSlots()->size() != layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>())</div> +<div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>  {</div> +<div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The number of outputslots ({0}) does not match the number expected ({1})"</span></div> +<div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>  <span class="stringliteral">" for layer index: {2} {3}"</span>,</div> +<div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  baseLayer->outputSlots()->size(),</div> +<div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>(),</div> +<div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  layerIndex,</div> +<div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  }</div> <div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  </div> -<div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  <span class="keywordflow">if</span> (baseLayer->inputSlots()->size() != (layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>() - ignoreSlots.size()))</div> +<div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>(); ++i)</div> <div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>  {</div> -<div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The number of inputslots ({0}) does not match the number expected ({1})"</span></div> -<div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  <span class="stringliteral">" for layer index:{2} {3}"</span>,</div> -<div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>  baseLayer->inputSlots()->size(),</div> -<div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>(),</div> -<div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  layerIndex,</div> -<div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>  }</div> -<div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>  </div> -<div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>(); ++i)</div> -<div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  {</div> -<div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  <span class="comment">// Check if slot should be ignored.</span></div> -<div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>  <span class="keywordflow">if</span> (std::find(ignoreSlots.begin(), ignoreSlots.end(), i) == ignoreSlots.end())</div> -<div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>  {</div> -<div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>  <span class="keyword">auto</span> fbInputSlot = baseLayer->inputSlots()->Get(i);</div> -<div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>  <span class="keyword">auto</span> fbConnection = fbInputSlot->connection();</div> -<div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  <a class="code" href="classarmnn_1_1_i_input_slot.html">armnn::IInputSlot</a>* inputSlot = &(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(fbInputSlot->index()));</div> -<div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>  </div> -<div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>  <span class="comment">// If the slot has an Overridden tensorInfo then extract it</span></div> -<div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>  <span class="keywordflow">if</span> (fbInputSlot->isOverridden())</div> -<div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>  {</div> -<div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> overriddenTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(fbInputSlot->overriddenTensorInfo());</div> -<div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  inputSlot-><a class="code" href="classarmnn_1_1_i_input_slot.html#ac8591a782840b802efd266f2743efe2e">SetTensorInfo</a>(overriddenTensorInfo);</div> -<div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>  }</div> -<div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>  RegisterInputSlotOfConnection(fbConnection->sourceLayerIndex(), fbConnection->outputSlotIndex(), inputSlot);</div> -<div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>  }</div> -<div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>  }</div> -<div class="line"><a name="l01191"></a><span class="lineno"> 1191</span> }</div> -<div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>  </div> -<div class="line"><a name="l01193"></a><span class="lineno"> 1193</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::RegisterInputSlotOfConnection(uint32_t sourceLayerIndex,</div> -<div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>  uint32_t outputSlotIndex,</div> -<div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  <a class="code" href="classarmnn_1_1_i_input_slot.html">armnn::IInputSlot</a>* inputSlot)</div> -<div class="line"><a name="l01196"></a><span class="lineno"> 1196</span> {</div> -<div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  <span class="keywordflow">if</span> (m_GraphConnections.find(sourceLayerIndex) == m_GraphConnections.end())</div> -<div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>  {</div> -<div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>  m_GraphConnections[sourceLayerIndex] = Connections();</div> -<div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>  }</div> -<div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>  </div> -<div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  Connections& connections = m_GraphConnections[sourceLayerIndex];</div> -<div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>  <span class="keywordflow">if</span> (connections.inputSlots.find(outputSlotIndex) == connections.inputSlots.end())</div> -<div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  {</div> -<div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>  connections.inputSlots[outputSlotIndex] = {inputSlot};</div> -<div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>  }</div> -<div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  {</div> -<div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>  connections.inputSlots[outputSlotIndex].push_back(inputSlot);</div> -<div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  }</div> -<div class="line"><a name="l01211"></a><span class="lineno"> 1211</span> }</div> -<div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  </div> -<div class="line"><a name="l01213"></a><span class="lineno"> 1213</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::RegisterOutputSlotOfConnection(uint32_t sourceLayerIndex,</div> -<div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  uint32_t outputSlotIndex,</div> -<div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>  <a class="code" href="classarmnn_1_1_i_output_slot.html">armnn::IOutputSlot</a>* outputSlot)</div> -<div class="line"><a name="l01216"></a><span class="lineno"> 1216</span> {</div> -<div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>  <span class="keywordflow">if</span> (m_GraphConnections.find(sourceLayerIndex) == m_GraphConnections.end())</div> -<div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>  {</div> -<div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  m_GraphConnections[sourceLayerIndex] = Connections();</div> -<div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  }</div> -<div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>  </div> -<div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  Connections& connections = m_GraphConnections[sourceLayerIndex];</div> -<div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  <span class="keywordflow">if</span> (connections.outputSlots.find(outputSlotIndex) != connections.outputSlots.end())</div> -<div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  {</div> -<div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Same output slot index processed twice"</span>);</div> -<div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  }</div> -<div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  </div> -<div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  connections.outputSlots[outputSlotIndex] = outputSlot;</div> -<div class="line"><a name="l01229"></a><span class="lineno"> 1229</span> }</div> -<div class="line"><a name="l01230"></a><span class="lineno"> 1230</span>  </div> -<div class="line"><a name="l01231"></a><span class="lineno"> 1231</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseAbs(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01232"></a><span class="lineno"> 1232</span> {</div> -<div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01235"></a><span class="lineno"> 1235</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01236"></a><span class="lineno"> 1236</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01237"></a><span class="lineno"> 1237</span>  </div> -<div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>  </div> -<div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>  </div> -<div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>  <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.html">armnn::ElementwiseUnaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a1e34af023adeb7d5f484f8eb4b9826b6">armnn::UnaryOperation::Abs</a>);</div> -<div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  </div> -<div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01250"></a><span class="lineno"> 1250</span> }</div> -<div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>  </div> -<div class="line"><a name="l01252"></a><span class="lineno"> 1252</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseActivation(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01253"></a><span class="lineno"> 1253</span> {</div> -<div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01256"></a><span class="lineno"> 1256</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>  </div> -<div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>  </div> -<div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ActivationLayer();</div> +<div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> slotIndex = baseLayer->outputSlots()->Get(i)->index();</div> +<div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  <a class="code" href="classarmnn_1_1_i_output_slot.html">armnn::IOutputSlot</a>* outputSlot = &(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(slotIndex));</div> +<div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>  <span class="comment">// layerIndex is not necessarily the same as baseLayer->index(). The latter is needed here</span></div> +<div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  RegisterOutputSlotOfConnection(baseLayer->index(), slotIndex, outputSlot);</div> +<div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  }</div> +<div class="line"><a name="l01170"></a><span class="lineno"> 1170</span> }</div> +<div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>  </div> +<div class="line"><a name="l01172"></a><span class="lineno"> 1172</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::RegisterInputSlots(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph,</div> +<div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  uint32_t layerIndex,</div> +<div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer,</div> +<div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  std::vector<unsigned int> ignoreSlots)</div> +<div class="line"><a name="l01176"></a><span class="lineno"> 1176</span> {</div> +<div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>  <span class="keywordflow">if</span> (layer == <span class="keyword">nullptr</span>)</div> +<div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>  {</div> +<div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(</div> +<div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  <span class="stringliteral">"RegisterInputSlots: pointer to layer with index [{0}] is null"</span>, layerIndex));</div> +<div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>  }</div> +<div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>  <a class="code" href="namespacearmnn_deserializer.html#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = GetBaseLayer(graph, layerIndex);</div> +<div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>  </div> +<div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>  <span class="keywordflow">if</span> (baseLayer->inputSlots()->size() != (layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>() - ignoreSlots.size()))</div> +<div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  {</div> +<div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The number of inputslots ({0}) does not match the number expected ({1})"</span></div> +<div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>  <span class="stringliteral">" for layer index:{2} {3}"</span>,</div> +<div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>  baseLayer->inputSlots()->size(),</div> +<div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>(),</div> +<div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>  layerIndex,</div> +<div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>  }</div> +<div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>  </div> +<div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>(); ++i)</div> +<div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>  {</div> +<div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  <span class="comment">// Check if slot should be ignored.</span></div> +<div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>  <span class="keywordflow">if</span> (std::find(ignoreSlots.begin(), ignoreSlots.end(), i) == ignoreSlots.end())</div> +<div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>  {</div> +<div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>  <span class="keyword">auto</span> fbInputSlot = baseLayer->inputSlots()->Get(i);</div> +<div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>  <span class="keyword">auto</span> fbConnection = fbInputSlot->connection();</div> +<div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  <a class="code" href="classarmnn_1_1_i_input_slot.html">armnn::IInputSlot</a>* inputSlot = &(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(fbInputSlot->index()));</div> +<div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>  </div> +<div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  <span class="comment">// If the slot has an Overridden tensorInfo then extract it</span></div> +<div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>  <span class="keywordflow">if</span> (fbInputSlot->isOverridden())</div> +<div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>  {</div> +<div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> overriddenTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(fbInputSlot->overriddenTensorInfo());</div> +<div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  inputSlot-><a class="code" href="classarmnn_1_1_i_input_slot.html#ac8591a782840b802efd266f2743efe2e">SetTensorInfo</a>(overriddenTensorInfo);</div> +<div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>  }</div> +<div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  RegisterInputSlotOfConnection(fbConnection->sourceLayerIndex(), fbConnection->outputSlotIndex(), inputSlot);</div> +<div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>  }</div> +<div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  }</div> +<div class="line"><a name="l01213"></a><span class="lineno"> 1213</span> }</div> +<div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  </div> +<div class="line"><a name="l01215"></a><span class="lineno"> 1215</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::RegisterInputSlotOfConnection(uint32_t sourceLayerIndex,</div> +<div class="line"><a name="l01216"></a><span class="lineno"> 1216</span>  uint32_t outputSlotIndex,</div> +<div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>  <a class="code" href="classarmnn_1_1_i_input_slot.html">armnn::IInputSlot</a>* inputSlot)</div> +<div class="line"><a name="l01218"></a><span class="lineno"> 1218</span> {</div> +<div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  <span class="keywordflow">if</span> (m_GraphConnections.find(sourceLayerIndex) == m_GraphConnections.end())</div> +<div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  {</div> +<div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>  m_GraphConnections[sourceLayerIndex] = Connections();</div> +<div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  }</div> +<div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  </div> +<div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  Connections& connections = m_GraphConnections[sourceLayerIndex];</div> +<div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  <span class="keywordflow">if</span> (connections.inputSlots.find(outputSlotIndex) == connections.inputSlots.end())</div> +<div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  {</div> +<div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  connections.inputSlots[outputSlotIndex] = {inputSlot};</div> +<div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  }</div> +<div class="line"><a name="l01229"></a><span class="lineno"> 1229</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l01230"></a><span class="lineno"> 1230</span>  {</div> +<div class="line"><a name="l01231"></a><span class="lineno"> 1231</span>  connections.inputSlots[outputSlotIndex].push_back(inputSlot);</div> +<div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>  }</div> +<div class="line"><a name="l01233"></a><span class="lineno"> 1233</span> }</div> +<div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>  </div> +<div class="line"><a name="l01235"></a><span class="lineno"> 1235</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::RegisterOutputSlotOfConnection(uint32_t sourceLayerIndex,</div> +<div class="line"><a name="l01236"></a><span class="lineno"> 1236</span>  uint32_t outputSlotIndex,</div> +<div class="line"><a name="l01237"></a><span class="lineno"> 1237</span>  <a class="code" href="classarmnn_1_1_i_output_slot.html">armnn::IOutputSlot</a>* outputSlot)</div> +<div class="line"><a name="l01238"></a><span class="lineno"> 1238</span> {</div> +<div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>  <span class="keywordflow">if</span> (m_GraphConnections.find(sourceLayerIndex) == m_GraphConnections.end())</div> +<div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>  {</div> +<div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>  m_GraphConnections[sourceLayerIndex] = Connections();</div> +<div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>  }</div> +<div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>  </div> +<div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  Connections& connections = m_GraphConnections[sourceLayerIndex];</div> +<div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>  <span class="keywordflow">if</span> (connections.outputSlots.find(outputSlotIndex) != connections.outputSlots.end())</div> +<div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>  {</div> +<div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Same output slot index processed twice"</span>);</div> +<div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>  }</div> +<div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>  </div> +<div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>  connections.outputSlots[outputSlotIndex] = outputSlot;</div> +<div class="line"><a name="l01251"></a><span class="lineno"> 1251</span> }</div> +<div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>  </div> +<div class="line"><a name="l01253"></a><span class="lineno"> 1253</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseAbs(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01254"></a><span class="lineno"> 1254</span> {</div> +<div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01256"></a><span class="lineno"> 1256</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>  </div> +<div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>  </div> <div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> -<div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>  </div> -<div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  <a class="code" href="structarmnn_1_1_activation_descriptor.html">armnn::ActivationDescriptor</a> descriptor;</div> -<div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.html#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn_deserializer.html#a2ee1264a9803ff8dc1323a26f1f4c986">ToActivationFunction</a>(serializerDescriptor->activationFunction());</div> -<div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.html#a017b2990003a014234f13e999dc7c689">m_A</a> = serializerDescriptor->a();</div> -<div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.html#a28c4c9cb15f6be3499abbc46b356060b">m_B</a> = serializerDescriptor->b();</div> -<div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>  </div> -<div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddActivationLayer(descriptor,</div> -<div class="line"><a name="l01272"></a><span class="lineno"> 1272</span>  layerName.c_str());</div> -<div class="line"><a name="l01273"></a><span class="lineno"> 1273</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01275"></a><span class="lineno"> 1275</span>  </div> -<div class="line"><a name="l01276"></a><span class="lineno"> 1276</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01278"></a><span class="lineno"> 1278</span> }</div> -<div class="line"><a name="l01279"></a><span class="lineno"> 1279</span>  </div> -<div class="line"><a name="l01280"></a><span class="lineno"> 1280</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseAdd(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01281"></a><span class="lineno"> 1281</span> {</div> -<div class="line"><a name="l01282"></a><span class="lineno"> 1282</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01284"></a><span class="lineno"> 1284</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01285"></a><span class="lineno"> 1285</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l01286"></a><span class="lineno"> 1286</span>  </div> -<div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01288"></a><span class="lineno"> 1288</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>  </div> -<div class="line"><a name="l01290"></a><span class="lineno"> 1290</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01291"></a><span class="lineno"> 1291</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aec211f7c20af43e742bf2570c3cb84f9">armnn::BinaryOperation::Add</a>);</div> -<div class="line"><a name="l01292"></a><span class="lineno"> 1292</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>  </div> -<div class="line"><a name="l01294"></a><span class="lineno"> 1294</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01296"></a><span class="lineno"> 1296</span>  </div> -<div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01299"></a><span class="lineno"> 1299</span> }</div> -<div class="line"><a name="l01300"></a><span class="lineno"> 1300</span>  </div> -<div class="line"><a name="l01301"></a><span class="lineno"> 1301</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseArgMinMax(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01302"></a><span class="lineno"> 1302</span> {</div> -<div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>  </div> -<div class="line"><a name="l01308"></a><span class="lineno"> 1308</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01310"></a><span class="lineno"> 1310</span>  </div> -<div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ArgMinMaxLayer();</div> -<div class="line"><a name="l01312"></a><span class="lineno"> 1312</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> -<div class="line"><a name="l01313"></a><span class="lineno"> 1313</span>  </div> -<div class="line"><a name="l01314"></a><span class="lineno"> 1314</span>  <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.html">armnn::ArgMinMaxDescriptor</a> descriptor;</div> -<div class="line"><a name="l01315"></a><span class="lineno"> 1315</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.html#ab1ae6f520bb1a4da191a0ae907477f23">m_Function</a> = <a class="code" href="namespacearmnn_deserializer.html#a8fb47fe218330370a5c9c066ac1571ea">ToArgMinMaxFunction</a>(serializerDescriptor->argMinMaxFunction());</div> -<div class="line"><a name="l01316"></a><span class="lineno"> 1316</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.html#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = serializerDescriptor->axis();</div> -<div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddArgMinMaxLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>  </div> -<div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01321"></a><span class="lineno"> 1321</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>  </div> +<div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>  <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.html">armnn::ElementwiseUnaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a1e34af023adeb7d5f484f8eb4b9826b6">armnn::UnaryOperation::Abs</a>);</div> +<div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>  </div> +<div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01272"></a><span class="lineno"> 1272</span> }</div> +<div class="line"><a name="l01273"></a><span class="lineno"> 1273</span>  </div> +<div class="line"><a name="l01274"></a><span class="lineno"> 1274</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseActivation(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01275"></a><span class="lineno"> 1275</span> {</div> +<div class="line"><a name="l01276"></a><span class="lineno"> 1276</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01278"></a><span class="lineno"> 1278</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01279"></a><span class="lineno"> 1279</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>  </div> +<div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01282"></a><span class="lineno"> 1282</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>  </div> +<div class="line"><a name="l01284"></a><span class="lineno"> 1284</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ActivationLayer();</div> +<div class="line"><a name="l01285"></a><span class="lineno"> 1285</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01286"></a><span class="lineno"> 1286</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> +<div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>  </div> +<div class="line"><a name="l01288"></a><span class="lineno"> 1288</span>  <a class="code" href="structarmnn_1_1_activation_descriptor.html">armnn::ActivationDescriptor</a> descriptor;</div> +<div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.html#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn_deserializer.html#a2ee1264a9803ff8dc1323a26f1f4c986">ToActivationFunction</a>(serializerDescriptor->activationFunction());</div> +<div class="line"><a name="l01290"></a><span class="lineno"> 1290</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.html#a017b2990003a014234f13e999dc7c689">m_A</a> = serializerDescriptor->a();</div> +<div class="line"><a name="l01291"></a><span class="lineno"> 1291</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.html#a28c4c9cb15f6be3499abbc46b356060b">m_B</a> = serializerDescriptor->b();</div> +<div class="line"><a name="l01292"></a><span class="lineno"> 1292</span>  </div> +<div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddActivationLayer(descriptor,</div> +<div class="line"><a name="l01294"></a><span class="lineno"> 1294</span>  layerName.c_str());</div> +<div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01296"></a><span class="lineno"> 1296</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>  </div> +<div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01300"></a><span class="lineno"> 1300</span> }</div> +<div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>  </div> +<div class="line"><a name="l01302"></a><span class="lineno"> 1302</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseAdd(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01303"></a><span class="lineno"> 1303</span> {</div> +<div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l01308"></a><span class="lineno"> 1308</span>  </div> +<div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01310"></a><span class="lineno"> 1310</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>  </div> +<div class="line"><a name="l01312"></a><span class="lineno"> 1312</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01313"></a><span class="lineno"> 1313</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aec211f7c20af43e742bf2570c3cb84f9">armnn::BinaryOperation::Add</a>);</div> +<div class="line"><a name="l01314"></a><span class="lineno"> 1314</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01315"></a><span class="lineno"> 1315</span>  </div> +<div class="line"><a name="l01316"></a><span class="lineno"> 1316</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>  </div> +<div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01321"></a><span class="lineno"> 1321</span> }</div> <div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>  </div> -<div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01325"></a><span class="lineno"> 1325</span> }</div> -<div class="line"><a name="l01326"></a><span class="lineno"> 1326</span>  </div> -<div class="line"><a name="l01327"></a><span class="lineno"> 1327</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseBatchMatMul(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01328"></a><span class="lineno"> 1328</span> {</div> -<div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>  </div> -<div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>  </div> -<div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>  </div> -<div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_BatchMatMulLayer();</div> -<div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> -<div class="line"><a name="l01340"></a><span class="lineno"> 1340</span>  </div> -<div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>  <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html">armnn::BatchMatMulDescriptor</a> descriptor(serializerDescriptor->transposeX(),</div> -<div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>  serializerDescriptor->transposeY(),</div> -<div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>  serializerDescriptor->adjointX(),</div> -<div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>  serializerDescriptor->adjointY(),</div> -<div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>  <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayoutX()),</div> -<div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>  <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayoutY()));</div> -<div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>  </div> -<div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddBatchMatMulLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>  </div> -<div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>  </div> -<div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01355"></a><span class="lineno"> 1355</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01356"></a><span class="lineno"> 1356</span> }</div> -<div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>  </div> -<div class="line"><a name="l01358"></a><span class="lineno"> 1358</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseBatchToSpaceNd(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01359"></a><span class="lineno"> 1359</span> {</div> -<div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>  </div> -<div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01364"></a><span class="lineno"> 1364</span>  </div> -<div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01366"></a><span class="lineno"> 1366</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>  </div> -<div class="line"><a name="l01368"></a><span class="lineno"> 1368</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->descriptor();</div> -<div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>  <span class="keyword">auto</span> flatBufferCrops = flatBufferDescriptor->crops();</div> -<div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>  <span class="keyword">auto</span> flatBufferBlockShape = flatBufferDescriptor->blockShape();</div> -<div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>  </div> -<div class="line"><a name="l01372"></a><span class="lineno"> 1372</span>  <span class="keywordflow">if</span> (flatBufferCrops->size() % 2 != 0)</div> -<div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>  {</div> -<div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The size of crops must be divisible by 2 {}"</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>  }</div> -<div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>  </div> -<div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>  std::vector<std::pair<unsigned int, unsigned int>> crops;</div> -<div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>  crops.reserve(flatBufferCrops->size() / 2);</div> -<div class="line"><a name="l01379"></a><span class="lineno"> 1379</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < flatBufferCrops->size() - 1; i += 2)</div> -<div class="line"><a name="l01380"></a><span class="lineno"> 1380</span>  {</div> -<div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>  crops.emplace_back(flatBufferCrops->Get(i), flatBufferCrops->Get(i+1));</div> -<div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>  }</div> +<div class="line"><a name="l01323"></a><span class="lineno"> 1323</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseArgMinMax(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01324"></a><span class="lineno"> 1324</span> {</div> +<div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01326"></a><span class="lineno"> 1326</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01328"></a><span class="lineno"> 1328</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>  </div> +<div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>  </div> +<div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ArgMinMaxLayer();</div> +<div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> +<div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>  </div> +<div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>  <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.html">armnn::ArgMinMaxDescriptor</a> descriptor;</div> +<div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.html#ab1ae6f520bb1a4da191a0ae907477f23">m_Function</a> = <a class="code" href="namespacearmnn_deserializer.html#a8fb47fe218330370a5c9c066ac1571ea">ToArgMinMaxFunction</a>(serializerDescriptor->argMinMaxFunction());</div> +<div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.html#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = serializerDescriptor->axis();</div> +<div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01340"></a><span class="lineno"> 1340</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddArgMinMaxLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>  </div> +<div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>  </div> +<div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01347"></a><span class="lineno"> 1347</span> }</div> +<div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>  </div> +<div class="line"><a name="l01349"></a><span class="lineno"> 1349</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseBatchMatMul(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01350"></a><span class="lineno"> 1350</span> {</div> +<div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>  </div> +<div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01355"></a><span class="lineno"> 1355</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l01356"></a><span class="lineno"> 1356</span>  </div> +<div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>  </div> +<div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_BatchMatMulLayer();</div> +<div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> +<div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>  </div> +<div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>  <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html">armnn::BatchMatMulDescriptor</a> descriptor(serializerDescriptor->transposeX(),</div> +<div class="line"><a name="l01364"></a><span class="lineno"> 1364</span>  serializerDescriptor->transposeY(),</div> +<div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>  serializerDescriptor->adjointX(),</div> +<div class="line"><a name="l01366"></a><span class="lineno"> 1366</span>  serializerDescriptor->adjointY(),</div> +<div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>  <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayoutX()),</div> +<div class="line"><a name="l01368"></a><span class="lineno"> 1368</span>  <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayoutY()));</div> +<div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>  </div> +<div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddBatchMatMulLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01372"></a><span class="lineno"> 1372</span>  </div> +<div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>  </div> +<div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01378"></a><span class="lineno"> 1378</span> }</div> +<div class="line"><a name="l01379"></a><span class="lineno"> 1379</span>  </div> +<div class="line"><a name="l01380"></a><span class="lineno"> 1380</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseBatchToSpaceNd(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01381"></a><span class="lineno"> 1381</span> {</div> +<div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>  </div> -<div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>  <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html">armnn::BatchToSpaceNdDescriptor</a> descriptor;</div> -<div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> -<div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> =</div> -<div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>  std::vector<unsigned int>(flatBufferBlockShape->begin(), flatBufferBlockShape->end());</div> -<div class="line"><a name="l01388"></a><span class="lineno"> 1388</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a3941f674c071c9503e00d2b59e92e454">m_Crops</a> = crops;</div> +<div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>  </div> +<div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01388"></a><span class="lineno"> 1388</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>  </div> -<div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddBatchToSpaceNdLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>  </div> -<div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>  </div> -<div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01398"></a><span class="lineno"> 1398</span> }</div> -<div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>  </div> -<div class="line"><a name="l01400"></a><span class="lineno"> 1400</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseBatchNormalization(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01401"></a><span class="lineno"> 1401</span> {</div> -<div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>  </div> -<div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>  </div> -<div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>  </div> -<div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>  </div> -<div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_BatchNormalizationLayer();</div> -<div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> -<div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>  </div> -<div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>  <a class="code" href="structarmnn_1_1_batch_normalization_descriptor.html">armnn::BatchNormalizationDescriptor</a> descriptor;</div> -<div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> = serializerDescriptor->eps();</div> -<div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div> -<div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>  </div> -<div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> mean = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->mean());</div> -<div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> variance = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->variance());</div> -<div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> beta = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->beta());</div> -<div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> gamma = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->gamma());</div> -<div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>  </div> -<div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddBatchNormalizationLayer(descriptor,</div> -<div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>  mean,</div> -<div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>  variance,</div> -<div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>  beta,</div> -<div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>  gamma,</div> -<div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>  layerName.c_str());</div> -<div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->descriptor();</div> +<div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>  <span class="keyword">auto</span> flatBufferCrops = flatBufferDescriptor->crops();</div> +<div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>  <span class="keyword">auto</span> flatBufferBlockShape = flatBufferDescriptor->blockShape();</div> +<div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>  </div> +<div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>  <span class="keywordflow">if</span> (flatBufferCrops->size() % 2 != 0)</div> +<div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>  {</div> +<div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The size of crops must be divisible by 2 {}"</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>  }</div> +<div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>  </div> +<div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>  std::vector<std::pair<unsigned int, unsigned int>> crops;</div> +<div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>  crops.reserve(flatBufferCrops->size() / 2);</div> +<div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < flatBufferCrops->size() - 1; i += 2)</div> +<div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>  {</div> +<div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>  crops.emplace_back(flatBufferCrops->Get(i), flatBufferCrops->Get(i+1));</div> +<div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>  }</div> +<div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>  </div> +<div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>  <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html">armnn::BatchToSpaceNdDescriptor</a> descriptor;</div> +<div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> +<div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> =</div> +<div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>  std::vector<unsigned int>(flatBufferBlockShape->begin(), flatBufferBlockShape->end());</div> +<div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a3941f674c071c9503e00d2b59e92e454">m_Crops</a> = crops;</div> +<div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>  </div> +<div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddBatchToSpaceNdLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>  </div> +<div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>  </div> +<div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01420"></a><span class="lineno"> 1420</span> }</div> +<div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>  </div> +<div class="line"><a name="l01422"></a><span class="lineno"> 1422</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseBatchNormalization(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01423"></a><span class="lineno"> 1423</span> {</div> +<div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>  </div> +<div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>  </div> +<div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> <div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>  </div> -<div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01435"></a><span class="lineno"> 1435</span> }</div> -<div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>  </div> -<div class="line"><a name="l01437"></a><span class="lineno"> 1437</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseCast(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01438"></a><span class="lineno"> 1438</span> {</div> -<div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01441"></a><span class="lineno"> 1441</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  </div> -<div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>  </div> +<div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_BatchNormalizationLayer();</div> +<div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> +<div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>  </div> +<div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>  <a class="code" href="structarmnn_1_1_batch_normalization_descriptor.html">armnn::BatchNormalizationDescriptor</a> descriptor;</div> +<div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> = serializerDescriptor->eps();</div> +<div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div> +<div class="line"><a name="l01441"></a><span class="lineno"> 1441</span>  </div> +<div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> mean = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->mean());</div> +<div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> variance = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->variance());</div> +<div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> beta = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->beta());</div> +<div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> gamma = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->gamma());</div> <div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>  </div> -<div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>  </div> -<div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddCastLayer(layerName.c_str());</div> -<div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>  </div> -<div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>  </div> -<div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01456"></a><span class="lineno"> 1456</span> }</div> -<div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>  </div> -<div class="line"><a name="l01458"></a><span class="lineno"> 1458</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseConstant(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01459"></a><span class="lineno"> 1459</span> {</div> -<div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>  </div> -<div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddBatchNormalizationLayer(descriptor,</div> +<div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>  mean,</div> +<div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>  variance,</div> +<div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>  beta,</div> +<div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>  gamma,</div> +<div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>  layerName.c_str());</div> +<div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>  </div> +<div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01457"></a><span class="lineno"> 1457</span> }</div> +<div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>  </div> +<div class="line"><a name="l01459"></a><span class="lineno"> 1459</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseCast(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01460"></a><span class="lineno"> 1460</span> {</div> +<div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> <div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>  </div> -<div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>  </div> -<div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ConstantLayer();</div> -<div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>  <span class="keyword">auto</span> serializerInput = serializerLayer->input();</div> +<div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>  </div> +<div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> <div class="line"><a name="l01470"></a><span class="lineno"> 1470</span>  </div> -<div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> input = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerInput);</div> -<div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer;</div> -<div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>  </div> -<div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>  <span class="comment">// Required for when Constant Layer is used as an inputs to DepthwiseConvolution2d Layer.</span></div> -<div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>  <span class="comment">// Running a model that was created before weights layout scheme version was added to our flatbuffers</span></div> -<div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>  <span class="comment">// file ensuring older models can still be read and executed. featureVersion weights layout scheme 1</span></div> -<div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>  <span class="comment">// indicates a change in the depthwise weights layout within ArmNN from [M,I,H,W] --> [1,H,W,I*M]</span></div> -<div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_WeightsLayoutScheme <= 0)</div> -<div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>  {</div> -<div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>  <span class="comment">// Permute weights [ H, W, M, I ] --> [ 1, H, W, I*M ]</span></div> -<div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>  <span class="comment">// Step1: [ M, I, H, W ] --> [ H, W, I, M]</span></div> -<div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>  <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permutationVector = { 3, 2, 0, 1 };</div> -<div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> weightsInfo = input.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>();</div> -<div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>  std::unique_ptr<unsigned char[]> permuteBuffer(<span class="keyword">new</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>[weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>()]);</div> -<div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>  weightsInfo = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(weightsInfo, permutationVector);</div> -<div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>  <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), permutationVector,</div> -<div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>  input.<a class="code" href="classarmnn_1_1_base_tensor.html#aa81f67ac64f0c249e26499600c45d996">GetMemoryArea</a>(), permuteBuffer.get(),</div> -<div class="line"><a name="l01488"></a><span class="lineno"> 1488</span>  <a class="code" href="namespacearmnn.html#aa02b9e06fb20fa3c13da0427e6ee5ab2">GetDataTypeSize</a>(weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>()));</div> +<div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddCastLayer(layerName.c_str());</div> +<div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>  </div> +<div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>  </div> +<div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01478"></a><span class="lineno"> 1478</span> }</div> +<div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>  </div> +<div class="line"><a name="l01480"></a><span class="lineno"> 1480</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseConstant(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01481"></a><span class="lineno"> 1481</span> {</div> +<div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>  </div> +<div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>  </div> +<div class="line"><a name="l01488"></a><span class="lineno"> 1488</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> <div class="line"><a name="l01489"></a><span class="lineno"> 1489</span>  </div> -<div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>  <span class="comment">// Step2: Reshape [ H, W, I, M] --> [ 1, H, W, I*M ]</span></div> -<div class="line"><a name="l01491"></a><span class="lineno"> 1491</span>  <span class="keyword">auto</span> weightsShape = weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> -<div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>  weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({1,</div> -<div class="line"><a name="l01493"></a><span class="lineno"> 1493</span>  weightsShape[0],</div> -<div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>  weightsShape[1],</div> -<div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>  weightsShape[2]*weightsShape[3]});</div> -<div class="line"><a name="l01496"></a><span class="lineno"> 1496</span>  weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">SetConstant</a>(<span class="keyword">true</span>);</div> -<div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>  </div> -<div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weightsPermuted(weightsInfo, permuteBuffer.get());</div> -<div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>  </div> -<div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>  layer = m_Network->AddConstantLayer(weightsPermuted, layerName.c_str());</div> -<div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>  </div> -<div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(weightsPermuted.GetInfo());</div> -<div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>  </div> -<div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>  </div> -<div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>  <span class="keywordflow">return</span>;</div> -<div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>  }</div> -<div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>  {</div> -<div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>  layer = m_Network->AddConstantLayer(input, layerName.c_str());</div> +<div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ConstantLayer();</div> +<div class="line"><a name="l01491"></a><span class="lineno"> 1491</span>  <span class="keyword">auto</span> serializerInput = serializerLayer->input();</div> +<div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>  </div> +<div class="line"><a name="l01493"></a><span class="lineno"> 1493</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> input = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerInput);</div> +<div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer;</div> +<div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>  </div> +<div class="line"><a name="l01496"></a><span class="lineno"> 1496</span>  <span class="comment">// Required for when Constant Layer is used as an inputs to DepthwiseConvolution2d Layer.</span></div> +<div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>  <span class="comment">// Running a model that was created before weights layout scheme version was added to our flatbuffers</span></div> +<div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>  <span class="comment">// file ensuring older models can still be read and executed. featureVersion weights layout scheme 1</span></div> +<div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>  <span class="comment">// indicates a change in the depthwise weights layout within ArmNN from [M,I,H,W] --> [1,H,W,I*M]</span></div> +<div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_WeightsLayoutScheme <= 0)</div> +<div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>  {</div> +<div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>  <span class="comment">// Permute weights [ H, W, M, I ] --> [ 1, H, W, I*M ]</span></div> +<div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>  <span class="comment">// Step1: [ M, I, H, W ] --> [ H, W, I, M]</span></div> +<div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>  <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permutationVector = { 3, 2, 0, 1 };</div> +<div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> weightsInfo = input.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>();</div> +<div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>  std::unique_ptr<unsigned char[]> permuteBuffer(<span class="keyword">new</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>[weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>()]);</div> +<div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>  weightsInfo = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(weightsInfo, permutationVector);</div> +<div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>  <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), permutationVector,</div> +<div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>  input.<a class="code" href="classarmnn_1_1_base_tensor.html#aa81f67ac64f0c249e26499600c45d996">GetMemoryArea</a>(), permuteBuffer.get(),</div> +<div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>  <a class="code" href="namespacearmnn.html#aa02b9e06fb20fa3c13da0427e6ee5ab2">GetDataTypeSize</a>(weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>()));</div> <div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>  </div> -<div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">SetConstant</a>(<span class="keyword">true</span>);</div> -<div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>  }</div> -<div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>  </div> -<div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01518"></a><span class="lineno"> 1518</span> }</div> +<div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>  <span class="comment">// Step2: Reshape [ H, W, I, M] --> [ 1, H, W, I*M ]</span></div> +<div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>  <span class="keyword">auto</span> weightsShape = weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> +<div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>  weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({1,</div> +<div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>  weightsShape[0],</div> +<div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>  weightsShape[1],</div> +<div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>  weightsShape[2]*weightsShape[3]});</div> +<div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>  weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">SetConstant</a>(<span class="keyword">true</span>);</div> <div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>  </div> -<div class="line"><a name="l01520"></a><span class="lineno"> 1520</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseConvolution2d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01521"></a><span class="lineno"> 1521</span> {</div> -<div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01523"></a><span class="lineno"> 1523</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01520"></a><span class="lineno"> 1520</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weightsPermuted(weightsInfo, permuteBuffer.get());</div> +<div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>  </div> +<div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>  layer = m_Network->AddConstantLayer(weightsPermuted, layerName.c_str());</div> +<div class="line"><a name="l01523"></a><span class="lineno"> 1523</span>  </div> +<div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(weightsPermuted.GetInfo());</div> <div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>  </div> -<div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>  </div> -<div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_Convolution2dLayer();</div> -<div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>  </div> -<div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>  <span class="keyword">auto</span> flatbufferDescriptor = flatBufferLayer->descriptor();</div> +<div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>  </div> +<div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>  <span class="keywordflow">return</span>;</div> +<div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>  }</div> +<div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>  {</div> +<div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>  layer = m_Network->AddConstantLayer(input, layerName.c_str());</div> <div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>  </div> -<div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">armnn::Convolution2dDescriptor</a> descriptor;</div> -<div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = flatbufferDescriptor->padLeft();</div> -<div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = flatbufferDescriptor->padRight();</div> -<div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = flatbufferDescriptor->padTop();</div> -<div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = flatbufferDescriptor->padBottom();</div> -<div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = flatbufferDescriptor->strideX();</div> -<div class="line"><a name="l01540"></a><span class="lineno"> 1540</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = flatbufferDescriptor->strideY();;</div> -<div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = flatbufferDescriptor->dilationX();</div> -<div class="line"><a name="l01542"></a><span class="lineno"> 1542</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = flatbufferDescriptor->dilationY();;</div> -<div class="line"><a name="l01543"></a><span class="lineno"> 1543</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = flatbufferDescriptor->biasEnabled();;</div> -<div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatbufferDescriptor->dataLayout());</div> -<div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>  </div> -<div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer;</div> -<div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>  std::vector<unsigned int> ignoreSlots {};</div> -<div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>  </div> -<div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> biasTensor;</div> -<div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>  <span class="comment">// Weights and biases used to be always constant and were stored as members of the layer. This has changed and</span></div> -<div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>  <span class="comment">// they are now passed as inputs. If they are constant then they will be stored in a ConstantLayer.</span></div> -<div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_ConstTensorsAsInputs <= 0)</div> -<div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>  {</div> -<div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>  <span class="comment">// If the model stores weights and biases as members of the layer we have to read them from there</span></div> -<div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>  <span class="comment">// but add them to their own ConstantLayer for compatibility</span></div> -<div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>  </div> -<div class="line"><a name="l01558"></a><span class="lineno"> 1558</span>  layer = m_Network->AddConvolution2dLayer(descriptor,</div> -<div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>  layerName.c_str());</div> -<div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>  </div> -<div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weightsTensor = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->weights());</div> -<div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>  <span class="keyword">auto</span> weightsLayer = m_Network->AddConstantLayer(weightsTensor);</div> -<div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>  weightsLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1u));</div> -<div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>  weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> -<div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>  ignoreSlots.emplace_back(1u);</div> -<div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>  </div> -<div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div> -<div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>  {</div> -<div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>  biasTensor = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->biases());</div> -<div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>  <span class="keyword">auto</span> biasLayer = m_Network->AddConstantLayer(biasTensor);</div> -<div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>  biasLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(2u));</div> -<div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>  biasLayer->GetOutputSlot(0).SetTensorInfo(biasTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> -<div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>  ignoreSlots.emplace_back(2u);</div> -<div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>  }</div> -<div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>  }</div> -<div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>  {</div> -<div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>  layer = m_Network->AddConvolution2dLayer(descriptor,</div> -<div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>  layerName.c_str());</div> -<div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>  uint32_t numInputs = descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>();</div> -<div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> -<div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>  }</div> -<div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>  </div> -<div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>  </div> -<div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>  RegisterInputSlots(graph, layerIndex, layer, ignoreSlots);</div> -<div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01589"></a><span class="lineno"> 1589</span> }</div> -<div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>  </div> -<div class="line"><a name="l01591"></a><span class="lineno"> 1591</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseConvolution3d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01592"></a><span class="lineno"> 1592</span> {</div> -<div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01595"></a><span class="lineno"> 1595</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>  </div> -<div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>  </div> -<div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_Convolution3dLayer();</div> -<div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> -<div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>  </div> -<div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>  <a class="code" href="structarmnn_1_1_convolution3d_descriptor.html">armnn::Convolution3dDescriptor</a> descriptor;</div> -<div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = serializerDescriptor->padLeft();</div> -<div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = serializerDescriptor->padRight();</div> -<div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = serializerDescriptor->padTop();</div> -<div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = serializerDescriptor->padBottom();</div> -<div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a83ca447892f460dabaa2f87d3dc3db61">m_PadFront</a> = serializerDescriptor->padFront();</div> -<div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a11d5c25face9b54e90f79ee8bdc1d0fb">m_PadBack</a> = serializerDescriptor->padBack();</div> -<div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = serializerDescriptor->strideX();</div> -<div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = serializerDescriptor->strideY();</div> -<div class="line"><a name="l01613"></a><span class="lineno"> 1613</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a5164336f6a1b15be0d434a6bbf7289da">m_StrideZ</a> = serializerDescriptor->strideZ();</div> -<div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = serializerDescriptor->dilationX();</div> -<div class="line"><a name="l01615"></a><span class="lineno"> 1615</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = serializerDescriptor->dilationY();</div> -<div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a16543bce17aa2e4d6e81c88f74227192">m_DilationZ</a> = serializerDescriptor->dilationZ();</div> -<div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = serializerDescriptor->biasEnabled();</div> -<div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div> -<div class="line"><a name="l01619"></a><span class="lineno"> 1619</span>  </div> -<div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>  uint32_t numInputs = descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>();</div> -<div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> -<div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>  </div> -<div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddConvolution3dLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>  </div> -<div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>  </div> -<div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01629"></a><span class="lineno"> 1629</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01630"></a><span class="lineno"> 1630</span> }</div> -<div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>  </div> -<div class="line"><a name="l01632"></a><span class="lineno"> 1632</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDepthToSpace(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01633"></a><span class="lineno"> 1633</span> {</div> -<div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>  </div> -<div class="line"><a name="l01636"></a><span class="lineno"> 1636</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>  </div> -<div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">SetConstant</a>(<span class="keyword">true</span>);</div> +<div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>  }</div> +<div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>  </div> +<div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01540"></a><span class="lineno"> 1540</span> }</div> +<div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>  </div> +<div class="line"><a name="l01542"></a><span class="lineno"> 1542</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseConvolution2d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01543"></a><span class="lineno"> 1543</span> {</div> +<div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>  </div> +<div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>  </div> +<div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_Convolution2dLayer();</div> +<div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>  </div> +<div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>  <span class="keyword">auto</span> flatbufferDescriptor = flatBufferLayer->descriptor();</div> +<div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>  </div> +<div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">armnn::Convolution2dDescriptor</a> descriptor;</div> +<div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = flatbufferDescriptor->padLeft();</div> +<div class="line"><a name="l01558"></a><span class="lineno"> 1558</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = flatbufferDescriptor->padRight();</div> +<div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = flatbufferDescriptor->padTop();</div> +<div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = flatbufferDescriptor->padBottom();</div> +<div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = flatbufferDescriptor->strideX();</div> +<div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = flatbufferDescriptor->strideY();;</div> +<div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = flatbufferDescriptor->dilationX();</div> +<div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = flatbufferDescriptor->dilationY();;</div> +<div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = flatbufferDescriptor->biasEnabled();;</div> +<div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatbufferDescriptor->dataLayout());</div> +<div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>  </div> +<div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer;</div> +<div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>  std::vector<unsigned int> ignoreSlots {};</div> +<div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>  </div> +<div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> biasTensor;</div> +<div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>  <span class="comment">// Weights and biases used to be always constant and were stored as members of the layer. This has changed and</span></div> +<div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>  <span class="comment">// they are now passed as inputs. If they are constant then they will be stored in a ConstantLayer.</span></div> +<div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_ConstTensorsAsInputs <= 0)</div> +<div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>  {</div> +<div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>  <span class="comment">// If the model stores weights and biases as members of the layer we have to read them from there</span></div> +<div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>  <span class="comment">// but add them to their own ConstantLayer for compatibility</span></div> +<div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>  </div> +<div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>  layer = m_Network->AddConvolution2dLayer(descriptor,</div> +<div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>  layerName.c_str());</div> +<div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>  </div> +<div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weightsTensor = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->weights());</div> +<div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>  <span class="keyword">auto</span> weightsLayer = m_Network->AddConstantLayer(weightsTensor);</div> +<div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>  weightsLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1u));</div> +<div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>  weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> +<div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>  ignoreSlots.emplace_back(1u);</div> +<div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>  </div> +<div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div> +<div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>  {</div> +<div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>  biasTensor = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->biases());</div> +<div class="line"><a name="l01592"></a><span class="lineno"> 1592</span>  <span class="keyword">auto</span> biasLayer = m_Network->AddConstantLayer(biasTensor);</div> +<div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>  biasLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(2u));</div> +<div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>  biasLayer->GetOutputSlot(0).SetTensorInfo(biasTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> +<div class="line"><a name="l01595"></a><span class="lineno"> 1595</span>  ignoreSlots.emplace_back(2u);</div> +<div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>  }</div> +<div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>  }</div> +<div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>  {</div> +<div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>  layer = m_Network->AddConvolution2dLayer(descriptor,</div> +<div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>  layerName.c_str());</div> +<div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>  uint32_t numInputs = descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>();</div> +<div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> +<div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>  }</div> +<div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>  </div> +<div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>  </div> +<div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>  RegisterInputSlots(graph, layerIndex, layer, ignoreSlots);</div> +<div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01611"></a><span class="lineno"> 1611</span> }</div> +<div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>  </div> +<div class="line"><a name="l01613"></a><span class="lineno"> 1613</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseConvolution3d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01614"></a><span class="lineno"> 1614</span> {</div> +<div class="line"><a name="l01615"></a><span class="lineno"> 1615</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>  </div> +<div class="line"><a name="l01619"></a><span class="lineno"> 1619</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>  </div> +<div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_Convolution3dLayer();</div> +<div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> +<div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>  </div> +<div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>  <a class="code" href="structarmnn_1_1_convolution3d_descriptor.html">armnn::Convolution3dDescriptor</a> descriptor;</div> +<div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = serializerDescriptor->padLeft();</div> +<div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = serializerDescriptor->padRight();</div> +<div class="line"><a name="l01629"></a><span class="lineno"> 1629</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = serializerDescriptor->padTop();</div> +<div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = serializerDescriptor->padBottom();</div> +<div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a83ca447892f460dabaa2f87d3dc3db61">m_PadFront</a> = serializerDescriptor->padFront();</div> +<div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a11d5c25face9b54e90f79ee8bdc1d0fb">m_PadBack</a> = serializerDescriptor->padBack();</div> +<div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = serializerDescriptor->strideX();</div> +<div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = serializerDescriptor->strideY();</div> +<div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a5164336f6a1b15be0d434a6bbf7289da">m_StrideZ</a> = serializerDescriptor->strideZ();</div> +<div class="line"><a name="l01636"></a><span class="lineno"> 1636</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = serializerDescriptor->dilationX();</div> +<div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = serializerDescriptor->dilationY();</div> +<div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a16543bce17aa2e4d6e81c88f74227192">m_DilationZ</a> = serializerDescriptor->dilationZ();</div> +<div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = serializerDescriptor->biasEnabled();</div> +<div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div> <div class="line"><a name="l01641"></a><span class="lineno"> 1641</span>  </div> -<div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>  <span class="keyword">auto</span> fbDescriptor = graph->layers()->Get(layerIndex)->layer_as_DepthToSpaceLayer()->descriptor();</div> -<div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>  </div> -<div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>  <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html">armnn::DepthToSpaceDescriptor</a> descriptor;</div> -<div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a> = fbDescriptor->blockSize();</div> -<div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(fbDescriptor->dataLayout());</div> -<div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>  </div> -<div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddDepthToSpaceLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01650"></a><span class="lineno"> 1650</span>  </div> -<div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>  uint32_t numInputs = descriptor.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>();</div> +<div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> +<div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>  </div> +<div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddConvolution3dLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>  </div> +<div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>  </div> +<div class="line"><a name="l01650"></a><span class="lineno"> 1650</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01652"></a><span class="lineno"> 1652</span> }</div> <div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>  </div> -<div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01655"></a><span class="lineno"> 1655</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01656"></a><span class="lineno"> 1656</span> }</div> +<div class="line"><a name="l01654"></a><span class="lineno"> 1654</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDepthToSpace(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01655"></a><span class="lineno"> 1655</span> {</div> +<div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l01657"></a><span class="lineno"> 1657</span>  </div> -<div class="line"><a name="l01658"></a><span class="lineno"> 1658</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDepthwiseConvolution2d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01659"></a><span class="lineno"> 1659</span> {</div> -<div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>  </div> +<div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l01663"></a><span class="lineno"> 1663</span>  </div> -<div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>  </div> -<div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer();</div> -<div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> -<div class="line"><a name="l01670"></a><span class="lineno"> 1670</span>  </div> -<div class="line"><a name="l01671"></a><span class="lineno"> 1671</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">armnn::DepthwiseConvolution2dDescriptor</a> descriptor;</div> -<div class="line"><a name="l01672"></a><span class="lineno"> 1672</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = serializerDescriptor->padLeft();</div> -<div class="line"><a name="l01673"></a><span class="lineno"> 1673</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = serializerDescriptor->padRight();</div> -<div class="line"><a name="l01674"></a><span class="lineno"> 1674</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = serializerDescriptor->padTop();</div> -<div class="line"><a name="l01675"></a><span class="lineno"> 1675</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = serializerDescriptor->padBottom();</div> -<div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = serializerDescriptor->strideX();</div> -<div class="line"><a name="l01677"></a><span class="lineno"> 1677</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = serializerDescriptor->strideY();</div> -<div class="line"><a name="l01678"></a><span class="lineno"> 1678</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = serializerDescriptor->dilationX();</div> -<div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = serializerDescriptor->dilationY();</div> -<div class="line"><a name="l01680"></a><span class="lineno"> 1680</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = serializerDescriptor->biasEnabled();</div> -<div class="line"><a name="l01681"></a><span class="lineno"> 1681</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div> -<div class="line"><a name="l01682"></a><span class="lineno"> 1682</span>  </div> -<div class="line"><a name="l01683"></a><span class="lineno"> 1683</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer;</div> -<div class="line"><a name="l01684"></a><span class="lineno"> 1684</span>  std::vector<unsigned int> ignoreSlots {};</div> +<div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>  <span class="keyword">auto</span> fbDescriptor = graph->layers()->Get(layerIndex)->layer_as_DepthToSpaceLayer()->descriptor();</div> +<div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>  </div> +<div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>  <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html">armnn::DepthToSpaceDescriptor</a> descriptor;</div> +<div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a> = fbDescriptor->blockSize();</div> +<div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(fbDescriptor->dataLayout());</div> +<div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>  </div> +<div class="line"><a name="l01670"></a><span class="lineno"> 1670</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01671"></a><span class="lineno"> 1671</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddDepthToSpaceLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01672"></a><span class="lineno"> 1672</span>  </div> +<div class="line"><a name="l01673"></a><span class="lineno"> 1673</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01674"></a><span class="lineno"> 1674</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l01675"></a><span class="lineno"> 1675</span>  </div> +<div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01677"></a><span class="lineno"> 1677</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01678"></a><span class="lineno"> 1678</span> }</div> +<div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>  </div> +<div class="line"><a name="l01680"></a><span class="lineno"> 1680</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDepthwiseConvolution2d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01681"></a><span class="lineno"> 1681</span> {</div> +<div class="line"><a name="l01682"></a><span class="lineno"> 1682</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01683"></a><span class="lineno"> 1683</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01684"></a><span class="lineno"> 1684</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> <div class="line"><a name="l01685"></a><span class="lineno"> 1685</span>  </div> -<div class="line"><a name="l01686"></a><span class="lineno"> 1686</span>  <span class="comment">// Weights and biases used to be always constant and were stored as members of the layer. This has changed and</span></div> -<div class="line"><a name="l01687"></a><span class="lineno"> 1687</span>  <span class="comment">// they are now passed as inputs. If they are constant then they will be stored in a ConstantLayer.</span></div> -<div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_ConstTensorsAsInputs <= 0)</div> -<div class="line"><a name="l01689"></a><span class="lineno"> 1689</span>  {</div> -<div class="line"><a name="l01690"></a><span class="lineno"> 1690</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01691"></a><span class="lineno"> 1691</span>  </div> -<div class="line"><a name="l01692"></a><span class="lineno"> 1692</span>  <span class="comment">// If the model stores weights and biases as members of the layer we have to read them from there</span></div> -<div class="line"><a name="l01693"></a><span class="lineno"> 1693</span>  <span class="comment">// but add them to their own ConstantLayer for compatibility</span></div> -<div class="line"><a name="l01694"></a><span class="lineno"> 1694</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->weights());</div> -<div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>  ignoreSlots.emplace_back(1u);</div> -<div class="line"><a name="l01696"></a><span class="lineno"> 1696</span>  </div> -<div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>  layer = m_Network->AddDepthwiseConvolution2dLayer(descriptor,</div> -<div class="line"><a name="l01698"></a><span class="lineno"> 1698</span>  layerName.c_str());</div> -<div class="line"><a name="l01699"></a><span class="lineno"> 1699</span>  </div> -<div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>  <a class="code" href="classarmnn_1_1_optional.html">armnn::Optional<armnn::ConstTensor></a> optionalBiases = <a class="code" href="structarmnn_1_1_empty_optional.html">armnn::EmptyOptional</a>();</div> -<div class="line"><a name="l01701"></a><span class="lineno"> 1701</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div> -<div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>  {</div> -<div class="line"><a name="l01703"></a><span class="lineno"> 1703</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> biases = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->biases());</div> -<div class="line"><a name="l01704"></a><span class="lineno"> 1704</span>  ignoreSlots.emplace_back(2u);</div> -<div class="line"><a name="l01705"></a><span class="lineno"> 1705</span>  </div> -<div class="line"><a name="l01706"></a><span class="lineno"> 1706</span>  <span class="keyword">auto</span> biasLayer = m_Network->AddConstantLayer(biases);</div> -<div class="line"><a name="l01707"></a><span class="lineno"> 1707</span>  biasLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(2u));</div> -<div class="line"><a name="l01708"></a><span class="lineno"> 1708</span>  biasLayer->GetOutputSlot(0).SetTensorInfo(biases.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> -<div class="line"><a name="l01709"></a><span class="lineno"> 1709</span>  }</div> -<div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>  </div> -<div class="line"><a name="l01711"></a><span class="lineno"> 1711</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_WeightsLayoutScheme <= 0)</div> -<div class="line"><a name="l01712"></a><span class="lineno"> 1712</span>  {</div> -<div class="line"><a name="l01713"></a><span class="lineno"> 1713</span>  <span class="comment">// Permute weights [ H, W, M, I ] --> [ 1, H, W, I*M ]</span></div> -<div class="line"><a name="l01714"></a><span class="lineno"> 1714</span>  <span class="comment">// Step1: [ M, I, H, W ] --> [ H, W, I, M]</span></div> -<div class="line"><a name="l01715"></a><span class="lineno"> 1715</span>  <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permutationVector = { 3, 2, 0, 1 };</div> -<div class="line"><a name="l01716"></a><span class="lineno"> 1716</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> weightsInfo = weights.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>();</div> -<div class="line"><a name="l01717"></a><span class="lineno"> 1717</span>  std::unique_ptr<unsigned char[]> permuteBuffer(<span class="keyword">new</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>[weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>()]);</div> -<div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>  weightsInfo = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(weightsInfo, permutationVector);</div> -<div class="line"><a name="l01719"></a><span class="lineno"> 1719</span>  <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), permutationVector,</div> -<div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>  weights.<a class="code" href="classarmnn_1_1_base_tensor.html#aa81f67ac64f0c249e26499600c45d996">GetMemoryArea</a>(), permuteBuffer.get(),</div> -<div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>  <a class="code" href="namespacearmnn.html#aa02b9e06fb20fa3c13da0427e6ee5ab2">GetDataTypeSize</a>(weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>()));</div> -<div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>  </div> -<div class="line"><a name="l01723"></a><span class="lineno"> 1723</span>  <span class="comment">// Step2: Reshape [ H, W, I, M] --> [ 1, H, W, I*M ]</span></div> -<div class="line"><a name="l01724"></a><span class="lineno"> 1724</span>  <span class="keyword">auto</span> weightsShape = weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> -<div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>  weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({1,</div> -<div class="line"><a name="l01726"></a><span class="lineno"> 1726</span>  weightsShape[0],</div> -<div class="line"><a name="l01727"></a><span class="lineno"> 1727</span>  weightsShape[1],</div> -<div class="line"><a name="l01728"></a><span class="lineno"> 1728</span>  weightsShape[2]*weightsShape[3]});</div> -<div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>  </div> -<div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weightsPermuted(weightsInfo, permuteBuffer.get());</div> -<div class="line"><a name="l01731"></a><span class="lineno"> 1731</span>  </div> -<div class="line"><a name="l01732"></a><span class="lineno"> 1732</span>  <span class="keyword">auto</span> weightsLayer = m_Network->AddConstantLayer(weightsPermuted);</div> -<div class="line"><a name="l01733"></a><span class="lineno"> 1733</span>  weightsLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1u));</div> -<div class="line"><a name="l01734"></a><span class="lineno"> 1734</span>  weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsPermuted.GetInfo());</div> -<div class="line"><a name="l01735"></a><span class="lineno"> 1735</span>  }</div> -<div class="line"><a name="l01736"></a><span class="lineno"> 1736</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l01737"></a><span class="lineno"> 1737</span>  {</div> -<div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>  <span class="keyword">auto</span> weightsLayer = m_Network->AddConstantLayer(weights);</div> -<div class="line"><a name="l01739"></a><span class="lineno"> 1739</span>  weightsLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1u));</div> -<div class="line"><a name="l01740"></a><span class="lineno"> 1740</span>  weightsLayer->GetOutputSlot(0).SetTensorInfo(weights.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> -<div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>  }</div> -<div class="line"><a name="l01742"></a><span class="lineno"> 1742</span>  }</div> -<div class="line"><a name="l01743"></a><span class="lineno"> 1743</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l01744"></a><span class="lineno"> 1744</span>  {</div> -<div class="line"><a name="l01745"></a><span class="lineno"> 1745</span>  layer = m_Network->AddDepthwiseConvolution2dLayer(descriptor,</div> -<div class="line"><a name="l01746"></a><span class="lineno"> 1746</span>  layerName.c_str());</div> -<div class="line"><a name="l01747"></a><span class="lineno"> 1747</span>  uint32_t numInputs = descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>();</div> -<div class="line"><a name="l01748"></a><span class="lineno"> 1748</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> -<div class="line"><a name="l01749"></a><span class="lineno"> 1749</span>  }</div> -<div class="line"><a name="l01750"></a><span class="lineno"> 1750</span>  </div> -<div class="line"><a name="l01751"></a><span class="lineno"> 1751</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01752"></a><span class="lineno"> 1752</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01686"></a><span class="lineno"> 1686</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01687"></a><span class="lineno"> 1687</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>  </div> +<div class="line"><a name="l01689"></a><span class="lineno"> 1689</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer();</div> +<div class="line"><a name="l01690"></a><span class="lineno"> 1690</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01691"></a><span class="lineno"> 1691</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> +<div class="line"><a name="l01692"></a><span class="lineno"> 1692</span>  </div> +<div class="line"><a name="l01693"></a><span class="lineno"> 1693</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">armnn::DepthwiseConvolution2dDescriptor</a> descriptor;</div> +<div class="line"><a name="l01694"></a><span class="lineno"> 1694</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = serializerDescriptor->padLeft();</div> +<div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = serializerDescriptor->padRight();</div> +<div class="line"><a name="l01696"></a><span class="lineno"> 1696</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = serializerDescriptor->padTop();</div> +<div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = serializerDescriptor->padBottom();</div> +<div class="line"><a name="l01698"></a><span class="lineno"> 1698</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = serializerDescriptor->strideX();</div> +<div class="line"><a name="l01699"></a><span class="lineno"> 1699</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = serializerDescriptor->strideY();</div> +<div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = serializerDescriptor->dilationX();</div> +<div class="line"><a name="l01701"></a><span class="lineno"> 1701</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = serializerDescriptor->dilationY();</div> +<div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = serializerDescriptor->biasEnabled();</div> +<div class="line"><a name="l01703"></a><span class="lineno"> 1703</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div> +<div class="line"><a name="l01704"></a><span class="lineno"> 1704</span>  </div> +<div class="line"><a name="l01705"></a><span class="lineno"> 1705</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer;</div> +<div class="line"><a name="l01706"></a><span class="lineno"> 1706</span>  std::vector<unsigned int> ignoreSlots {};</div> +<div class="line"><a name="l01707"></a><span class="lineno"> 1707</span>  </div> +<div class="line"><a name="l01708"></a><span class="lineno"> 1708</span>  <span class="comment">// Weights and biases used to be always constant and were stored as members of the layer. This has changed and</span></div> +<div class="line"><a name="l01709"></a><span class="lineno"> 1709</span>  <span class="comment">// they are now passed as inputs. If they are constant then they will be stored in a ConstantLayer.</span></div> +<div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_ConstTensorsAsInputs <= 0)</div> +<div class="line"><a name="l01711"></a><span class="lineno"> 1711</span>  {</div> +<div class="line"><a name="l01712"></a><span class="lineno"> 1712</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01713"></a><span class="lineno"> 1713</span>  </div> +<div class="line"><a name="l01714"></a><span class="lineno"> 1714</span>  <span class="comment">// If the model stores weights and biases as members of the layer we have to read them from there</span></div> +<div class="line"><a name="l01715"></a><span class="lineno"> 1715</span>  <span class="comment">// but add them to their own ConstantLayer for compatibility</span></div> +<div class="line"><a name="l01716"></a><span class="lineno"> 1716</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->weights());</div> +<div class="line"><a name="l01717"></a><span class="lineno"> 1717</span>  ignoreSlots.emplace_back(1u);</div> +<div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>  </div> +<div class="line"><a name="l01719"></a><span class="lineno"> 1719</span>  layer = m_Network->AddDepthwiseConvolution2dLayer(descriptor,</div> +<div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>  layerName.c_str());</div> +<div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>  </div> +<div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>  <a class="code" href="classarmnn_1_1_optional.html">armnn::Optional<armnn::ConstTensor></a> optionalBiases = <a class="code" href="structarmnn_1_1_empty_optional.html">armnn::EmptyOptional</a>();</div> +<div class="line"><a name="l01723"></a><span class="lineno"> 1723</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div> +<div class="line"><a name="l01724"></a><span class="lineno"> 1724</span>  {</div> +<div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> biases = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->biases());</div> +<div class="line"><a name="l01726"></a><span class="lineno"> 1726</span>  ignoreSlots.emplace_back(2u);</div> +<div class="line"><a name="l01727"></a><span class="lineno"> 1727</span>  </div> +<div class="line"><a name="l01728"></a><span class="lineno"> 1728</span>  <span class="keyword">auto</span> biasLayer = m_Network->AddConstantLayer(biases);</div> +<div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>  biasLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(2u));</div> +<div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>  biasLayer->GetOutputSlot(0).SetTensorInfo(biases.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> +<div class="line"><a name="l01731"></a><span class="lineno"> 1731</span>  }</div> +<div class="line"><a name="l01732"></a><span class="lineno"> 1732</span>  </div> +<div class="line"><a name="l01733"></a><span class="lineno"> 1733</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_WeightsLayoutScheme <= 0)</div> +<div class="line"><a name="l01734"></a><span class="lineno"> 1734</span>  {</div> +<div class="line"><a name="l01735"></a><span class="lineno"> 1735</span>  <span class="comment">// Permute weights [ H, W, M, I ] --> [ 1, H, W, I*M ]</span></div> +<div class="line"><a name="l01736"></a><span class="lineno"> 1736</span>  <span class="comment">// Step1: [ M, I, H, W ] --> [ H, W, I, M]</span></div> +<div class="line"><a name="l01737"></a><span class="lineno"> 1737</span>  <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permutationVector = { 3, 2, 0, 1 };</div> +<div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> weightsInfo = weights.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>();</div> +<div class="line"><a name="l01739"></a><span class="lineno"> 1739</span>  std::unique_ptr<unsigned char[]> permuteBuffer(<span class="keyword">new</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>[weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>()]);</div> +<div class="line"><a name="l01740"></a><span class="lineno"> 1740</span>  weightsInfo = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(weightsInfo, permutationVector);</div> +<div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>  <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), permutationVector,</div> +<div class="line"><a name="l01742"></a><span class="lineno"> 1742</span>  weights.<a class="code" href="classarmnn_1_1_base_tensor.html#aa81f67ac64f0c249e26499600c45d996">GetMemoryArea</a>(), permuteBuffer.get(),</div> +<div class="line"><a name="l01743"></a><span class="lineno"> 1743</span>  <a class="code" href="namespacearmnn.html#aa02b9e06fb20fa3c13da0427e6ee5ab2">GetDataTypeSize</a>(weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>()));</div> +<div class="line"><a name="l01744"></a><span class="lineno"> 1744</span>  </div> +<div class="line"><a name="l01745"></a><span class="lineno"> 1745</span>  <span class="comment">// Step2: Reshape [ H, W, I, M] --> [ 1, H, W, I*M ]</span></div> +<div class="line"><a name="l01746"></a><span class="lineno"> 1746</span>  <span class="keyword">auto</span> weightsShape = weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> +<div class="line"><a name="l01747"></a><span class="lineno"> 1747</span>  weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({1,</div> +<div class="line"><a name="l01748"></a><span class="lineno"> 1748</span>  weightsShape[0],</div> +<div class="line"><a name="l01749"></a><span class="lineno"> 1749</span>  weightsShape[1],</div> +<div class="line"><a name="l01750"></a><span class="lineno"> 1750</span>  weightsShape[2]*weightsShape[3]});</div> +<div class="line"><a name="l01751"></a><span class="lineno"> 1751</span>  </div> +<div class="line"><a name="l01752"></a><span class="lineno"> 1752</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weightsPermuted(weightsInfo, permuteBuffer.get());</div> <div class="line"><a name="l01753"></a><span class="lineno"> 1753</span>  </div> -<div class="line"><a name="l01754"></a><span class="lineno"> 1754</span>  RegisterInputSlots(graph, layerIndex, layer, ignoreSlots);</div> -<div class="line"><a name="l01755"></a><span class="lineno"> 1755</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01756"></a><span class="lineno"> 1756</span> }</div> -<div class="line"><a name="l01757"></a><span class="lineno"> 1757</span>  </div> -<div class="line"><a name="l01758"></a><span class="lineno"> 1758</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDetectionPostProcess(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01759"></a><span class="lineno"> 1759</span> {</div> -<div class="line"><a name="l01760"></a><span class="lineno"> 1760</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01761"></a><span class="lineno"> 1761</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01762"></a><span class="lineno"> 1762</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01763"></a><span class="lineno"> 1763</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l01764"></a><span class="lineno"> 1764</span>  </div> -<div class="line"><a name="l01765"></a><span class="lineno"> 1765</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01766"></a><span class="lineno"> 1766</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 4);</div> -<div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>  </div> -<div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_DetectionPostProcessLayer();</div> -<div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01770"></a><span class="lineno"> 1770</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> -<div class="line"><a name="l01771"></a><span class="lineno"> 1771</span>  </div> -<div class="line"><a name="l01772"></a><span class="lineno"> 1772</span>  <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html">armnn::DetectionPostProcessDescriptor</a> descriptor;</div> -<div class="line"><a name="l01773"></a><span class="lineno"> 1773</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a> = flatBufferDescriptor->maxDetections();</div> -<div class="line"><a name="l01774"></a><span class="lineno"> 1774</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a9ae2c9796692ebeafe19a4d3f09c8ea8">m_MaxClassesPerDetection</a> = flatBufferDescriptor->maxClassesPerDetection();</div> -<div class="line"><a name="l01775"></a><span class="lineno"> 1775</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a7e2f87544b8bc7e497e1dec8d3ca4055">m_DetectionsPerClass</a> = flatBufferDescriptor->detectionsPerClass();</div> -<div class="line"><a name="l01776"></a><span class="lineno"> 1776</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a4392dd6b4862cc9cf95ae8f1001ba592">m_NmsScoreThreshold</a> = flatBufferDescriptor->nmsScoreThreshold();</div> -<div class="line"><a name="l01777"></a><span class="lineno"> 1777</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a53c8a7f33a40e1e240256bcfcf41b101">m_NmsIouThreshold</a> = flatBufferDescriptor->nmsIouThreshold();</div> -<div class="line"><a name="l01778"></a><span class="lineno"> 1778</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a3a04b0ccee4bb2f21721ee5045e83df4">m_NumClasses</a> = flatBufferDescriptor->numClasses();</div> -<div class="line"><a name="l01779"></a><span class="lineno"> 1779</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a7ed9bc7c26df67d274d5dd4cd83adf0f">m_UseRegularNms</a> = flatBufferDescriptor->useRegularNms();</div> -<div class="line"><a name="l01780"></a><span class="lineno"> 1780</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#ae64523937ea910030ad66fee6fddd51f">m_ScaleX</a> = flatBufferDescriptor->scaleX();</div> -<div class="line"><a name="l01781"></a><span class="lineno"> 1781</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a7a2156ec7d9c012ce00bbcc6afcb9028">m_ScaleY</a> = flatBufferDescriptor->scaleY();</div> -<div class="line"><a name="l01782"></a><span class="lineno"> 1782</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#ab509802c659de19929f18bad14a35c58">m_ScaleW</a> = flatBufferDescriptor->scaleW();</div> -<div class="line"><a name="l01783"></a><span class="lineno"> 1783</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#aa61510cbd529870182e918ac6e8b9d72">m_ScaleH</a> = flatBufferDescriptor->scaleH();</div> -<div class="line"><a name="l01784"></a><span class="lineno"> 1784</span>  </div> -<div class="line"><a name="l01785"></a><span class="lineno"> 1785</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> anchors = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->anchors());</div> +<div class="line"><a name="l01754"></a><span class="lineno"> 1754</span>  <span class="keyword">auto</span> weightsLayer = m_Network->AddConstantLayer(weightsPermuted);</div> +<div class="line"><a name="l01755"></a><span class="lineno"> 1755</span>  weightsLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1u));</div> +<div class="line"><a name="l01756"></a><span class="lineno"> 1756</span>  weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsPermuted.GetInfo());</div> +<div class="line"><a name="l01757"></a><span class="lineno"> 1757</span>  }</div> +<div class="line"><a name="l01758"></a><span class="lineno"> 1758</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l01759"></a><span class="lineno"> 1759</span>  {</div> +<div class="line"><a name="l01760"></a><span class="lineno"> 1760</span>  <span class="keyword">auto</span> weightsLayer = m_Network->AddConstantLayer(weights);</div> +<div class="line"><a name="l01761"></a><span class="lineno"> 1761</span>  weightsLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1u));</div> +<div class="line"><a name="l01762"></a><span class="lineno"> 1762</span>  weightsLayer->GetOutputSlot(0).SetTensorInfo(weights.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> +<div class="line"><a name="l01763"></a><span class="lineno"> 1763</span>  }</div> +<div class="line"><a name="l01764"></a><span class="lineno"> 1764</span>  }</div> +<div class="line"><a name="l01765"></a><span class="lineno"> 1765</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l01766"></a><span class="lineno"> 1766</span>  {</div> +<div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>  layer = m_Network->AddDepthwiseConvolution2dLayer(descriptor,</div> +<div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>  layerName.c_str());</div> +<div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>  uint32_t numInputs = descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>();</div> +<div class="line"><a name="l01770"></a><span class="lineno"> 1770</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> +<div class="line"><a name="l01771"></a><span class="lineno"> 1771</span>  }</div> +<div class="line"><a name="l01772"></a><span class="lineno"> 1772</span>  </div> +<div class="line"><a name="l01773"></a><span class="lineno"> 1773</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01774"></a><span class="lineno"> 1774</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01775"></a><span class="lineno"> 1775</span>  </div> +<div class="line"><a name="l01776"></a><span class="lineno"> 1776</span>  RegisterInputSlots(graph, layerIndex, layer, ignoreSlots);</div> +<div class="line"><a name="l01777"></a><span class="lineno"> 1777</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01778"></a><span class="lineno"> 1778</span> }</div> +<div class="line"><a name="l01779"></a><span class="lineno"> 1779</span>  </div> +<div class="line"><a name="l01780"></a><span class="lineno"> 1780</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDetectionPostProcess(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01781"></a><span class="lineno"> 1781</span> {</div> +<div class="line"><a name="l01782"></a><span class="lineno"> 1782</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01783"></a><span class="lineno"> 1783</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01784"></a><span class="lineno"> 1784</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01785"></a><span class="lineno"> 1785</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> <div class="line"><a name="l01786"></a><span class="lineno"> 1786</span>  </div> -<div class="line"><a name="l01787"></a><span class="lineno"> 1787</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddDetectionPostProcessLayer(descriptor,</div> -<div class="line"><a name="l01788"></a><span class="lineno"> 1788</span>  anchors,</div> -<div class="line"><a name="l01789"></a><span class="lineno"> 1789</span>  layerName.c_str());</div> -<div class="line"><a name="l01790"></a><span class="lineno"> 1790</span>  </div> -<div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < 4; i++)</div> -<div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>  {</div> -<div class="line"><a name="l01793"></a><span class="lineno"> 1793</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(i).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[i]));</div> -<div class="line"><a name="l01794"></a><span class="lineno"> 1794</span>  }</div> -<div class="line"><a name="l01795"></a><span class="lineno"> 1795</span>  </div> -<div class="line"><a name="l01796"></a><span class="lineno"> 1796</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01797"></a><span class="lineno"> 1797</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01798"></a><span class="lineno"> 1798</span> }</div> -<div class="line"><a name="l01799"></a><span class="lineno"> 1799</span>  </div> -<div class="line"><a name="l01800"></a><span class="lineno"> 1800</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDivision(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01801"></a><span class="lineno"> 1801</span> {</div> -<div class="line"><a name="l01802"></a><span class="lineno"> 1802</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01803"></a><span class="lineno"> 1803</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01804"></a><span class="lineno"> 1804</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01805"></a><span class="lineno"> 1805</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l01787"></a><span class="lineno"> 1787</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01788"></a><span class="lineno"> 1788</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 4);</div> +<div class="line"><a name="l01789"></a><span class="lineno"> 1789</span>  </div> +<div class="line"><a name="l01790"></a><span class="lineno"> 1790</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_DetectionPostProcessLayer();</div> +<div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> +<div class="line"><a name="l01793"></a><span class="lineno"> 1793</span>  </div> +<div class="line"><a name="l01794"></a><span class="lineno"> 1794</span>  <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html">armnn::DetectionPostProcessDescriptor</a> descriptor;</div> +<div class="line"><a name="l01795"></a><span class="lineno"> 1795</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a> = flatBufferDescriptor->maxDetections();</div> +<div class="line"><a name="l01796"></a><span class="lineno"> 1796</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a9ae2c9796692ebeafe19a4d3f09c8ea8">m_MaxClassesPerDetection</a> = flatBufferDescriptor->maxClassesPerDetection();</div> +<div class="line"><a name="l01797"></a><span class="lineno"> 1797</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a7e2f87544b8bc7e497e1dec8d3ca4055">m_DetectionsPerClass</a> = flatBufferDescriptor->detectionsPerClass();</div> +<div class="line"><a name="l01798"></a><span class="lineno"> 1798</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a4392dd6b4862cc9cf95ae8f1001ba592">m_NmsScoreThreshold</a> = flatBufferDescriptor->nmsScoreThreshold();</div> +<div class="line"><a name="l01799"></a><span class="lineno"> 1799</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a53c8a7f33a40e1e240256bcfcf41b101">m_NmsIouThreshold</a> = flatBufferDescriptor->nmsIouThreshold();</div> +<div class="line"><a name="l01800"></a><span class="lineno"> 1800</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a3a04b0ccee4bb2f21721ee5045e83df4">m_NumClasses</a> = flatBufferDescriptor->numClasses();</div> +<div class="line"><a name="l01801"></a><span class="lineno"> 1801</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a7ed9bc7c26df67d274d5dd4cd83adf0f">m_UseRegularNms</a> = flatBufferDescriptor->useRegularNms();</div> +<div class="line"><a name="l01802"></a><span class="lineno"> 1802</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#ae64523937ea910030ad66fee6fddd51f">m_ScaleX</a> = flatBufferDescriptor->scaleX();</div> +<div class="line"><a name="l01803"></a><span class="lineno"> 1803</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#a7a2156ec7d9c012ce00bbcc6afcb9028">m_ScaleY</a> = flatBufferDescriptor->scaleY();</div> +<div class="line"><a name="l01804"></a><span class="lineno"> 1804</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#ab509802c659de19929f18bad14a35c58">m_ScaleW</a> = flatBufferDescriptor->scaleW();</div> +<div class="line"><a name="l01805"></a><span class="lineno"> 1805</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#aa61510cbd529870182e918ac6e8b9d72">m_ScaleH</a> = flatBufferDescriptor->scaleH();</div> <div class="line"><a name="l01806"></a><span class="lineno"> 1806</span>  </div> -<div class="line"><a name="l01807"></a><span class="lineno"> 1807</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01808"></a><span class="lineno"> 1808</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01809"></a><span class="lineno"> 1809</span>  </div> -<div class="line"><a name="l01810"></a><span class="lineno"> 1810</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01811"></a><span class="lineno"> 1811</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a43d11850893d2fe84a1e618121c1cc0a">armnn::BinaryOperation::Div</a>);</div> -<div class="line"><a name="l01812"></a><span class="lineno"> 1812</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01813"></a><span class="lineno"> 1813</span>  </div> -<div class="line"><a name="l01814"></a><span class="lineno"> 1814</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01815"></a><span class="lineno"> 1815</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01816"></a><span class="lineno"> 1816</span>  </div> -<div class="line"><a name="l01817"></a><span class="lineno"> 1817</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01818"></a><span class="lineno"> 1818</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01819"></a><span class="lineno"> 1819</span> }</div> -<div class="line"><a name="l01820"></a><span class="lineno"> 1820</span>  </div> -<div class="line"><a name="l01821"></a><span class="lineno"> 1821</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseEqual(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01822"></a><span class="lineno"> 1822</span> {</div> -<div class="line"><a name="l01823"></a><span class="lineno"> 1823</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01824"></a><span class="lineno"> 1824</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01825"></a><span class="lineno"> 1825</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01826"></a><span class="lineno"> 1826</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l01827"></a><span class="lineno"> 1827</span>  </div> -<div class="line"><a name="l01828"></a><span class="lineno"> 1828</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01829"></a><span class="lineno"> 1829</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01830"></a><span class="lineno"> 1830</span>  </div> -<div class="line"><a name="l01831"></a><span class="lineno"> 1831</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01832"></a><span class="lineno"> 1832</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.html">armnn::ComparisonDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">armnn::ComparisonOperation::Equal</a>);</div> -<div class="line"><a name="l01833"></a><span class="lineno"> 1833</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddComparisonLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01834"></a><span class="lineno"> 1834</span>  </div> -<div class="line"><a name="l01835"></a><span class="lineno"> 1835</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01836"></a><span class="lineno"> 1836</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01837"></a><span class="lineno"> 1837</span>  </div> -<div class="line"><a name="l01838"></a><span class="lineno"> 1838</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01839"></a><span class="lineno"> 1839</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01840"></a><span class="lineno"> 1840</span> }</div> -<div class="line"><a name="l01841"></a><span class="lineno"> 1841</span>  </div> -<div class="line"><a name="l01842"></a><span class="lineno"> 1842</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseFill(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01843"></a><span class="lineno"> 1843</span> {</div> -<div class="line"><a name="l01844"></a><span class="lineno"> 1844</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01845"></a><span class="lineno"> 1845</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01846"></a><span class="lineno"> 1846</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01847"></a><span class="lineno"> 1847</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01848"></a><span class="lineno"> 1848</span>  </div> -<div class="line"><a name="l01849"></a><span class="lineno"> 1849</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01850"></a><span class="lineno"> 1850</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01851"></a><span class="lineno"> 1851</span>  </div> -<div class="line"><a name="l01852"></a><span class="lineno"> 1852</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01853"></a><span class="lineno"> 1853</span>  <a class="code" href="structarmnn_1_1_fill_descriptor.html">armnn::FillDescriptor</a> descriptor;</div> -<div class="line"><a name="l01854"></a><span class="lineno"> 1854</span>  descriptor.<a class="code" href="structarmnn_1_1_fill_descriptor.html#ab3ebc5cf4a617d43371a4cb7fecdeb32">m_Value</a> = graph->layers()->Get(layerIndex)->layer_as_FillLayer()->descriptor()->value();</div> -<div class="line"><a name="l01855"></a><span class="lineno"> 1855</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddFillLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01807"></a><span class="lineno"> 1807</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> anchors = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->anchors());</div> +<div class="line"><a name="l01808"></a><span class="lineno"> 1808</span>  </div> +<div class="line"><a name="l01809"></a><span class="lineno"> 1809</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddDetectionPostProcessLayer(descriptor,</div> +<div class="line"><a name="l01810"></a><span class="lineno"> 1810</span>  anchors,</div> +<div class="line"><a name="l01811"></a><span class="lineno"> 1811</span>  layerName.c_str());</div> +<div class="line"><a name="l01812"></a><span class="lineno"> 1812</span>  </div> +<div class="line"><a name="l01813"></a><span class="lineno"> 1813</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < 4; i++)</div> +<div class="line"><a name="l01814"></a><span class="lineno"> 1814</span>  {</div> +<div class="line"><a name="l01815"></a><span class="lineno"> 1815</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(i).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[i]));</div> +<div class="line"><a name="l01816"></a><span class="lineno"> 1816</span>  }</div> +<div class="line"><a name="l01817"></a><span class="lineno"> 1817</span>  </div> +<div class="line"><a name="l01818"></a><span class="lineno"> 1818</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01819"></a><span class="lineno"> 1819</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01820"></a><span class="lineno"> 1820</span> }</div> +<div class="line"><a name="l01821"></a><span class="lineno"> 1821</span>  </div> +<div class="line"><a name="l01822"></a><span class="lineno"> 1822</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDivision(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01823"></a><span class="lineno"> 1823</span> {</div> +<div class="line"><a name="l01824"></a><span class="lineno"> 1824</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01825"></a><span class="lineno"> 1825</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01826"></a><span class="lineno"> 1826</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01827"></a><span class="lineno"> 1827</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l01828"></a><span class="lineno"> 1828</span>  </div> +<div class="line"><a name="l01829"></a><span class="lineno"> 1829</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01830"></a><span class="lineno"> 1830</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01831"></a><span class="lineno"> 1831</span>  </div> +<div class="line"><a name="l01832"></a><span class="lineno"> 1832</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01833"></a><span class="lineno"> 1833</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a43d11850893d2fe84a1e618121c1cc0a">armnn::BinaryOperation::Div</a>);</div> +<div class="line"><a name="l01834"></a><span class="lineno"> 1834</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01835"></a><span class="lineno"> 1835</span>  </div> +<div class="line"><a name="l01836"></a><span class="lineno"> 1836</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01837"></a><span class="lineno"> 1837</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01838"></a><span class="lineno"> 1838</span>  </div> +<div class="line"><a name="l01839"></a><span class="lineno"> 1839</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01840"></a><span class="lineno"> 1840</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01841"></a><span class="lineno"> 1841</span> }</div> +<div class="line"><a name="l01842"></a><span class="lineno"> 1842</span>  </div> +<div class="line"><a name="l01843"></a><span class="lineno"> 1843</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseEqual(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01844"></a><span class="lineno"> 1844</span> {</div> +<div class="line"><a name="l01845"></a><span class="lineno"> 1845</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01846"></a><span class="lineno"> 1846</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01847"></a><span class="lineno"> 1847</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01848"></a><span class="lineno"> 1848</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l01849"></a><span class="lineno"> 1849</span>  </div> +<div class="line"><a name="l01850"></a><span class="lineno"> 1850</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01851"></a><span class="lineno"> 1851</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01852"></a><span class="lineno"> 1852</span>  </div> +<div class="line"><a name="l01853"></a><span class="lineno"> 1853</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01854"></a><span class="lineno"> 1854</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.html">armnn::ComparisonDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">armnn::ComparisonOperation::Equal</a>);</div> +<div class="line"><a name="l01855"></a><span class="lineno"> 1855</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddComparisonLayer(descriptor, layerName.c_str());</div> <div class="line"><a name="l01856"></a><span class="lineno"> 1856</span>  </div> <div class="line"><a name="l01857"></a><span class="lineno"> 1857</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> <div class="line"><a name="l01858"></a><span class="lineno"> 1858</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> @@ -1959,2168 +1959,2219 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="line"><a name="l01861"></a><span class="lineno"> 1861</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> <div class="line"><a name="l01862"></a><span class="lineno"> 1862</span> }</div> <div class="line"><a name="l01863"></a><span class="lineno"> 1863</span>  </div> -<div class="line"><a name="l01864"></a><span class="lineno"> 1864</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseGreater(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01864"></a><span class="lineno"> 1864</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseFill(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> <div class="line"><a name="l01865"></a><span class="lineno"> 1865</span> {</div> <div class="line"><a name="l01866"></a><span class="lineno"> 1866</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l01867"></a><span class="lineno"> 1867</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> <div class="line"><a name="l01868"></a><span class="lineno"> 1868</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01869"></a><span class="lineno"> 1869</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l01869"></a><span class="lineno"> 1869</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> <div class="line"><a name="l01870"></a><span class="lineno"> 1870</span>  </div> <div class="line"><a name="l01871"></a><span class="lineno"> 1871</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> <div class="line"><a name="l01872"></a><span class="lineno"> 1872</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l01873"></a><span class="lineno"> 1873</span>  </div> <div class="line"><a name="l01874"></a><span class="lineno"> 1874</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01875"></a><span class="lineno"> 1875</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.html">armnn::ComparisonDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">armnn::ComparisonOperation::Greater</a>);</div> -<div class="line"><a name="l01876"></a><span class="lineno"> 1876</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddComparisonLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01877"></a><span class="lineno"> 1877</span>  </div> -<div class="line"><a name="l01878"></a><span class="lineno"> 1878</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01879"></a><span class="lineno"> 1879</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01880"></a><span class="lineno"> 1880</span>  </div> -<div class="line"><a name="l01881"></a><span class="lineno"> 1881</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01882"></a><span class="lineno"> 1882</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01883"></a><span class="lineno"> 1883</span> }</div> -<div class="line"><a name="l01884"></a><span class="lineno"> 1884</span>  </div> -<div class="line"><a name="l01885"></a><span class="lineno"> 1885</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseInstanceNormalization(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01886"></a><span class="lineno"> 1886</span> {</div> -<div class="line"><a name="l01887"></a><span class="lineno"> 1887</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01888"></a><span class="lineno"> 1888</span>  </div> +<div class="line"><a name="l01875"></a><span class="lineno"> 1875</span>  <a class="code" href="structarmnn_1_1_fill_descriptor.html">armnn::FillDescriptor</a> descriptor;</div> +<div class="line"><a name="l01876"></a><span class="lineno"> 1876</span>  descriptor.<a class="code" href="structarmnn_1_1_fill_descriptor.html#ab3ebc5cf4a617d43371a4cb7fecdeb32">m_Value</a> = graph->layers()->Get(layerIndex)->layer_as_FillLayer()->descriptor()->value();</div> +<div class="line"><a name="l01877"></a><span class="lineno"> 1877</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddFillLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01878"></a><span class="lineno"> 1878</span>  </div> +<div class="line"><a name="l01879"></a><span class="lineno"> 1879</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01880"></a><span class="lineno"> 1880</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01881"></a><span class="lineno"> 1881</span>  </div> +<div class="line"><a name="l01882"></a><span class="lineno"> 1882</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01883"></a><span class="lineno"> 1883</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01884"></a><span class="lineno"> 1884</span> }</div> +<div class="line"><a name="l01885"></a><span class="lineno"> 1885</span>  </div> +<div class="line"><a name="l01886"></a><span class="lineno"> 1886</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseGreater(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01887"></a><span class="lineno"> 1887</span> {</div> +<div class="line"><a name="l01888"></a><span class="lineno"> 1888</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l01889"></a><span class="lineno"> 1889</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01890"></a><span class="lineno"> 1890</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01891"></a><span class="lineno"> 1891</span>  </div> -<div class="line"><a name="l01892"></a><span class="lineno"> 1892</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01893"></a><span class="lineno"> 1893</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01894"></a><span class="lineno"> 1894</span>  </div> -<div class="line"><a name="l01895"></a><span class="lineno"> 1895</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_InstanceNormalizationLayer();</div> -<div class="line"><a name="l01896"></a><span class="lineno"> 1896</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> -<div class="line"><a name="l01897"></a><span class="lineno"> 1897</span>  </div> -<div class="line"><a name="l01898"></a><span class="lineno"> 1898</span>  <a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html">armnn::InstanceNormalizationDescriptor</a> descriptor;</div> -<div class="line"><a name="l01899"></a><span class="lineno"> 1899</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html#a5e078fd505aef7bccaa05c8058e096cc">m_Gamma</a> = fbDescriptor->gamma();</div> -<div class="line"><a name="l01900"></a><span class="lineno"> 1900</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = fbDescriptor->beta();</div> -<div class="line"><a name="l01901"></a><span class="lineno"> 1901</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> = fbDescriptor->eps();</div> -<div class="line"><a name="l01902"></a><span class="lineno"> 1902</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(fbDescriptor->dataLayout());</div> -<div class="line"><a name="l01903"></a><span class="lineno"> 1903</span>  </div> -<div class="line"><a name="l01904"></a><span class="lineno"> 1904</span>  <span class="keyword">const</span> std::string layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01905"></a><span class="lineno"> 1905</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01890"></a><span class="lineno"> 1890</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l01891"></a><span class="lineno"> 1891</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l01892"></a><span class="lineno"> 1892</span>  </div> +<div class="line"><a name="l01893"></a><span class="lineno"> 1893</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01894"></a><span class="lineno"> 1894</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01895"></a><span class="lineno"> 1895</span>  </div> +<div class="line"><a name="l01896"></a><span class="lineno"> 1896</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01897"></a><span class="lineno"> 1897</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.html">armnn::ComparisonDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">armnn::ComparisonOperation::Greater</a>);</div> +<div class="line"><a name="l01898"></a><span class="lineno"> 1898</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddComparisonLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01899"></a><span class="lineno"> 1899</span>  </div> +<div class="line"><a name="l01900"></a><span class="lineno"> 1900</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01901"></a><span class="lineno"> 1901</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01902"></a><span class="lineno"> 1902</span>  </div> +<div class="line"><a name="l01903"></a><span class="lineno"> 1903</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01904"></a><span class="lineno"> 1904</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01905"></a><span class="lineno"> 1905</span> }</div> <div class="line"><a name="l01906"></a><span class="lineno"> 1906</span>  </div> -<div class="line"><a name="l01907"></a><span class="lineno"> 1907</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddInstanceNormalizationLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01908"></a><span class="lineno"> 1908</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> -<div class="line"><a name="l01909"></a><span class="lineno"> 1909</span>  </div> -<div class="line"><a name="l01910"></a><span class="lineno"> 1910</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01911"></a><span class="lineno"> 1911</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01912"></a><span class="lineno"> 1912</span> }</div> +<div class="line"><a name="l01907"></a><span class="lineno"> 1907</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseInstanceNormalization(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01908"></a><span class="lineno"> 1908</span> {</div> +<div class="line"><a name="l01909"></a><span class="lineno"> 1909</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01910"></a><span class="lineno"> 1910</span>  </div> +<div class="line"><a name="l01911"></a><span class="lineno"> 1911</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01912"></a><span class="lineno"> 1912</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> <div class="line"><a name="l01913"></a><span class="lineno"> 1913</span>  </div> -<div class="line"><a name="l01914"></a><span class="lineno"> 1914</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseL2Normalization(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01915"></a><span class="lineno"> 1915</span> {</div> -<div class="line"><a name="l01916"></a><span class="lineno"> 1916</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01917"></a><span class="lineno"> 1917</span>  </div> -<div class="line"><a name="l01918"></a><span class="lineno"> 1918</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01919"></a><span class="lineno"> 1919</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01920"></a><span class="lineno"> 1920</span>  </div> -<div class="line"><a name="l01921"></a><span class="lineno"> 1921</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01922"></a><span class="lineno"> 1922</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01924"></a><span class="lineno"> 1924</span>  </div> -<div class="line"><a name="l01925"></a><span class="lineno"> 1925</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_L2NormalizationLayer();</div> -<div class="line"><a name="l01926"></a><span class="lineno"> 1926</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> -<div class="line"><a name="l01927"></a><span class="lineno"> 1927</span>  </div> -<div class="line"><a name="l01928"></a><span class="lineno"> 1928</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01929"></a><span class="lineno"> 1929</span>  <a class="code" href="structarmnn_1_1_l2_normalization_descriptor.html">armnn::L2NormalizationDescriptor</a> descriptor;</div> -<div class="line"><a name="l01930"></a><span class="lineno"> 1930</span>  descriptor.<a class="code" href="structarmnn_1_1_l2_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> -<div class="line"><a name="l01931"></a><span class="lineno"> 1931</span>  descriptor.<a class="code" href="structarmnn_1_1_l2_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> = flatBufferDescriptor->eps();</div> -<div class="line"><a name="l01932"></a><span class="lineno"> 1932</span>  </div> -<div class="line"><a name="l01933"></a><span class="lineno"> 1933</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddL2NormalizationLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01934"></a><span class="lineno"> 1934</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l01914"></a><span class="lineno"> 1914</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01915"></a><span class="lineno"> 1915</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01916"></a><span class="lineno"> 1916</span>  </div> +<div class="line"><a name="l01917"></a><span class="lineno"> 1917</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_InstanceNormalizationLayer();</div> +<div class="line"><a name="l01918"></a><span class="lineno"> 1918</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> +<div class="line"><a name="l01919"></a><span class="lineno"> 1919</span>  </div> +<div class="line"><a name="l01920"></a><span class="lineno"> 1920</span>  <a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html">armnn::InstanceNormalizationDescriptor</a> descriptor;</div> +<div class="line"><a name="l01921"></a><span class="lineno"> 1921</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html#a5e078fd505aef7bccaa05c8058e096cc">m_Gamma</a> = fbDescriptor->gamma();</div> +<div class="line"><a name="l01922"></a><span class="lineno"> 1922</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = fbDescriptor->beta();</div> +<div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> = fbDescriptor->eps();</div> +<div class="line"><a name="l01924"></a><span class="lineno"> 1924</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(fbDescriptor->dataLayout());</div> +<div class="line"><a name="l01925"></a><span class="lineno"> 1925</span>  </div> +<div class="line"><a name="l01926"></a><span class="lineno"> 1926</span>  <span class="keyword">const</span> std::string layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01927"></a><span class="lineno"> 1927</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01928"></a><span class="lineno"> 1928</span>  </div> +<div class="line"><a name="l01929"></a><span class="lineno"> 1929</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddInstanceNormalizationLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01930"></a><span class="lineno"> 1930</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l01931"></a><span class="lineno"> 1931</span>  </div> +<div class="line"><a name="l01932"></a><span class="lineno"> 1932</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01933"></a><span class="lineno"> 1933</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01934"></a><span class="lineno"> 1934</span> }</div> <div class="line"><a name="l01935"></a><span class="lineno"> 1935</span>  </div> -<div class="line"><a name="l01936"></a><span class="lineno"> 1936</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01937"></a><span class="lineno"> 1937</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01938"></a><span class="lineno"> 1938</span> }</div> +<div class="line"><a name="l01936"></a><span class="lineno"> 1936</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseL2Normalization(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01937"></a><span class="lineno"> 1937</span> {</div> +<div class="line"><a name="l01938"></a><span class="lineno"> 1938</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l01939"></a><span class="lineno"> 1939</span>  </div> -<div class="line"><a name="l01940"></a><span class="lineno"> 1940</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseLogicalBinary(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01941"></a><span class="lineno"> 1941</span> {</div> -<div class="line"><a name="l01942"></a><span class="lineno"> 1942</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01943"></a><span class="lineno"> 1943</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>  </div> -<div class="line"><a name="l01945"></a><span class="lineno"> 1945</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01946"></a><span class="lineno"> 1946</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l01947"></a><span class="lineno"> 1947</span>  </div> -<div class="line"><a name="l01948"></a><span class="lineno"> 1948</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01949"></a><span class="lineno"> 1949</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01950"></a><span class="lineno"> 1950</span>  </div> -<div class="line"><a name="l01951"></a><span class="lineno"> 1951</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_LogicalBinaryLayer();</div> -<div class="line"><a name="l01952"></a><span class="lineno"> 1952</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> -<div class="line"><a name="l01953"></a><span class="lineno"> 1953</span>  </div> -<div class="line"><a name="l01954"></a><span class="lineno"> 1954</span>  <a class="code" href="structarmnn_1_1_logical_binary_descriptor.html">armnn::LogicalBinaryDescriptor</a> descriptor;</div> -<div class="line"><a name="l01955"></a><span class="lineno"> 1955</span>  descriptor.<a class="code" href="structarmnn_1_1_logical_binary_descriptor.html#a32c95d929d2e2e0fa7fc1a3a25865eb0">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.html#a2ccbea2c0078ba1d34c2ac48a8bdd342">ToLogicalBinaryOperation</a>(fbDescriptor->operation());</div> -<div class="line"><a name="l01956"></a><span class="lineno"> 1956</span>  </div> -<div class="line"><a name="l01957"></a><span class="lineno"> 1957</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l01958"></a><span class="lineno"> 1958</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddLogicalBinaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01959"></a><span class="lineno"> 1959</span>  </div> -<div class="line"><a name="l01960"></a><span class="lineno"> 1960</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01961"></a><span class="lineno"> 1961</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01962"></a><span class="lineno"> 1962</span>  </div> -<div class="line"><a name="l01963"></a><span class="lineno"> 1963</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01964"></a><span class="lineno"> 1964</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01965"></a><span class="lineno"> 1965</span> }</div> +<div class="line"><a name="l01940"></a><span class="lineno"> 1940</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01941"></a><span class="lineno"> 1941</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01942"></a><span class="lineno"> 1942</span>  </div> +<div class="line"><a name="l01943"></a><span class="lineno"> 1943</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01945"></a><span class="lineno"> 1945</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01946"></a><span class="lineno"> 1946</span>  </div> +<div class="line"><a name="l01947"></a><span class="lineno"> 1947</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_L2NormalizationLayer();</div> +<div class="line"><a name="l01948"></a><span class="lineno"> 1948</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> +<div class="line"><a name="l01949"></a><span class="lineno"> 1949</span>  </div> +<div class="line"><a name="l01950"></a><span class="lineno"> 1950</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01951"></a><span class="lineno"> 1951</span>  <a class="code" href="structarmnn_1_1_l2_normalization_descriptor.html">armnn::L2NormalizationDescriptor</a> descriptor;</div> +<div class="line"><a name="l01952"></a><span class="lineno"> 1952</span>  descriptor.<a class="code" href="structarmnn_1_1_l2_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> +<div class="line"><a name="l01953"></a><span class="lineno"> 1953</span>  descriptor.<a class="code" href="structarmnn_1_1_l2_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> = flatBufferDescriptor->eps();</div> +<div class="line"><a name="l01954"></a><span class="lineno"> 1954</span>  </div> +<div class="line"><a name="l01955"></a><span class="lineno"> 1955</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddL2NormalizationLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l01956"></a><span class="lineno"> 1956</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l01957"></a><span class="lineno"> 1957</span>  </div> +<div class="line"><a name="l01958"></a><span class="lineno"> 1958</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01959"></a><span class="lineno"> 1959</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01960"></a><span class="lineno"> 1960</span> }</div> +<div class="line"><a name="l01961"></a><span class="lineno"> 1961</span>  </div> +<div class="line"><a name="l01962"></a><span class="lineno"> 1962</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseLogicalBinary(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01963"></a><span class="lineno"> 1963</span> {</div> +<div class="line"><a name="l01964"></a><span class="lineno"> 1964</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01965"></a><span class="lineno"> 1965</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> <div class="line"><a name="l01966"></a><span class="lineno"> 1966</span>  </div> -<div class="line"><a name="l01967"></a><span class="lineno"> 1967</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseLogSoftmax(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01968"></a><span class="lineno"> 1968</span> {</div> -<div class="line"><a name="l01969"></a><span class="lineno"> 1969</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01970"></a><span class="lineno"> 1970</span>  </div> -<div class="line"><a name="l01971"></a><span class="lineno"> 1971</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01972"></a><span class="lineno"> 1972</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l01973"></a><span class="lineno"> 1973</span>  </div> -<div class="line"><a name="l01974"></a><span class="lineno"> 1974</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01975"></a><span class="lineno"> 1975</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l01976"></a><span class="lineno"> 1976</span>  </div> -<div class="line"><a name="l01977"></a><span class="lineno"> 1977</span>  <a class="code" href="structarmnn_1_1_softmax_descriptor.html">armnn::LogSoftmaxDescriptor</a> descriptor;</div> -<div class="line"><a name="l01978"></a><span class="lineno"> 1978</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = graph->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->descriptor()->beta();</div> -<div class="line"><a name="l01979"></a><span class="lineno"> 1979</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = graph->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->descriptor()->axis();</div> -<div class="line"><a name="l01980"></a><span class="lineno"> 1980</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01967"></a><span class="lineno"> 1967</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01968"></a><span class="lineno"> 1968</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l01969"></a><span class="lineno"> 1969</span>  </div> +<div class="line"><a name="l01970"></a><span class="lineno"> 1970</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01971"></a><span class="lineno"> 1971</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01972"></a><span class="lineno"> 1972</span>  </div> +<div class="line"><a name="l01973"></a><span class="lineno"> 1973</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_LogicalBinaryLayer();</div> +<div class="line"><a name="l01974"></a><span class="lineno"> 1974</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> +<div class="line"><a name="l01975"></a><span class="lineno"> 1975</span>  </div> +<div class="line"><a name="l01976"></a><span class="lineno"> 1976</span>  <a class="code" href="structarmnn_1_1_logical_binary_descriptor.html">armnn::LogicalBinaryDescriptor</a> descriptor;</div> +<div class="line"><a name="l01977"></a><span class="lineno"> 1977</span>  descriptor.<a class="code" href="structarmnn_1_1_logical_binary_descriptor.html#a32c95d929d2e2e0fa7fc1a3a25865eb0">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.html#a2ccbea2c0078ba1d34c2ac48a8bdd342">ToLogicalBinaryOperation</a>(fbDescriptor->operation());</div> +<div class="line"><a name="l01978"></a><span class="lineno"> 1978</span>  </div> +<div class="line"><a name="l01979"></a><span class="lineno"> 1979</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l01980"></a><span class="lineno"> 1980</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddLogicalBinaryLayer(descriptor, layerName.c_str());</div> <div class="line"><a name="l01981"></a><span class="lineno"> 1981</span>  </div> -<div class="line"><a name="l01982"></a><span class="lineno"> 1982</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddLogSoftmaxLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l01983"></a><span class="lineno"> 1983</span>  </div> -<div class="line"><a name="l01984"></a><span class="lineno"> 1984</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l01985"></a><span class="lineno"> 1985</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l01986"></a><span class="lineno"> 1986</span>  </div> -<div class="line"><a name="l01987"></a><span class="lineno"> 1987</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01988"></a><span class="lineno"> 1988</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l01989"></a><span class="lineno"> 1989</span> }</div> -<div class="line"><a name="l01990"></a><span class="lineno"> 1990</span>  </div> -<div class="line"><a name="l01991"></a><span class="lineno"> 1991</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMinimum(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l01992"></a><span class="lineno"> 1992</span> {</div> -<div class="line"><a name="l01993"></a><span class="lineno"> 1993</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l01994"></a><span class="lineno"> 1994</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l01995"></a><span class="lineno"> 1995</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l01996"></a><span class="lineno"> 1996</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l01997"></a><span class="lineno"> 1997</span>  </div> -<div class="line"><a name="l01998"></a><span class="lineno"> 1998</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l01999"></a><span class="lineno"> 1999</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02000"></a><span class="lineno"> 2000</span>  </div> -<div class="line"><a name="l02001"></a><span class="lineno"> 2001</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02002"></a><span class="lineno"> 2002</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aa1d0ec6d56f8833a078b5a7ac4caf2d4">armnn::BinaryOperation::Minimum</a>);</div> -<div class="line"><a name="l02003"></a><span class="lineno"> 2003</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02004"></a><span class="lineno"> 2004</span>  </div> -<div class="line"><a name="l02005"></a><span class="lineno"> 2005</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02006"></a><span class="lineno"> 2006</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02007"></a><span class="lineno"> 2007</span>  </div> -<div class="line"><a name="l02008"></a><span class="lineno"> 2008</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02009"></a><span class="lineno"> 2009</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02010"></a><span class="lineno"> 2010</span> }</div> -<div class="line"><a name="l02011"></a><span class="lineno"> 2011</span>  </div> -<div class="line"><a name="l02012"></a><span class="lineno"> 2012</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMaximum(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02013"></a><span class="lineno"> 2013</span> {</div> -<div class="line"><a name="l02014"></a><span class="lineno"> 2014</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02015"></a><span class="lineno"> 2015</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02016"></a><span class="lineno"> 2016</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l02017"></a><span class="lineno"> 2017</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l02018"></a><span class="lineno"> 2018</span>  </div> -<div class="line"><a name="l02019"></a><span class="lineno"> 2019</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02020"></a><span class="lineno"> 2020</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02021"></a><span class="lineno"> 2021</span>  </div> -<div class="line"><a name="l02022"></a><span class="lineno"> 2022</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02023"></a><span class="lineno"> 2023</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a8321e79c278ec510f63675c040594892">armnn::BinaryOperation::Maximum</a>);</div> -<div class="line"><a name="l02024"></a><span class="lineno"> 2024</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02025"></a><span class="lineno"> 2025</span>  </div> -<div class="line"><a name="l02026"></a><span class="lineno"> 2026</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02027"></a><span class="lineno"> 2027</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02028"></a><span class="lineno"> 2028</span>  </div> -<div class="line"><a name="l02029"></a><span class="lineno"> 2029</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02030"></a><span class="lineno"> 2030</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02031"></a><span class="lineno"> 2031</span> }</div> -<div class="line"><a name="l02032"></a><span class="lineno"> 2032</span>  </div> -<div class="line"><a name="l02033"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a63d3841a5ebb0a5ce572cfb4cb634376"> 2033</a></span> <span class="keyword">const</span> armnnSerializer::OriginsDescriptor* <a class="code" href="namespacearmnn_deserializer.html#a63d3841a5ebb0a5ce572cfb4cb634376">GetOriginsDescriptor</a>(<span class="keyword">const</span> armnnSerializer::SerializedGraph* graph,</div> -<div class="line"><a name="l02034"></a><span class="lineno"> 2034</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01982"></a><span class="lineno"> 1982</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l01983"></a><span class="lineno"> 1983</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l01984"></a><span class="lineno"> 1984</span>  </div> +<div class="line"><a name="l01985"></a><span class="lineno"> 1985</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01986"></a><span class="lineno"> 1986</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l01987"></a><span class="lineno"> 1987</span> }</div> +<div class="line"><a name="l01988"></a><span class="lineno"> 1988</span>  </div> +<div class="line"><a name="l01989"></a><span class="lineno"> 1989</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseLogSoftmax(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l01990"></a><span class="lineno"> 1990</span> {</div> +<div class="line"><a name="l01991"></a><span class="lineno"> 1991</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l01992"></a><span class="lineno"> 1992</span>  </div> +<div class="line"><a name="l01993"></a><span class="lineno"> 1993</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l01994"></a><span class="lineno"> 1994</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l01995"></a><span class="lineno"> 1995</span>  </div> +<div class="line"><a name="l01996"></a><span class="lineno"> 1996</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l01997"></a><span class="lineno"> 1997</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l01998"></a><span class="lineno"> 1998</span>  </div> +<div class="line"><a name="l01999"></a><span class="lineno"> 1999</span>  <a class="code" href="structarmnn_1_1_softmax_descriptor.html">armnn::LogSoftmaxDescriptor</a> descriptor;</div> +<div class="line"><a name="l02000"></a><span class="lineno"> 2000</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = graph->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->descriptor()->beta();</div> +<div class="line"><a name="l02001"></a><span class="lineno"> 2001</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = graph->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->descriptor()->axis();</div> +<div class="line"><a name="l02002"></a><span class="lineno"> 2002</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02003"></a><span class="lineno"> 2003</span>  </div> +<div class="line"><a name="l02004"></a><span class="lineno"> 2004</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddLogSoftmaxLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02005"></a><span class="lineno"> 2005</span>  </div> +<div class="line"><a name="l02006"></a><span class="lineno"> 2006</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02007"></a><span class="lineno"> 2007</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02008"></a><span class="lineno"> 2008</span>  </div> +<div class="line"><a name="l02009"></a><span class="lineno"> 2009</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02010"></a><span class="lineno"> 2010</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02011"></a><span class="lineno"> 2011</span> }</div> +<div class="line"><a name="l02012"></a><span class="lineno"> 2012</span>  </div> +<div class="line"><a name="l02013"></a><span class="lineno"> 2013</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMinimum(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02014"></a><span class="lineno"> 2014</span> {</div> +<div class="line"><a name="l02015"></a><span class="lineno"> 2015</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02016"></a><span class="lineno"> 2016</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02017"></a><span class="lineno"> 2017</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l02018"></a><span class="lineno"> 2018</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l02019"></a><span class="lineno"> 2019</span>  </div> +<div class="line"><a name="l02020"></a><span class="lineno"> 2020</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02021"></a><span class="lineno"> 2021</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02022"></a><span class="lineno"> 2022</span>  </div> +<div class="line"><a name="l02023"></a><span class="lineno"> 2023</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02024"></a><span class="lineno"> 2024</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aa1d0ec6d56f8833a078b5a7ac4caf2d4">armnn::BinaryOperation::Minimum</a>);</div> +<div class="line"><a name="l02025"></a><span class="lineno"> 2025</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02026"></a><span class="lineno"> 2026</span>  </div> +<div class="line"><a name="l02027"></a><span class="lineno"> 2027</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02028"></a><span class="lineno"> 2028</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02029"></a><span class="lineno"> 2029</span>  </div> +<div class="line"><a name="l02030"></a><span class="lineno"> 2030</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02031"></a><span class="lineno"> 2031</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02032"></a><span class="lineno"> 2032</span> }</div> +<div class="line"><a name="l02033"></a><span class="lineno"> 2033</span>  </div> +<div class="line"><a name="l02034"></a><span class="lineno"> 2034</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMaximum(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> <div class="line"><a name="l02035"></a><span class="lineno"> 2035</span> {</div> -<div class="line"><a name="l02036"></a><span class="lineno"> 2036</span>  <span class="keyword">auto</span> layerType = graph->layers()->Get(layerIndex)->layer_type();</div> -<div class="line"><a name="l02037"></a><span class="lineno"> 2037</span>  </div> -<div class="line"><a name="l02038"></a><span class="lineno"> 2038</span>  <span class="keywordflow">switch</span> (layerType)</div> -<div class="line"><a name="l02039"></a><span class="lineno"> 2039</span>  {</div> -<div class="line"><a name="l02040"></a><span class="lineno"> 2040</span>  <span class="keywordflow">case</span> Layer::Layer_ConcatLayer:</div> -<div class="line"><a name="l02041"></a><span class="lineno"> 2041</span>  <span class="keywordflow">return</span> graph->layers()->Get(layerIndex)->layer_as_ConcatLayer()->descriptor();</div> -<div class="line"><a name="l02042"></a><span class="lineno"> 2042</span>  <span class="keywordflow">case</span> Layer::Layer_MergerLayer:</div> -<div class="line"><a name="l02043"></a><span class="lineno"> 2043</span>  <span class="keywordflow">return</span> graph->layers()->Get(layerIndex)->layer_as_MergerLayer()->descriptor();</div> -<div class="line"><a name="l02044"></a><span class="lineno"> 2044</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02045"></a><span class="lineno"> 2045</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"unknown layer type, should be concat or merger"</span>);</div> -<div class="line"><a name="l02046"></a><span class="lineno"> 2046</span>  }</div> -<div class="line"><a name="l02047"></a><span class="lineno"> 2047</span> }</div> -<div class="line"><a name="l02048"></a><span class="lineno"> 2048</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseChannelShuffle(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02049"></a><span class="lineno"> 2049</span> {</div> -<div class="line"><a name="l02050"></a><span class="lineno"> 2050</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02051"></a><span class="lineno"> 2051</span>  </div> -<div class="line"><a name="l02052"></a><span class="lineno"> 2052</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02053"></a><span class="lineno"> 2053</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02036"></a><span class="lineno"> 2036</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02037"></a><span class="lineno"> 2037</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02038"></a><span class="lineno"> 2038</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l02039"></a><span class="lineno"> 2039</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l02040"></a><span class="lineno"> 2040</span>  </div> +<div class="line"><a name="l02041"></a><span class="lineno"> 2041</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02042"></a><span class="lineno"> 2042</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02043"></a><span class="lineno"> 2043</span>  </div> +<div class="line"><a name="l02044"></a><span class="lineno"> 2044</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02045"></a><span class="lineno"> 2045</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a8321e79c278ec510f63675c040594892">armnn::BinaryOperation::Maximum</a>);</div> +<div class="line"><a name="l02046"></a><span class="lineno"> 2046</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02047"></a><span class="lineno"> 2047</span>  </div> +<div class="line"><a name="l02048"></a><span class="lineno"> 2048</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02049"></a><span class="lineno"> 2049</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02050"></a><span class="lineno"> 2050</span>  </div> +<div class="line"><a name="l02051"></a><span class="lineno"> 2051</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02052"></a><span class="lineno"> 2052</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02053"></a><span class="lineno"> 2053</span> }</div> <div class="line"><a name="l02054"></a><span class="lineno"> 2054</span>  </div> -<div class="line"><a name="l02055"></a><span class="lineno"> 2055</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02056"></a><span class="lineno"> 2056</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02057"></a><span class="lineno"> 2057</span>  </div> -<div class="line"><a name="l02058"></a><span class="lineno"> 2058</span>  <a class="code" href="structarmnn_1_1_channel_shuffle_descriptor.html">armnn::ChannelShuffleDescriptor</a> descriptor;</div> -<div class="line"><a name="l02059"></a><span class="lineno"> 2059</span>  descriptor.<a class="code" href="structarmnn_1_1_channel_shuffle_descriptor.html#ab218de7805899c8412d75d1fd1d846d2">m_Axis</a> = graph->layers()->Get(layerIndex)->layer_as_ChannelShuffleLayer()->descriptor()->axis();</div> -<div class="line"><a name="l02060"></a><span class="lineno"> 2060</span>  descriptor.<a class="code" href="structarmnn_1_1_channel_shuffle_descriptor.html#a1953d00371489c32ebded5a42eabc0cf">m_NumGroups</a> =</div> -<div class="line"><a name="l02061"></a><span class="lineno"> 2061</span>  graph->layers()->Get(layerIndex)->layer_as_ChannelShuffleLayer()->descriptor()->numGroups();</div> -<div class="line"><a name="l02062"></a><span class="lineno"> 2062</span>  </div> -<div class="line"><a name="l02063"></a><span class="lineno"> 2063</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02064"></a><span class="lineno"> 2064</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddChannelShuffleLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02065"></a><span class="lineno"> 2065</span>  </div> -<div class="line"><a name="l02066"></a><span class="lineno"> 2066</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02067"></a><span class="lineno"> 2067</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02068"></a><span class="lineno"> 2068</span>  </div> -<div class="line"><a name="l02069"></a><span class="lineno"> 2069</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02070"></a><span class="lineno"> 2070</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02071"></a><span class="lineno"> 2071</span> }</div> -<div class="line"><a name="l02072"></a><span class="lineno"> 2072</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseComparison(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02073"></a><span class="lineno"> 2073</span> {</div> -<div class="line"><a name="l02074"></a><span class="lineno"> 2074</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02075"></a><span class="lineno"> 2075</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l02055"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.html#a63d3841a5ebb0a5ce572cfb4cb634376"> 2055</a></span> <span class="keyword">const</span> armnnSerializer::OriginsDescriptor* <a class="code" href="namespacearmnn_deserializer.html#a63d3841a5ebb0a5ce572cfb4cb634376">GetOriginsDescriptor</a>(<span class="keyword">const</span> armnnSerializer::SerializedGraph* graph,</div> +<div class="line"><a name="l02056"></a><span class="lineno"> 2056</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02057"></a><span class="lineno"> 2057</span> {</div> +<div class="line"><a name="l02058"></a><span class="lineno"> 2058</span>  <span class="keyword">auto</span> layerType = graph->layers()->Get(layerIndex)->layer_type();</div> +<div class="line"><a name="l02059"></a><span class="lineno"> 2059</span>  </div> +<div class="line"><a name="l02060"></a><span class="lineno"> 2060</span>  <span class="keywordflow">switch</span> (layerType)</div> +<div class="line"><a name="l02061"></a><span class="lineno"> 2061</span>  {</div> +<div class="line"><a name="l02062"></a><span class="lineno"> 2062</span>  <span class="keywordflow">case</span> Layer::Layer_ConcatLayer:</div> +<div class="line"><a name="l02063"></a><span class="lineno"> 2063</span>  <span class="keywordflow">return</span> graph->layers()->Get(layerIndex)->layer_as_ConcatLayer()->descriptor();</div> +<div class="line"><a name="l02064"></a><span class="lineno"> 2064</span>  <span class="keywordflow">case</span> Layer::Layer_MergerLayer:</div> +<div class="line"><a name="l02065"></a><span class="lineno"> 2065</span>  <span class="keywordflow">return</span> graph->layers()->Get(layerIndex)->layer_as_MergerLayer()->descriptor();</div> +<div class="line"><a name="l02066"></a><span class="lineno"> 2066</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02067"></a><span class="lineno"> 2067</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"unknown layer type, should be concat or merger"</span>);</div> +<div class="line"><a name="l02068"></a><span class="lineno"> 2068</span>  }</div> +<div class="line"><a name="l02069"></a><span class="lineno"> 2069</span> }</div> +<div class="line"><a name="l02070"></a><span class="lineno"> 2070</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseChannelShuffle(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02071"></a><span class="lineno"> 2071</span> {</div> +<div class="line"><a name="l02072"></a><span class="lineno"> 2072</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02073"></a><span class="lineno"> 2073</span>  </div> +<div class="line"><a name="l02074"></a><span class="lineno"> 2074</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02075"></a><span class="lineno"> 2075</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> <div class="line"><a name="l02076"></a><span class="lineno"> 2076</span>  </div> -<div class="line"><a name="l02077"></a><span class="lineno"> 2077</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02078"></a><span class="lineno"> 2078</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l02077"></a><span class="lineno"> 2077</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02078"></a><span class="lineno"> 2078</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l02079"></a><span class="lineno"> 2079</span>  </div> -<div class="line"><a name="l02080"></a><span class="lineno"> 2080</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02081"></a><span class="lineno"> 2081</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02082"></a><span class="lineno"> 2082</span>  </div> -<div class="line"><a name="l02083"></a><span class="lineno"> 2083</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ComparisonLayer();</div> -<div class="line"><a name="l02084"></a><span class="lineno"> 2084</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> -<div class="line"><a name="l02085"></a><span class="lineno"> 2085</span>  </div> -<div class="line"><a name="l02086"></a><span class="lineno"> 2086</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.html">armnn::ComparisonDescriptor</a> descriptor;</div> -<div class="line"><a name="l02087"></a><span class="lineno"> 2087</span>  descriptor.<a class="code" href="structarmnn_1_1_comparison_descriptor.html#a865dc4f43cb0ff01a1dcf78036912fd1">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.html#a28f896fb78cdf6607b61c196c98b2570">ToComparisonOperation</a>(fbDescriptor->operation());</div> -<div class="line"><a name="l02088"></a><span class="lineno"> 2088</span>  </div> -<div class="line"><a name="l02089"></a><span class="lineno"> 2089</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02090"></a><span class="lineno"> 2090</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddComparisonLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02091"></a><span class="lineno"> 2091</span>  </div> -<div class="line"><a name="l02092"></a><span class="lineno"> 2092</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02093"></a><span class="lineno"> 2093</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02094"></a><span class="lineno"> 2094</span>  </div> -<div class="line"><a name="l02095"></a><span class="lineno"> 2095</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02096"></a><span class="lineno"> 2096</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02097"></a><span class="lineno"> 2097</span> }</div> +<div class="line"><a name="l02080"></a><span class="lineno"> 2080</span>  <a class="code" href="structarmnn_1_1_channel_shuffle_descriptor.html">armnn::ChannelShuffleDescriptor</a> descriptor;</div> +<div class="line"><a name="l02081"></a><span class="lineno"> 2081</span>  descriptor.<a class="code" href="structarmnn_1_1_channel_shuffle_descriptor.html#ab218de7805899c8412d75d1fd1d846d2">m_Axis</a> = graph->layers()->Get(layerIndex)->layer_as_ChannelShuffleLayer()->descriptor()->axis();</div> +<div class="line"><a name="l02082"></a><span class="lineno"> 2082</span>  descriptor.<a class="code" href="structarmnn_1_1_channel_shuffle_descriptor.html#a1953d00371489c32ebded5a42eabc0cf">m_NumGroups</a> =</div> +<div class="line"><a name="l02083"></a><span class="lineno"> 2083</span>  graph->layers()->Get(layerIndex)->layer_as_ChannelShuffleLayer()->descriptor()->numGroups();</div> +<div class="line"><a name="l02084"></a><span class="lineno"> 2084</span>  </div> +<div class="line"><a name="l02085"></a><span class="lineno"> 2085</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02086"></a><span class="lineno"> 2086</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddChannelShuffleLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02087"></a><span class="lineno"> 2087</span>  </div> +<div class="line"><a name="l02088"></a><span class="lineno"> 2088</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02089"></a><span class="lineno"> 2089</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02090"></a><span class="lineno"> 2090</span>  </div> +<div class="line"><a name="l02091"></a><span class="lineno"> 2091</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02092"></a><span class="lineno"> 2092</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02093"></a><span class="lineno"> 2093</span> }</div> +<div class="line"><a name="l02094"></a><span class="lineno"> 2094</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseComparison(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02095"></a><span class="lineno"> 2095</span> {</div> +<div class="line"><a name="l02096"></a><span class="lineno"> 2096</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02097"></a><span class="lineno"> 2097</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> <div class="line"><a name="l02098"></a><span class="lineno"> 2098</span>  </div> -<div class="line"><a name="l02099"></a><span class="lineno"> 2099</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseElementwiseBinary(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02100"></a><span class="lineno"> 2100</span> {</div> -<div class="line"><a name="l02101"></a><span class="lineno"> 2101</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02102"></a><span class="lineno"> 2102</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l02103"></a><span class="lineno"> 2103</span>  </div> -<div class="line"><a name="l02104"></a><span class="lineno"> 2104</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02105"></a><span class="lineno"> 2105</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l02106"></a><span class="lineno"> 2106</span>  </div> -<div class="line"><a name="l02107"></a><span class="lineno"> 2107</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02108"></a><span class="lineno"> 2108</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02109"></a><span class="lineno"> 2109</span>  </div> -<div class="line"><a name="l02110"></a><span class="lineno"> 2110</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ElementwiseBinaryLayer();</div> -<div class="line"><a name="l02111"></a><span class="lineno"> 2111</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> -<div class="line"><a name="l02112"></a><span class="lineno"> 2112</span>  </div> -<div class="line"><a name="l02113"></a><span class="lineno"> 2113</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor;</div> -<div class="line"><a name="l02114"></a><span class="lineno"> 2114</span>  descriptor.<a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html#a7e4ece533ef2cb0f251e11c47a17371c">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.html#a3bb16a8c4f68fd2dfde128f1dc623571">ToElementwiseBinaryOperation</a>(fbDescriptor->operation());</div> -<div class="line"><a name="l02115"></a><span class="lineno"> 2115</span>  </div> -<div class="line"><a name="l02116"></a><span class="lineno"> 2116</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02117"></a><span class="lineno"> 2117</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02118"></a><span class="lineno"> 2118</span>  </div> -<div class="line"><a name="l02119"></a><span class="lineno"> 2119</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02120"></a><span class="lineno"> 2120</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02121"></a><span class="lineno"> 2121</span>  </div> -<div class="line"><a name="l02122"></a><span class="lineno"> 2122</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02123"></a><span class="lineno"> 2123</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02124"></a><span class="lineno"> 2124</span> }</div> +<div class="line"><a name="l02099"></a><span class="lineno"> 2099</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02100"></a><span class="lineno"> 2100</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l02101"></a><span class="lineno"> 2101</span>  </div> +<div class="line"><a name="l02102"></a><span class="lineno"> 2102</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02103"></a><span class="lineno"> 2103</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02104"></a><span class="lineno"> 2104</span>  </div> +<div class="line"><a name="l02105"></a><span class="lineno"> 2105</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ComparisonLayer();</div> +<div class="line"><a name="l02106"></a><span class="lineno"> 2106</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> +<div class="line"><a name="l02107"></a><span class="lineno"> 2107</span>  </div> +<div class="line"><a name="l02108"></a><span class="lineno"> 2108</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.html">armnn::ComparisonDescriptor</a> descriptor;</div> +<div class="line"><a name="l02109"></a><span class="lineno"> 2109</span>  descriptor.<a class="code" href="structarmnn_1_1_comparison_descriptor.html#a865dc4f43cb0ff01a1dcf78036912fd1">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.html#a28f896fb78cdf6607b61c196c98b2570">ToComparisonOperation</a>(fbDescriptor->operation());</div> +<div class="line"><a name="l02110"></a><span class="lineno"> 2110</span>  </div> +<div class="line"><a name="l02111"></a><span class="lineno"> 2111</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02112"></a><span class="lineno"> 2112</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddComparisonLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02113"></a><span class="lineno"> 2113</span>  </div> +<div class="line"><a name="l02114"></a><span class="lineno"> 2114</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02115"></a><span class="lineno"> 2115</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02116"></a><span class="lineno"> 2116</span>  </div> +<div class="line"><a name="l02117"></a><span class="lineno"> 2117</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02118"></a><span class="lineno"> 2118</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02119"></a><span class="lineno"> 2119</span> }</div> +<div class="line"><a name="l02120"></a><span class="lineno"> 2120</span>  </div> +<div class="line"><a name="l02121"></a><span class="lineno"> 2121</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseElementwiseBinary(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02122"></a><span class="lineno"> 2122</span> {</div> +<div class="line"><a name="l02123"></a><span class="lineno"> 2123</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02124"></a><span class="lineno"> 2124</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> <div class="line"><a name="l02125"></a><span class="lineno"> 2125</span>  </div> -<div class="line"><a name="l02126"></a><span class="lineno"> 2126</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseElementwiseUnary(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02127"></a><span class="lineno"> 2127</span> {</div> -<div class="line"><a name="l02128"></a><span class="lineno"> 2128</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02129"></a><span class="lineno"> 2129</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l02130"></a><span class="lineno"> 2130</span>  </div> -<div class="line"><a name="l02131"></a><span class="lineno"> 2131</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02132"></a><span class="lineno"> 2132</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02133"></a><span class="lineno"> 2133</span>  </div> -<div class="line"><a name="l02134"></a><span class="lineno"> 2134</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02135"></a><span class="lineno"> 2135</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02136"></a><span class="lineno"> 2136</span>  </div> -<div class="line"><a name="l02137"></a><span class="lineno"> 2137</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ElementwiseUnaryLayer();</div> -<div class="line"><a name="l02138"></a><span class="lineno"> 2138</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> -<div class="line"><a name="l02139"></a><span class="lineno"> 2139</span>  </div> -<div class="line"><a name="l02140"></a><span class="lineno"> 2140</span>  <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.html">armnn::ElementwiseUnaryDescriptor</a> descriptor;</div> -<div class="line"><a name="l02141"></a><span class="lineno"> 2141</span>  descriptor.<a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.html#afe768be66897eb3d73284424e3239b23">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.html#a9c11dfb7a73226061b83ecd995b91582">ToElementwiseUnaryOperation</a>(fbDescriptor->operation());</div> -<div class="line"><a name="l02142"></a><span class="lineno"> 2142</span>  </div> -<div class="line"><a name="l02143"></a><span class="lineno"> 2143</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02144"></a><span class="lineno"> 2144</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02145"></a><span class="lineno"> 2145</span>  </div> -<div class="line"><a name="l02146"></a><span class="lineno"> 2146</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02147"></a><span class="lineno"> 2147</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02148"></a><span class="lineno"> 2148</span>  </div> -<div class="line"><a name="l02149"></a><span class="lineno"> 2149</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02150"></a><span class="lineno"> 2150</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02151"></a><span class="lineno"> 2151</span> }</div> +<div class="line"><a name="l02126"></a><span class="lineno"> 2126</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02127"></a><span class="lineno"> 2127</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l02128"></a><span class="lineno"> 2128</span>  </div> +<div class="line"><a name="l02129"></a><span class="lineno"> 2129</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02130"></a><span class="lineno"> 2130</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02131"></a><span class="lineno"> 2131</span>  </div> +<div class="line"><a name="l02132"></a><span class="lineno"> 2132</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ElementwiseBinaryLayer();</div> +<div class="line"><a name="l02133"></a><span class="lineno"> 2133</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> +<div class="line"><a name="l02134"></a><span class="lineno"> 2134</span>  </div> +<div class="line"><a name="l02135"></a><span class="lineno"> 2135</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor;</div> +<div class="line"><a name="l02136"></a><span class="lineno"> 2136</span>  descriptor.<a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html#a7e4ece533ef2cb0f251e11c47a17371c">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.html#a3bb16a8c4f68fd2dfde128f1dc623571">ToElementwiseBinaryOperation</a>(fbDescriptor->operation());</div> +<div class="line"><a name="l02137"></a><span class="lineno"> 2137</span>  </div> +<div class="line"><a name="l02138"></a><span class="lineno"> 2138</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02139"></a><span class="lineno"> 2139</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02140"></a><span class="lineno"> 2140</span>  </div> +<div class="line"><a name="l02141"></a><span class="lineno"> 2141</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02142"></a><span class="lineno"> 2142</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02143"></a><span class="lineno"> 2143</span>  </div> +<div class="line"><a name="l02144"></a><span class="lineno"> 2144</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02145"></a><span class="lineno"> 2145</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02146"></a><span class="lineno"> 2146</span> }</div> +<div class="line"><a name="l02147"></a><span class="lineno"> 2147</span>  </div> +<div class="line"><a name="l02148"></a><span class="lineno"> 2148</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseElementwiseUnary(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02149"></a><span class="lineno"> 2149</span> {</div> +<div class="line"><a name="l02150"></a><span class="lineno"> 2150</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02151"></a><span class="lineno"> 2151</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> <div class="line"><a name="l02152"></a><span class="lineno"> 2152</span>  </div> -<div class="line"><a name="l02153"></a><span class="lineno"> 2153</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseConcat(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02154"></a><span class="lineno"> 2154</span> {</div> -<div class="line"><a name="l02155"></a><span class="lineno"> 2155</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02156"></a><span class="lineno"> 2156</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l02157"></a><span class="lineno"> 2157</span>  </div> -<div class="line"><a name="l02158"></a><span class="lineno"> 2158</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02159"></a><span class="lineno"> 2159</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02160"></a><span class="lineno"> 2160</span>  </div> -<div class="line"><a name="l02161"></a><span class="lineno"> 2161</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02162"></a><span class="lineno"> 2162</span>  <span class="keyword">auto</span> originsDescriptor = <a class="code" href="namespacearmnn_deserializer.html#a63d3841a5ebb0a5ce572cfb4cb634376">GetOriginsDescriptor</a>(graph, layerIndex);</div> -<div class="line"><a name="l02163"></a><span class="lineno"> 2163</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numViews = originsDescriptor->numViews();</div> -<div class="line"><a name="l02164"></a><span class="lineno"> 2164</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions = originsDescriptor->numDimensions();</div> -<div class="line"><a name="l02165"></a><span class="lineno"> 2165</span>  </div> -<div class="line"><a name="l02166"></a><span class="lineno"> 2166</span>  <span class="comment">// can now check the number of inputs == number of views</span></div> -<div class="line"><a name="l02167"></a><span class="lineno"> 2167</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02168"></a><span class="lineno"> 2168</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numViews);</div> -<div class="line"><a name="l02169"></a><span class="lineno"> 2169</span>  </div> -<div class="line"><a name="l02170"></a><span class="lineno"> 2170</span>  <a class="code" href="structarmnn_1_1_origins_descriptor.html">armnn::OriginsDescriptor</a> descriptor(numViews, numDimensions);</div> -<div class="line"><a name="l02171"></a><span class="lineno"> 2171</span>  <span class="keyword">auto</span> originsPtr = originsDescriptor->viewOrigins();</div> -<div class="line"><a name="l02172"></a><span class="lineno"> 2172</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> v = 0; v < numViews; ++v)</div> -<div class="line"><a name="l02173"></a><span class="lineno"> 2173</span>  {</div> -<div class="line"><a name="l02174"></a><span class="lineno"> 2174</span>  <span class="keyword">auto</span> originPtr = originsPtr->Get(v);</div> -<div class="line"><a name="l02175"></a><span class="lineno"> 2175</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> d = 0; d < numDimensions; ++d)</div> -<div class="line"><a name="l02176"></a><span class="lineno"> 2176</span>  {</div> -<div class="line"><a name="l02177"></a><span class="lineno"> 2177</span>  uint32_t value = originPtr->data()->Get(d);</div> -<div class="line"><a name="l02178"></a><span class="lineno"> 2178</span>  descriptor.SetViewOriginCoord(v, d, value);</div> -<div class="line"><a name="l02179"></a><span class="lineno"> 2179</span>  }</div> -<div class="line"><a name="l02180"></a><span class="lineno"> 2180</span>  }</div> -<div class="line"><a name="l02181"></a><span class="lineno"> 2181</span>  descriptor.SetConcatAxis(originsDescriptor->concatAxis());</div> +<div class="line"><a name="l02153"></a><span class="lineno"> 2153</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02154"></a><span class="lineno"> 2154</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02155"></a><span class="lineno"> 2155</span>  </div> +<div class="line"><a name="l02156"></a><span class="lineno"> 2156</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02157"></a><span class="lineno"> 2157</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02158"></a><span class="lineno"> 2158</span>  </div> +<div class="line"><a name="l02159"></a><span class="lineno"> 2159</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ElementwiseUnaryLayer();</div> +<div class="line"><a name="l02160"></a><span class="lineno"> 2160</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> +<div class="line"><a name="l02161"></a><span class="lineno"> 2161</span>  </div> +<div class="line"><a name="l02162"></a><span class="lineno"> 2162</span>  <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.html">armnn::ElementwiseUnaryDescriptor</a> descriptor;</div> +<div class="line"><a name="l02163"></a><span class="lineno"> 2163</span>  descriptor.<a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.html#afe768be66897eb3d73284424e3239b23">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.html#a9c11dfb7a73226061b83ecd995b91582">ToElementwiseUnaryOperation</a>(fbDescriptor->operation());</div> +<div class="line"><a name="l02164"></a><span class="lineno"> 2164</span>  </div> +<div class="line"><a name="l02165"></a><span class="lineno"> 2165</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02166"></a><span class="lineno"> 2166</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02167"></a><span class="lineno"> 2167</span>  </div> +<div class="line"><a name="l02168"></a><span class="lineno"> 2168</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02169"></a><span class="lineno"> 2169</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02170"></a><span class="lineno"> 2170</span>  </div> +<div class="line"><a name="l02171"></a><span class="lineno"> 2171</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02172"></a><span class="lineno"> 2172</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02173"></a><span class="lineno"> 2173</span> }</div> +<div class="line"><a name="l02174"></a><span class="lineno"> 2174</span>  </div> +<div class="line"><a name="l02175"></a><span class="lineno"> 2175</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseConcat(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02176"></a><span class="lineno"> 2176</span> {</div> +<div class="line"><a name="l02177"></a><span class="lineno"> 2177</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02178"></a><span class="lineno"> 2178</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l02179"></a><span class="lineno"> 2179</span>  </div> +<div class="line"><a name="l02180"></a><span class="lineno"> 2180</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02181"></a><span class="lineno"> 2181</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l02182"></a><span class="lineno"> 2182</span>  </div> -<div class="line"><a name="l02183"></a><span class="lineno"> 2183</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddConcatLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02184"></a><span class="lineno"> 2184</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02185"></a><span class="lineno"> 2185</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02186"></a><span class="lineno"> 2186</span>  </div> -<div class="line"><a name="l02187"></a><span class="lineno"> 2187</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02188"></a><span class="lineno"> 2188</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02189"></a><span class="lineno"> 2189</span> }</div> -<div class="line"><a name="l02190"></a><span class="lineno"> 2190</span>  </div> -<div class="line"><a name="l02191"></a><span class="lineno"> 2191</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMultiplication(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02192"></a><span class="lineno"> 2192</span> {</div> -<div class="line"><a name="l02193"></a><span class="lineno"> 2193</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02194"></a><span class="lineno"> 2194</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02195"></a><span class="lineno"> 2195</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l02196"></a><span class="lineno"> 2196</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l02197"></a><span class="lineno"> 2197</span>  </div> -<div class="line"><a name="l02198"></a><span class="lineno"> 2198</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02199"></a><span class="lineno"> 2199</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02200"></a><span class="lineno"> 2200</span>  </div> -<div class="line"><a name="l02201"></a><span class="lineno"> 2201</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02202"></a><span class="lineno"> 2202</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a62b6d55816cf737bfc6f42e60df1a3f2">armnn::BinaryOperation::Mul</a>);</div> -<div class="line"><a name="l02203"></a><span class="lineno"> 2203</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02183"></a><span class="lineno"> 2183</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02184"></a><span class="lineno"> 2184</span>  <span class="keyword">auto</span> originsDescriptor = <a class="code" href="namespacearmnn_deserializer.html#a63d3841a5ebb0a5ce572cfb4cb634376">GetOriginsDescriptor</a>(graph, layerIndex);</div> +<div class="line"><a name="l02185"></a><span class="lineno"> 2185</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numViews = originsDescriptor->numViews();</div> +<div class="line"><a name="l02186"></a><span class="lineno"> 2186</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions = originsDescriptor->numDimensions();</div> +<div class="line"><a name="l02187"></a><span class="lineno"> 2187</span>  </div> +<div class="line"><a name="l02188"></a><span class="lineno"> 2188</span>  <span class="comment">// can now check the number of inputs == number of views</span></div> +<div class="line"><a name="l02189"></a><span class="lineno"> 2189</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02190"></a><span class="lineno"> 2190</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numViews);</div> +<div class="line"><a name="l02191"></a><span class="lineno"> 2191</span>  </div> +<div class="line"><a name="l02192"></a><span class="lineno"> 2192</span>  <a class="code" href="structarmnn_1_1_origins_descriptor.html">armnn::OriginsDescriptor</a> descriptor(numViews, numDimensions);</div> +<div class="line"><a name="l02193"></a><span class="lineno"> 2193</span>  <span class="keyword">auto</span> originsPtr = originsDescriptor->viewOrigins();</div> +<div class="line"><a name="l02194"></a><span class="lineno"> 2194</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> v = 0; v < numViews; ++v)</div> +<div class="line"><a name="l02195"></a><span class="lineno"> 2195</span>  {</div> +<div class="line"><a name="l02196"></a><span class="lineno"> 2196</span>  <span class="keyword">auto</span> originPtr = originsPtr->Get(v);</div> +<div class="line"><a name="l02197"></a><span class="lineno"> 2197</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> d = 0; d < numDimensions; ++d)</div> +<div class="line"><a name="l02198"></a><span class="lineno"> 2198</span>  {</div> +<div class="line"><a name="l02199"></a><span class="lineno"> 2199</span>  uint32_t value = originPtr->data()->Get(d);</div> +<div class="line"><a name="l02200"></a><span class="lineno"> 2200</span>  descriptor.SetViewOriginCoord(v, d, value);</div> +<div class="line"><a name="l02201"></a><span class="lineno"> 2201</span>  }</div> +<div class="line"><a name="l02202"></a><span class="lineno"> 2202</span>  }</div> +<div class="line"><a name="l02203"></a><span class="lineno"> 2203</span>  descriptor.SetConcatAxis(originsDescriptor->concatAxis());</div> <div class="line"><a name="l02204"></a><span class="lineno"> 2204</span>  </div> -<div class="line"><a name="l02205"></a><span class="lineno"> 2205</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02206"></a><span class="lineno"> 2206</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02207"></a><span class="lineno"> 2207</span>  </div> -<div class="line"><a name="l02208"></a><span class="lineno"> 2208</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02209"></a><span class="lineno"> 2209</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02210"></a><span class="lineno"> 2210</span> }</div> -<div class="line"><a name="l02211"></a><span class="lineno"> 2211</span>  </div> -<div class="line"><a name="l02212"></a><span class="lineno"> 2212</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseFloor(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02213"></a><span class="lineno"> 2213</span> {</div> -<div class="line"><a name="l02214"></a><span class="lineno"> 2214</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02215"></a><span class="lineno"> 2215</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l02216"></a><span class="lineno"> 2216</span>  </div> -<div class="line"><a name="l02217"></a><span class="lineno"> 2217</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02218"></a><span class="lineno"> 2218</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02205"></a><span class="lineno"> 2205</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddConcatLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02206"></a><span class="lineno"> 2206</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02207"></a><span class="lineno"> 2207</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02208"></a><span class="lineno"> 2208</span>  </div> +<div class="line"><a name="l02209"></a><span class="lineno"> 2209</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02210"></a><span class="lineno"> 2210</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02211"></a><span class="lineno"> 2211</span> }</div> +<div class="line"><a name="l02212"></a><span class="lineno"> 2212</span>  </div> +<div class="line"><a name="l02213"></a><span class="lineno"> 2213</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMultiplication(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02214"></a><span class="lineno"> 2214</span> {</div> +<div class="line"><a name="l02215"></a><span class="lineno"> 2215</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02216"></a><span class="lineno"> 2216</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02217"></a><span class="lineno"> 2217</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l02218"></a><span class="lineno"> 2218</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> <div class="line"><a name="l02219"></a><span class="lineno"> 2219</span>  </div> <div class="line"><a name="l02220"></a><span class="lineno"> 2220</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> <div class="line"><a name="l02221"></a><span class="lineno"> 2221</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l02222"></a><span class="lineno"> 2222</span>  </div> <div class="line"><a name="l02223"></a><span class="lineno"> 2223</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02224"></a><span class="lineno"> 2224</span>  </div> -<div class="line"><a name="l02225"></a><span class="lineno"> 2225</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer;</div> +<div class="line"><a name="l02224"></a><span class="lineno"> 2224</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a62b6d55816cf737bfc6f42e60df1a3f2">armnn::BinaryOperation::Mul</a>);</div> +<div class="line"><a name="l02225"></a><span class="lineno"> 2225</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> <div class="line"><a name="l02226"></a><span class="lineno"> 2226</span>  </div> -<div class="line"><a name="l02227"></a><span class="lineno"> 2227</span>  layer = m_Network->AddFloorLayer(layerName.c_str());</div> -<div class="line"><a name="l02228"></a><span class="lineno"> 2228</span>  </div> -<div class="line"><a name="l02229"></a><span class="lineno"> 2229</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02230"></a><span class="lineno"> 2230</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02231"></a><span class="lineno"> 2231</span>  </div> -<div class="line"><a name="l02232"></a><span class="lineno"> 2232</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02233"></a><span class="lineno"> 2233</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02234"></a><span class="lineno"> 2234</span> }</div> -<div class="line"><a name="l02235"></a><span class="lineno"> 2235</span>  </div> -<div class="line"><a name="l02236"></a><span class="lineno"> 2236</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseFullyConnected(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02237"></a><span class="lineno"> 2237</span> {</div> -<div class="line"><a name="l02238"></a><span class="lineno"> 2238</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02227"></a><span class="lineno"> 2227</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02228"></a><span class="lineno"> 2228</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02229"></a><span class="lineno"> 2229</span>  </div> +<div class="line"><a name="l02230"></a><span class="lineno"> 2230</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02231"></a><span class="lineno"> 2231</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02232"></a><span class="lineno"> 2232</span> }</div> +<div class="line"><a name="l02233"></a><span class="lineno"> 2233</span>  </div> +<div class="line"><a name="l02234"></a><span class="lineno"> 2234</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseFloor(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02235"></a><span class="lineno"> 2235</span> {</div> +<div class="line"><a name="l02236"></a><span class="lineno"> 2236</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02237"></a><span class="lineno"> 2237</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l02238"></a><span class="lineno"> 2238</span>  </div> <div class="line"><a name="l02239"></a><span class="lineno"> 2239</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02240"></a><span class="lineno"> 2240</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l02240"></a><span class="lineno"> 2240</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> <div class="line"><a name="l02241"></a><span class="lineno"> 2241</span>  </div> <div class="line"><a name="l02242"></a><span class="lineno"> 2242</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> <div class="line"><a name="l02243"></a><span class="lineno"> 2243</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l02244"></a><span class="lineno"> 2244</span>  </div> -<div class="line"><a name="l02245"></a><span class="lineno"> 2245</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_FullyConnectedLayer();</div> -<div class="line"><a name="l02246"></a><span class="lineno"> 2246</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02247"></a><span class="lineno"> 2247</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> +<div class="line"><a name="l02245"></a><span class="lineno"> 2245</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02246"></a><span class="lineno"> 2246</span>  </div> +<div class="line"><a name="l02247"></a><span class="lineno"> 2247</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer;</div> <div class="line"><a name="l02248"></a><span class="lineno"> 2248</span>  </div> -<div class="line"><a name="l02249"></a><span class="lineno"> 2249</span>  <a class="code" href="structarmnn_1_1_fully_connected_descriptor.html">armnn::FullyConnectedDescriptor</a> fullyConnectedDescriptor;</div> -<div class="line"><a name="l02250"></a><span class="lineno"> 2250</span>  fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = flatBufferDescriptor->biasEnabled();</div> -<div class="line"><a name="l02251"></a><span class="lineno"> 2251</span>  fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#a281fcaec86e17c97f7b8402633f6b55a">m_TransposeWeightMatrix</a> = flatBufferDescriptor->transposeWeightsMatrix();</div> -<div class="line"><a name="l02252"></a><span class="lineno"> 2252</span>  fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#a2d3dcfc10f90adedc995b64211dab6e9">m_ConstantWeights</a> = flatBufferDescriptor->constantWeights();</div> +<div class="line"><a name="l02249"></a><span class="lineno"> 2249</span>  layer = m_Network->AddFloorLayer(layerName.c_str());</div> +<div class="line"><a name="l02250"></a><span class="lineno"> 2250</span>  </div> +<div class="line"><a name="l02251"></a><span class="lineno"> 2251</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02252"></a><span class="lineno"> 2252</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> <div class="line"><a name="l02253"></a><span class="lineno"> 2253</span>  </div> -<div class="line"><a name="l02254"></a><span class="lineno"> 2254</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer;</div> -<div class="line"><a name="l02255"></a><span class="lineno"> 2255</span>  std::vector<unsigned int> ignoreSlots {};</div> -<div class="line"><a name="l02256"></a><span class="lineno"> 2256</span>  </div> -<div class="line"><a name="l02257"></a><span class="lineno"> 2257</span>  <span class="comment">// Weights and biases used to be always constant and were stored as members of the layer. This has changed and</span></div> -<div class="line"><a name="l02258"></a><span class="lineno"> 2258</span>  <span class="comment">// they are now passed as inputs. If they are constant then they will be stored in a ConstantLayer.</span></div> -<div class="line"><a name="l02259"></a><span class="lineno"> 2259</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_ConstTensorsAsInputs <= 0)</div> -<div class="line"><a name="l02260"></a><span class="lineno"> 2260</span>  {</div> -<div class="line"><a name="l02261"></a><span class="lineno"> 2261</span>  <span class="comment">// If the model stores weights and biases as members of the layer we have to read them from there</span></div> -<div class="line"><a name="l02262"></a><span class="lineno"> 2262</span>  <span class="comment">// but add them to their own ConstantLayer for compatibility</span></div> -<div class="line"><a name="l02263"></a><span class="lineno"> 2263</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02264"></a><span class="lineno"> 2264</span>  layer = m_Network->AddFullyConnectedLayer(fullyConnectedDescriptor,</div> -<div class="line"><a name="l02265"></a><span class="lineno"> 2265</span>  layerName.c_str());</div> +<div class="line"><a name="l02254"></a><span class="lineno"> 2254</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02255"></a><span class="lineno"> 2255</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02256"></a><span class="lineno"> 2256</span> }</div> +<div class="line"><a name="l02257"></a><span class="lineno"> 2257</span>  </div> +<div class="line"><a name="l02258"></a><span class="lineno"> 2258</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseFullyConnected(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02259"></a><span class="lineno"> 2259</span> {</div> +<div class="line"><a name="l02260"></a><span class="lineno"> 2260</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02261"></a><span class="lineno"> 2261</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02262"></a><span class="lineno"> 2262</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l02263"></a><span class="lineno"> 2263</span>  </div> +<div class="line"><a name="l02264"></a><span class="lineno"> 2264</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02265"></a><span class="lineno"> 2265</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l02266"></a><span class="lineno"> 2266</span>  </div> -<div class="line"><a name="l02267"></a><span class="lineno"> 2267</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weightsTensor = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->weights());</div> -<div class="line"><a name="l02268"></a><span class="lineno"> 2268</span>  <span class="keyword">auto</span> weightsLayer = m_Network->AddConstantLayer(weightsTensor);</div> -<div class="line"><a name="l02269"></a><span class="lineno"> 2269</span>  weightsLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1u));</div> -<div class="line"><a name="l02270"></a><span class="lineno"> 2270</span>  weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> -<div class="line"><a name="l02271"></a><span class="lineno"> 2271</span>  ignoreSlots.emplace_back(1u);</div> -<div class="line"><a name="l02272"></a><span class="lineno"> 2272</span>  </div> -<div class="line"><a name="l02273"></a><span class="lineno"> 2273</span>  <span class="keywordflow">if</span> (fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div> -<div class="line"><a name="l02274"></a><span class="lineno"> 2274</span>  {</div> -<div class="line"><a name="l02275"></a><span class="lineno"> 2275</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> biasTensor = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->biases());</div> -<div class="line"><a name="l02276"></a><span class="lineno"> 2276</span>  <span class="keyword">auto</span> biasLayer = m_Network->AddConstantLayer(biasTensor);</div> -<div class="line"><a name="l02277"></a><span class="lineno"> 2277</span>  biasLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(2u));</div> -<div class="line"><a name="l02278"></a><span class="lineno"> 2278</span>  biasLayer->GetOutputSlot(0).SetTensorInfo(biasTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> -<div class="line"><a name="l02279"></a><span class="lineno"> 2279</span>  ignoreSlots.emplace_back(2u);</div> -<div class="line"><a name="l02280"></a><span class="lineno"> 2280</span>  }</div> -<div class="line"><a name="l02281"></a><span class="lineno"> 2281</span>  }</div> -<div class="line"><a name="l02282"></a><span class="lineno"> 2282</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l02283"></a><span class="lineno"> 2283</span>  {</div> -<div class="line"><a name="l02284"></a><span class="lineno"> 2284</span>  layer = m_Network->AddFullyConnectedLayer(fullyConnectedDescriptor,</div> -<div class="line"><a name="l02285"></a><span class="lineno"> 2285</span>  layerName.c_str());</div> -<div class="line"><a name="l02286"></a><span class="lineno"> 2286</span>  uint32_t numInputs = fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>();</div> -<div class="line"><a name="l02287"></a><span class="lineno"> 2287</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> -<div class="line"><a name="l02288"></a><span class="lineno"> 2288</span>  }</div> -<div class="line"><a name="l02289"></a><span class="lineno"> 2289</span>  </div> -<div class="line"><a name="l02290"></a><span class="lineno"> 2290</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02291"></a><span class="lineno"> 2291</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02292"></a><span class="lineno"> 2292</span>  </div> -<div class="line"><a name="l02293"></a><span class="lineno"> 2293</span>  RegisterInputSlots(graph, layerIndex, layer, ignoreSlots);</div> -<div class="line"><a name="l02294"></a><span class="lineno"> 2294</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02295"></a><span class="lineno"> 2295</span> }</div> -<div class="line"><a name="l02296"></a><span class="lineno"> 2296</span>  </div> -<div class="line"><a name="l02297"></a><span class="lineno"> 2297</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePad(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02298"></a><span class="lineno"> 2298</span> {</div> -<div class="line"><a name="l02299"></a><span class="lineno"> 2299</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02300"></a><span class="lineno"> 2300</span>  </div> -<div class="line"><a name="l02301"></a><span class="lineno"> 2301</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02302"></a><span class="lineno"> 2302</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02303"></a><span class="lineno"> 2303</span>  </div> -<div class="line"><a name="l02304"></a><span class="lineno"> 2304</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02305"></a><span class="lineno"> 2305</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02306"></a><span class="lineno"> 2306</span>  </div> -<div class="line"><a name="l02307"></a><span class="lineno"> 2307</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_PadLayer()->descriptor();</div> -<div class="line"><a name="l02308"></a><span class="lineno"> 2308</span>  <span class="keyword">auto</span> flatBufferPadList = flatBufferDescriptor->padList();</div> -<div class="line"><a name="l02309"></a><span class="lineno"> 2309</span>  <span class="keyword">auto</span> paddingMode = flatBufferDescriptor->paddingMode();</div> -<div class="line"><a name="l02310"></a><span class="lineno"> 2310</span>  <span class="keywordtype">float</span> padValue = flatBufferDescriptor->padValue();</div> +<div class="line"><a name="l02267"></a><span class="lineno"> 2267</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_FullyConnectedLayer();</div> +<div class="line"><a name="l02268"></a><span class="lineno"> 2268</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02269"></a><span class="lineno"> 2269</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> +<div class="line"><a name="l02270"></a><span class="lineno"> 2270</span>  </div> +<div class="line"><a name="l02271"></a><span class="lineno"> 2271</span>  <a class="code" href="structarmnn_1_1_fully_connected_descriptor.html">armnn::FullyConnectedDescriptor</a> fullyConnectedDescriptor;</div> +<div class="line"><a name="l02272"></a><span class="lineno"> 2272</span>  fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = flatBufferDescriptor->biasEnabled();</div> +<div class="line"><a name="l02273"></a><span class="lineno"> 2273</span>  fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#a281fcaec86e17c97f7b8402633f6b55a">m_TransposeWeightMatrix</a> = flatBufferDescriptor->transposeWeightsMatrix();</div> +<div class="line"><a name="l02274"></a><span class="lineno"> 2274</span>  fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#a2d3dcfc10f90adedc995b64211dab6e9">m_ConstantWeights</a> = flatBufferDescriptor->constantWeights();</div> +<div class="line"><a name="l02275"></a><span class="lineno"> 2275</span>  </div> +<div class="line"><a name="l02276"></a><span class="lineno"> 2276</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer;</div> +<div class="line"><a name="l02277"></a><span class="lineno"> 2277</span>  std::vector<unsigned int> ignoreSlots {};</div> +<div class="line"><a name="l02278"></a><span class="lineno"> 2278</span>  </div> +<div class="line"><a name="l02279"></a><span class="lineno"> 2279</span>  <span class="comment">// Weights and biases used to be always constant and were stored as members of the layer. This has changed and</span></div> +<div class="line"><a name="l02280"></a><span class="lineno"> 2280</span>  <span class="comment">// they are now passed as inputs. If they are constant then they will be stored in a ConstantLayer.</span></div> +<div class="line"><a name="l02281"></a><span class="lineno"> 2281</span>  <span class="keywordflow">if</span> (this->GetFeatureVersions(graph).m_ConstTensorsAsInputs <= 0)</div> +<div class="line"><a name="l02282"></a><span class="lineno"> 2282</span>  {</div> +<div class="line"><a name="l02283"></a><span class="lineno"> 2283</span>  <span class="comment">// If the model stores weights and biases as members of the layer we have to read them from there</span></div> +<div class="line"><a name="l02284"></a><span class="lineno"> 2284</span>  <span class="comment">// but add them to their own ConstantLayer for compatibility</span></div> +<div class="line"><a name="l02285"></a><span class="lineno"> 2285</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02286"></a><span class="lineno"> 2286</span>  layer = m_Network->AddFullyConnectedLayer(fullyConnectedDescriptor,</div> +<div class="line"><a name="l02287"></a><span class="lineno"> 2287</span>  layerName.c_str());</div> +<div class="line"><a name="l02288"></a><span class="lineno"> 2288</span>  </div> +<div class="line"><a name="l02289"></a><span class="lineno"> 2289</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weightsTensor = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->weights());</div> +<div class="line"><a name="l02290"></a><span class="lineno"> 2290</span>  <span class="keyword">auto</span> weightsLayer = m_Network->AddConstantLayer(weightsTensor);</div> +<div class="line"><a name="l02291"></a><span class="lineno"> 2291</span>  weightsLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1u));</div> +<div class="line"><a name="l02292"></a><span class="lineno"> 2292</span>  weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> +<div class="line"><a name="l02293"></a><span class="lineno"> 2293</span>  ignoreSlots.emplace_back(1u);</div> +<div class="line"><a name="l02294"></a><span class="lineno"> 2294</span>  </div> +<div class="line"><a name="l02295"></a><span class="lineno"> 2295</span>  <span class="keywordflow">if</span> (fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div> +<div class="line"><a name="l02296"></a><span class="lineno"> 2296</span>  {</div> +<div class="line"><a name="l02297"></a><span class="lineno"> 2297</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> biasTensor = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferLayer->biases());</div> +<div class="line"><a name="l02298"></a><span class="lineno"> 2298</span>  <span class="keyword">auto</span> biasLayer = m_Network->AddConstantLayer(biasTensor);</div> +<div class="line"><a name="l02299"></a><span class="lineno"> 2299</span>  biasLayer->GetOutputSlot(0).Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(2u));</div> +<div class="line"><a name="l02300"></a><span class="lineno"> 2300</span>  biasLayer->GetOutputSlot(0).SetTensorInfo(biasTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>());</div> +<div class="line"><a name="l02301"></a><span class="lineno"> 2301</span>  ignoreSlots.emplace_back(2u);</div> +<div class="line"><a name="l02302"></a><span class="lineno"> 2302</span>  }</div> +<div class="line"><a name="l02303"></a><span class="lineno"> 2303</span>  }</div> +<div class="line"><a name="l02304"></a><span class="lineno"> 2304</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l02305"></a><span class="lineno"> 2305</span>  {</div> +<div class="line"><a name="l02306"></a><span class="lineno"> 2306</span>  layer = m_Network->AddFullyConnectedLayer(fullyConnectedDescriptor,</div> +<div class="line"><a name="l02307"></a><span class="lineno"> 2307</span>  layerName.c_str());</div> +<div class="line"><a name="l02308"></a><span class="lineno"> 2308</span>  uint32_t numInputs = fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>();</div> +<div class="line"><a name="l02309"></a><span class="lineno"> 2309</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> +<div class="line"><a name="l02310"></a><span class="lineno"> 2310</span>  }</div> <div class="line"><a name="l02311"></a><span class="lineno"> 2311</span>  </div> -<div class="line"><a name="l02312"></a><span class="lineno"> 2312</span>  <span class="keywordflow">if</span> (flatBufferPadList->size() % 2 != 0)</div> -<div class="line"><a name="l02313"></a><span class="lineno"> 2313</span>  {</div> -<div class="line"><a name="l02314"></a><span class="lineno"> 2314</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The size of the pad list must be divisible by 2 {}"</span>,</div> -<div class="line"><a name="l02315"></a><span class="lineno"> 2315</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l02316"></a><span class="lineno"> 2316</span>  }</div> -<div class="line"><a name="l02317"></a><span class="lineno"> 2317</span>  </div> -<div class="line"><a name="l02318"></a><span class="lineno"> 2318</span>  std::vector<std::pair<unsigned int, unsigned int>> padList;</div> -<div class="line"><a name="l02319"></a><span class="lineno"> 2319</span>  padList.reserve(flatBufferPadList->size() / 2);</div> -<div class="line"><a name="l02320"></a><span class="lineno"> 2320</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < flatBufferPadList->size() - 1; i += 2)</div> -<div class="line"><a name="l02321"></a><span class="lineno"> 2321</span>  {</div> -<div class="line"><a name="l02322"></a><span class="lineno"> 2322</span>  padList.emplace_back(flatBufferPadList->Get(i), flatBufferPadList->Get(i+1));</div> -<div class="line"><a name="l02323"></a><span class="lineno"> 2323</span>  }</div> -<div class="line"><a name="l02324"></a><span class="lineno"> 2324</span>  </div> -<div class="line"><a name="l02325"></a><span class="lineno"> 2325</span>  <a class="code" href="structarmnn_1_1_pad_descriptor.html">armnn::PadDescriptor</a> descriptor(padList, padValue, <a class="code" href="namespacearmnn_deserializer.html#ac33cddeda1d847c4a17d679ea1dab6be">ToPaddingMode</a>(paddingMode));</div> -<div class="line"><a name="l02326"></a><span class="lineno"> 2326</span>  </div> -<div class="line"><a name="l02327"></a><span class="lineno"> 2327</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02328"></a><span class="lineno"> 2328</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPadLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02329"></a><span class="lineno"> 2329</span>  </div> -<div class="line"><a name="l02330"></a><span class="lineno"> 2330</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02331"></a><span class="lineno"> 2331</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02332"></a><span class="lineno"> 2332</span>  </div> -<div class="line"><a name="l02333"></a><span class="lineno"> 2333</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02334"></a><span class="lineno"> 2334</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02335"></a><span class="lineno"> 2335</span> }</div> -<div class="line"><a name="l02336"></a><span class="lineno"> 2336</span>  </div> -<div class="line"><a name="l02337"></a><span class="lineno"> 2337</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePermute(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02338"></a><span class="lineno"> 2338</span> {</div> -<div class="line"><a name="l02339"></a><span class="lineno"> 2339</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02340"></a><span class="lineno"> 2340</span>  </div> -<div class="line"><a name="l02341"></a><span class="lineno"> 2341</span>  <span class="keyword">auto</span> dimsMapping =</div> -<div class="line"><a name="l02342"></a><span class="lineno"> 2342</span>  graph->layers()->Get(layerIndex)->layer_as_PermuteLayer()->descriptor()->dimMappings();</div> -<div class="line"><a name="l02343"></a><span class="lineno"> 2343</span>  </div> -<div class="line"><a name="l02344"></a><span class="lineno"> 2344</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02345"></a><span class="lineno"> 2345</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02312"></a><span class="lineno"> 2312</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02313"></a><span class="lineno"> 2313</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02314"></a><span class="lineno"> 2314</span>  </div> +<div class="line"><a name="l02315"></a><span class="lineno"> 2315</span>  RegisterInputSlots(graph, layerIndex, layer, ignoreSlots);</div> +<div class="line"><a name="l02316"></a><span class="lineno"> 2316</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02317"></a><span class="lineno"> 2317</span> }</div> +<div class="line"><a name="l02318"></a><span class="lineno"> 2318</span>  </div> +<div class="line"><a name="l02319"></a><span class="lineno"> 2319</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePad(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02320"></a><span class="lineno"> 2320</span> {</div> +<div class="line"><a name="l02321"></a><span class="lineno"> 2321</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02322"></a><span class="lineno"> 2322</span>  </div> +<div class="line"><a name="l02323"></a><span class="lineno"> 2323</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02324"></a><span class="lineno"> 2324</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02325"></a><span class="lineno"> 2325</span>  </div> +<div class="line"><a name="l02326"></a><span class="lineno"> 2326</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02327"></a><span class="lineno"> 2327</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02328"></a><span class="lineno"> 2328</span>  </div> +<div class="line"><a name="l02329"></a><span class="lineno"> 2329</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_PadLayer()->descriptor();</div> +<div class="line"><a name="l02330"></a><span class="lineno"> 2330</span>  <span class="keyword">auto</span> flatBufferPadList = flatBufferDescriptor->padList();</div> +<div class="line"><a name="l02331"></a><span class="lineno"> 2331</span>  <span class="keyword">auto</span> paddingMode = flatBufferDescriptor->paddingMode();</div> +<div class="line"><a name="l02332"></a><span class="lineno"> 2332</span>  <span class="keywordtype">float</span> padValue = flatBufferDescriptor->padValue();</div> +<div class="line"><a name="l02333"></a><span class="lineno"> 2333</span>  </div> +<div class="line"><a name="l02334"></a><span class="lineno"> 2334</span>  <span class="keywordflow">if</span> (flatBufferPadList->size() % 2 != 0)</div> +<div class="line"><a name="l02335"></a><span class="lineno"> 2335</span>  {</div> +<div class="line"><a name="l02336"></a><span class="lineno"> 2336</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The size of the pad list must be divisible by 2 {}"</span>,</div> +<div class="line"><a name="l02337"></a><span class="lineno"> 2337</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l02338"></a><span class="lineno"> 2338</span>  }</div> +<div class="line"><a name="l02339"></a><span class="lineno"> 2339</span>  </div> +<div class="line"><a name="l02340"></a><span class="lineno"> 2340</span>  std::vector<std::pair<unsigned int, unsigned int>> padList;</div> +<div class="line"><a name="l02341"></a><span class="lineno"> 2341</span>  padList.reserve(flatBufferPadList->size() / 2);</div> +<div class="line"><a name="l02342"></a><span class="lineno"> 2342</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < flatBufferPadList->size() - 1; i += 2)</div> +<div class="line"><a name="l02343"></a><span class="lineno"> 2343</span>  {</div> +<div class="line"><a name="l02344"></a><span class="lineno"> 2344</span>  padList.emplace_back(flatBufferPadList->Get(i), flatBufferPadList->Get(i+1));</div> +<div class="line"><a name="l02345"></a><span class="lineno"> 2345</span>  }</div> <div class="line"><a name="l02346"></a><span class="lineno"> 2346</span>  </div> -<div class="line"><a name="l02347"></a><span class="lineno"> 2347</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02348"></a><span class="lineno"> 2348</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02349"></a><span class="lineno"> 2349</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02350"></a><span class="lineno"> 2350</span>  </div> -<div class="line"><a name="l02351"></a><span class="lineno"> 2351</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02352"></a><span class="lineno"> 2352</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_permute_descriptor.html">armnn::PermuteDescriptor</a> descriptor(<a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a>(dimsMapping->data(), dimsMapping->size()));</div> -<div class="line"><a name="l02353"></a><span class="lineno"> 2353</span>  </div> -<div class="line"><a name="l02354"></a><span class="lineno"> 2354</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPermuteLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02355"></a><span class="lineno"> 2355</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> -<div class="line"><a name="l02356"></a><span class="lineno"> 2356</span>  </div> -<div class="line"><a name="l02357"></a><span class="lineno"> 2357</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02358"></a><span class="lineno"> 2358</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02359"></a><span class="lineno"> 2359</span> }</div> -<div class="line"><a name="l02360"></a><span class="lineno"> 2360</span>  </div> -<div class="line"><a name="l02361"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac17b9b154461bfa49ff7ade08f3c4bdf"> 2361</a></span> <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac17b9b154461bfa49ff7ade08f3c4bdf">IDeserializer::DeserializerImpl::GetPooling2dDescriptor</a>(<a class="code" href="namespacearmnn_deserializer.html#a7e75f47f676327bce37149932aa4a011">Pooling2dDescriptor</a> pooling2dDesc,</div> -<div class="line"><a name="l02362"></a><span class="lineno"> 2362</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02363"></a><span class="lineno"> 2363</span> {</div> -<div class="line"><a name="l02364"></a><span class="lineno"> 2364</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> -<div class="line"><a name="l02365"></a><span class="lineno"> 2365</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> desc;</div> -<div class="line"><a name="l02366"></a><span class="lineno"> 2366</span>  </div> -<div class="line"><a name="l02367"></a><span class="lineno"> 2367</span>  <span class="keywordflow">switch</span> (pooling2dDesc->poolType())</div> -<div class="line"><a name="l02368"></a><span class="lineno"> 2368</span>  {</div> -<div class="line"><a name="l02369"></a><span class="lineno"> 2369</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Average:</div> -<div class="line"><a name="l02370"></a><span class="lineno"> 2370</span>  {</div> -<div class="line"><a name="l02371"></a><span class="lineno"> 2371</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div> -<div class="line"><a name="l02372"></a><span class="lineno"> 2372</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02373"></a><span class="lineno"> 2373</span>  }</div> -<div class="line"><a name="l02374"></a><span class="lineno"> 2374</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Max:</div> -<div class="line"><a name="l02375"></a><span class="lineno"> 2375</span>  {</div> -<div class="line"><a name="l02376"></a><span class="lineno"> 2376</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div> -<div class="line"><a name="l02377"></a><span class="lineno"> 2377</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02378"></a><span class="lineno"> 2378</span>  }</div> -<div class="line"><a name="l02379"></a><span class="lineno"> 2379</span>  <span class="keywordflow">case</span> PoolingAlgorithm_L2:</div> -<div class="line"><a name="l02380"></a><span class="lineno"> 2380</span>  {</div> -<div class="line"><a name="l02381"></a><span class="lineno"> 2381</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div> -<div class="line"><a name="l02382"></a><span class="lineno"> 2382</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02383"></a><span class="lineno"> 2383</span>  }</div> -<div class="line"><a name="l02384"></a><span class="lineno"> 2384</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02385"></a><span class="lineno"> 2385</span>  {</div> -<div class="line"><a name="l02386"></a><span class="lineno"> 2386</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported pooling algorithm"</span>);</div> -<div class="line"><a name="l02387"></a><span class="lineno"> 2387</span>  }</div> -<div class="line"><a name="l02388"></a><span class="lineno"> 2388</span>  }</div> -<div class="line"><a name="l02389"></a><span class="lineno"> 2389</span>  </div> -<div class="line"><a name="l02390"></a><span class="lineno"> 2390</span>  <span class="keywordflow">switch</span> (pooling2dDesc->outputShapeRounding())</div> -<div class="line"><a name="l02391"></a><span class="lineno"> 2391</span>  {</div> -<div class="line"><a name="l02392"></a><span class="lineno"> 2392</span>  <span class="keywordflow">case</span> OutputShapeRounding_Floor:</div> -<div class="line"><a name="l02393"></a><span class="lineno"> 2393</span>  {</div> -<div class="line"><a name="l02394"></a><span class="lineno"> 2394</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div> -<div class="line"><a name="l02395"></a><span class="lineno"> 2395</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02396"></a><span class="lineno"> 2396</span>  }</div> -<div class="line"><a name="l02397"></a><span class="lineno"> 2397</span>  <span class="keywordflow">case</span> OutputShapeRounding_Ceiling:</div> -<div class="line"><a name="l02398"></a><span class="lineno"> 2398</span>  {</div> -<div class="line"><a name="l02399"></a><span class="lineno"> 2399</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">armnn::OutputShapeRounding::Ceiling</a>;</div> -<div class="line"><a name="l02400"></a><span class="lineno"> 2400</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02401"></a><span class="lineno"> 2401</span>  }</div> -<div class="line"><a name="l02402"></a><span class="lineno"> 2402</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02403"></a><span class="lineno"> 2403</span>  {</div> -<div class="line"><a name="l02404"></a><span class="lineno"> 2404</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported output shape rounding"</span>);</div> +<div class="line"><a name="l02347"></a><span class="lineno"> 2347</span>  <a class="code" href="structarmnn_1_1_pad_descriptor.html">armnn::PadDescriptor</a> descriptor(padList, padValue, <a class="code" href="namespacearmnn_deserializer.html#ac33cddeda1d847c4a17d679ea1dab6be">ToPaddingMode</a>(paddingMode));</div> +<div class="line"><a name="l02348"></a><span class="lineno"> 2348</span>  </div> +<div class="line"><a name="l02349"></a><span class="lineno"> 2349</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02350"></a><span class="lineno"> 2350</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPadLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02351"></a><span class="lineno"> 2351</span>  </div> +<div class="line"><a name="l02352"></a><span class="lineno"> 2352</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02353"></a><span class="lineno"> 2353</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02354"></a><span class="lineno"> 2354</span>  </div> +<div class="line"><a name="l02355"></a><span class="lineno"> 2355</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02356"></a><span class="lineno"> 2356</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02357"></a><span class="lineno"> 2357</span> }</div> +<div class="line"><a name="l02358"></a><span class="lineno"> 2358</span>  </div> +<div class="line"><a name="l02359"></a><span class="lineno"> 2359</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePermute(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02360"></a><span class="lineno"> 2360</span> {</div> +<div class="line"><a name="l02361"></a><span class="lineno"> 2361</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02362"></a><span class="lineno"> 2362</span>  </div> +<div class="line"><a name="l02363"></a><span class="lineno"> 2363</span>  <span class="keyword">auto</span> dimsMapping =</div> +<div class="line"><a name="l02364"></a><span class="lineno"> 2364</span>  graph->layers()->Get(layerIndex)->layer_as_PermuteLayer()->descriptor()->dimMappings();</div> +<div class="line"><a name="l02365"></a><span class="lineno"> 2365</span>  </div> +<div class="line"><a name="l02366"></a><span class="lineno"> 2366</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02367"></a><span class="lineno"> 2367</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02368"></a><span class="lineno"> 2368</span>  </div> +<div class="line"><a name="l02369"></a><span class="lineno"> 2369</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02370"></a><span class="lineno"> 2370</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02371"></a><span class="lineno"> 2371</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02372"></a><span class="lineno"> 2372</span>  </div> +<div class="line"><a name="l02373"></a><span class="lineno"> 2373</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02374"></a><span class="lineno"> 2374</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_permute_descriptor.html">armnn::PermuteDescriptor</a> descriptor(<a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a>(dimsMapping->data(), dimsMapping->size()));</div> +<div class="line"><a name="l02375"></a><span class="lineno"> 2375</span>  </div> +<div class="line"><a name="l02376"></a><span class="lineno"> 2376</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPermuteLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02377"></a><span class="lineno"> 2377</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l02378"></a><span class="lineno"> 2378</span>  </div> +<div class="line"><a name="l02379"></a><span class="lineno"> 2379</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02380"></a><span class="lineno"> 2380</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02381"></a><span class="lineno"> 2381</span> }</div> +<div class="line"><a name="l02382"></a><span class="lineno"> 2382</span>  </div> +<div class="line"><a name="l02383"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac17b9b154461bfa49ff7ade08f3c4bdf"> 2383</a></span> <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac17b9b154461bfa49ff7ade08f3c4bdf">IDeserializer::DeserializerImpl::GetPooling2dDescriptor</a>(<a class="code" href="namespacearmnn_deserializer.html#a7e75f47f676327bce37149932aa4a011">Pooling2dDescriptor</a> pooling2dDesc,</div> +<div class="line"><a name="l02384"></a><span class="lineno"> 2384</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02385"></a><span class="lineno"> 2385</span> {</div> +<div class="line"><a name="l02386"></a><span class="lineno"> 2386</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> +<div class="line"><a name="l02387"></a><span class="lineno"> 2387</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> desc;</div> +<div class="line"><a name="l02388"></a><span class="lineno"> 2388</span>  </div> +<div class="line"><a name="l02389"></a><span class="lineno"> 2389</span>  <span class="keywordflow">switch</span> (pooling2dDesc->poolType())</div> +<div class="line"><a name="l02390"></a><span class="lineno"> 2390</span>  {</div> +<div class="line"><a name="l02391"></a><span class="lineno"> 2391</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Average:</div> +<div class="line"><a name="l02392"></a><span class="lineno"> 2392</span>  {</div> +<div class="line"><a name="l02393"></a><span class="lineno"> 2393</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div> +<div class="line"><a name="l02394"></a><span class="lineno"> 2394</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02395"></a><span class="lineno"> 2395</span>  }</div> +<div class="line"><a name="l02396"></a><span class="lineno"> 2396</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Max:</div> +<div class="line"><a name="l02397"></a><span class="lineno"> 2397</span>  {</div> +<div class="line"><a name="l02398"></a><span class="lineno"> 2398</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div> +<div class="line"><a name="l02399"></a><span class="lineno"> 2399</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02400"></a><span class="lineno"> 2400</span>  }</div> +<div class="line"><a name="l02401"></a><span class="lineno"> 2401</span>  <span class="keywordflow">case</span> PoolingAlgorithm_L2:</div> +<div class="line"><a name="l02402"></a><span class="lineno"> 2402</span>  {</div> +<div class="line"><a name="l02403"></a><span class="lineno"> 2403</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div> +<div class="line"><a name="l02404"></a><span class="lineno"> 2404</span>  <span class="keywordflow">break</span>;</div> <div class="line"><a name="l02405"></a><span class="lineno"> 2405</span>  }</div> -<div class="line"><a name="l02406"></a><span class="lineno"> 2406</span>  }</div> -<div class="line"><a name="l02407"></a><span class="lineno"> 2407</span>  </div> -<div class="line"><a name="l02408"></a><span class="lineno"> 2408</span>  <span class="keywordflow">switch</span> (pooling2dDesc->paddingMethod())</div> -<div class="line"><a name="l02409"></a><span class="lineno"> 2409</span>  {</div> -<div class="line"><a name="l02410"></a><span class="lineno"> 2410</span>  <span class="keywordflow">case</span> PaddingMethod_Exclude:</div> -<div class="line"><a name="l02411"></a><span class="lineno"> 2411</span>  {</div> -<div class="line"><a name="l02412"></a><span class="lineno"> 2412</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div> -<div class="line"><a name="l02413"></a><span class="lineno"> 2413</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02414"></a><span class="lineno"> 2414</span>  }</div> -<div class="line"><a name="l02415"></a><span class="lineno"> 2415</span>  <span class="keywordflow">case</span> PaddingMethod_IgnoreValue:</div> -<div class="line"><a name="l02416"></a><span class="lineno"> 2416</span>  {</div> -<div class="line"><a name="l02417"></a><span class="lineno"> 2417</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a>;</div> -<div class="line"><a name="l02418"></a><span class="lineno"> 2418</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02419"></a><span class="lineno"> 2419</span>  }</div> -<div class="line"><a name="l02420"></a><span class="lineno"> 2420</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02421"></a><span class="lineno"> 2421</span>  {</div> -<div class="line"><a name="l02422"></a><span class="lineno"> 2422</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported padding method"</span>);</div> +<div class="line"><a name="l02406"></a><span class="lineno"> 2406</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02407"></a><span class="lineno"> 2407</span>  {</div> +<div class="line"><a name="l02408"></a><span class="lineno"> 2408</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported pooling algorithm"</span>);</div> +<div class="line"><a name="l02409"></a><span class="lineno"> 2409</span>  }</div> +<div class="line"><a name="l02410"></a><span class="lineno"> 2410</span>  }</div> +<div class="line"><a name="l02411"></a><span class="lineno"> 2411</span>  </div> +<div class="line"><a name="l02412"></a><span class="lineno"> 2412</span>  <span class="keywordflow">switch</span> (pooling2dDesc->outputShapeRounding())</div> +<div class="line"><a name="l02413"></a><span class="lineno"> 2413</span>  {</div> +<div class="line"><a name="l02414"></a><span class="lineno"> 2414</span>  <span class="keywordflow">case</span> OutputShapeRounding_Floor:</div> +<div class="line"><a name="l02415"></a><span class="lineno"> 2415</span>  {</div> +<div class="line"><a name="l02416"></a><span class="lineno"> 2416</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div> +<div class="line"><a name="l02417"></a><span class="lineno"> 2417</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02418"></a><span class="lineno"> 2418</span>  }</div> +<div class="line"><a name="l02419"></a><span class="lineno"> 2419</span>  <span class="keywordflow">case</span> OutputShapeRounding_Ceiling:</div> +<div class="line"><a name="l02420"></a><span class="lineno"> 2420</span>  {</div> +<div class="line"><a name="l02421"></a><span class="lineno"> 2421</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">armnn::OutputShapeRounding::Ceiling</a>;</div> +<div class="line"><a name="l02422"></a><span class="lineno"> 2422</span>  <span class="keywordflow">break</span>;</div> <div class="line"><a name="l02423"></a><span class="lineno"> 2423</span>  }</div> -<div class="line"><a name="l02424"></a><span class="lineno"> 2424</span>  }</div> -<div class="line"><a name="l02425"></a><span class="lineno"> 2425</span>  </div> -<div class="line"><a name="l02426"></a><span class="lineno"> 2426</span>  <span class="keywordflow">switch</span> (pooling2dDesc->dataLayout())</div> -<div class="line"><a name="l02427"></a><span class="lineno"> 2427</span>  {</div> -<div class="line"><a name="l02428"></a><span class="lineno"> 2428</span>  <span class="keywordflow">case</span> DataLayout_NCHW:</div> -<div class="line"><a name="l02429"></a><span class="lineno"> 2429</span>  {</div> -<div class="line"><a name="l02430"></a><span class="lineno"> 2430</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div> -<div class="line"><a name="l02431"></a><span class="lineno"> 2431</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02432"></a><span class="lineno"> 2432</span>  }</div> -<div class="line"><a name="l02433"></a><span class="lineno"> 2433</span>  <span class="keywordflow">case</span> DataLayout_NHWC:</div> -<div class="line"><a name="l02434"></a><span class="lineno"> 2434</span>  {</div> -<div class="line"><a name="l02435"></a><span class="lineno"> 2435</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div> -<div class="line"><a name="l02436"></a><span class="lineno"> 2436</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02437"></a><span class="lineno"> 2437</span>  }</div> -<div class="line"><a name="l02438"></a><span class="lineno"> 2438</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02439"></a><span class="lineno"> 2439</span>  {</div> -<div class="line"><a name="l02440"></a><span class="lineno"> 2440</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported data layout"</span>);</div> +<div class="line"><a name="l02424"></a><span class="lineno"> 2424</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02425"></a><span class="lineno"> 2425</span>  {</div> +<div class="line"><a name="l02426"></a><span class="lineno"> 2426</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported output shape rounding"</span>);</div> +<div class="line"><a name="l02427"></a><span class="lineno"> 2427</span>  }</div> +<div class="line"><a name="l02428"></a><span class="lineno"> 2428</span>  }</div> +<div class="line"><a name="l02429"></a><span class="lineno"> 2429</span>  </div> +<div class="line"><a name="l02430"></a><span class="lineno"> 2430</span>  <span class="keywordflow">switch</span> (pooling2dDesc->paddingMethod())</div> +<div class="line"><a name="l02431"></a><span class="lineno"> 2431</span>  {</div> +<div class="line"><a name="l02432"></a><span class="lineno"> 2432</span>  <span class="keywordflow">case</span> PaddingMethod_Exclude:</div> +<div class="line"><a name="l02433"></a><span class="lineno"> 2433</span>  {</div> +<div class="line"><a name="l02434"></a><span class="lineno"> 2434</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div> +<div class="line"><a name="l02435"></a><span class="lineno"> 2435</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02436"></a><span class="lineno"> 2436</span>  }</div> +<div class="line"><a name="l02437"></a><span class="lineno"> 2437</span>  <span class="keywordflow">case</span> PaddingMethod_IgnoreValue:</div> +<div class="line"><a name="l02438"></a><span class="lineno"> 2438</span>  {</div> +<div class="line"><a name="l02439"></a><span class="lineno"> 2439</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a>;</div> +<div class="line"><a name="l02440"></a><span class="lineno"> 2440</span>  <span class="keywordflow">break</span>;</div> <div class="line"><a name="l02441"></a><span class="lineno"> 2441</span>  }</div> -<div class="line"><a name="l02442"></a><span class="lineno"> 2442</span>  }</div> -<div class="line"><a name="l02443"></a><span class="lineno"> 2443</span>  </div> -<div class="line"><a name="l02444"></a><span class="lineno"> 2444</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = pooling2dDesc->padRight();</div> -<div class="line"><a name="l02445"></a><span class="lineno"> 2445</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = pooling2dDesc->padLeft();</div> -<div class="line"><a name="l02446"></a><span class="lineno"> 2446</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = pooling2dDesc->padBottom();</div> -<div class="line"><a name="l02447"></a><span class="lineno"> 2447</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = pooling2dDesc->padTop();</div> -<div class="line"><a name="l02448"></a><span class="lineno"> 2448</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = pooling2dDesc->strideX();</div> -<div class="line"><a name="l02449"></a><span class="lineno"> 2449</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = pooling2dDesc->strideY();</div> -<div class="line"><a name="l02450"></a><span class="lineno"> 2450</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = pooling2dDesc->poolWidth();</div> -<div class="line"><a name="l02451"></a><span class="lineno"> 2451</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = pooling2dDesc->poolHeight();</div> -<div class="line"><a name="l02452"></a><span class="lineno"> 2452</span>  </div> -<div class="line"><a name="l02453"></a><span class="lineno"> 2453</span>  <span class="keywordflow">return</span> desc;</div> -<div class="line"><a name="l02454"></a><span class="lineno"> 2454</span> }</div> -<div class="line"><a name="l02455"></a><span class="lineno"> 2455</span>  </div> -<div class="line"><a name="l02456"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a1467999b659959577bb2efc8fc62e15a"> 2456</a></span> <a class="code" href="structarmnn_1_1_pooling3d_descriptor.html">armnn::Pooling3dDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a1467999b659959577bb2efc8fc62e15a">IDeserializer::DeserializerImpl::GetPooling3dDescriptor</a>(<a class="code" href="namespacearmnn_deserializer.html#a6713b8a83104db317823b5367b195d2e">Pooling3dDescriptor</a> pooling3dDesc,</div> -<div class="line"><a name="l02457"></a><span class="lineno"> 2457</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02458"></a><span class="lineno"> 2458</span> {</div> -<div class="line"><a name="l02459"></a><span class="lineno"> 2459</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> -<div class="line"><a name="l02460"></a><span class="lineno"> 2460</span>  <a class="code" href="structarmnn_1_1_pooling3d_descriptor.html">armnn::Pooling3dDescriptor</a> desc;</div> -<div class="line"><a name="l02461"></a><span class="lineno"> 2461</span>  </div> -<div class="line"><a name="l02462"></a><span class="lineno"> 2462</span>  <span class="keywordflow">switch</span> (pooling3dDesc->poolType())</div> -<div class="line"><a name="l02463"></a><span class="lineno"> 2463</span>  {</div> -<div class="line"><a name="l02464"></a><span class="lineno"> 2464</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Average:</div> -<div class="line"><a name="l02465"></a><span class="lineno"> 2465</span>  {</div> -<div class="line"><a name="l02466"></a><span class="lineno"> 2466</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div> -<div class="line"><a name="l02467"></a><span class="lineno"> 2467</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02468"></a><span class="lineno"> 2468</span>  }</div> -<div class="line"><a name="l02469"></a><span class="lineno"> 2469</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Max:</div> -<div class="line"><a name="l02470"></a><span class="lineno"> 2470</span>  {</div> -<div class="line"><a name="l02471"></a><span class="lineno"> 2471</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div> -<div class="line"><a name="l02472"></a><span class="lineno"> 2472</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02473"></a><span class="lineno"> 2473</span>  }</div> -<div class="line"><a name="l02474"></a><span class="lineno"> 2474</span>  <span class="keywordflow">case</span> PoolingAlgorithm_L2:</div> -<div class="line"><a name="l02475"></a><span class="lineno"> 2475</span>  {</div> -<div class="line"><a name="l02476"></a><span class="lineno"> 2476</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div> -<div class="line"><a name="l02477"></a><span class="lineno"> 2477</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02478"></a><span class="lineno"> 2478</span>  }</div> -<div class="line"><a name="l02479"></a><span class="lineno"> 2479</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02480"></a><span class="lineno"> 2480</span>  {</div> -<div class="line"><a name="l02481"></a><span class="lineno"> 2481</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported pooling algorithm"</span>);</div> -<div class="line"><a name="l02482"></a><span class="lineno"> 2482</span>  }</div> -<div class="line"><a name="l02483"></a><span class="lineno"> 2483</span>  }</div> -<div class="line"><a name="l02484"></a><span class="lineno"> 2484</span>  </div> -<div class="line"><a name="l02485"></a><span class="lineno"> 2485</span>  <span class="keywordflow">switch</span> (pooling3dDesc->outputShapeRounding())</div> -<div class="line"><a name="l02486"></a><span class="lineno"> 2486</span>  {</div> -<div class="line"><a name="l02487"></a><span class="lineno"> 2487</span>  <span class="keywordflow">case</span> OutputShapeRounding_Floor:</div> -<div class="line"><a name="l02488"></a><span class="lineno"> 2488</span>  {</div> -<div class="line"><a name="l02489"></a><span class="lineno"> 2489</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div> -<div class="line"><a name="l02490"></a><span class="lineno"> 2490</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02491"></a><span class="lineno"> 2491</span>  }</div> -<div class="line"><a name="l02492"></a><span class="lineno"> 2492</span>  <span class="keywordflow">case</span> OutputShapeRounding_Ceiling:</div> -<div class="line"><a name="l02493"></a><span class="lineno"> 2493</span>  {</div> -<div class="line"><a name="l02494"></a><span class="lineno"> 2494</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">armnn::OutputShapeRounding::Ceiling</a>;</div> -<div class="line"><a name="l02495"></a><span class="lineno"> 2495</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02496"></a><span class="lineno"> 2496</span>  }</div> -<div class="line"><a name="l02497"></a><span class="lineno"> 2497</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02498"></a><span class="lineno"> 2498</span>  {</div> -<div class="line"><a name="l02499"></a><span class="lineno"> 2499</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported output shape rounding"</span>);</div> +<div class="line"><a name="l02442"></a><span class="lineno"> 2442</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02443"></a><span class="lineno"> 2443</span>  {</div> +<div class="line"><a name="l02444"></a><span class="lineno"> 2444</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported padding method"</span>);</div> +<div class="line"><a name="l02445"></a><span class="lineno"> 2445</span>  }</div> +<div class="line"><a name="l02446"></a><span class="lineno"> 2446</span>  }</div> +<div class="line"><a name="l02447"></a><span class="lineno"> 2447</span>  </div> +<div class="line"><a name="l02448"></a><span class="lineno"> 2448</span>  <span class="keywordflow">switch</span> (pooling2dDesc->dataLayout())</div> +<div class="line"><a name="l02449"></a><span class="lineno"> 2449</span>  {</div> +<div class="line"><a name="l02450"></a><span class="lineno"> 2450</span>  <span class="keywordflow">case</span> DataLayout_NCHW:</div> +<div class="line"><a name="l02451"></a><span class="lineno"> 2451</span>  {</div> +<div class="line"><a name="l02452"></a><span class="lineno"> 2452</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div> +<div class="line"><a name="l02453"></a><span class="lineno"> 2453</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02454"></a><span class="lineno"> 2454</span>  }</div> +<div class="line"><a name="l02455"></a><span class="lineno"> 2455</span>  <span class="keywordflow">case</span> DataLayout_NHWC:</div> +<div class="line"><a name="l02456"></a><span class="lineno"> 2456</span>  {</div> +<div class="line"><a name="l02457"></a><span class="lineno"> 2457</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div> +<div class="line"><a name="l02458"></a><span class="lineno"> 2458</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02459"></a><span class="lineno"> 2459</span>  }</div> +<div class="line"><a name="l02460"></a><span class="lineno"> 2460</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02461"></a><span class="lineno"> 2461</span>  {</div> +<div class="line"><a name="l02462"></a><span class="lineno"> 2462</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported data layout"</span>);</div> +<div class="line"><a name="l02463"></a><span class="lineno"> 2463</span>  }</div> +<div class="line"><a name="l02464"></a><span class="lineno"> 2464</span>  }</div> +<div class="line"><a name="l02465"></a><span class="lineno"> 2465</span>  </div> +<div class="line"><a name="l02466"></a><span class="lineno"> 2466</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = pooling2dDesc->padRight();</div> +<div class="line"><a name="l02467"></a><span class="lineno"> 2467</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = pooling2dDesc->padLeft();</div> +<div class="line"><a name="l02468"></a><span class="lineno"> 2468</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = pooling2dDesc->padBottom();</div> +<div class="line"><a name="l02469"></a><span class="lineno"> 2469</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = pooling2dDesc->padTop();</div> +<div class="line"><a name="l02470"></a><span class="lineno"> 2470</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = pooling2dDesc->strideX();</div> +<div class="line"><a name="l02471"></a><span class="lineno"> 2471</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = pooling2dDesc->strideY();</div> +<div class="line"><a name="l02472"></a><span class="lineno"> 2472</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = pooling2dDesc->poolWidth();</div> +<div class="line"><a name="l02473"></a><span class="lineno"> 2473</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = pooling2dDesc->poolHeight();</div> +<div class="line"><a name="l02474"></a><span class="lineno"> 2474</span>  </div> +<div class="line"><a name="l02475"></a><span class="lineno"> 2475</span>  <span class="keywordflow">return</span> desc;</div> +<div class="line"><a name="l02476"></a><span class="lineno"> 2476</span> }</div> +<div class="line"><a name="l02477"></a><span class="lineno"> 2477</span>  </div> +<div class="line"><a name="l02478"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a1467999b659959577bb2efc8fc62e15a"> 2478</a></span> <a class="code" href="structarmnn_1_1_pooling3d_descriptor.html">armnn::Pooling3dDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a1467999b659959577bb2efc8fc62e15a">IDeserializer::DeserializerImpl::GetPooling3dDescriptor</a>(<a class="code" href="namespacearmnn_deserializer.html#a6713b8a83104db317823b5367b195d2e">Pooling3dDescriptor</a> pooling3dDesc,</div> +<div class="line"><a name="l02479"></a><span class="lineno"> 2479</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02480"></a><span class="lineno"> 2480</span> {</div> +<div class="line"><a name="l02481"></a><span class="lineno"> 2481</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> +<div class="line"><a name="l02482"></a><span class="lineno"> 2482</span>  <a class="code" href="structarmnn_1_1_pooling3d_descriptor.html">armnn::Pooling3dDescriptor</a> desc;</div> +<div class="line"><a name="l02483"></a><span class="lineno"> 2483</span>  </div> +<div class="line"><a name="l02484"></a><span class="lineno"> 2484</span>  <span class="keywordflow">switch</span> (pooling3dDesc->poolType())</div> +<div class="line"><a name="l02485"></a><span class="lineno"> 2485</span>  {</div> +<div class="line"><a name="l02486"></a><span class="lineno"> 2486</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Average:</div> +<div class="line"><a name="l02487"></a><span class="lineno"> 2487</span>  {</div> +<div class="line"><a name="l02488"></a><span class="lineno"> 2488</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div> +<div class="line"><a name="l02489"></a><span class="lineno"> 2489</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02490"></a><span class="lineno"> 2490</span>  }</div> +<div class="line"><a name="l02491"></a><span class="lineno"> 2491</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Max:</div> +<div class="line"><a name="l02492"></a><span class="lineno"> 2492</span>  {</div> +<div class="line"><a name="l02493"></a><span class="lineno"> 2493</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div> +<div class="line"><a name="l02494"></a><span class="lineno"> 2494</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02495"></a><span class="lineno"> 2495</span>  }</div> +<div class="line"><a name="l02496"></a><span class="lineno"> 2496</span>  <span class="keywordflow">case</span> PoolingAlgorithm_L2:</div> +<div class="line"><a name="l02497"></a><span class="lineno"> 2497</span>  {</div> +<div class="line"><a name="l02498"></a><span class="lineno"> 2498</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div> +<div class="line"><a name="l02499"></a><span class="lineno"> 2499</span>  <span class="keywordflow">break</span>;</div> <div class="line"><a name="l02500"></a><span class="lineno"> 2500</span>  }</div> -<div class="line"><a name="l02501"></a><span class="lineno"> 2501</span>  }</div> -<div class="line"><a name="l02502"></a><span class="lineno"> 2502</span>  </div> -<div class="line"><a name="l02503"></a><span class="lineno"> 2503</span>  <span class="keywordflow">switch</span> (pooling3dDesc->paddingMethod())</div> -<div class="line"><a name="l02504"></a><span class="lineno"> 2504</span>  {</div> -<div class="line"><a name="l02505"></a><span class="lineno"> 2505</span>  <span class="keywordflow">case</span> PaddingMethod_Exclude:</div> -<div class="line"><a name="l02506"></a><span class="lineno"> 2506</span>  {</div> -<div class="line"><a name="l02507"></a><span class="lineno"> 2507</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div> -<div class="line"><a name="l02508"></a><span class="lineno"> 2508</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02509"></a><span class="lineno"> 2509</span>  }</div> -<div class="line"><a name="l02510"></a><span class="lineno"> 2510</span>  <span class="keywordflow">case</span> PaddingMethod_IgnoreValue:</div> -<div class="line"><a name="l02511"></a><span class="lineno"> 2511</span>  {</div> -<div class="line"><a name="l02512"></a><span class="lineno"> 2512</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a>;</div> -<div class="line"><a name="l02513"></a><span class="lineno"> 2513</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02514"></a><span class="lineno"> 2514</span>  }</div> -<div class="line"><a name="l02515"></a><span class="lineno"> 2515</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02516"></a><span class="lineno"> 2516</span>  {</div> -<div class="line"><a name="l02517"></a><span class="lineno"> 2517</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported padding method"</span>);</div> +<div class="line"><a name="l02501"></a><span class="lineno"> 2501</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02502"></a><span class="lineno"> 2502</span>  {</div> +<div class="line"><a name="l02503"></a><span class="lineno"> 2503</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported pooling algorithm"</span>);</div> +<div class="line"><a name="l02504"></a><span class="lineno"> 2504</span>  }</div> +<div class="line"><a name="l02505"></a><span class="lineno"> 2505</span>  }</div> +<div class="line"><a name="l02506"></a><span class="lineno"> 2506</span>  </div> +<div class="line"><a name="l02507"></a><span class="lineno"> 2507</span>  <span class="keywordflow">switch</span> (pooling3dDesc->outputShapeRounding())</div> +<div class="line"><a name="l02508"></a><span class="lineno"> 2508</span>  {</div> +<div class="line"><a name="l02509"></a><span class="lineno"> 2509</span>  <span class="keywordflow">case</span> OutputShapeRounding_Floor:</div> +<div class="line"><a name="l02510"></a><span class="lineno"> 2510</span>  {</div> +<div class="line"><a name="l02511"></a><span class="lineno"> 2511</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div> +<div class="line"><a name="l02512"></a><span class="lineno"> 2512</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02513"></a><span class="lineno"> 2513</span>  }</div> +<div class="line"><a name="l02514"></a><span class="lineno"> 2514</span>  <span class="keywordflow">case</span> OutputShapeRounding_Ceiling:</div> +<div class="line"><a name="l02515"></a><span class="lineno"> 2515</span>  {</div> +<div class="line"><a name="l02516"></a><span class="lineno"> 2516</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">armnn::OutputShapeRounding::Ceiling</a>;</div> +<div class="line"><a name="l02517"></a><span class="lineno"> 2517</span>  <span class="keywordflow">break</span>;</div> <div class="line"><a name="l02518"></a><span class="lineno"> 2518</span>  }</div> -<div class="line"><a name="l02519"></a><span class="lineno"> 2519</span>  }</div> -<div class="line"><a name="l02520"></a><span class="lineno"> 2520</span>  </div> -<div class="line"><a name="l02521"></a><span class="lineno"> 2521</span>  <span class="keywordflow">switch</span> (pooling3dDesc->dataLayout())</div> -<div class="line"><a name="l02522"></a><span class="lineno"> 2522</span>  {</div> -<div class="line"><a name="l02523"></a><span class="lineno"> 2523</span>  <span class="keywordflow">case</span> DataLayout_NCDHW:</div> -<div class="line"><a name="l02524"></a><span class="lineno"> 2524</span>  {</div> -<div class="line"><a name="l02525"></a><span class="lineno"> 2525</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015">armnn::DataLayout::NCDHW</a>;</div> -<div class="line"><a name="l02526"></a><span class="lineno"> 2526</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02527"></a><span class="lineno"> 2527</span>  }</div> -<div class="line"><a name="l02528"></a><span class="lineno"> 2528</span>  <span class="keywordflow">case</span> DataLayout_NDHWC:</div> -<div class="line"><a name="l02529"></a><span class="lineno"> 2529</span>  {</div> -<div class="line"><a name="l02530"></a><span class="lineno"> 2530</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a4dd0194b114cbf51da5b3a72569863ef">armnn::DataLayout::NDHWC</a>;</div> -<div class="line"><a name="l02531"></a><span class="lineno"> 2531</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02532"></a><span class="lineno"> 2532</span>  }</div> -<div class="line"><a name="l02533"></a><span class="lineno"> 2533</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02534"></a><span class="lineno"> 2534</span>  {</div> -<div class="line"><a name="l02535"></a><span class="lineno"> 2535</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported data layout"</span>);</div> +<div class="line"><a name="l02519"></a><span class="lineno"> 2519</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02520"></a><span class="lineno"> 2520</span>  {</div> +<div class="line"><a name="l02521"></a><span class="lineno"> 2521</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported output shape rounding"</span>);</div> +<div class="line"><a name="l02522"></a><span class="lineno"> 2522</span>  }</div> +<div class="line"><a name="l02523"></a><span class="lineno"> 2523</span>  }</div> +<div class="line"><a name="l02524"></a><span class="lineno"> 2524</span>  </div> +<div class="line"><a name="l02525"></a><span class="lineno"> 2525</span>  <span class="keywordflow">switch</span> (pooling3dDesc->paddingMethod())</div> +<div class="line"><a name="l02526"></a><span class="lineno"> 2526</span>  {</div> +<div class="line"><a name="l02527"></a><span class="lineno"> 2527</span>  <span class="keywordflow">case</span> PaddingMethod_Exclude:</div> +<div class="line"><a name="l02528"></a><span class="lineno"> 2528</span>  {</div> +<div class="line"><a name="l02529"></a><span class="lineno"> 2529</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div> +<div class="line"><a name="l02530"></a><span class="lineno"> 2530</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02531"></a><span class="lineno"> 2531</span>  }</div> +<div class="line"><a name="l02532"></a><span class="lineno"> 2532</span>  <span class="keywordflow">case</span> PaddingMethod_IgnoreValue:</div> +<div class="line"><a name="l02533"></a><span class="lineno"> 2533</span>  {</div> +<div class="line"><a name="l02534"></a><span class="lineno"> 2534</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a>;</div> +<div class="line"><a name="l02535"></a><span class="lineno"> 2535</span>  <span class="keywordflow">break</span>;</div> <div class="line"><a name="l02536"></a><span class="lineno"> 2536</span>  }</div> -<div class="line"><a name="l02537"></a><span class="lineno"> 2537</span>  }</div> -<div class="line"><a name="l02538"></a><span class="lineno"> 2538</span>  </div> -<div class="line"><a name="l02539"></a><span class="lineno"> 2539</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = pooling3dDesc->padRight();</div> -<div class="line"><a name="l02540"></a><span class="lineno"> 2540</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = pooling3dDesc->padLeft();</div> -<div class="line"><a name="l02541"></a><span class="lineno"> 2541</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = pooling3dDesc->padBottom();</div> -<div class="line"><a name="l02542"></a><span class="lineno"> 2542</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = pooling3dDesc->padTop();</div> -<div class="line"><a name="l02543"></a><span class="lineno"> 2543</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a83ca447892f460dabaa2f87d3dc3db61">m_PadFront</a> = pooling3dDesc->padFront();</div> -<div class="line"><a name="l02544"></a><span class="lineno"> 2544</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a11d5c25face9b54e90f79ee8bdc1d0fb">m_PadBack</a> = pooling3dDesc->padBack();</div> -<div class="line"><a name="l02545"></a><span class="lineno"> 2545</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = pooling3dDesc->strideX();</div> -<div class="line"><a name="l02546"></a><span class="lineno"> 2546</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = pooling3dDesc->strideY();</div> -<div class="line"><a name="l02547"></a><span class="lineno"> 2547</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a5164336f6a1b15be0d434a6bbf7289da">m_StrideZ</a> = pooling3dDesc->strideZ();</div> -<div class="line"><a name="l02548"></a><span class="lineno"> 2548</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = pooling3dDesc->poolWidth();</div> -<div class="line"><a name="l02549"></a><span class="lineno"> 2549</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = pooling3dDesc->poolHeight();</div> -<div class="line"><a name="l02550"></a><span class="lineno"> 2550</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#acc978b36fd5d949bc781d7638e6e08b9">m_PoolDepth</a> = pooling3dDesc->poolDepth();</div> -<div class="line"><a name="l02551"></a><span class="lineno"> 2551</span>  </div> -<div class="line"><a name="l02552"></a><span class="lineno"> 2552</span>  <span class="keywordflow">return</span> desc;</div> -<div class="line"><a name="l02553"></a><span class="lineno"> 2553</span> }</div> -<div class="line"><a name="l02554"></a><span class="lineno"> 2554</span>  </div> -<div class="line"><a name="l02555"></a><span class="lineno"> 2555</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePooling2d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02556"></a><span class="lineno"> 2556</span> {</div> -<div class="line"><a name="l02557"></a><span class="lineno"> 2557</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02558"></a><span class="lineno"> 2558</span>  </div> -<div class="line"><a name="l02559"></a><span class="lineno"> 2559</span>  <span class="keyword">auto</span> pooling2dDes = graph->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->descriptor();</div> -<div class="line"><a name="l02560"></a><span class="lineno"> 2560</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02561"></a><span class="lineno"> 2561</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02562"></a><span class="lineno"> 2562</span>  </div> -<div class="line"><a name="l02563"></a><span class="lineno"> 2563</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02564"></a><span class="lineno"> 2564</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02565"></a><span class="lineno"> 2565</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02566"></a><span class="lineno"> 2566</span>  </div> -<div class="line"><a name="l02567"></a><span class="lineno"> 2567</span>  <span class="keyword">auto</span> pooling2dDescriptor = GetPooling2dDescriptor(pooling2dDes, layerIndex);</div> -<div class="line"><a name="l02568"></a><span class="lineno"> 2568</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02569"></a><span class="lineno"> 2569</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPooling2dLayer(pooling2dDescriptor, layerName.c_str());</div> -<div class="line"><a name="l02570"></a><span class="lineno"> 2570</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> -<div class="line"><a name="l02571"></a><span class="lineno"> 2571</span>  </div> -<div class="line"><a name="l02572"></a><span class="lineno"> 2572</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02573"></a><span class="lineno"> 2573</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02574"></a><span class="lineno"> 2574</span> }</div> -<div class="line"><a name="l02575"></a><span class="lineno"> 2575</span>  </div> -<div class="line"><a name="l02576"></a><span class="lineno"> 2576</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePooling3d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02577"></a><span class="lineno"> 2577</span> {</div> -<div class="line"><a name="l02578"></a><span class="lineno"> 2578</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02579"></a><span class="lineno"> 2579</span>  </div> -<div class="line"><a name="l02580"></a><span class="lineno"> 2580</span>  <span class="keyword">auto</span> pooling3dDes = graph->layers()->Get(layerIndex)->layer_as_Pooling3dLayer()->descriptor();</div> -<div class="line"><a name="l02581"></a><span class="lineno"> 2581</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02582"></a><span class="lineno"> 2582</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02583"></a><span class="lineno"> 2583</span>  </div> -<div class="line"><a name="l02584"></a><span class="lineno"> 2584</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02585"></a><span class="lineno"> 2585</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02586"></a><span class="lineno"> 2586</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02587"></a><span class="lineno"> 2587</span>  </div> -<div class="line"><a name="l02588"></a><span class="lineno"> 2588</span>  <span class="keyword">auto</span> pooling3dDescriptor = GetPooling3dDescriptor(pooling3dDes, layerIndex);</div> -<div class="line"><a name="l02589"></a><span class="lineno"> 2589</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02590"></a><span class="lineno"> 2590</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPooling3dLayer(pooling3dDescriptor, layerName.c_str());</div> -<div class="line"><a name="l02591"></a><span class="lineno"> 2591</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> -<div class="line"><a name="l02592"></a><span class="lineno"> 2592</span>  </div> -<div class="line"><a name="l02593"></a><span class="lineno"> 2593</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02594"></a><span class="lineno"> 2594</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02595"></a><span class="lineno"> 2595</span> }</div> -<div class="line"><a name="l02596"></a><span class="lineno"> 2596</span>  </div> -<div class="line"><a name="l02597"></a><span class="lineno"> 2597</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseQuantize(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02598"></a><span class="lineno"> 2598</span> {</div> -<div class="line"><a name="l02599"></a><span class="lineno"> 2599</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02600"></a><span class="lineno"> 2600</span>  </div> -<div class="line"><a name="l02601"></a><span class="lineno"> 2601</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02602"></a><span class="lineno"> 2602</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02603"></a><span class="lineno"> 2603</span>  </div> -<div class="line"><a name="l02604"></a><span class="lineno"> 2604</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02605"></a><span class="lineno"> 2605</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02606"></a><span class="lineno"> 2606</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02607"></a><span class="lineno"> 2607</span>  </div> -<div class="line"><a name="l02608"></a><span class="lineno"> 2608</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02609"></a><span class="lineno"> 2609</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddQuantizeLayer(layerName.c_str());</div> -<div class="line"><a name="l02610"></a><span class="lineno"> 2610</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> -<div class="line"><a name="l02611"></a><span class="lineno"> 2611</span>  </div> -<div class="line"><a name="l02612"></a><span class="lineno"> 2612</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02613"></a><span class="lineno"> 2613</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02614"></a><span class="lineno"> 2614</span> }</div> -<div class="line"><a name="l02615"></a><span class="lineno"> 2615</span>  </div> -<div class="line"><a name="l02616"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a8752c2b994619ae67201a297c2c76be2"> 2616</a></span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a8752c2b994619ae67201a297c2c76be2">IDeserializer::DeserializerImpl::OutputShapeOfReshape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& inputTensorInfo,</div> -<div class="line"><a name="l02617"></a><span class="lineno"> 2617</span>  <span class="keyword">const</span> std::vector<uint32_t>& targetDimsIn)</div> -<div class="line"><a name="l02618"></a><span class="lineno"> 2618</span> {</div> -<div class="line"><a name="l02619"></a><span class="lineno"> 2619</span>  std::vector<unsigned int> outputDims(targetDimsIn.begin(), targetDimsIn.end());</div> -<div class="line"><a name="l02620"></a><span class="lineno"> 2620</span>  <span class="keyword">const</span> <span class="keyword">auto</span> stretchDim = std::find(targetDimsIn.begin(), targetDimsIn.end(), -1);</div> -<div class="line"><a name="l02621"></a><span class="lineno"> 2621</span>  </div> -<div class="line"><a name="l02622"></a><span class="lineno"> 2622</span>  <span class="keywordflow">if</span> (stretchDim != targetDimsIn.end())</div> -<div class="line"><a name="l02623"></a><span class="lineno"> 2623</span>  {</div> -<div class="line"><a name="l02624"></a><span class="lineno"> 2624</span>  <span class="keywordflow">if</span> (std::find(std::next(stretchDim), targetDimsIn.end(), -1) != targetDimsIn.end())</div> -<div class="line"><a name="l02625"></a><span class="lineno"> 2625</span>  {</div> -<div class="line"><a name="l02626"></a><span class="lineno"> 2626</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"At most one component of shape can be -1 {}"</span>,</div> -<div class="line"><a name="l02627"></a><span class="lineno"> 2627</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l02628"></a><span class="lineno"> 2628</span>  }</div> +<div class="line"><a name="l02537"></a><span class="lineno"> 2537</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02538"></a><span class="lineno"> 2538</span>  {</div> +<div class="line"><a name="l02539"></a><span class="lineno"> 2539</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported padding method"</span>);</div> +<div class="line"><a name="l02540"></a><span class="lineno"> 2540</span>  }</div> +<div class="line"><a name="l02541"></a><span class="lineno"> 2541</span>  }</div> +<div class="line"><a name="l02542"></a><span class="lineno"> 2542</span>  </div> +<div class="line"><a name="l02543"></a><span class="lineno"> 2543</span>  <span class="keywordflow">switch</span> (pooling3dDesc->dataLayout())</div> +<div class="line"><a name="l02544"></a><span class="lineno"> 2544</span>  {</div> +<div class="line"><a name="l02545"></a><span class="lineno"> 2545</span>  <span class="keywordflow">case</span> DataLayout_NCDHW:</div> +<div class="line"><a name="l02546"></a><span class="lineno"> 2546</span>  {</div> +<div class="line"><a name="l02547"></a><span class="lineno"> 2547</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015">armnn::DataLayout::NCDHW</a>;</div> +<div class="line"><a name="l02548"></a><span class="lineno"> 2548</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02549"></a><span class="lineno"> 2549</span>  }</div> +<div class="line"><a name="l02550"></a><span class="lineno"> 2550</span>  <span class="keywordflow">case</span> DataLayout_NDHWC:</div> +<div class="line"><a name="l02551"></a><span class="lineno"> 2551</span>  {</div> +<div class="line"><a name="l02552"></a><span class="lineno"> 2552</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a4dd0194b114cbf51da5b3a72569863ef">armnn::DataLayout::NDHWC</a>;</div> +<div class="line"><a name="l02553"></a><span class="lineno"> 2553</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02554"></a><span class="lineno"> 2554</span>  }</div> +<div class="line"><a name="l02555"></a><span class="lineno"> 2555</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02556"></a><span class="lineno"> 2556</span>  {</div> +<div class="line"><a name="l02557"></a><span class="lineno"> 2557</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported data layout"</span>);</div> +<div class="line"><a name="l02558"></a><span class="lineno"> 2558</span>  }</div> +<div class="line"><a name="l02559"></a><span class="lineno"> 2559</span>  }</div> +<div class="line"><a name="l02560"></a><span class="lineno"> 2560</span>  </div> +<div class="line"><a name="l02561"></a><span class="lineno"> 2561</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = pooling3dDesc->padRight();</div> +<div class="line"><a name="l02562"></a><span class="lineno"> 2562</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = pooling3dDesc->padLeft();</div> +<div class="line"><a name="l02563"></a><span class="lineno"> 2563</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = pooling3dDesc->padBottom();</div> +<div class="line"><a name="l02564"></a><span class="lineno"> 2564</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = pooling3dDesc->padTop();</div> +<div class="line"><a name="l02565"></a><span class="lineno"> 2565</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a83ca447892f460dabaa2f87d3dc3db61">m_PadFront</a> = pooling3dDesc->padFront();</div> +<div class="line"><a name="l02566"></a><span class="lineno"> 2566</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a11d5c25face9b54e90f79ee8bdc1d0fb">m_PadBack</a> = pooling3dDesc->padBack();</div> +<div class="line"><a name="l02567"></a><span class="lineno"> 2567</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = pooling3dDesc->strideX();</div> +<div class="line"><a name="l02568"></a><span class="lineno"> 2568</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = pooling3dDesc->strideY();</div> +<div class="line"><a name="l02569"></a><span class="lineno"> 2569</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a5164336f6a1b15be0d434a6bbf7289da">m_StrideZ</a> = pooling3dDesc->strideZ();</div> +<div class="line"><a name="l02570"></a><span class="lineno"> 2570</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = pooling3dDesc->poolWidth();</div> +<div class="line"><a name="l02571"></a><span class="lineno"> 2571</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = pooling3dDesc->poolHeight();</div> +<div class="line"><a name="l02572"></a><span class="lineno"> 2572</span>  desc.<a class="code" href="structarmnn_1_1_pooling3d_descriptor.html#acc978b36fd5d949bc781d7638e6e08b9">m_PoolDepth</a> = pooling3dDesc->poolDepth();</div> +<div class="line"><a name="l02573"></a><span class="lineno"> 2573</span>  </div> +<div class="line"><a name="l02574"></a><span class="lineno"> 2574</span>  <span class="keywordflow">return</span> desc;</div> +<div class="line"><a name="l02575"></a><span class="lineno"> 2575</span> }</div> +<div class="line"><a name="l02576"></a><span class="lineno"> 2576</span>  </div> +<div class="line"><a name="l02577"></a><span class="lineno"> 2577</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePooling2d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02578"></a><span class="lineno"> 2578</span> {</div> +<div class="line"><a name="l02579"></a><span class="lineno"> 2579</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02580"></a><span class="lineno"> 2580</span>  </div> +<div class="line"><a name="l02581"></a><span class="lineno"> 2581</span>  <span class="keyword">auto</span> pooling2dDes = graph->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->descriptor();</div> +<div class="line"><a name="l02582"></a><span class="lineno"> 2582</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02583"></a><span class="lineno"> 2583</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02584"></a><span class="lineno"> 2584</span>  </div> +<div class="line"><a name="l02585"></a><span class="lineno"> 2585</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02586"></a><span class="lineno"> 2586</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02587"></a><span class="lineno"> 2587</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02588"></a><span class="lineno"> 2588</span>  </div> +<div class="line"><a name="l02589"></a><span class="lineno"> 2589</span>  <span class="keyword">auto</span> pooling2dDescriptor = GetPooling2dDescriptor(pooling2dDes, layerIndex);</div> +<div class="line"><a name="l02590"></a><span class="lineno"> 2590</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02591"></a><span class="lineno"> 2591</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPooling2dLayer(pooling2dDescriptor, layerName.c_str());</div> +<div class="line"><a name="l02592"></a><span class="lineno"> 2592</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l02593"></a><span class="lineno"> 2593</span>  </div> +<div class="line"><a name="l02594"></a><span class="lineno"> 2594</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02595"></a><span class="lineno"> 2595</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02596"></a><span class="lineno"> 2596</span> }</div> +<div class="line"><a name="l02597"></a><span class="lineno"> 2597</span>  </div> +<div class="line"><a name="l02598"></a><span class="lineno"> 2598</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePooling3d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02599"></a><span class="lineno"> 2599</span> {</div> +<div class="line"><a name="l02600"></a><span class="lineno"> 2600</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02601"></a><span class="lineno"> 2601</span>  </div> +<div class="line"><a name="l02602"></a><span class="lineno"> 2602</span>  <span class="keyword">auto</span> pooling3dDes = graph->layers()->Get(layerIndex)->layer_as_Pooling3dLayer()->descriptor();</div> +<div class="line"><a name="l02603"></a><span class="lineno"> 2603</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02604"></a><span class="lineno"> 2604</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02605"></a><span class="lineno"> 2605</span>  </div> +<div class="line"><a name="l02606"></a><span class="lineno"> 2606</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02607"></a><span class="lineno"> 2607</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02608"></a><span class="lineno"> 2608</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02609"></a><span class="lineno"> 2609</span>  </div> +<div class="line"><a name="l02610"></a><span class="lineno"> 2610</span>  <span class="keyword">auto</span> pooling3dDescriptor = GetPooling3dDescriptor(pooling3dDes, layerIndex);</div> +<div class="line"><a name="l02611"></a><span class="lineno"> 2611</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02612"></a><span class="lineno"> 2612</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPooling3dLayer(pooling3dDescriptor, layerName.c_str());</div> +<div class="line"><a name="l02613"></a><span class="lineno"> 2613</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l02614"></a><span class="lineno"> 2614</span>  </div> +<div class="line"><a name="l02615"></a><span class="lineno"> 2615</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02616"></a><span class="lineno"> 2616</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02617"></a><span class="lineno"> 2617</span> }</div> +<div class="line"><a name="l02618"></a><span class="lineno"> 2618</span>  </div> +<div class="line"><a name="l02619"></a><span class="lineno"> 2619</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseQuantize(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02620"></a><span class="lineno"> 2620</span> {</div> +<div class="line"><a name="l02621"></a><span class="lineno"> 2621</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02622"></a><span class="lineno"> 2622</span>  </div> +<div class="line"><a name="l02623"></a><span class="lineno"> 2623</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02624"></a><span class="lineno"> 2624</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02625"></a><span class="lineno"> 2625</span>  </div> +<div class="line"><a name="l02626"></a><span class="lineno"> 2626</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02627"></a><span class="lineno"> 2627</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02628"></a><span class="lineno"> 2628</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> <div class="line"><a name="l02629"></a><span class="lineno"> 2629</span>  </div> -<div class="line"><a name="l02630"></a><span class="lineno"> 2630</span>  <span class="keyword">auto</span> targetNumElements =</div> -<div class="line"><a name="l02631"></a><span class="lineno"> 2631</span>  armnn::numeric_cast<unsigned int>(</div> -<div class="line"><a name="l02632"></a><span class="lineno"> 2632</span>  std::accumulate(targetDimsIn.begin(), targetDimsIn.end(), -1, std::multiplies<int32_t>()));</div> +<div class="line"><a name="l02630"></a><span class="lineno"> 2630</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02631"></a><span class="lineno"> 2631</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddQuantizeLayer(layerName.c_str());</div> +<div class="line"><a name="l02632"></a><span class="lineno"> 2632</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> <div class="line"><a name="l02633"></a><span class="lineno"> 2633</span>  </div> -<div class="line"><a name="l02634"></a><span class="lineno"> 2634</span>  <span class="keyword">auto</span> stretchIndex = <span class="keyword">static_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(std::distance(targetDimsIn.begin(), stretchDim));</div> -<div class="line"><a name="l02635"></a><span class="lineno"> 2635</span>  <span class="keywordflow">if</span> (targetNumElements == 0)</div> -<div class="line"><a name="l02636"></a><span class="lineno"> 2636</span>  {</div> -<div class="line"><a name="l02637"></a><span class="lineno"> 2637</span>  <span class="keywordflow">if</span> (inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>() == 0)</div> -<div class="line"><a name="l02638"></a><span class="lineno"> 2638</span>  {</div> -<div class="line"><a name="l02639"></a><span class="lineno"> 2639</span>  outputDims[stretchIndex] = 0;</div> -<div class="line"><a name="l02640"></a><span class="lineno"> 2640</span>  }</div> -<div class="line"><a name="l02641"></a><span class="lineno"> 2641</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l02642"></a><span class="lineno"> 2642</span>  {</div> -<div class="line"><a name="l02643"></a><span class="lineno"> 2643</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(</div> -<div class="line"><a name="l02644"></a><span class="lineno"> 2644</span>  fmt::format(<span class="stringliteral">"Input to reshape is a tensor with elements, but the requested shape has 0. {}"</span>,</div> -<div class="line"><a name="l02645"></a><span class="lineno"> 2645</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l02646"></a><span class="lineno"> 2646</span>  }</div> -<div class="line"><a name="l02647"></a><span class="lineno"> 2647</span>  }</div> -<div class="line"><a name="l02648"></a><span class="lineno"> 2648</span>  <span class="keywordflow">else</span></div> -<div class="line"><a name="l02649"></a><span class="lineno"> 2649</span>  {</div> -<div class="line"><a name="l02650"></a><span class="lineno"> 2650</span>  outputDims[stretchIndex] = inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>() / targetNumElements;</div> -<div class="line"><a name="l02651"></a><span class="lineno"> 2651</span>  }</div> -<div class="line"><a name="l02652"></a><span class="lineno"> 2652</span>  }</div> -<div class="line"><a name="l02653"></a><span class="lineno"> 2653</span>  </div> -<div class="line"><a name="l02654"></a><span class="lineno"> 2654</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape = <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>(<span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(outputDims.size()), outputDims.data());</div> +<div class="line"><a name="l02634"></a><span class="lineno"> 2634</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02635"></a><span class="lineno"> 2635</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02636"></a><span class="lineno"> 2636</span> }</div> +<div class="line"><a name="l02637"></a><span class="lineno"> 2637</span>  </div> +<div class="line"><a name="l02638"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a8752c2b994619ae67201a297c2c76be2"> 2638</a></span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a8752c2b994619ae67201a297c2c76be2">IDeserializer::DeserializerImpl::OutputShapeOfReshape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& inputTensorInfo,</div> +<div class="line"><a name="l02639"></a><span class="lineno"> 2639</span>  <span class="keyword">const</span> std::vector<uint32_t>& targetDimsIn)</div> +<div class="line"><a name="l02640"></a><span class="lineno"> 2640</span> {</div> +<div class="line"><a name="l02641"></a><span class="lineno"> 2641</span>  std::vector<unsigned int> outputDims(targetDimsIn.begin(), targetDimsIn.end());</div> +<div class="line"><a name="l02642"></a><span class="lineno"> 2642</span>  <span class="keyword">const</span> <span class="keyword">auto</span> stretchDim = std::find(targetDimsIn.begin(), targetDimsIn.end(), -1);</div> +<div class="line"><a name="l02643"></a><span class="lineno"> 2643</span>  </div> +<div class="line"><a name="l02644"></a><span class="lineno"> 2644</span>  <span class="keywordflow">if</span> (stretchDim != targetDimsIn.end())</div> +<div class="line"><a name="l02645"></a><span class="lineno"> 2645</span>  {</div> +<div class="line"><a name="l02646"></a><span class="lineno"> 2646</span>  <span class="keywordflow">if</span> (std::find(std::next(stretchDim), targetDimsIn.end(), -1) != targetDimsIn.end())</div> +<div class="line"><a name="l02647"></a><span class="lineno"> 2647</span>  {</div> +<div class="line"><a name="l02648"></a><span class="lineno"> 2648</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"At most one component of shape can be -1 {}"</span>,</div> +<div class="line"><a name="l02649"></a><span class="lineno"> 2649</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l02650"></a><span class="lineno"> 2650</span>  }</div> +<div class="line"><a name="l02651"></a><span class="lineno"> 2651</span>  </div> +<div class="line"><a name="l02652"></a><span class="lineno"> 2652</span>  <span class="keyword">auto</span> targetNumElements =</div> +<div class="line"><a name="l02653"></a><span class="lineno"> 2653</span>  armnn::numeric_cast<unsigned int>(</div> +<div class="line"><a name="l02654"></a><span class="lineno"> 2654</span>  std::accumulate(targetDimsIn.begin(), targetDimsIn.end(), -1, std::multiplies<int32_t>()));</div> <div class="line"><a name="l02655"></a><span class="lineno"> 2655</span>  </div> -<div class="line"><a name="l02656"></a><span class="lineno"> 2656</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> reshapeInfo = inputTensorInfo;</div> -<div class="line"><a name="l02657"></a><span class="lineno"> 2657</span>  reshapeInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(outputShape);</div> -<div class="line"><a name="l02658"></a><span class="lineno"> 2658</span>  </div> -<div class="line"><a name="l02659"></a><span class="lineno"> 2659</span>  <span class="keywordflow">return</span> reshapeInfo;</div> -<div class="line"><a name="l02660"></a><span class="lineno"> 2660</span> }</div> -<div class="line"><a name="l02661"></a><span class="lineno"> 2661</span>  </div> -<div class="line"><a name="l02662"></a><span class="lineno"> 2662</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseRank(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02663"></a><span class="lineno"> 2663</span> {</div> -<div class="line"><a name="l02664"></a><span class="lineno"> 2664</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02665"></a><span class="lineno"> 2665</span>  </div> -<div class="line"><a name="l02666"></a><span class="lineno"> 2666</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02667"></a><span class="lineno"> 2667</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02668"></a><span class="lineno"> 2668</span>  </div> -<div class="line"><a name="l02669"></a><span class="lineno"> 2669</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02670"></a><span class="lineno"> 2670</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02671"></a><span class="lineno"> 2671</span>  </div> -<div class="line"><a name="l02672"></a><span class="lineno"> 2672</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02673"></a><span class="lineno"> 2673</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddRankLayer( layerName.c_str());</div> -<div class="line"><a name="l02674"></a><span class="lineno"> 2674</span>  </div> -<div class="line"><a name="l02675"></a><span class="lineno"> 2675</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02676"></a><span class="lineno"> 2676</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02656"></a><span class="lineno"> 2656</span>  <span class="keyword">auto</span> stretchIndex = <span class="keyword">static_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(std::distance(targetDimsIn.begin(), stretchDim));</div> +<div class="line"><a name="l02657"></a><span class="lineno"> 2657</span>  <span class="keywordflow">if</span> (targetNumElements == 0)</div> +<div class="line"><a name="l02658"></a><span class="lineno"> 2658</span>  {</div> +<div class="line"><a name="l02659"></a><span class="lineno"> 2659</span>  <span class="keywordflow">if</span> (inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>() == 0)</div> +<div class="line"><a name="l02660"></a><span class="lineno"> 2660</span>  {</div> +<div class="line"><a name="l02661"></a><span class="lineno"> 2661</span>  outputDims[stretchIndex] = 0;</div> +<div class="line"><a name="l02662"></a><span class="lineno"> 2662</span>  }</div> +<div class="line"><a name="l02663"></a><span class="lineno"> 2663</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l02664"></a><span class="lineno"> 2664</span>  {</div> +<div class="line"><a name="l02665"></a><span class="lineno"> 2665</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(</div> +<div class="line"><a name="l02666"></a><span class="lineno"> 2666</span>  fmt::format(<span class="stringliteral">"Input to reshape is a tensor with elements, but the requested shape has 0. {}"</span>,</div> +<div class="line"><a name="l02667"></a><span class="lineno"> 2667</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l02668"></a><span class="lineno"> 2668</span>  }</div> +<div class="line"><a name="l02669"></a><span class="lineno"> 2669</span>  }</div> +<div class="line"><a name="l02670"></a><span class="lineno"> 2670</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l02671"></a><span class="lineno"> 2671</span>  {</div> +<div class="line"><a name="l02672"></a><span class="lineno"> 2672</span>  outputDims[stretchIndex] = inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>() / targetNumElements;</div> +<div class="line"><a name="l02673"></a><span class="lineno"> 2673</span>  }</div> +<div class="line"><a name="l02674"></a><span class="lineno"> 2674</span>  }</div> +<div class="line"><a name="l02675"></a><span class="lineno"> 2675</span>  </div> +<div class="line"><a name="l02676"></a><span class="lineno"> 2676</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape = <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>(<span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(outputDims.size()), outputDims.data());</div> <div class="line"><a name="l02677"></a><span class="lineno"> 2677</span>  </div> -<div class="line"><a name="l02678"></a><span class="lineno"> 2678</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02679"></a><span class="lineno"> 2679</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02680"></a><span class="lineno"> 2680</span> }</div> -<div class="line"><a name="l02681"></a><span class="lineno"> 2681</span>  </div> -<div class="line"><a name="l02682"></a><span class="lineno"> 2682</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseReduce(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02683"></a><span class="lineno"> 2683</span> {</div> -<div class="line"><a name="l02684"></a><span class="lineno"> 2684</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02685"></a><span class="lineno"> 2685</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l02686"></a><span class="lineno"> 2686</span>  </div> -<div class="line"><a name="l02687"></a><span class="lineno"> 2687</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02688"></a><span class="lineno"> 2688</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02689"></a><span class="lineno"> 2689</span>  </div> -<div class="line"><a name="l02690"></a><span class="lineno"> 2690</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02691"></a><span class="lineno"> 2691</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02692"></a><span class="lineno"> 2692</span>  </div> -<div class="line"><a name="l02693"></a><span class="lineno"> 2693</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ReduceLayer();</div> -<div class="line"><a name="l02694"></a><span class="lineno"> 2694</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> -<div class="line"><a name="l02695"></a><span class="lineno"> 2695</span>  <span class="keyword">auto</span> flatBufferAxis = fbDescriptor->axis();</div> +<div class="line"><a name="l02678"></a><span class="lineno"> 2678</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> reshapeInfo = inputTensorInfo;</div> +<div class="line"><a name="l02679"></a><span class="lineno"> 2679</span>  reshapeInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(outputShape);</div> +<div class="line"><a name="l02680"></a><span class="lineno"> 2680</span>  </div> +<div class="line"><a name="l02681"></a><span class="lineno"> 2681</span>  <span class="keywordflow">return</span> reshapeInfo;</div> +<div class="line"><a name="l02682"></a><span class="lineno"> 2682</span> }</div> +<div class="line"><a name="l02683"></a><span class="lineno"> 2683</span>  </div> +<div class="line"><a name="l02684"></a><span class="lineno"> 2684</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseRank(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02685"></a><span class="lineno"> 2685</span> {</div> +<div class="line"><a name="l02686"></a><span class="lineno"> 2686</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02687"></a><span class="lineno"> 2687</span>  </div> +<div class="line"><a name="l02688"></a><span class="lineno"> 2688</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02689"></a><span class="lineno"> 2689</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02690"></a><span class="lineno"> 2690</span>  </div> +<div class="line"><a name="l02691"></a><span class="lineno"> 2691</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02692"></a><span class="lineno"> 2692</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02693"></a><span class="lineno"> 2693</span>  </div> +<div class="line"><a name="l02694"></a><span class="lineno"> 2694</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02695"></a><span class="lineno"> 2695</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddRankLayer( layerName.c_str());</div> <div class="line"><a name="l02696"></a><span class="lineno"> 2696</span>  </div> -<div class="line"><a name="l02697"></a><span class="lineno"> 2697</span>  <a class="code" href="structarmnn_1_1_reduce_descriptor.html">armnn::ReduceDescriptor</a> descriptor;</div> -<div class="line"><a name="l02698"></a><span class="lineno"> 2698</span>  descriptor.<a class="code" href="structarmnn_1_1_reduce_descriptor.html#a28e0548abfc4e79c48f29a3d11a062e9">m_KeepDims</a> = fbDescriptor->keepDims();</div> -<div class="line"><a name="l02699"></a><span class="lineno"> 2699</span>  descriptor.<a class="code" href="structarmnn_1_1_reduce_descriptor.html#aa1c6fc8c96404252f1072632fc5acb59">m_vAxis</a> = std::vector<unsigned int>(flatBufferAxis->begin(), flatBufferAxis->end());</div> -<div class="line"><a name="l02700"></a><span class="lineno"> 2700</span>  descriptor.<a class="code" href="structarmnn_1_1_reduce_descriptor.html#aa57c67b1da0011b1abb30170146e870f">m_ReduceOperation</a> = <a class="code" href="namespacearmnn_deserializer.html#afa869143574c5885c6ad75f5a6f0333d">ToReduceOperation</a>(fbDescriptor->reduceOperation());</div> -<div class="line"><a name="l02701"></a><span class="lineno"> 2701</span>  </div> -<div class="line"><a name="l02702"></a><span class="lineno"> 2702</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02703"></a><span class="lineno"> 2703</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddReduceLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02704"></a><span class="lineno"> 2704</span>  </div> -<div class="line"><a name="l02705"></a><span class="lineno"> 2705</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02706"></a><span class="lineno"> 2706</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02707"></a><span class="lineno"> 2707</span>  </div> -<div class="line"><a name="l02708"></a><span class="lineno"> 2708</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02709"></a><span class="lineno"> 2709</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02710"></a><span class="lineno"> 2710</span> }</div> +<div class="line"><a name="l02697"></a><span class="lineno"> 2697</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02698"></a><span class="lineno"> 2698</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02699"></a><span class="lineno"> 2699</span>  </div> +<div class="line"><a name="l02700"></a><span class="lineno"> 2700</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02701"></a><span class="lineno"> 2701</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02702"></a><span class="lineno"> 2702</span> }</div> +<div class="line"><a name="l02703"></a><span class="lineno"> 2703</span>  </div> +<div class="line"><a name="l02704"></a><span class="lineno"> 2704</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseReduce(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02705"></a><span class="lineno"> 2705</span> {</div> +<div class="line"><a name="l02706"></a><span class="lineno"> 2706</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02707"></a><span class="lineno"> 2707</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l02708"></a><span class="lineno"> 2708</span>  </div> +<div class="line"><a name="l02709"></a><span class="lineno"> 2709</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02710"></a><span class="lineno"> 2710</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> <div class="line"><a name="l02711"></a><span class="lineno"> 2711</span>  </div> -<div class="line"><a name="l02712"></a><span class="lineno"> 2712</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseReshape(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02713"></a><span class="lineno"> 2713</span> {</div> -<div class="line"><a name="l02714"></a><span class="lineno"> 2714</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02715"></a><span class="lineno"> 2715</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02716"></a><span class="lineno"> 2716</span>  </div> -<div class="line"><a name="l02717"></a><span class="lineno"> 2717</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02718"></a><span class="lineno"> 2718</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02719"></a><span class="lineno"> 2719</span>  </div> -<div class="line"><a name="l02720"></a><span class="lineno"> 2720</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(inputs[0]);</div> -<div class="line"><a name="l02721"></a><span class="lineno"> 2721</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> actualOutputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02722"></a><span class="lineno"> 2722</span>  </div> -<div class="line"><a name="l02723"></a><span class="lineno"> 2723</span>  <span class="keyword">const</span> <span class="keyword">auto</span> targetDims = graph->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->descriptor()->targetShape();</div> -<div class="line"><a name="l02724"></a><span class="lineno"> 2724</span>  std::vector<uint32_t> outputDims(targetDims->begin(), targetDims->begin() + targetDims->size());</div> -<div class="line"><a name="l02725"></a><span class="lineno"> 2725</span>  </div> -<div class="line"><a name="l02726"></a><span class="lineno"> 2726</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> reshapeOutputTensorInfo = <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a8752c2b994619ae67201a297c2c76be2">DeserializerImpl::OutputShapeOfReshape</a>(inputTensorInfo, outputDims);</div> -<div class="line"><a name="l02727"></a><span class="lineno"> 2727</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a>& reshapeOutputTensorShape = reshapeOutputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> -<div class="line"><a name="l02728"></a><span class="lineno"> 2728</span>  </div> -<div class="line"><a name="l02729"></a><span class="lineno"> 2729</span>  <span class="keyword">const</span> std::vector<uint32_t> expectedDims(outputs[0]->dimensions()->begin(),</div> -<div class="line"><a name="l02730"></a><span class="lineno"> 2730</span>  outputs[0]->dimensions()->begin() + outputs[0]->dimensions()->size());</div> -<div class="line"><a name="l02731"></a><span class="lineno"> 2731</span>  </div> -<div class="line"><a name="l02732"></a><span class="lineno"> 2732</span>  <span class="keywordflow">if</span> (inputs.size() > 1 && !<a class="code" href="namespacearmnn_deserializer.html#a97b50f22cd99f0e09e6e48d20a35f6b2">CheckShape</a>(reshapeOutputTensorShape, expectedDims))</div> -<div class="line"><a name="l02733"></a><span class="lineno"> 2733</span>  {</div> -<div class="line"><a name="l02734"></a><span class="lineno"> 2734</span>  std::stringstream ss;</div> -<div class="line"><a name="l02735"></a><span class="lineno"> 2735</span>  ss << <span class="stringliteral">"New shape defined in reshape parameters "</span></div> -<div class="line"><a name="l02736"></a><span class="lineno"> 2736</span>  << reshapeOutputTensorShape</div> -<div class="line"><a name="l02737"></a><span class="lineno"> 2737</span>  << <span class="stringliteral">" does not equal output shape "</span></div> -<div class="line"><a name="l02738"></a><span class="lineno"> 2738</span>  << actualOutputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()</div> -<div class="line"><a name="l02739"></a><span class="lineno"> 2739</span>  << <span class="stringliteral">": "</span></div> -<div class="line"><a name="l02740"></a><span class="lineno"> 2740</span>  << <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString();</div> -<div class="line"><a name="l02741"></a><span class="lineno"> 2741</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(ss.str());</div> -<div class="line"><a name="l02742"></a><span class="lineno"> 2742</span>  }</div> -<div class="line"><a name="l02743"></a><span class="lineno"> 2743</span>  </div> -<div class="line"><a name="l02744"></a><span class="lineno"> 2744</span>  <a class="code" href="structarmnn_1_1_reshape_descriptor.html">armnn::ReshapeDescriptor</a> reshapeDesc;</div> -<div class="line"><a name="l02745"></a><span class="lineno"> 2745</span>  reshapeDesc.<a class="code" href="structarmnn_1_1_reshape_descriptor.html#a1178f4dafdda81f59c15145ec327f7d9">m_TargetShape</a> = reshapeOutputTensorShape;</div> -<div class="line"><a name="l02746"></a><span class="lineno"> 2746</span>  </div> -<div class="line"><a name="l02747"></a><span class="lineno"> 2747</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02748"></a><span class="lineno"> 2748</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddReshapeLayer(reshapeDesc, layerName.c_str());</div> -<div class="line"><a name="l02749"></a><span class="lineno"> 2749</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(reshapeOutputTensorInfo);</div> +<div class="line"><a name="l02712"></a><span class="lineno"> 2712</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02713"></a><span class="lineno"> 2713</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02714"></a><span class="lineno"> 2714</span>  </div> +<div class="line"><a name="l02715"></a><span class="lineno"> 2715</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ReduceLayer();</div> +<div class="line"><a name="l02716"></a><span class="lineno"> 2716</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> +<div class="line"><a name="l02717"></a><span class="lineno"> 2717</span>  <span class="keyword">auto</span> flatBufferAxis = fbDescriptor->axis();</div> +<div class="line"><a name="l02718"></a><span class="lineno"> 2718</span>  </div> +<div class="line"><a name="l02719"></a><span class="lineno"> 2719</span>  <a class="code" href="structarmnn_1_1_reduce_descriptor.html">armnn::ReduceDescriptor</a> descriptor;</div> +<div class="line"><a name="l02720"></a><span class="lineno"> 2720</span>  descriptor.<a class="code" href="structarmnn_1_1_reduce_descriptor.html#a28e0548abfc4e79c48f29a3d11a062e9">m_KeepDims</a> = fbDescriptor->keepDims();</div> +<div class="line"><a name="l02721"></a><span class="lineno"> 2721</span>  descriptor.<a class="code" href="structarmnn_1_1_reduce_descriptor.html#aa1c6fc8c96404252f1072632fc5acb59">m_vAxis</a> = std::vector<unsigned int>(flatBufferAxis->begin(), flatBufferAxis->end());</div> +<div class="line"><a name="l02722"></a><span class="lineno"> 2722</span>  descriptor.<a class="code" href="structarmnn_1_1_reduce_descriptor.html#aa57c67b1da0011b1abb30170146e870f">m_ReduceOperation</a> = <a class="code" href="namespacearmnn_deserializer.html#afa869143574c5885c6ad75f5a6f0333d">ToReduceOperation</a>(fbDescriptor->reduceOperation());</div> +<div class="line"><a name="l02723"></a><span class="lineno"> 2723</span>  </div> +<div class="line"><a name="l02724"></a><span class="lineno"> 2724</span>  <span class="keyword">const</span> std::string& layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02725"></a><span class="lineno"> 2725</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddReduceLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02726"></a><span class="lineno"> 2726</span>  </div> +<div class="line"><a name="l02727"></a><span class="lineno"> 2727</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02728"></a><span class="lineno"> 2728</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02729"></a><span class="lineno"> 2729</span>  </div> +<div class="line"><a name="l02730"></a><span class="lineno"> 2730</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02731"></a><span class="lineno"> 2731</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02732"></a><span class="lineno"> 2732</span> }</div> +<div class="line"><a name="l02733"></a><span class="lineno"> 2733</span>  </div> +<div class="line"><a name="l02734"></a><span class="lineno"> 2734</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseReshape(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02735"></a><span class="lineno"> 2735</span> {</div> +<div class="line"><a name="l02736"></a><span class="lineno"> 2736</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02737"></a><span class="lineno"> 2737</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02738"></a><span class="lineno"> 2738</span>  </div> +<div class="line"><a name="l02739"></a><span class="lineno"> 2739</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02740"></a><span class="lineno"> 2740</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02741"></a><span class="lineno"> 2741</span>  </div> +<div class="line"><a name="l02742"></a><span class="lineno"> 2742</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(inputs[0]);</div> +<div class="line"><a name="l02743"></a><span class="lineno"> 2743</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> actualOutputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02744"></a><span class="lineno"> 2744</span>  </div> +<div class="line"><a name="l02745"></a><span class="lineno"> 2745</span>  <span class="keyword">const</span> <span class="keyword">auto</span> targetDims = graph->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->descriptor()->targetShape();</div> +<div class="line"><a name="l02746"></a><span class="lineno"> 2746</span>  std::vector<uint32_t> outputDims(targetDims->begin(), targetDims->begin() + targetDims->size());</div> +<div class="line"><a name="l02747"></a><span class="lineno"> 2747</span>  </div> +<div class="line"><a name="l02748"></a><span class="lineno"> 2748</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> reshapeOutputTensorInfo = <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a8752c2b994619ae67201a297c2c76be2">DeserializerImpl::OutputShapeOfReshape</a>(inputTensorInfo, outputDims);</div> +<div class="line"><a name="l02749"></a><span class="lineno"> 2749</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a>& reshapeOutputTensorShape = reshapeOutputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> <div class="line"><a name="l02750"></a><span class="lineno"> 2750</span>  </div> -<div class="line"><a name="l02751"></a><span class="lineno"> 2751</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02752"></a><span class="lineno"> 2752</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02753"></a><span class="lineno"> 2753</span> }</div> -<div class="line"><a name="l02754"></a><span class="lineno"> 2754</span>  </div> -<div class="line"><a name="l02755"></a><span class="lineno"> 2755</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseResize(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02756"></a><span class="lineno"> 2756</span> {</div> -<div class="line"><a name="l02757"></a><span class="lineno"> 2757</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02758"></a><span class="lineno"> 2758</span>  </div> -<div class="line"><a name="l02759"></a><span class="lineno"> 2759</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02760"></a><span class="lineno"> 2760</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02761"></a><span class="lineno"> 2761</span>  </div> -<div class="line"><a name="l02762"></a><span class="lineno"> 2762</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02763"></a><span class="lineno"> 2763</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02764"></a><span class="lineno"> 2764</span>  </div> -<div class="line"><a name="l02765"></a><span class="lineno"> 2765</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_ResizeLayer()->descriptor();</div> -<div class="line"><a name="l02766"></a><span class="lineno"> 2766</span>  </div> -<div class="line"><a name="l02767"></a><span class="lineno"> 2767</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.html">armnn::ResizeDescriptor</a> descriptor;</div> -<div class="line"><a name="l02768"></a><span class="lineno"> 2768</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = flatBufferDescriptor->targetWidth();</div> -<div class="line"><a name="l02769"></a><span class="lineno"> 2769</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = flatBufferDescriptor->targetHeight();</div> -<div class="line"><a name="l02770"></a><span class="lineno"> 2770</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a869254cb56968986a78a79e1d6d4a86b">m_Method</a> = <a class="code" href="namespacearmnn_deserializer.html#a8b51e137fab21d758b965c6c6e3b02f3">ToResizeMethod</a>(flatBufferDescriptor->method());</div> -<div class="line"><a name="l02771"></a><span class="lineno"> 2771</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> -<div class="line"><a name="l02772"></a><span class="lineno"> 2772</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#ae1a4b3b6c60552509b89747cebb900a2">m_AlignCorners</a> = flatBufferDescriptor->alignCorners();</div> -<div class="line"><a name="l02773"></a><span class="lineno"> 2773</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a4022d5107338aaf5eb7abebf78a1360b">m_HalfPixelCenters</a> = flatBufferDescriptor->halfPixelCenters();</div> -<div class="line"><a name="l02774"></a><span class="lineno"> 2774</span>  </div> -<div class="line"><a name="l02775"></a><span class="lineno"> 2775</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02776"></a><span class="lineno"> 2776</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddResizeLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02777"></a><span class="lineno"> 2777</span>  </div> -<div class="line"><a name="l02778"></a><span class="lineno"> 2778</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02779"></a><span class="lineno"> 2779</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02751"></a><span class="lineno"> 2751</span>  <span class="keyword">const</span> std::vector<uint32_t> expectedDims(outputs[0]->dimensions()->begin(),</div> +<div class="line"><a name="l02752"></a><span class="lineno"> 2752</span>  outputs[0]->dimensions()->begin() + outputs[0]->dimensions()->size());</div> +<div class="line"><a name="l02753"></a><span class="lineno"> 2753</span>  </div> +<div class="line"><a name="l02754"></a><span class="lineno"> 2754</span>  <span class="keywordflow">if</span> (inputs.size() > 1 && !<a class="code" href="namespacearmnn_deserializer.html#a97b50f22cd99f0e09e6e48d20a35f6b2">CheckShape</a>(reshapeOutputTensorShape, expectedDims))</div> +<div class="line"><a name="l02755"></a><span class="lineno"> 2755</span>  {</div> +<div class="line"><a name="l02756"></a><span class="lineno"> 2756</span>  std::stringstream ss;</div> +<div class="line"><a name="l02757"></a><span class="lineno"> 2757</span>  ss << <span class="stringliteral">"New shape defined in reshape parameters "</span></div> +<div class="line"><a name="l02758"></a><span class="lineno"> 2758</span>  << reshapeOutputTensorShape</div> +<div class="line"><a name="l02759"></a><span class="lineno"> 2759</span>  << <span class="stringliteral">" does not equal output shape "</span></div> +<div class="line"><a name="l02760"></a><span class="lineno"> 2760</span>  << actualOutputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()</div> +<div class="line"><a name="l02761"></a><span class="lineno"> 2761</span>  << <span class="stringliteral">": "</span></div> +<div class="line"><a name="l02762"></a><span class="lineno"> 2762</span>  << <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString();</div> +<div class="line"><a name="l02763"></a><span class="lineno"> 2763</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(ss.str());</div> +<div class="line"><a name="l02764"></a><span class="lineno"> 2764</span>  }</div> +<div class="line"><a name="l02765"></a><span class="lineno"> 2765</span>  </div> +<div class="line"><a name="l02766"></a><span class="lineno"> 2766</span>  <a class="code" href="structarmnn_1_1_reshape_descriptor.html">armnn::ReshapeDescriptor</a> reshapeDesc;</div> +<div class="line"><a name="l02767"></a><span class="lineno"> 2767</span>  reshapeDesc.<a class="code" href="structarmnn_1_1_reshape_descriptor.html#a1178f4dafdda81f59c15145ec327f7d9">m_TargetShape</a> = reshapeOutputTensorShape;</div> +<div class="line"><a name="l02768"></a><span class="lineno"> 2768</span>  </div> +<div class="line"><a name="l02769"></a><span class="lineno"> 2769</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02770"></a><span class="lineno"> 2770</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddReshapeLayer(reshapeDesc, layerName.c_str());</div> +<div class="line"><a name="l02771"></a><span class="lineno"> 2771</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(reshapeOutputTensorInfo);</div> +<div class="line"><a name="l02772"></a><span class="lineno"> 2772</span>  </div> +<div class="line"><a name="l02773"></a><span class="lineno"> 2773</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02774"></a><span class="lineno"> 2774</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02775"></a><span class="lineno"> 2775</span> }</div> +<div class="line"><a name="l02776"></a><span class="lineno"> 2776</span>  </div> +<div class="line"><a name="l02777"></a><span class="lineno"> 2777</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseResize(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02778"></a><span class="lineno"> 2778</span> {</div> +<div class="line"><a name="l02779"></a><span class="lineno"> 2779</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l02780"></a><span class="lineno"> 2780</span>  </div> -<div class="line"><a name="l02781"></a><span class="lineno"> 2781</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02782"></a><span class="lineno"> 2782</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02783"></a><span class="lineno"> 2783</span> }</div> -<div class="line"><a name="l02784"></a><span class="lineno"> 2784</span>  </div> -<div class="line"><a name="l02785"></a><span class="lineno"> 2785</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseReverseV2(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02786"></a><span class="lineno"> 2786</span> {</div> -<div class="line"><a name="l02787"></a><span class="lineno"> 2787</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02781"></a><span class="lineno"> 2781</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02782"></a><span class="lineno"> 2782</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02783"></a><span class="lineno"> 2783</span>  </div> +<div class="line"><a name="l02784"></a><span class="lineno"> 2784</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02785"></a><span class="lineno"> 2785</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02786"></a><span class="lineno"> 2786</span>  </div> +<div class="line"><a name="l02787"></a><span class="lineno"> 2787</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_ResizeLayer()->descriptor();</div> <div class="line"><a name="l02788"></a><span class="lineno"> 2788</span>  </div> -<div class="line"><a name="l02789"></a><span class="lineno"> 2789</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02790"></a><span class="lineno"> 2790</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l02791"></a><span class="lineno"> 2791</span>  </div> -<div class="line"><a name="l02792"></a><span class="lineno"> 2792</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02793"></a><span class="lineno"> 2793</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02794"></a><span class="lineno"> 2794</span>  </div> -<div class="line"><a name="l02795"></a><span class="lineno"> 2795</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02796"></a><span class="lineno"> 2796</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddReverseV2Layer(layerName.c_str());</div> -<div class="line"><a name="l02797"></a><span class="lineno"> 2797</span>  </div> -<div class="line"><a name="l02798"></a><span class="lineno"> 2798</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02799"></a><span class="lineno"> 2799</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02800"></a><span class="lineno"> 2800</span>  </div> -<div class="line"><a name="l02801"></a><span class="lineno"> 2801</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02802"></a><span class="lineno"> 2802</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02803"></a><span class="lineno"> 2803</span> }</div> -<div class="line"><a name="l02804"></a><span class="lineno"> 2804</span> <span class="comment"></span> </div> -<div class="line"><a name="l02805"></a><span class="lineno"> 2805</span> <span class="comment">/// @Note The ResizeBiliniar operation was deprecated and removed in favor of the Resize operation.</span></div> -<div class="line"><a name="l02806"></a><span class="lineno"> 2806</span> <span class="comment">/// This function is kept for backwards compatibility.</span></div> -<div class="line"><a name="l02807"></a><span class="lineno"> 2807</span> <span class="comment"></span><span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseResizeBilinear(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02789"></a><span class="lineno"> 2789</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.html">armnn::ResizeDescriptor</a> descriptor;</div> +<div class="line"><a name="l02790"></a><span class="lineno"> 2790</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = flatBufferDescriptor->targetWidth();</div> +<div class="line"><a name="l02791"></a><span class="lineno"> 2791</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = flatBufferDescriptor->targetHeight();</div> +<div class="line"><a name="l02792"></a><span class="lineno"> 2792</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a869254cb56968986a78a79e1d6d4a86b">m_Method</a> = <a class="code" href="namespacearmnn_deserializer.html#a8b51e137fab21d758b965c6c6e3b02f3">ToResizeMethod</a>(flatBufferDescriptor->method());</div> +<div class="line"><a name="l02793"></a><span class="lineno"> 2793</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> +<div class="line"><a name="l02794"></a><span class="lineno"> 2794</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#ae1a4b3b6c60552509b89747cebb900a2">m_AlignCorners</a> = flatBufferDescriptor->alignCorners();</div> +<div class="line"><a name="l02795"></a><span class="lineno"> 2795</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a4022d5107338aaf5eb7abebf78a1360b">m_HalfPixelCenters</a> = flatBufferDescriptor->halfPixelCenters();</div> +<div class="line"><a name="l02796"></a><span class="lineno"> 2796</span>  </div> +<div class="line"><a name="l02797"></a><span class="lineno"> 2797</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02798"></a><span class="lineno"> 2798</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddResizeLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02799"></a><span class="lineno"> 2799</span>  </div> +<div class="line"><a name="l02800"></a><span class="lineno"> 2800</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02801"></a><span class="lineno"> 2801</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02802"></a><span class="lineno"> 2802</span>  </div> +<div class="line"><a name="l02803"></a><span class="lineno"> 2803</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02804"></a><span class="lineno"> 2804</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02805"></a><span class="lineno"> 2805</span> }</div> +<div class="line"><a name="l02806"></a><span class="lineno"> 2806</span>  </div> +<div class="line"><a name="l02807"></a><span class="lineno"> 2807</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseReverseV2(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> <div class="line"><a name="l02808"></a><span class="lineno"> 2808</span> {</div> <div class="line"><a name="l02809"></a><span class="lineno"> 2809</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l02810"></a><span class="lineno"> 2810</span>  </div> <div class="line"><a name="l02811"></a><span class="lineno"> 2811</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02812"></a><span class="lineno"> 2812</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02812"></a><span class="lineno"> 2812</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> <div class="line"><a name="l02813"></a><span class="lineno"> 2813</span>  </div> <div class="line"><a name="l02814"></a><span class="lineno"> 2814</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> <div class="line"><a name="l02815"></a><span class="lineno"> 2815</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l02816"></a><span class="lineno"> 2816</span>  </div> -<div class="line"><a name="l02817"></a><span class="lineno"> 2817</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_ResizeBilinearLayer()->descriptor();</div> -<div class="line"><a name="l02818"></a><span class="lineno"> 2818</span>  </div> -<div class="line"><a name="l02819"></a><span class="lineno"> 2819</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.html">armnn::ResizeDescriptor</a> descriptor;</div> -<div class="line"><a name="l02820"></a><span class="lineno"> 2820</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = flatBufferDescriptor->targetWidth();</div> -<div class="line"><a name="l02821"></a><span class="lineno"> 2821</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = flatBufferDescriptor->targetHeight();</div> -<div class="line"><a name="l02822"></a><span class="lineno"> 2822</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a869254cb56968986a78a79e1d6d4a86b">m_Method</a> = <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a>;</div> -<div class="line"><a name="l02823"></a><span class="lineno"> 2823</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> -<div class="line"><a name="l02824"></a><span class="lineno"> 2824</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#ae1a4b3b6c60552509b89747cebb900a2">m_AlignCorners</a> = flatBufferDescriptor->alignCorners();</div> -<div class="line"><a name="l02825"></a><span class="lineno"> 2825</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a4022d5107338aaf5eb7abebf78a1360b">m_HalfPixelCenters</a> = flatBufferDescriptor->halfPixelCenters();</div> -<div class="line"><a name="l02826"></a><span class="lineno"> 2826</span>  </div> -<div class="line"><a name="l02827"></a><span class="lineno"> 2827</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02828"></a><span class="lineno"> 2828</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddResizeLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02829"></a><span class="lineno"> 2829</span>  </div> -<div class="line"><a name="l02830"></a><span class="lineno"> 2830</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02831"></a><span class="lineno"> 2831</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02817"></a><span class="lineno"> 2817</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02818"></a><span class="lineno"> 2818</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddReverseV2Layer(layerName.c_str());</div> +<div class="line"><a name="l02819"></a><span class="lineno"> 2819</span>  </div> +<div class="line"><a name="l02820"></a><span class="lineno"> 2820</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02821"></a><span class="lineno"> 2821</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02822"></a><span class="lineno"> 2822</span>  </div> +<div class="line"><a name="l02823"></a><span class="lineno"> 2823</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02824"></a><span class="lineno"> 2824</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02825"></a><span class="lineno"> 2825</span> }</div> +<div class="line"><a name="l02826"></a><span class="lineno"> 2826</span> <span class="comment"></span> </div> +<div class="line"><a name="l02827"></a><span class="lineno"> 2827</span> <span class="comment">/// @Note The ResizeBiliniar operation was deprecated and removed in favor of the Resize operation.</span></div> +<div class="line"><a name="l02828"></a><span class="lineno"> 2828</span> <span class="comment">/// This function is kept for backwards compatibility.</span></div> +<div class="line"><a name="l02829"></a><span class="lineno"> 2829</span> <span class="comment"></span><span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseResizeBilinear(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02830"></a><span class="lineno"> 2830</span> {</div> +<div class="line"><a name="l02831"></a><span class="lineno"> 2831</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l02832"></a><span class="lineno"> 2832</span>  </div> -<div class="line"><a name="l02833"></a><span class="lineno"> 2833</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02834"></a><span class="lineno"> 2834</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02835"></a><span class="lineno"> 2835</span> }</div> -<div class="line"><a name="l02836"></a><span class="lineno"> 2836</span>  </div> -<div class="line"><a name="l02837"></a><span class="lineno"> 2837</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseShape(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02838"></a><span class="lineno"> 2838</span> {</div> -<div class="line"><a name="l02839"></a><span class="lineno"> 2839</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02833"></a><span class="lineno"> 2833</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02834"></a><span class="lineno"> 2834</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02835"></a><span class="lineno"> 2835</span>  </div> +<div class="line"><a name="l02836"></a><span class="lineno"> 2836</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02837"></a><span class="lineno"> 2837</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02838"></a><span class="lineno"> 2838</span>  </div> +<div class="line"><a name="l02839"></a><span class="lineno"> 2839</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_ResizeBilinearLayer()->descriptor();</div> <div class="line"><a name="l02840"></a><span class="lineno"> 2840</span>  </div> -<div class="line"><a name="l02841"></a><span class="lineno"> 2841</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02842"></a><span class="lineno"> 2842</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02843"></a><span class="lineno"> 2843</span>  </div> -<div class="line"><a name="l02844"></a><span class="lineno"> 2844</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02845"></a><span class="lineno"> 2845</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02846"></a><span class="lineno"> 2846</span>  </div> -<div class="line"><a name="l02847"></a><span class="lineno"> 2847</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02848"></a><span class="lineno"> 2848</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddShapeLayer( layerName.c_str());</div> -<div class="line"><a name="l02849"></a><span class="lineno"> 2849</span>  </div> -<div class="line"><a name="l02850"></a><span class="lineno"> 2850</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02851"></a><span class="lineno"> 2851</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02852"></a><span class="lineno"> 2852</span>  </div> -<div class="line"><a name="l02853"></a><span class="lineno"> 2853</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02854"></a><span class="lineno"> 2854</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02855"></a><span class="lineno"> 2855</span> }</div> -<div class="line"><a name="l02856"></a><span class="lineno"> 2856</span>  </div> -<div class="line"><a name="l02857"></a><span class="lineno"> 2857</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSoftmax(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02858"></a><span class="lineno"> 2858</span> {</div> -<div class="line"><a name="l02859"></a><span class="lineno"> 2859</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02860"></a><span class="lineno"> 2860</span>  </div> -<div class="line"><a name="l02861"></a><span class="lineno"> 2861</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02862"></a><span class="lineno"> 2862</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02863"></a><span class="lineno"> 2863</span>  </div> -<div class="line"><a name="l02864"></a><span class="lineno"> 2864</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02865"></a><span class="lineno"> 2865</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02866"></a><span class="lineno"> 2866</span>  </div> -<div class="line"><a name="l02867"></a><span class="lineno"> 2867</span>  <a class="code" href="structarmnn_1_1_softmax_descriptor.html">armnn::SoftmaxDescriptor</a> descriptor;</div> -<div class="line"><a name="l02868"></a><span class="lineno"> 2868</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = graph->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->descriptor()->beta();</div> -<div class="line"><a name="l02869"></a><span class="lineno"> 2869</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = graph->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->descriptor()->axis();</div> -<div class="line"><a name="l02870"></a><span class="lineno"> 2870</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02841"></a><span class="lineno"> 2841</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.html">armnn::ResizeDescriptor</a> descriptor;</div> +<div class="line"><a name="l02842"></a><span class="lineno"> 2842</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = flatBufferDescriptor->targetWidth();</div> +<div class="line"><a name="l02843"></a><span class="lineno"> 2843</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = flatBufferDescriptor->targetHeight();</div> +<div class="line"><a name="l02844"></a><span class="lineno"> 2844</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a869254cb56968986a78a79e1d6d4a86b">m_Method</a> = <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a>;</div> +<div class="line"><a name="l02845"></a><span class="lineno"> 2845</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> +<div class="line"><a name="l02846"></a><span class="lineno"> 2846</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#ae1a4b3b6c60552509b89747cebb900a2">m_AlignCorners</a> = flatBufferDescriptor->alignCorners();</div> +<div class="line"><a name="l02847"></a><span class="lineno"> 2847</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a4022d5107338aaf5eb7abebf78a1360b">m_HalfPixelCenters</a> = flatBufferDescriptor->halfPixelCenters();</div> +<div class="line"><a name="l02848"></a><span class="lineno"> 2848</span>  </div> +<div class="line"><a name="l02849"></a><span class="lineno"> 2849</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02850"></a><span class="lineno"> 2850</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddResizeLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02851"></a><span class="lineno"> 2851</span>  </div> +<div class="line"><a name="l02852"></a><span class="lineno"> 2852</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02853"></a><span class="lineno"> 2853</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02854"></a><span class="lineno"> 2854</span>  </div> +<div class="line"><a name="l02855"></a><span class="lineno"> 2855</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02856"></a><span class="lineno"> 2856</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02857"></a><span class="lineno"> 2857</span> }</div> +<div class="line"><a name="l02858"></a><span class="lineno"> 2858</span>  </div> +<div class="line"><a name="l02859"></a><span class="lineno"> 2859</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseShape(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02860"></a><span class="lineno"> 2860</span> {</div> +<div class="line"><a name="l02861"></a><span class="lineno"> 2861</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02862"></a><span class="lineno"> 2862</span>  </div> +<div class="line"><a name="l02863"></a><span class="lineno"> 2863</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02864"></a><span class="lineno"> 2864</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02865"></a><span class="lineno"> 2865</span>  </div> +<div class="line"><a name="l02866"></a><span class="lineno"> 2866</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02867"></a><span class="lineno"> 2867</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02868"></a><span class="lineno"> 2868</span>  </div> +<div class="line"><a name="l02869"></a><span class="lineno"> 2869</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02870"></a><span class="lineno"> 2870</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddShapeLayer( layerName.c_str());</div> <div class="line"><a name="l02871"></a><span class="lineno"> 2871</span>  </div> -<div class="line"><a name="l02872"></a><span class="lineno"> 2872</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSoftmaxLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02873"></a><span class="lineno"> 2873</span>  </div> -<div class="line"><a name="l02874"></a><span class="lineno"> 2874</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02875"></a><span class="lineno"> 2875</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02876"></a><span class="lineno"> 2876</span>  </div> -<div class="line"><a name="l02877"></a><span class="lineno"> 2877</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02878"></a><span class="lineno"> 2878</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02879"></a><span class="lineno"> 2879</span> }</div> -<div class="line"><a name="l02880"></a><span class="lineno"> 2880</span>  </div> -<div class="line"><a name="l02881"></a><span class="lineno"> 2881</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSpaceToBatchNd(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02882"></a><span class="lineno"> 2882</span> {</div> -<div class="line"><a name="l02883"></a><span class="lineno"> 2883</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02884"></a><span class="lineno"> 2884</span>  </div> -<div class="line"><a name="l02885"></a><span class="lineno"> 2885</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02886"></a><span class="lineno"> 2886</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02887"></a><span class="lineno"> 2887</span>  </div> -<div class="line"><a name="l02888"></a><span class="lineno"> 2888</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02889"></a><span class="lineno"> 2889</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02890"></a><span class="lineno"> 2890</span>  </div> -<div class="line"><a name="l02891"></a><span class="lineno"> 2891</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->descriptor();</div> -<div class="line"><a name="l02892"></a><span class="lineno"> 2892</span>  <span class="keyword">auto</span> flatBufferPadList = flatBufferDescriptor->padList();</div> -<div class="line"><a name="l02893"></a><span class="lineno"> 2893</span>  <span class="keyword">auto</span> flatBufferBlockShape = flatBufferDescriptor->blockShape();</div> -<div class="line"><a name="l02894"></a><span class="lineno"> 2894</span>  </div> -<div class="line"><a name="l02895"></a><span class="lineno"> 2895</span>  <span class="keywordflow">if</span> (flatBufferPadList->size() % 2 != 0)</div> -<div class="line"><a name="l02896"></a><span class="lineno"> 2896</span>  {</div> -<div class="line"><a name="l02897"></a><span class="lineno"> 2897</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The size of the pad list must be divisible by 2 {}"</span>,</div> -<div class="line"><a name="l02898"></a><span class="lineno"> 2898</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l02899"></a><span class="lineno"> 2899</span>  }</div> -<div class="line"><a name="l02900"></a><span class="lineno"> 2900</span>  </div> -<div class="line"><a name="l02901"></a><span class="lineno"> 2901</span>  std::vector<std::pair<unsigned int, unsigned int>> padList;</div> -<div class="line"><a name="l02902"></a><span class="lineno"> 2902</span>  padList.reserve(flatBufferPadList->size() / 2);</div> -<div class="line"><a name="l02903"></a><span class="lineno"> 2903</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < flatBufferPadList->size() - 1; i += 2)</div> -<div class="line"><a name="l02904"></a><span class="lineno"> 2904</span>  {</div> -<div class="line"><a name="l02905"></a><span class="lineno"> 2905</span>  padList.emplace_back(flatBufferPadList->Get(i), flatBufferPadList->Get(i+1));</div> -<div class="line"><a name="l02906"></a><span class="lineno"> 2906</span>  }</div> -<div class="line"><a name="l02907"></a><span class="lineno"> 2907</span>  </div> -<div class="line"><a name="l02908"></a><span class="lineno"> 2908</span>  <a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html">armnn::SpaceToBatchNdDescriptor</a> descriptor;</div> -<div class="line"><a name="l02909"></a><span class="lineno"> 2909</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> -<div class="line"><a name="l02910"></a><span class="lineno"> 2910</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> =</div> -<div class="line"><a name="l02911"></a><span class="lineno"> 2911</span>  std::vector<unsigned int>(flatBufferBlockShape->begin(), flatBufferBlockShape->end());</div> -<div class="line"><a name="l02912"></a><span class="lineno"> 2912</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a> = padList;</div> -<div class="line"><a name="l02913"></a><span class="lineno"> 2913</span>  </div> -<div class="line"><a name="l02914"></a><span class="lineno"> 2914</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02915"></a><span class="lineno"> 2915</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSpaceToBatchNdLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02872"></a><span class="lineno"> 2872</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02873"></a><span class="lineno"> 2873</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02874"></a><span class="lineno"> 2874</span>  </div> +<div class="line"><a name="l02875"></a><span class="lineno"> 2875</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02876"></a><span class="lineno"> 2876</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02877"></a><span class="lineno"> 2877</span> }</div> +<div class="line"><a name="l02878"></a><span class="lineno"> 2878</span>  </div> +<div class="line"><a name="l02879"></a><span class="lineno"> 2879</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSoftmax(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02880"></a><span class="lineno"> 2880</span> {</div> +<div class="line"><a name="l02881"></a><span class="lineno"> 2881</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02882"></a><span class="lineno"> 2882</span>  </div> +<div class="line"><a name="l02883"></a><span class="lineno"> 2883</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02884"></a><span class="lineno"> 2884</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02885"></a><span class="lineno"> 2885</span>  </div> +<div class="line"><a name="l02886"></a><span class="lineno"> 2886</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02887"></a><span class="lineno"> 2887</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02888"></a><span class="lineno"> 2888</span>  </div> +<div class="line"><a name="l02889"></a><span class="lineno"> 2889</span>  <a class="code" href="structarmnn_1_1_softmax_descriptor.html">armnn::SoftmaxDescriptor</a> descriptor;</div> +<div class="line"><a name="l02890"></a><span class="lineno"> 2890</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = graph->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->descriptor()->beta();</div> +<div class="line"><a name="l02891"></a><span class="lineno"> 2891</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = graph->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->descriptor()->axis();</div> +<div class="line"><a name="l02892"></a><span class="lineno"> 2892</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02893"></a><span class="lineno"> 2893</span>  </div> +<div class="line"><a name="l02894"></a><span class="lineno"> 2894</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSoftmaxLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02895"></a><span class="lineno"> 2895</span>  </div> +<div class="line"><a name="l02896"></a><span class="lineno"> 2896</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02897"></a><span class="lineno"> 2897</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02898"></a><span class="lineno"> 2898</span>  </div> +<div class="line"><a name="l02899"></a><span class="lineno"> 2899</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02900"></a><span class="lineno"> 2900</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02901"></a><span class="lineno"> 2901</span> }</div> +<div class="line"><a name="l02902"></a><span class="lineno"> 2902</span>  </div> +<div class="line"><a name="l02903"></a><span class="lineno"> 2903</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSpaceToBatchNd(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02904"></a><span class="lineno"> 2904</span> {</div> +<div class="line"><a name="l02905"></a><span class="lineno"> 2905</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l02906"></a><span class="lineno"> 2906</span>  </div> +<div class="line"><a name="l02907"></a><span class="lineno"> 2907</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02908"></a><span class="lineno"> 2908</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02909"></a><span class="lineno"> 2909</span>  </div> +<div class="line"><a name="l02910"></a><span class="lineno"> 2910</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02911"></a><span class="lineno"> 2911</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02912"></a><span class="lineno"> 2912</span>  </div> +<div class="line"><a name="l02913"></a><span class="lineno"> 2913</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->descriptor();</div> +<div class="line"><a name="l02914"></a><span class="lineno"> 2914</span>  <span class="keyword">auto</span> flatBufferPadList = flatBufferDescriptor->padList();</div> +<div class="line"><a name="l02915"></a><span class="lineno"> 2915</span>  <span class="keyword">auto</span> flatBufferBlockShape = flatBufferDescriptor->blockShape();</div> <div class="line"><a name="l02916"></a><span class="lineno"> 2916</span>  </div> -<div class="line"><a name="l02917"></a><span class="lineno"> 2917</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02918"></a><span class="lineno"> 2918</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l02919"></a><span class="lineno"> 2919</span>  </div> -<div class="line"><a name="l02920"></a><span class="lineno"> 2920</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02921"></a><span class="lineno"> 2921</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02922"></a><span class="lineno"> 2922</span> }</div> -<div class="line"><a name="l02923"></a><span class="lineno"> 2923</span>  </div> -<div class="line"><a name="l02924"></a><span class="lineno"> 2924</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSpaceToDepth(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02925"></a><span class="lineno"> 2925</span> {</div> -<div class="line"><a name="l02926"></a><span class="lineno"> 2926</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l02927"></a><span class="lineno"> 2927</span>  </div> -<div class="line"><a name="l02928"></a><span class="lineno"> 2928</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l02929"></a><span class="lineno"> 2929</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l02930"></a><span class="lineno"> 2930</span>  </div> -<div class="line"><a name="l02931"></a><span class="lineno"> 2931</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l02932"></a><span class="lineno"> 2932</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l02933"></a><span class="lineno"> 2933</span>  </div> -<div class="line"><a name="l02934"></a><span class="lineno"> 2934</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_SpaceToDepthLayer()->descriptor();</div> +<div class="line"><a name="l02917"></a><span class="lineno"> 2917</span>  <span class="keywordflow">if</span> (flatBufferPadList->size() % 2 != 0)</div> +<div class="line"><a name="l02918"></a><span class="lineno"> 2918</span>  {</div> +<div class="line"><a name="l02919"></a><span class="lineno"> 2919</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The size of the pad list must be divisible by 2 {}"</span>,</div> +<div class="line"><a name="l02920"></a><span class="lineno"> 2920</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l02921"></a><span class="lineno"> 2921</span>  }</div> +<div class="line"><a name="l02922"></a><span class="lineno"> 2922</span>  </div> +<div class="line"><a name="l02923"></a><span class="lineno"> 2923</span>  std::vector<std::pair<unsigned int, unsigned int>> padList;</div> +<div class="line"><a name="l02924"></a><span class="lineno"> 2924</span>  padList.reserve(flatBufferPadList->size() / 2);</div> +<div class="line"><a name="l02925"></a><span class="lineno"> 2925</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < flatBufferPadList->size() - 1; i += 2)</div> +<div class="line"><a name="l02926"></a><span class="lineno"> 2926</span>  {</div> +<div class="line"><a name="l02927"></a><span class="lineno"> 2927</span>  padList.emplace_back(flatBufferPadList->Get(i), flatBufferPadList->Get(i+1));</div> +<div class="line"><a name="l02928"></a><span class="lineno"> 2928</span>  }</div> +<div class="line"><a name="l02929"></a><span class="lineno"> 2929</span>  </div> +<div class="line"><a name="l02930"></a><span class="lineno"> 2930</span>  <a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html">armnn::SpaceToBatchNdDescriptor</a> descriptor;</div> +<div class="line"><a name="l02931"></a><span class="lineno"> 2931</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> +<div class="line"><a name="l02932"></a><span class="lineno"> 2932</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> =</div> +<div class="line"><a name="l02933"></a><span class="lineno"> 2933</span>  std::vector<unsigned int>(flatBufferBlockShape->begin(), flatBufferBlockShape->end());</div> +<div class="line"><a name="l02934"></a><span class="lineno"> 2934</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a> = padList;</div> <div class="line"><a name="l02935"></a><span class="lineno"> 2935</span>  </div> -<div class="line"><a name="l02936"></a><span class="lineno"> 2936</span>  <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html">armnn::SpaceToDepthDescriptor</a> descriptor;</div> -<div class="line"><a name="l02937"></a><span class="lineno"> 2937</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a> = flatBufferDescriptor->blockSize();</div> -<div class="line"><a name="l02938"></a><span class="lineno"> 2938</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> -<div class="line"><a name="l02939"></a><span class="lineno"> 2939</span>  </div> -<div class="line"><a name="l02940"></a><span class="lineno"> 2940</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l02941"></a><span class="lineno"> 2941</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSpaceToDepthLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l02942"></a><span class="lineno"> 2942</span>  </div> -<div class="line"><a name="l02943"></a><span class="lineno"> 2943</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l02944"></a><span class="lineno"> 2944</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02936"></a><span class="lineno"> 2936</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02937"></a><span class="lineno"> 2937</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSpaceToBatchNdLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02938"></a><span class="lineno"> 2938</span>  </div> +<div class="line"><a name="l02939"></a><span class="lineno"> 2939</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02940"></a><span class="lineno"> 2940</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02941"></a><span class="lineno"> 2941</span>  </div> +<div class="line"><a name="l02942"></a><span class="lineno"> 2942</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02943"></a><span class="lineno"> 2943</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02944"></a><span class="lineno"> 2944</span> }</div> <div class="line"><a name="l02945"></a><span class="lineno"> 2945</span>  </div> -<div class="line"><a name="l02946"></a><span class="lineno"> 2946</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02947"></a><span class="lineno"> 2947</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l02948"></a><span class="lineno"> 2948</span> }</div> +<div class="line"><a name="l02946"></a><span class="lineno"> 2946</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSpaceToDepth(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02947"></a><span class="lineno"> 2947</span> {</div> +<div class="line"><a name="l02948"></a><span class="lineno"> 2948</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l02949"></a><span class="lineno"> 2949</span>  </div> -<div class="line"><a name="l02950"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a920251d49a8f32085d458ba23f776800"> 2950</a></span> <a class="code" href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a920251d49a8f32085d458ba23f776800">IDeserializer::DeserializerImpl::GetNormalizationDescriptor</a>(</div> -<div class="line"><a name="l02951"></a><span class="lineno"> 2951</span>  <a class="code" href="namespacearmnn_deserializer.html#a2a282cf18fcfe848b47e946327ca1048">NormalizationDescriptorPtr</a> normalizationDescriptor,</div> -<div class="line"><a name="l02952"></a><span class="lineno"> 2952</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l02953"></a><span class="lineno"> 2953</span> {</div> -<div class="line"><a name="l02954"></a><span class="lineno"> 2954</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> -<div class="line"><a name="l02955"></a><span class="lineno"> 2955</span>  <a class="code" href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a> desc;</div> -<div class="line"><a name="l02956"></a><span class="lineno"> 2956</span>  </div> -<div class="line"><a name="l02957"></a><span class="lineno"> 2957</span>  <span class="keywordflow">switch</span> (normalizationDescriptor->normChannelType())</div> -<div class="line"><a name="l02958"></a><span class="lineno"> 2958</span>  {</div> -<div class="line"><a name="l02959"></a><span class="lineno"> 2959</span>  <span class="keywordflow">case</span> NormalizationAlgorithmChannel_Across:</div> -<div class="line"><a name="l02960"></a><span class="lineno"> 2960</span>  {</div> -<div class="line"><a name="l02961"></a><span class="lineno"> 2961</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#afe1f0f09d49ad2befc01f8789187b7dd">m_NormChannelType</a> = <a class="code" href="namespacearmnn.html#abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc">armnn::NormalizationAlgorithmChannel::Across</a>;</div> -<div class="line"><a name="l02962"></a><span class="lineno"> 2962</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02963"></a><span class="lineno"> 2963</span>  }</div> -<div class="line"><a name="l02964"></a><span class="lineno"> 2964</span>  <span class="keywordflow">case</span> NormalizationAlgorithmChannel_Within:</div> -<div class="line"><a name="l02965"></a><span class="lineno"> 2965</span>  {</div> -<div class="line"><a name="l02966"></a><span class="lineno"> 2966</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#afe1f0f09d49ad2befc01f8789187b7dd">m_NormChannelType</a> = <a class="code" href="namespacearmnn.html#abe18a5033f2ab9c0de82c676b48f5437a37bac6dce4f46277d89bfa3003e2e39b">armnn::NormalizationAlgorithmChannel::Within</a>;</div> -<div class="line"><a name="l02967"></a><span class="lineno"> 2967</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02968"></a><span class="lineno"> 2968</span>  }</div> -<div class="line"><a name="l02969"></a><span class="lineno"> 2969</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02970"></a><span class="lineno"> 2970</span>  {</div> -<div class="line"><a name="l02971"></a><span class="lineno"> 2971</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported normalization channel type"</span>);</div> -<div class="line"><a name="l02972"></a><span class="lineno"> 2972</span>  }</div> -<div class="line"><a name="l02973"></a><span class="lineno"> 2973</span>  }</div> -<div class="line"><a name="l02974"></a><span class="lineno"> 2974</span>  </div> -<div class="line"><a name="l02975"></a><span class="lineno"> 2975</span>  <span class="keywordflow">switch</span> (normalizationDescriptor->normMethodType())</div> -<div class="line"><a name="l02976"></a><span class="lineno"> 2976</span>  {</div> -<div class="line"><a name="l02977"></a><span class="lineno"> 2977</span>  <span class="keywordflow">case</span> NormalizationAlgorithmMethod_LocalBrightness:</div> -<div class="line"><a name="l02978"></a><span class="lineno"> 2978</span>  {</div> -<div class="line"><a name="l02979"></a><span class="lineno"> 2979</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a05945f080edf694b631960728b87aadb">m_NormMethodType</a> = <a class="code" href="namespacearmnn.html#ad605d1661fa0d8c7fea651d82fbe11c9ac65d2e51c610dd3853a3c777aa8bfe9d">armnn::NormalizationAlgorithmMethod::LocalBrightness</a>;</div> -<div class="line"><a name="l02980"></a><span class="lineno"> 2980</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02981"></a><span class="lineno"> 2981</span>  }</div> -<div class="line"><a name="l02982"></a><span class="lineno"> 2982</span>  <span class="keywordflow">case</span> NormalizationAlgorithmMethod_LocalContrast:</div> -<div class="line"><a name="l02983"></a><span class="lineno"> 2983</span>  {</div> -<div class="line"><a name="l02984"></a><span class="lineno"> 2984</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a05945f080edf694b631960728b87aadb">m_NormMethodType</a> = <a class="code" href="namespacearmnn.html#ad605d1661fa0d8c7fea651d82fbe11c9aa94d2fcabc6b001015aeddfa19266e6f">armnn::NormalizationAlgorithmMethod::LocalContrast</a>;</div> -<div class="line"><a name="l02985"></a><span class="lineno"> 2985</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02986"></a><span class="lineno"> 2986</span>  }</div> -<div class="line"><a name="l02987"></a><span class="lineno"> 2987</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l02988"></a><span class="lineno"> 2988</span>  {</div> -<div class="line"><a name="l02989"></a><span class="lineno"> 2989</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported normalization method type"</span>);</div> +<div class="line"><a name="l02950"></a><span class="lineno"> 2950</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l02951"></a><span class="lineno"> 2951</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l02952"></a><span class="lineno"> 2952</span>  </div> +<div class="line"><a name="l02953"></a><span class="lineno"> 2953</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l02954"></a><span class="lineno"> 2954</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l02955"></a><span class="lineno"> 2955</span>  </div> +<div class="line"><a name="l02956"></a><span class="lineno"> 2956</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_SpaceToDepthLayer()->descriptor();</div> +<div class="line"><a name="l02957"></a><span class="lineno"> 2957</span>  </div> +<div class="line"><a name="l02958"></a><span class="lineno"> 2958</span>  <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html">armnn::SpaceToDepthDescriptor</a> descriptor;</div> +<div class="line"><a name="l02959"></a><span class="lineno"> 2959</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a> = flatBufferDescriptor->blockSize();</div> +<div class="line"><a name="l02960"></a><span class="lineno"> 2960</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> +<div class="line"><a name="l02961"></a><span class="lineno"> 2961</span>  </div> +<div class="line"><a name="l02962"></a><span class="lineno"> 2962</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l02963"></a><span class="lineno"> 2963</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSpaceToDepthLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l02964"></a><span class="lineno"> 2964</span>  </div> +<div class="line"><a name="l02965"></a><span class="lineno"> 2965</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l02966"></a><span class="lineno"> 2966</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l02967"></a><span class="lineno"> 2967</span>  </div> +<div class="line"><a name="l02968"></a><span class="lineno"> 2968</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02969"></a><span class="lineno"> 2969</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l02970"></a><span class="lineno"> 2970</span> }</div> +<div class="line"><a name="l02971"></a><span class="lineno"> 2971</span>  </div> +<div class="line"><a name="l02972"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a920251d49a8f32085d458ba23f776800"> 2972</a></span> <a class="code" href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a920251d49a8f32085d458ba23f776800">IDeserializer::DeserializerImpl::GetNormalizationDescriptor</a>(</div> +<div class="line"><a name="l02973"></a><span class="lineno"> 2973</span>  <a class="code" href="namespacearmnn_deserializer.html#a2a282cf18fcfe848b47e946327ca1048">NormalizationDescriptorPtr</a> normalizationDescriptor,</div> +<div class="line"><a name="l02974"></a><span class="lineno"> 2974</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l02975"></a><span class="lineno"> 2975</span> {</div> +<div class="line"><a name="l02976"></a><span class="lineno"> 2976</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div> +<div class="line"><a name="l02977"></a><span class="lineno"> 2977</span>  <a class="code" href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a> desc;</div> +<div class="line"><a name="l02978"></a><span class="lineno"> 2978</span>  </div> +<div class="line"><a name="l02979"></a><span class="lineno"> 2979</span>  <span class="keywordflow">switch</span> (normalizationDescriptor->normChannelType())</div> +<div class="line"><a name="l02980"></a><span class="lineno"> 2980</span>  {</div> +<div class="line"><a name="l02981"></a><span class="lineno"> 2981</span>  <span class="keywordflow">case</span> NormalizationAlgorithmChannel_Across:</div> +<div class="line"><a name="l02982"></a><span class="lineno"> 2982</span>  {</div> +<div class="line"><a name="l02983"></a><span class="lineno"> 2983</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#afe1f0f09d49ad2befc01f8789187b7dd">m_NormChannelType</a> = <a class="code" href="namespacearmnn.html#abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc">armnn::NormalizationAlgorithmChannel::Across</a>;</div> +<div class="line"><a name="l02984"></a><span class="lineno"> 2984</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l02985"></a><span class="lineno"> 2985</span>  }</div> +<div class="line"><a name="l02986"></a><span class="lineno"> 2986</span>  <span class="keywordflow">case</span> NormalizationAlgorithmChannel_Within:</div> +<div class="line"><a name="l02987"></a><span class="lineno"> 2987</span>  {</div> +<div class="line"><a name="l02988"></a><span class="lineno"> 2988</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#afe1f0f09d49ad2befc01f8789187b7dd">m_NormChannelType</a> = <a class="code" href="namespacearmnn.html#abe18a5033f2ab9c0de82c676b48f5437a37bac6dce4f46277d89bfa3003e2e39b">armnn::NormalizationAlgorithmChannel::Within</a>;</div> +<div class="line"><a name="l02989"></a><span class="lineno"> 2989</span>  <span class="keywordflow">break</span>;</div> <div class="line"><a name="l02990"></a><span class="lineno"> 2990</span>  }</div> -<div class="line"><a name="l02991"></a><span class="lineno"> 2991</span>  }</div> -<div class="line"><a name="l02992"></a><span class="lineno"> 2992</span>  </div> -<div class="line"><a name="l02993"></a><span class="lineno"> 2993</span>  <span class="keywordflow">switch</span> (normalizationDescriptor->dataLayout())</div> -<div class="line"><a name="l02994"></a><span class="lineno"> 2994</span>  {</div> -<div class="line"><a name="l02995"></a><span class="lineno"> 2995</span>  <span class="keywordflow">case</span> DataLayout_NCHW:</div> -<div class="line"><a name="l02996"></a><span class="lineno"> 2996</span>  {</div> -<div class="line"><a name="l02997"></a><span class="lineno"> 2997</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div> -<div class="line"><a name="l02998"></a><span class="lineno"> 2998</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l02999"></a><span class="lineno"> 2999</span>  }</div> -<div class="line"><a name="l03000"></a><span class="lineno"> 3000</span>  <span class="keywordflow">case</span> DataLayout_NHWC:</div> -<div class="line"><a name="l03001"></a><span class="lineno"> 3001</span>  {</div> -<div class="line"><a name="l03002"></a><span class="lineno"> 3002</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div> -<div class="line"><a name="l03003"></a><span class="lineno"> 3003</span>  <span class="keywordflow">break</span>;</div> -<div class="line"><a name="l03004"></a><span class="lineno"> 3004</span>  }</div> -<div class="line"><a name="l03005"></a><span class="lineno"> 3005</span>  <span class="keywordflow">default</span>:</div> -<div class="line"><a name="l03006"></a><span class="lineno"> 3006</span>  {</div> -<div class="line"><a name="l03007"></a><span class="lineno"> 3007</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported data layout"</span>);</div> +<div class="line"><a name="l02991"></a><span class="lineno"> 2991</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l02992"></a><span class="lineno"> 2992</span>  {</div> +<div class="line"><a name="l02993"></a><span class="lineno"> 2993</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported normalization channel type"</span>);</div> +<div class="line"><a name="l02994"></a><span class="lineno"> 2994</span>  }</div> +<div class="line"><a name="l02995"></a><span class="lineno"> 2995</span>  }</div> +<div class="line"><a name="l02996"></a><span class="lineno"> 2996</span>  </div> +<div class="line"><a name="l02997"></a><span class="lineno"> 2997</span>  <span class="keywordflow">switch</span> (normalizationDescriptor->normMethodType())</div> +<div class="line"><a name="l02998"></a><span class="lineno"> 2998</span>  {</div> +<div class="line"><a name="l02999"></a><span class="lineno"> 2999</span>  <span class="keywordflow">case</span> NormalizationAlgorithmMethod_LocalBrightness:</div> +<div class="line"><a name="l03000"></a><span class="lineno"> 3000</span>  {</div> +<div class="line"><a name="l03001"></a><span class="lineno"> 3001</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a05945f080edf694b631960728b87aadb">m_NormMethodType</a> = <a class="code" href="namespacearmnn.html#ad605d1661fa0d8c7fea651d82fbe11c9ac65d2e51c610dd3853a3c777aa8bfe9d">armnn::NormalizationAlgorithmMethod::LocalBrightness</a>;</div> +<div class="line"><a name="l03002"></a><span class="lineno"> 3002</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l03003"></a><span class="lineno"> 3003</span>  }</div> +<div class="line"><a name="l03004"></a><span class="lineno"> 3004</span>  <span class="keywordflow">case</span> NormalizationAlgorithmMethod_LocalContrast:</div> +<div class="line"><a name="l03005"></a><span class="lineno"> 3005</span>  {</div> +<div class="line"><a name="l03006"></a><span class="lineno"> 3006</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a05945f080edf694b631960728b87aadb">m_NormMethodType</a> = <a class="code" href="namespacearmnn.html#ad605d1661fa0d8c7fea651d82fbe11c9aa94d2fcabc6b001015aeddfa19266e6f">armnn::NormalizationAlgorithmMethod::LocalContrast</a>;</div> +<div class="line"><a name="l03007"></a><span class="lineno"> 3007</span>  <span class="keywordflow">break</span>;</div> <div class="line"><a name="l03008"></a><span class="lineno"> 3008</span>  }</div> -<div class="line"><a name="l03009"></a><span class="lineno"> 3009</span>  }</div> -<div class="line"><a name="l03010"></a><span class="lineno"> 3010</span>  </div> -<div class="line"><a name="l03011"></a><span class="lineno"> 3011</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a174279be57d7596eeb04c6b7f7510f99">m_Alpha</a> = normalizationDescriptor->alpha();</div> -<div class="line"><a name="l03012"></a><span class="lineno"> 3012</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = normalizationDescriptor->beta();</div> -<div class="line"><a name="l03013"></a><span class="lineno"> 3013</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a8526ea7cf860d8e7f8340e9f9354f9f0">m_K</a> = normalizationDescriptor->k();</div> -<div class="line"><a name="l03014"></a><span class="lineno"> 3014</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#aa70c05f1aad12fbd9d9ec43ea4557b03">m_NormSize</a> = normalizationDescriptor->normSize();</div> -<div class="line"><a name="l03015"></a><span class="lineno"> 3015</span>  </div> -<div class="line"><a name="l03016"></a><span class="lineno"> 3016</span>  <span class="keywordflow">return</span> desc;</div> -<div class="line"><a name="l03017"></a><span class="lineno"> 3017</span> }</div> -<div class="line"><a name="l03018"></a><span class="lineno"> 3018</span>  </div> -<div class="line"><a name="l03019"></a><span class="lineno"> 3019</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseNormalization(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03020"></a><span class="lineno"> 3020</span> {</div> -<div class="line"><a name="l03021"></a><span class="lineno"> 3021</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03022"></a><span class="lineno"> 3022</span>  </div> -<div class="line"><a name="l03023"></a><span class="lineno"> 3023</span>  <span class="keyword">auto</span> normalizationDes = graph->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->descriptor();</div> -<div class="line"><a name="l03024"></a><span class="lineno"> 3024</span>  </div> -<div class="line"><a name="l03025"></a><span class="lineno"> 3025</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03026"></a><span class="lineno"> 3026</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l03027"></a><span class="lineno"> 3027</span>  </div> -<div class="line"><a name="l03028"></a><span class="lineno"> 3028</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03029"></a><span class="lineno"> 3029</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03030"></a><span class="lineno"> 3030</span>  </div> -<div class="line"><a name="l03031"></a><span class="lineno"> 3031</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03009"></a><span class="lineno"> 3009</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l03010"></a><span class="lineno"> 3010</span>  {</div> +<div class="line"><a name="l03011"></a><span class="lineno"> 3011</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported normalization method type"</span>);</div> +<div class="line"><a name="l03012"></a><span class="lineno"> 3012</span>  }</div> +<div class="line"><a name="l03013"></a><span class="lineno"> 3013</span>  }</div> +<div class="line"><a name="l03014"></a><span class="lineno"> 3014</span>  </div> +<div class="line"><a name="l03015"></a><span class="lineno"> 3015</span>  <span class="keywordflow">switch</span> (normalizationDescriptor->dataLayout())</div> +<div class="line"><a name="l03016"></a><span class="lineno"> 3016</span>  {</div> +<div class="line"><a name="l03017"></a><span class="lineno"> 3017</span>  <span class="keywordflow">case</span> DataLayout_NCHW:</div> +<div class="line"><a name="l03018"></a><span class="lineno"> 3018</span>  {</div> +<div class="line"><a name="l03019"></a><span class="lineno"> 3019</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div> +<div class="line"><a name="l03020"></a><span class="lineno"> 3020</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l03021"></a><span class="lineno"> 3021</span>  }</div> +<div class="line"><a name="l03022"></a><span class="lineno"> 3022</span>  <span class="keywordflow">case</span> DataLayout_NHWC:</div> +<div class="line"><a name="l03023"></a><span class="lineno"> 3023</span>  {</div> +<div class="line"><a name="l03024"></a><span class="lineno"> 3024</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div> +<div class="line"><a name="l03025"></a><span class="lineno"> 3025</span>  <span class="keywordflow">break</span>;</div> +<div class="line"><a name="l03026"></a><span class="lineno"> 3026</span>  }</div> +<div class="line"><a name="l03027"></a><span class="lineno"> 3027</span>  <span class="keywordflow">default</span>:</div> +<div class="line"><a name="l03028"></a><span class="lineno"> 3028</span>  {</div> +<div class="line"><a name="l03029"></a><span class="lineno"> 3029</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(<span class="stringliteral">"Unsupported data layout"</span>);</div> +<div class="line"><a name="l03030"></a><span class="lineno"> 3030</span>  }</div> +<div class="line"><a name="l03031"></a><span class="lineno"> 3031</span>  }</div> <div class="line"><a name="l03032"></a><span class="lineno"> 3032</span>  </div> -<div class="line"><a name="l03033"></a><span class="lineno"> 3033</span>  <span class="keyword">auto</span> normalizationDescriptor = GetNormalizationDescriptor(normalizationDes, layerIndex);</div> -<div class="line"><a name="l03034"></a><span class="lineno"> 3034</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03035"></a><span class="lineno"> 3035</span>  </div> -<div class="line"><a name="l03036"></a><span class="lineno"> 3036</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddNormalizationLayer(normalizationDescriptor, layerName.c_str());</div> -<div class="line"><a name="l03037"></a><span class="lineno"> 3037</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> -<div class="line"><a name="l03038"></a><span class="lineno"> 3038</span>  </div> -<div class="line"><a name="l03039"></a><span class="lineno"> 3039</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03040"></a><span class="lineno"> 3040</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03041"></a><span class="lineno"> 3041</span> }</div> -<div class="line"><a name="l03042"></a><span class="lineno"> 3042</span>  </div> -<div class="line"><a name="l03043"></a><span class="lineno"> 3043</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseRsqrt(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03044"></a><span class="lineno"> 3044</span> {</div> -<div class="line"><a name="l03045"></a><span class="lineno"> 3045</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03046"></a><span class="lineno"> 3046</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03047"></a><span class="lineno"> 3047</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l03033"></a><span class="lineno"> 3033</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a174279be57d7596eeb04c6b7f7510f99">m_Alpha</a> = normalizationDescriptor->alpha();</div> +<div class="line"><a name="l03034"></a><span class="lineno"> 3034</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = normalizationDescriptor->beta();</div> +<div class="line"><a name="l03035"></a><span class="lineno"> 3035</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#a8526ea7cf860d8e7f8340e9f9354f9f0">m_K</a> = normalizationDescriptor->k();</div> +<div class="line"><a name="l03036"></a><span class="lineno"> 3036</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.html#aa70c05f1aad12fbd9d9ec43ea4557b03">m_NormSize</a> = normalizationDescriptor->normSize();</div> +<div class="line"><a name="l03037"></a><span class="lineno"> 3037</span>  </div> +<div class="line"><a name="l03038"></a><span class="lineno"> 3038</span>  <span class="keywordflow">return</span> desc;</div> +<div class="line"><a name="l03039"></a><span class="lineno"> 3039</span> }</div> +<div class="line"><a name="l03040"></a><span class="lineno"> 3040</span>  </div> +<div class="line"><a name="l03041"></a><span class="lineno"> 3041</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseNormalization(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03042"></a><span class="lineno"> 3042</span> {</div> +<div class="line"><a name="l03043"></a><span class="lineno"> 3043</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03044"></a><span class="lineno"> 3044</span>  </div> +<div class="line"><a name="l03045"></a><span class="lineno"> 3045</span>  <span class="keyword">auto</span> normalizationDes = graph->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->descriptor();</div> +<div class="line"><a name="l03046"></a><span class="lineno"> 3046</span>  </div> +<div class="line"><a name="l03047"></a><span class="lineno"> 3047</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> <div class="line"><a name="l03048"></a><span class="lineno"> 3048</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> <div class="line"><a name="l03049"></a><span class="lineno"> 3049</span>  </div> -<div class="line"><a name="l03050"></a><span class="lineno"> 3050</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03050"></a><span class="lineno"> 3050</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> <div class="line"><a name="l03051"></a><span class="lineno"> 3051</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l03052"></a><span class="lineno"> 3052</span>  </div> -<div class="line"><a name="l03053"></a><span class="lineno"> 3053</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03053"></a><span class="lineno"> 3053</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> <div class="line"><a name="l03054"></a><span class="lineno"> 3054</span>  </div> -<div class="line"><a name="l03055"></a><span class="lineno"> 3055</span>  <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.html">armnn::ElementwiseUnaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4">armnn::UnaryOperation::Rsqrt</a>);</div> -<div class="line"><a name="l03056"></a><span class="lineno"> 3056</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l03057"></a><span class="lineno"> 3057</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03058"></a><span class="lineno"> 3058</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03059"></a><span class="lineno"> 3059</span>  </div> -<div class="line"><a name="l03060"></a><span class="lineno"> 3060</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03061"></a><span class="lineno"> 3061</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03062"></a><span class="lineno"> 3062</span> }</div> -<div class="line"><a name="l03063"></a><span class="lineno"> 3063</span>  </div> -<div class="line"><a name="l03064"></a><span class="lineno"> 3064</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSlice(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03065"></a><span class="lineno"> 3065</span> {</div> -<div class="line"><a name="l03066"></a><span class="lineno"> 3066</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03067"></a><span class="lineno"> 3067</span>  </div> +<div class="line"><a name="l03055"></a><span class="lineno"> 3055</span>  <span class="keyword">auto</span> normalizationDescriptor = GetNormalizationDescriptor(normalizationDes, layerIndex);</div> +<div class="line"><a name="l03056"></a><span class="lineno"> 3056</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03057"></a><span class="lineno"> 3057</span>  </div> +<div class="line"><a name="l03058"></a><span class="lineno"> 3058</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddNormalizationLayer(normalizationDescriptor, layerName.c_str());</div> +<div class="line"><a name="l03059"></a><span class="lineno"> 3059</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l03060"></a><span class="lineno"> 3060</span>  </div> +<div class="line"><a name="l03061"></a><span class="lineno"> 3061</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03062"></a><span class="lineno"> 3062</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03063"></a><span class="lineno"> 3063</span> }</div> +<div class="line"><a name="l03064"></a><span class="lineno"> 3064</span>  </div> +<div class="line"><a name="l03065"></a><span class="lineno"> 3065</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseRsqrt(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03066"></a><span class="lineno"> 3066</span> {</div> +<div class="line"><a name="l03067"></a><span class="lineno"> 3067</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l03068"></a><span class="lineno"> 3068</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03069"></a><span class="lineno"> 3069</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l03070"></a><span class="lineno"> 3070</span>  </div> -<div class="line"><a name="l03071"></a><span class="lineno"> 3071</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03072"></a><span class="lineno"> 3072</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03073"></a><span class="lineno"> 3073</span>  </div> -<div class="line"><a name="l03074"></a><span class="lineno"> 3074</span>  <span class="keyword">auto</span> fbDescriptor = graph->layers()->Get(layerIndex)->layer_as_SliceLayer()->descriptor();</div> -<div class="line"><a name="l03075"></a><span class="lineno"> 3075</span>  </div> -<div class="line"><a name="l03076"></a><span class="lineno"> 3076</span>  <span class="keyword">auto</span> fbBegin = fbDescriptor->begin();</div> -<div class="line"><a name="l03077"></a><span class="lineno"> 3077</span>  <span class="keyword">auto</span> fbSize = fbDescriptor->size();</div> -<div class="line"><a name="l03078"></a><span class="lineno"> 3078</span>  </div> -<div class="line"><a name="l03079"></a><span class="lineno"> 3079</span>  <span class="keywordflow">if</span> (fbBegin->size() != fbSize->size())</div> -<div class="line"><a name="l03080"></a><span class="lineno"> 3080</span>  {</div> -<div class="line"><a name="l03081"></a><span class="lineno"> 3081</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Begin and size descriptors must have the same length {}"</span>,</div> -<div class="line"><a name="l03082"></a><span class="lineno"> 3082</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l03083"></a><span class="lineno"> 3083</span>  }</div> -<div class="line"><a name="l03084"></a><span class="lineno"> 3084</span>  </div> -<div class="line"><a name="l03085"></a><span class="lineno"> 3085</span>  <a class="code" href="structarmnn_1_1_slice_descriptor.html">armnn::SliceDescriptor</a> descriptor;</div> -<div class="line"><a name="l03086"></a><span class="lineno"> 3086</span>  descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.html#a4939f00778f08d6c6fec6f74c0a59b7e">m_Begin</a>.insert(descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.html#a4939f00778f08d6c6fec6f74c0a59b7e">m_Begin</a>.end(), fbBegin->begin(), fbBegin->end());</div> -<div class="line"><a name="l03087"></a><span class="lineno"> 3087</span>  descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.html#ab52cabf19232290fa6b49828ba957ac0">m_Size</a>.insert(descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.html#ab52cabf19232290fa6b49828ba957ac0">m_Size</a>.end(), fbSize->begin(), fbSize->end());</div> -<div class="line"><a name="l03088"></a><span class="lineno"> 3088</span>  </div> -<div class="line"><a name="l03089"></a><span class="lineno"> 3089</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03090"></a><span class="lineno"> 3090</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSliceLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l03091"></a><span class="lineno"> 3091</span>  </div> -<div class="line"><a name="l03092"></a><span class="lineno"> 3092</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03093"></a><span class="lineno"> 3093</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03094"></a><span class="lineno"> 3094</span>  </div> -<div class="line"><a name="l03095"></a><span class="lineno"> 3095</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03096"></a><span class="lineno"> 3096</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03097"></a><span class="lineno"> 3097</span> }</div> -<div class="line"><a name="l03098"></a><span class="lineno"> 3098</span>  </div> -<div class="line"><a name="l03099"></a><span class="lineno"> 3099</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseStridedSlice(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03100"></a><span class="lineno"> 3100</span> {</div> -<div class="line"><a name="l03101"></a><span class="lineno"> 3101</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03102"></a><span class="lineno"> 3102</span>  </div> -<div class="line"><a name="l03103"></a><span class="lineno"> 3103</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03104"></a><span class="lineno"> 3104</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l03105"></a><span class="lineno"> 3105</span>  </div> -<div class="line"><a name="l03106"></a><span class="lineno"> 3106</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03107"></a><span class="lineno"> 3107</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03108"></a><span class="lineno"> 3108</span>  </div> -<div class="line"><a name="l03109"></a><span class="lineno"> 3109</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_StridedSliceLayer()->descriptor();</div> +<div class="line"><a name="l03069"></a><span class="lineno"> 3069</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l03070"></a><span class="lineno"> 3070</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03071"></a><span class="lineno"> 3071</span>  </div> +<div class="line"><a name="l03072"></a><span class="lineno"> 3072</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03073"></a><span class="lineno"> 3073</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03074"></a><span class="lineno"> 3074</span>  </div> +<div class="line"><a name="l03075"></a><span class="lineno"> 3075</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03076"></a><span class="lineno"> 3076</span>  </div> +<div class="line"><a name="l03077"></a><span class="lineno"> 3077</span>  <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.html">armnn::ElementwiseUnaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4">armnn::UnaryOperation::Rsqrt</a>);</div> +<div class="line"><a name="l03078"></a><span class="lineno"> 3078</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03079"></a><span class="lineno"> 3079</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03080"></a><span class="lineno"> 3080</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03081"></a><span class="lineno"> 3081</span>  </div> +<div class="line"><a name="l03082"></a><span class="lineno"> 3082</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03083"></a><span class="lineno"> 3083</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03084"></a><span class="lineno"> 3084</span> }</div> +<div class="line"><a name="l03085"></a><span class="lineno"> 3085</span>  </div> +<div class="line"><a name="l03086"></a><span class="lineno"> 3086</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSlice(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03087"></a><span class="lineno"> 3087</span> {</div> +<div class="line"><a name="l03088"></a><span class="lineno"> 3088</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03089"></a><span class="lineno"> 3089</span>  </div> +<div class="line"><a name="l03090"></a><span class="lineno"> 3090</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03091"></a><span class="lineno"> 3091</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03092"></a><span class="lineno"> 3092</span>  </div> +<div class="line"><a name="l03093"></a><span class="lineno"> 3093</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03094"></a><span class="lineno"> 3094</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03095"></a><span class="lineno"> 3095</span>  </div> +<div class="line"><a name="l03096"></a><span class="lineno"> 3096</span>  <span class="keyword">auto</span> fbDescriptor = graph->layers()->Get(layerIndex)->layer_as_SliceLayer()->descriptor();</div> +<div class="line"><a name="l03097"></a><span class="lineno"> 3097</span>  </div> +<div class="line"><a name="l03098"></a><span class="lineno"> 3098</span>  <span class="keyword">auto</span> fbBegin = fbDescriptor->begin();</div> +<div class="line"><a name="l03099"></a><span class="lineno"> 3099</span>  <span class="keyword">auto</span> fbSize = fbDescriptor->size();</div> +<div class="line"><a name="l03100"></a><span class="lineno"> 3100</span>  </div> +<div class="line"><a name="l03101"></a><span class="lineno"> 3101</span>  <span class="keywordflow">if</span> (fbBegin->size() != fbSize->size())</div> +<div class="line"><a name="l03102"></a><span class="lineno"> 3102</span>  {</div> +<div class="line"><a name="l03103"></a><span class="lineno"> 3103</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"Begin and size descriptors must have the same length {}"</span>,</div> +<div class="line"><a name="l03104"></a><span class="lineno"> 3104</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l03105"></a><span class="lineno"> 3105</span>  }</div> +<div class="line"><a name="l03106"></a><span class="lineno"> 3106</span>  </div> +<div class="line"><a name="l03107"></a><span class="lineno"> 3107</span>  <a class="code" href="structarmnn_1_1_slice_descriptor.html">armnn::SliceDescriptor</a> descriptor;</div> +<div class="line"><a name="l03108"></a><span class="lineno"> 3108</span>  descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.html#a4939f00778f08d6c6fec6f74c0a59b7e">m_Begin</a>.insert(descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.html#a4939f00778f08d6c6fec6f74c0a59b7e">m_Begin</a>.end(), fbBegin->begin(), fbBegin->end());</div> +<div class="line"><a name="l03109"></a><span class="lineno"> 3109</span>  descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.html#ab52cabf19232290fa6b49828ba957ac0">m_Size</a>.insert(descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.html#ab52cabf19232290fa6b49828ba957ac0">m_Size</a>.end(), fbSize->begin(), fbSize->end());</div> <div class="line"><a name="l03110"></a><span class="lineno"> 3110</span>  </div> -<div class="line"><a name="l03111"></a><span class="lineno"> 3111</span>  <span class="keyword">auto</span> flatBufferBegin = flatBufferDescriptor->begin();</div> -<div class="line"><a name="l03112"></a><span class="lineno"> 3112</span>  <span class="keyword">auto</span> flatBufferEnd = flatBufferDescriptor->end();</div> -<div class="line"><a name="l03113"></a><span class="lineno"> 3113</span>  <span class="keyword">auto</span> flatBufferStride = flatBufferDescriptor->stride();</div> -<div class="line"><a name="l03114"></a><span class="lineno"> 3114</span>  </div> -<div class="line"><a name="l03115"></a><span class="lineno"> 3115</span>  <span class="keywordflow">if</span> (!(flatBufferBegin->size() == flatBufferEnd->size() &&</div> -<div class="line"><a name="l03116"></a><span class="lineno"> 3116</span>  flatBufferBegin->size() == flatBufferStride->size()))</div> -<div class="line"><a name="l03117"></a><span class="lineno"> 3117</span>  {</div> -<div class="line"><a name="l03118"></a><span class="lineno"> 3118</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The size of the begin, end, and stride must be equal {}"</span>,</div> -<div class="line"><a name="l03119"></a><span class="lineno"> 3119</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> -<div class="line"><a name="l03120"></a><span class="lineno"> 3120</span>  }</div> -<div class="line"><a name="l03121"></a><span class="lineno"> 3121</span>  </div> -<div class="line"><a name="l03122"></a><span class="lineno"> 3122</span>  std::vector<int> begin(flatBufferBegin->begin(), flatBufferBegin->end());</div> -<div class="line"><a name="l03123"></a><span class="lineno"> 3123</span>  std::vector<int> end(flatBufferEnd->begin(), flatBufferEnd->end());</div> -<div class="line"><a name="l03124"></a><span class="lineno"> 3124</span>  std::vector<int> stride(flatBufferStride->begin(), flatBufferStride->end());</div> -<div class="line"><a name="l03125"></a><span class="lineno"> 3125</span>  </div> -<div class="line"><a name="l03126"></a><span class="lineno"> 3126</span>  <a class="code" href="structarmnn_1_1_strided_slice_descriptor.html">armnn::StridedSliceDescriptor</a> descriptor(begin, end, stride);</div> -<div class="line"><a name="l03127"></a><span class="lineno"> 3127</span>  descriptor.m_BeginMask = flatBufferDescriptor->beginMask();</div> -<div class="line"><a name="l03128"></a><span class="lineno"> 3128</span>  descriptor.m_EndMask = flatBufferDescriptor->endMask();</div> -<div class="line"><a name="l03129"></a><span class="lineno"> 3129</span>  descriptor.m_ShrinkAxisMask = flatBufferDescriptor->shrinkAxisMask();</div> -<div class="line"><a name="l03130"></a><span class="lineno"> 3130</span>  descriptor.m_EllipsisMask = flatBufferDescriptor->ellipsisMask();</div> -<div class="line"><a name="l03131"></a><span class="lineno"> 3131</span>  descriptor.m_NewAxisMask = flatBufferDescriptor->newAxisMask();</div> -<div class="line"><a name="l03132"></a><span class="lineno"> 3132</span>  descriptor.m_DataLayout = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> -<div class="line"><a name="l03133"></a><span class="lineno"> 3133</span>  </div> -<div class="line"><a name="l03134"></a><span class="lineno"> 3134</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03135"></a><span class="lineno"> 3135</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddStridedSliceLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03111"></a><span class="lineno"> 3111</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03112"></a><span class="lineno"> 3112</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSliceLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03113"></a><span class="lineno"> 3113</span>  </div> +<div class="line"><a name="l03114"></a><span class="lineno"> 3114</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03115"></a><span class="lineno"> 3115</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03116"></a><span class="lineno"> 3116</span>  </div> +<div class="line"><a name="l03117"></a><span class="lineno"> 3117</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03118"></a><span class="lineno"> 3118</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03119"></a><span class="lineno"> 3119</span> }</div> +<div class="line"><a name="l03120"></a><span class="lineno"> 3120</span>  </div> +<div class="line"><a name="l03121"></a><span class="lineno"> 3121</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseStridedSlice(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03122"></a><span class="lineno"> 3122</span> {</div> +<div class="line"><a name="l03123"></a><span class="lineno"> 3123</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03124"></a><span class="lineno"> 3124</span>  </div> +<div class="line"><a name="l03125"></a><span class="lineno"> 3125</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03126"></a><span class="lineno"> 3126</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03127"></a><span class="lineno"> 3127</span>  </div> +<div class="line"><a name="l03128"></a><span class="lineno"> 3128</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03129"></a><span class="lineno"> 3129</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03130"></a><span class="lineno"> 3130</span>  </div> +<div class="line"><a name="l03131"></a><span class="lineno"> 3131</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_StridedSliceLayer()->descriptor();</div> +<div class="line"><a name="l03132"></a><span class="lineno"> 3132</span>  </div> +<div class="line"><a name="l03133"></a><span class="lineno"> 3133</span>  <span class="keyword">auto</span> flatBufferBegin = flatBufferDescriptor->begin();</div> +<div class="line"><a name="l03134"></a><span class="lineno"> 3134</span>  <span class="keyword">auto</span> flatBufferEnd = flatBufferDescriptor->end();</div> +<div class="line"><a name="l03135"></a><span class="lineno"> 3135</span>  <span class="keyword">auto</span> flatBufferStride = flatBufferDescriptor->stride();</div> <div class="line"><a name="l03136"></a><span class="lineno"> 3136</span>  </div> -<div class="line"><a name="l03137"></a><span class="lineno"> 3137</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03138"></a><span class="lineno"> 3138</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03139"></a><span class="lineno"> 3139</span>  </div> -<div class="line"><a name="l03140"></a><span class="lineno"> 3140</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03141"></a><span class="lineno"> 3141</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03142"></a><span class="lineno"> 3142</span> }</div> +<div class="line"><a name="l03137"></a><span class="lineno"> 3137</span>  <span class="keywordflow">if</span> (!(flatBufferBegin->size() == flatBufferEnd->size() &&</div> +<div class="line"><a name="l03138"></a><span class="lineno"> 3138</span>  flatBufferBegin->size() == flatBufferStride->size()))</div> +<div class="line"><a name="l03139"></a><span class="lineno"> 3139</span>  {</div> +<div class="line"><a name="l03140"></a><span class="lineno"> 3140</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(fmt::format(<span class="stringliteral">"The size of the begin, end, and stride must be equal {}"</span>,</div> +<div class="line"><a name="l03141"></a><span class="lineno"> 3141</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div> +<div class="line"><a name="l03142"></a><span class="lineno"> 3142</span>  }</div> <div class="line"><a name="l03143"></a><span class="lineno"> 3143</span>  </div> -<div class="line"><a name="l03144"></a><span class="lineno"> 3144</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSubtraction(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03145"></a><span class="lineno"> 3145</span> {</div> -<div class="line"><a name="l03146"></a><span class="lineno"> 3146</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03147"></a><span class="lineno"> 3147</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03148"></a><span class="lineno"> 3148</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l03149"></a><span class="lineno"> 3149</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l03150"></a><span class="lineno"> 3150</span>  </div> -<div class="line"><a name="l03151"></a><span class="lineno"> 3151</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03152"></a><span class="lineno"> 3152</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03153"></a><span class="lineno"> 3153</span>  </div> -<div class="line"><a name="l03154"></a><span class="lineno"> 3154</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03155"></a><span class="lineno"> 3155</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047ae80155eceb940c89e2de63ad05868db2">armnn::BinaryOperation::Sub</a>);</div> -<div class="line"><a name="l03156"></a><span class="lineno"> 3156</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l03157"></a><span class="lineno"> 3157</span>  </div> -<div class="line"><a name="l03158"></a><span class="lineno"> 3158</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03159"></a><span class="lineno"> 3159</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03160"></a><span class="lineno"> 3160</span>  </div> -<div class="line"><a name="l03161"></a><span class="lineno"> 3161</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03162"></a><span class="lineno"> 3162</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03163"></a><span class="lineno"> 3163</span> }</div> -<div class="line"><a name="l03164"></a><span class="lineno"> 3164</span>  </div> -<div class="line"><a name="l03165"></a><span class="lineno"> 3165</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseGather(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03166"></a><span class="lineno"> 3166</span> {</div> -<div class="line"><a name="l03167"></a><span class="lineno"> 3167</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03168"></a><span class="lineno"> 3168</span>  </div> -<div class="line"><a name="l03169"></a><span class="lineno"> 3169</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03170"></a><span class="lineno"> 3170</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l03171"></a><span class="lineno"> 3171</span>  </div> -<div class="line"><a name="l03172"></a><span class="lineno"> 3172</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03173"></a><span class="lineno"> 3173</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03174"></a><span class="lineno"> 3174</span>  </div> -<div class="line"><a name="l03175"></a><span class="lineno"> 3175</span>  <a class="code" href="structarmnn_1_1_gather_descriptor.html">armnn::GatherDescriptor</a> descriptor;</div> -<div class="line"><a name="l03176"></a><span class="lineno"> 3176</span>  descriptor.<a class="code" href="structarmnn_1_1_gather_descriptor.html#a35d11c7d509d1adbae1ae01c58394a7f">m_Axis</a> = graph->layers()->Get(layerIndex)->layer_as_GatherLayer()->descriptor()->axis();</div> -<div class="line"><a name="l03177"></a><span class="lineno"> 3177</span>  </div> -<div class="line"><a name="l03178"></a><span class="lineno"> 3178</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03179"></a><span class="lineno"> 3179</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddGatherLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l03180"></a><span class="lineno"> 3180</span>  </div> -<div class="line"><a name="l03181"></a><span class="lineno"> 3181</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03182"></a><span class="lineno"> 3182</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03183"></a><span class="lineno"> 3183</span>  </div> -<div class="line"><a name="l03184"></a><span class="lineno"> 3184</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03185"></a><span class="lineno"> 3185</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03186"></a><span class="lineno"> 3186</span> }</div> -<div class="line"><a name="l03187"></a><span class="lineno"> 3187</span>  </div> -<div class="line"><a name="l03188"></a><span class="lineno"> 3188</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseGatherNd(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03189"></a><span class="lineno"> 3189</span> {</div> -<div class="line"><a name="l03190"></a><span class="lineno"> 3190</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03191"></a><span class="lineno"> 3191</span>  </div> -<div class="line"><a name="l03192"></a><span class="lineno"> 3192</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03193"></a><span class="lineno"> 3193</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l03194"></a><span class="lineno"> 3194</span>  </div> -<div class="line"><a name="l03195"></a><span class="lineno"> 3195</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03196"></a><span class="lineno"> 3196</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03197"></a><span class="lineno"> 3197</span>  </div> -<div class="line"><a name="l03198"></a><span class="lineno"> 3198</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03199"></a><span class="lineno"> 3199</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddGatherNdLayer(layerName.c_str());</div> -<div class="line"><a name="l03200"></a><span class="lineno"> 3200</span>  </div> -<div class="line"><a name="l03201"></a><span class="lineno"> 3201</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03202"></a><span class="lineno"> 3202</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03203"></a><span class="lineno"> 3203</span>  </div> -<div class="line"><a name="l03204"></a><span class="lineno"> 3204</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03205"></a><span class="lineno"> 3205</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03206"></a><span class="lineno"> 3206</span> }</div> -<div class="line"><a name="l03207"></a><span class="lineno"> 3207</span>  </div> -<div class="line"><a name="l03208"></a><span class="lineno"> 3208</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMean(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03209"></a><span class="lineno"> 3209</span> {</div> -<div class="line"><a name="l03210"></a><span class="lineno"> 3210</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03211"></a><span class="lineno"> 3211</span>  </div> -<div class="line"><a name="l03212"></a><span class="lineno"> 3212</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03213"></a><span class="lineno"> 3213</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l03214"></a><span class="lineno"> 3214</span>  </div> -<div class="line"><a name="l03215"></a><span class="lineno"> 3215</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03216"></a><span class="lineno"> 3216</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03217"></a><span class="lineno"> 3217</span>  </div> -<div class="line"><a name="l03218"></a><span class="lineno"> 3218</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_MeanLayer()->descriptor();</div> -<div class="line"><a name="l03219"></a><span class="lineno"> 3219</span>  <span class="keyword">auto</span> flatBufferAxis = flatBufferDescriptor->axis();</div> -<div class="line"><a name="l03220"></a><span class="lineno"> 3220</span>  <span class="keyword">auto</span> flatBufferKeepDims = flatBufferDescriptor->keepDims();</div> -<div class="line"><a name="l03221"></a><span class="lineno"> 3221</span>  </div> -<div class="line"><a name="l03222"></a><span class="lineno"> 3222</span>  <a class="code" href="structarmnn_1_1_mean_descriptor.html">armnn::MeanDescriptor</a> descriptor;</div> -<div class="line"><a name="l03223"></a><span class="lineno"> 3223</span>  descriptor.<a class="code" href="structarmnn_1_1_mean_descriptor.html#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a> = std::vector<unsigned int>(flatBufferAxis->begin(), flatBufferAxis->end());</div> -<div class="line"><a name="l03224"></a><span class="lineno"> 3224</span>  descriptor.<a class="code" href="structarmnn_1_1_mean_descriptor.html#a28e0548abfc4e79c48f29a3d11a062e9">m_KeepDims</a> = flatBufferKeepDims;</div> +<div class="line"><a name="l03144"></a><span class="lineno"> 3144</span>  std::vector<int> begin(flatBufferBegin->begin(), flatBufferBegin->end());</div> +<div class="line"><a name="l03145"></a><span class="lineno"> 3145</span>  std::vector<int> end(flatBufferEnd->begin(), flatBufferEnd->end());</div> +<div class="line"><a name="l03146"></a><span class="lineno"> 3146</span>  std::vector<int> stride(flatBufferStride->begin(), flatBufferStride->end());</div> +<div class="line"><a name="l03147"></a><span class="lineno"> 3147</span>  </div> +<div class="line"><a name="l03148"></a><span class="lineno"> 3148</span>  <a class="code" href="structarmnn_1_1_strided_slice_descriptor.html">armnn::StridedSliceDescriptor</a> descriptor(begin, end, stride);</div> +<div class="line"><a name="l03149"></a><span class="lineno"> 3149</span>  descriptor.m_BeginMask = flatBufferDescriptor->beginMask();</div> +<div class="line"><a name="l03150"></a><span class="lineno"> 3150</span>  descriptor.m_EndMask = flatBufferDescriptor->endMask();</div> +<div class="line"><a name="l03151"></a><span class="lineno"> 3151</span>  descriptor.m_ShrinkAxisMask = flatBufferDescriptor->shrinkAxisMask();</div> +<div class="line"><a name="l03152"></a><span class="lineno"> 3152</span>  descriptor.m_EllipsisMask = flatBufferDescriptor->ellipsisMask();</div> +<div class="line"><a name="l03153"></a><span class="lineno"> 3153</span>  descriptor.m_NewAxisMask = flatBufferDescriptor->newAxisMask();</div> +<div class="line"><a name="l03154"></a><span class="lineno"> 3154</span>  descriptor.m_DataLayout = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div> +<div class="line"><a name="l03155"></a><span class="lineno"> 3155</span>  </div> +<div class="line"><a name="l03156"></a><span class="lineno"> 3156</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03157"></a><span class="lineno"> 3157</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddStridedSliceLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03158"></a><span class="lineno"> 3158</span>  </div> +<div class="line"><a name="l03159"></a><span class="lineno"> 3159</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03160"></a><span class="lineno"> 3160</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03161"></a><span class="lineno"> 3161</span>  </div> +<div class="line"><a name="l03162"></a><span class="lineno"> 3162</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03163"></a><span class="lineno"> 3163</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03164"></a><span class="lineno"> 3164</span> }</div> +<div class="line"><a name="l03165"></a><span class="lineno"> 3165</span>  </div> +<div class="line"><a name="l03166"></a><span class="lineno"> 3166</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSubtraction(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03167"></a><span class="lineno"> 3167</span> {</div> +<div class="line"><a name="l03168"></a><span class="lineno"> 3168</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03169"></a><span class="lineno"> 3169</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03170"></a><span class="lineno"> 3170</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l03171"></a><span class="lineno"> 3171</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l03172"></a><span class="lineno"> 3172</span>  </div> +<div class="line"><a name="l03173"></a><span class="lineno"> 3173</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03174"></a><span class="lineno"> 3174</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03175"></a><span class="lineno"> 3175</span>  </div> +<div class="line"><a name="l03176"></a><span class="lineno"> 3176</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03177"></a><span class="lineno"> 3177</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047ae80155eceb940c89e2de63ad05868db2">armnn::BinaryOperation::Sub</a>);</div> +<div class="line"><a name="l03178"></a><span class="lineno"> 3178</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddElementwiseBinaryLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03179"></a><span class="lineno"> 3179</span>  </div> +<div class="line"><a name="l03180"></a><span class="lineno"> 3180</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03181"></a><span class="lineno"> 3181</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03182"></a><span class="lineno"> 3182</span>  </div> +<div class="line"><a name="l03183"></a><span class="lineno"> 3183</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03184"></a><span class="lineno"> 3184</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03185"></a><span class="lineno"> 3185</span> }</div> +<div class="line"><a name="l03186"></a><span class="lineno"> 3186</span>  </div> +<div class="line"><a name="l03187"></a><span class="lineno"> 3187</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseGather(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03188"></a><span class="lineno"> 3188</span> {</div> +<div class="line"><a name="l03189"></a><span class="lineno"> 3189</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03190"></a><span class="lineno"> 3190</span>  </div> +<div class="line"><a name="l03191"></a><span class="lineno"> 3191</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03192"></a><span class="lineno"> 3192</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l03193"></a><span class="lineno"> 3193</span>  </div> +<div class="line"><a name="l03194"></a><span class="lineno"> 3194</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03195"></a><span class="lineno"> 3195</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03196"></a><span class="lineno"> 3196</span>  </div> +<div class="line"><a name="l03197"></a><span class="lineno"> 3197</span>  <a class="code" href="structarmnn_1_1_gather_descriptor.html">armnn::GatherDescriptor</a> descriptor;</div> +<div class="line"><a name="l03198"></a><span class="lineno"> 3198</span>  descriptor.<a class="code" href="structarmnn_1_1_gather_descriptor.html#a35d11c7d509d1adbae1ae01c58394a7f">m_Axis</a> = graph->layers()->Get(layerIndex)->layer_as_GatherLayer()->descriptor()->axis();</div> +<div class="line"><a name="l03199"></a><span class="lineno"> 3199</span>  </div> +<div class="line"><a name="l03200"></a><span class="lineno"> 3200</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03201"></a><span class="lineno"> 3201</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddGatherLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03202"></a><span class="lineno"> 3202</span>  </div> +<div class="line"><a name="l03203"></a><span class="lineno"> 3203</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03204"></a><span class="lineno"> 3204</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03205"></a><span class="lineno"> 3205</span>  </div> +<div class="line"><a name="l03206"></a><span class="lineno"> 3206</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03207"></a><span class="lineno"> 3207</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03208"></a><span class="lineno"> 3208</span> }</div> +<div class="line"><a name="l03209"></a><span class="lineno"> 3209</span>  </div> +<div class="line"><a name="l03210"></a><span class="lineno"> 3210</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseGatherNd(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03211"></a><span class="lineno"> 3211</span> {</div> +<div class="line"><a name="l03212"></a><span class="lineno"> 3212</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03213"></a><span class="lineno"> 3213</span>  </div> +<div class="line"><a name="l03214"></a><span class="lineno"> 3214</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03215"></a><span class="lineno"> 3215</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l03216"></a><span class="lineno"> 3216</span>  </div> +<div class="line"><a name="l03217"></a><span class="lineno"> 3217</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03218"></a><span class="lineno"> 3218</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03219"></a><span class="lineno"> 3219</span>  </div> +<div class="line"><a name="l03220"></a><span class="lineno"> 3220</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03221"></a><span class="lineno"> 3221</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddGatherNdLayer(layerName.c_str());</div> +<div class="line"><a name="l03222"></a><span class="lineno"> 3222</span>  </div> +<div class="line"><a name="l03223"></a><span class="lineno"> 3223</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03224"></a><span class="lineno"> 3224</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> <div class="line"><a name="l03225"></a><span class="lineno"> 3225</span>  </div> -<div class="line"><a name="l03226"></a><span class="lineno"> 3226</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03227"></a><span class="lineno"> 3227</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddMeanLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l03228"></a><span class="lineno"> 3228</span>  </div> -<div class="line"><a name="l03229"></a><span class="lineno"> 3229</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03230"></a><span class="lineno"> 3230</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03231"></a><span class="lineno"> 3231</span>  </div> -<div class="line"><a name="l03232"></a><span class="lineno"> 3232</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03233"></a><span class="lineno"> 3233</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03234"></a><span class="lineno"> 3234</span> }</div> -<div class="line"><a name="l03235"></a><span class="lineno"> 3235</span>  </div> -<div class="line"><a name="l03236"></a><span class="lineno"> 3236</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSplitter(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03237"></a><span class="lineno"> 3237</span> {</div> -<div class="line"><a name="l03238"></a><span class="lineno"> 3238</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03226"></a><span class="lineno"> 3226</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03227"></a><span class="lineno"> 3227</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03228"></a><span class="lineno"> 3228</span> }</div> +<div class="line"><a name="l03229"></a><span class="lineno"> 3229</span>  </div> +<div class="line"><a name="l03230"></a><span class="lineno"> 3230</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMean(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03231"></a><span class="lineno"> 3231</span> {</div> +<div class="line"><a name="l03232"></a><span class="lineno"> 3232</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03233"></a><span class="lineno"> 3233</span>  </div> +<div class="line"><a name="l03234"></a><span class="lineno"> 3234</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03235"></a><span class="lineno"> 3235</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03236"></a><span class="lineno"> 3236</span>  </div> +<div class="line"><a name="l03237"></a><span class="lineno"> 3237</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03238"></a><span class="lineno"> 3238</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> <div class="line"><a name="l03239"></a><span class="lineno"> 3239</span>  </div> -<div class="line"><a name="l03240"></a><span class="lineno"> 3240</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03241"></a><span class="lineno"> 3241</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l03242"></a><span class="lineno"> 3242</span>  </div> -<div class="line"><a name="l03243"></a><span class="lineno"> 3243</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03244"></a><span class="lineno"> 3244</span>  </div> -<div class="line"><a name="l03245"></a><span class="lineno"> 3245</span>  <span class="keyword">auto</span> flatBufferViewsDescriptor = graph->layers()->Get(layerIndex)->layer_as_SplitterLayer()->descriptor();</div> -<div class="line"><a name="l03246"></a><span class="lineno"> 3246</span>  <span class="keyword">auto</span> flatBufferViewSizes = flatBufferViewsDescriptor->viewSizes();</div> -<div class="line"><a name="l03247"></a><span class="lineno"> 3247</span>  <span class="keyword">auto</span> flatBufferOriginsDescriptor = flatBufferViewsDescriptor->origins();</div> -<div class="line"><a name="l03248"></a><span class="lineno"> 3248</span>  <span class="keyword">auto</span> flatBufferViewOrigins = flatBufferOriginsDescriptor->viewOrigins();</div> -<div class="line"><a name="l03249"></a><span class="lineno"> 3249</span>  uint32_t numViews = flatBufferOriginsDescriptor->numViews();</div> -<div class="line"><a name="l03250"></a><span class="lineno"> 3250</span>  uint32_t numDimensions = flatBufferOriginsDescriptor->numDimensions();</div> -<div class="line"><a name="l03251"></a><span class="lineno"> 3251</span>  </div> -<div class="line"><a name="l03252"></a><span class="lineno"> 3252</span>  <span class="comment">// Check numViews and numDimensions corresponds to the ones already serialized ...</span></div> -<div class="line"><a name="l03253"></a><span class="lineno"> 3253</span>  <span class="comment">// numViews == flatBufferViewSizes.size();</span></div> -<div class="line"><a name="l03254"></a><span class="lineno"> 3254</span>  <span class="comment">// foreach: numDimensions == flatBufferViewSizes[x].size();</span></div> -<div class="line"><a name="l03255"></a><span class="lineno"> 3255</span>  </div> -<div class="line"><a name="l03256"></a><span class="lineno"> 3256</span>  <a class="code" href="structarmnn_1_1_views_descriptor.html">armnn::ViewsDescriptor</a> viewsDescriptor(numViews, numDimensions);</div> -<div class="line"><a name="l03257"></a><span class="lineno"> 3257</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> vIdx = 0; vIdx < numViews; ++vIdx)</div> -<div class="line"><a name="l03258"></a><span class="lineno"> 3258</span>  {</div> -<div class="line"><a name="l03259"></a><span class="lineno"> 3259</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dIdx = 0; dIdx < numDimensions; ++dIdx)</div> -<div class="line"><a name="l03260"></a><span class="lineno"> 3260</span>  {</div> -<div class="line"><a name="l03261"></a><span class="lineno"> 3261</span>  viewsDescriptor.SetViewSize(vIdx, dIdx, flatBufferViewSizes->Get(vIdx)->data()->Get(dIdx));</div> -<div class="line"><a name="l03262"></a><span class="lineno"> 3262</span>  viewsDescriptor.SetViewOriginCoord(vIdx, dIdx, flatBufferViewOrigins->Get(vIdx)->data()->Get(dIdx));</div> -<div class="line"><a name="l03263"></a><span class="lineno"> 3263</span>  }</div> -<div class="line"><a name="l03264"></a><span class="lineno"> 3264</span>  }</div> -<div class="line"><a name="l03265"></a><span class="lineno"> 3265</span>  </div> -<div class="line"><a name="l03266"></a><span class="lineno"> 3266</span>  <span class="keywordflow">if</span> (flatBufferViewsDescriptor->hasAxis())</div> -<div class="line"><a name="l03267"></a><span class="lineno"> 3267</span>  {</div> -<div class="line"><a name="l03268"></a><span class="lineno"> 3268</span>  viewsDescriptor.SetAxis(flatBufferViewsDescriptor->axis());</div> -<div class="line"><a name="l03269"></a><span class="lineno"> 3269</span>  }</div> -<div class="line"><a name="l03270"></a><span class="lineno"> 3270</span>  </div> -<div class="line"><a name="l03271"></a><span class="lineno"> 3271</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03272"></a><span class="lineno"> 3272</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSplitterLayer(viewsDescriptor, layerName.c_str());</div> +<div class="line"><a name="l03240"></a><span class="lineno"> 3240</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_MeanLayer()->descriptor();</div> +<div class="line"><a name="l03241"></a><span class="lineno"> 3241</span>  <span class="keyword">auto</span> flatBufferAxis = flatBufferDescriptor->axis();</div> +<div class="line"><a name="l03242"></a><span class="lineno"> 3242</span>  <span class="keyword">auto</span> flatBufferKeepDims = flatBufferDescriptor->keepDims();</div> +<div class="line"><a name="l03243"></a><span class="lineno"> 3243</span>  </div> +<div class="line"><a name="l03244"></a><span class="lineno"> 3244</span>  <a class="code" href="structarmnn_1_1_mean_descriptor.html">armnn::MeanDescriptor</a> descriptor;</div> +<div class="line"><a name="l03245"></a><span class="lineno"> 3245</span>  descriptor.<a class="code" href="structarmnn_1_1_mean_descriptor.html#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a> = std::vector<unsigned int>(flatBufferAxis->begin(), flatBufferAxis->end());</div> +<div class="line"><a name="l03246"></a><span class="lineno"> 3246</span>  descriptor.<a class="code" href="structarmnn_1_1_mean_descriptor.html#a28e0548abfc4e79c48f29a3d11a062e9">m_KeepDims</a> = flatBufferKeepDims;</div> +<div class="line"><a name="l03247"></a><span class="lineno"> 3247</span>  </div> +<div class="line"><a name="l03248"></a><span class="lineno"> 3248</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03249"></a><span class="lineno"> 3249</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddMeanLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03250"></a><span class="lineno"> 3250</span>  </div> +<div class="line"><a name="l03251"></a><span class="lineno"> 3251</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03252"></a><span class="lineno"> 3252</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03253"></a><span class="lineno"> 3253</span>  </div> +<div class="line"><a name="l03254"></a><span class="lineno"> 3254</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03255"></a><span class="lineno"> 3255</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03256"></a><span class="lineno"> 3256</span> }</div> +<div class="line"><a name="l03257"></a><span class="lineno"> 3257</span>  </div> +<div class="line"><a name="l03258"></a><span class="lineno"> 3258</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSplitter(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03259"></a><span class="lineno"> 3259</span> {</div> +<div class="line"><a name="l03260"></a><span class="lineno"> 3260</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03261"></a><span class="lineno"> 3261</span>  </div> +<div class="line"><a name="l03262"></a><span class="lineno"> 3262</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03263"></a><span class="lineno"> 3263</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03264"></a><span class="lineno"> 3264</span>  </div> +<div class="line"><a name="l03265"></a><span class="lineno"> 3265</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03266"></a><span class="lineno"> 3266</span>  </div> +<div class="line"><a name="l03267"></a><span class="lineno"> 3267</span>  <span class="keyword">auto</span> flatBufferViewsDescriptor = graph->layers()->Get(layerIndex)->layer_as_SplitterLayer()->descriptor();</div> +<div class="line"><a name="l03268"></a><span class="lineno"> 3268</span>  <span class="keyword">auto</span> flatBufferViewSizes = flatBufferViewsDescriptor->viewSizes();</div> +<div class="line"><a name="l03269"></a><span class="lineno"> 3269</span>  <span class="keyword">auto</span> flatBufferOriginsDescriptor = flatBufferViewsDescriptor->origins();</div> +<div class="line"><a name="l03270"></a><span class="lineno"> 3270</span>  <span class="keyword">auto</span> flatBufferViewOrigins = flatBufferOriginsDescriptor->viewOrigins();</div> +<div class="line"><a name="l03271"></a><span class="lineno"> 3271</span>  uint32_t numViews = flatBufferOriginsDescriptor->numViews();</div> +<div class="line"><a name="l03272"></a><span class="lineno"> 3272</span>  uint32_t numDimensions = flatBufferOriginsDescriptor->numDimensions();</div> <div class="line"><a name="l03273"></a><span class="lineno"> 3273</span>  </div> -<div class="line"><a name="l03274"></a><span class="lineno"> 3274</span>  <span class="comment">// I could have as many outputs as views ...</span></div> -<div class="line"><a name="l03275"></a><span class="lineno"> 3275</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> vIdx = 0; vIdx < numViews; ++vIdx)</div> -<div class="line"><a name="l03276"></a><span class="lineno"> 3276</span>  {</div> -<div class="line"><a name="l03277"></a><span class="lineno"> 3277</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[vIdx]);</div> -<div class="line"><a name="l03278"></a><span class="lineno"> 3278</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(vIdx).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03279"></a><span class="lineno"> 3279</span>  }</div> -<div class="line"><a name="l03280"></a><span class="lineno"> 3280</span>  </div> -<div class="line"><a name="l03281"></a><span class="lineno"> 3281</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03282"></a><span class="lineno"> 3282</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03283"></a><span class="lineno"> 3283</span> }</div> -<div class="line"><a name="l03284"></a><span class="lineno"> 3284</span>  </div> -<div class="line"><a name="l03285"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af7bb02c61c6a5663121da024b7e042e8"> 3285</a></span> <a class="code" href="structarmnn_1_1_lstm_descriptor.html">armnn::LstmDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af7bb02c61c6a5663121da024b7e042e8">IDeserializer::DeserializerImpl::GetLstmDescriptor</a>(<a class="code" href="namespacearmnn_deserializer.html#a15397ee26bc4b7d3a459b05e457be428">LstmDescriptorPtr</a> lstmDescriptor)</div> -<div class="line"><a name="l03286"></a><span class="lineno"> 3286</span> {</div> -<div class="line"><a name="l03287"></a><span class="lineno"> 3287</span>  <a class="code" href="structarmnn_1_1_lstm_descriptor.html">armnn::LstmDescriptor</a> desc;</div> -<div class="line"><a name="l03288"></a><span class="lineno"> 3288</span>  </div> -<div class="line"><a name="l03289"></a><span class="lineno"> 3289</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = lstmDescriptor->activationFunc();</div> -<div class="line"><a name="l03290"></a><span class="lineno"> 3290</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = lstmDescriptor->clippingThresCell();</div> -<div class="line"><a name="l03291"></a><span class="lineno"> 3291</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a> = lstmDescriptor->clippingThresProj();</div> -<div class="line"><a name="l03292"></a><span class="lineno"> 3292</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = lstmDescriptor->cifgEnabled();</div> -<div class="line"><a name="l03293"></a><span class="lineno"> 3293</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = lstmDescriptor->peepholeEnabled();</div> -<div class="line"><a name="l03294"></a><span class="lineno"> 3294</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = lstmDescriptor->projectionEnabled();</div> -<div class="line"><a name="l03295"></a><span class="lineno"> 3295</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = lstmDescriptor->layerNormEnabled();</div> -<div class="line"><a name="l03296"></a><span class="lineno"> 3296</span>  </div> -<div class="line"><a name="l03297"></a><span class="lineno"> 3297</span>  <span class="keywordflow">return</span> desc;</div> -<div class="line"><a name="l03298"></a><span class="lineno"> 3298</span> }</div> -<div class="line"><a name="l03299"></a><span class="lineno"> 3299</span>  </div> -<div class="line"><a name="l03300"></a><span class="lineno"> 3300</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseLstm(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03301"></a><span class="lineno"> 3301</span> {</div> -<div class="line"><a name="l03302"></a><span class="lineno"> 3302</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03303"></a><span class="lineno"> 3303</span>  </div> -<div class="line"><a name="l03304"></a><span class="lineno"> 3304</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03305"></a><span class="lineno"> 3305</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div> +<div class="line"><a name="l03274"></a><span class="lineno"> 3274</span>  <span class="comment">// Check numViews and numDimensions corresponds to the ones already serialized ...</span></div> +<div class="line"><a name="l03275"></a><span class="lineno"> 3275</span>  <span class="comment">// numViews == flatBufferViewSizes.size();</span></div> +<div class="line"><a name="l03276"></a><span class="lineno"> 3276</span>  <span class="comment">// foreach: numDimensions == flatBufferViewSizes[x].size();</span></div> +<div class="line"><a name="l03277"></a><span class="lineno"> 3277</span>  </div> +<div class="line"><a name="l03278"></a><span class="lineno"> 3278</span>  <a class="code" href="structarmnn_1_1_views_descriptor.html">armnn::ViewsDescriptor</a> viewsDescriptor(numViews, numDimensions);</div> +<div class="line"><a name="l03279"></a><span class="lineno"> 3279</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> vIdx = 0; vIdx < numViews; ++vIdx)</div> +<div class="line"><a name="l03280"></a><span class="lineno"> 3280</span>  {</div> +<div class="line"><a name="l03281"></a><span class="lineno"> 3281</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dIdx = 0; dIdx < numDimensions; ++dIdx)</div> +<div class="line"><a name="l03282"></a><span class="lineno"> 3282</span>  {</div> +<div class="line"><a name="l03283"></a><span class="lineno"> 3283</span>  viewsDescriptor.SetViewSize(vIdx, dIdx, flatBufferViewSizes->Get(vIdx)->data()->Get(dIdx));</div> +<div class="line"><a name="l03284"></a><span class="lineno"> 3284</span>  viewsDescriptor.SetViewOriginCoord(vIdx, dIdx, flatBufferViewOrigins->Get(vIdx)->data()->Get(dIdx));</div> +<div class="line"><a name="l03285"></a><span class="lineno"> 3285</span>  }</div> +<div class="line"><a name="l03286"></a><span class="lineno"> 3286</span>  }</div> +<div class="line"><a name="l03287"></a><span class="lineno"> 3287</span>  </div> +<div class="line"><a name="l03288"></a><span class="lineno"> 3288</span>  <span class="keywordflow">if</span> (flatBufferViewsDescriptor->hasAxis())</div> +<div class="line"><a name="l03289"></a><span class="lineno"> 3289</span>  {</div> +<div class="line"><a name="l03290"></a><span class="lineno"> 3290</span>  viewsDescriptor.SetAxis(flatBufferViewsDescriptor->axis());</div> +<div class="line"><a name="l03291"></a><span class="lineno"> 3291</span>  }</div> +<div class="line"><a name="l03292"></a><span class="lineno"> 3292</span>  </div> +<div class="line"><a name="l03293"></a><span class="lineno"> 3293</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03294"></a><span class="lineno"> 3294</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSplitterLayer(viewsDescriptor, layerName.c_str());</div> +<div class="line"><a name="l03295"></a><span class="lineno"> 3295</span>  </div> +<div class="line"><a name="l03296"></a><span class="lineno"> 3296</span>  <span class="comment">// I could have as many outputs as views ...</span></div> +<div class="line"><a name="l03297"></a><span class="lineno"> 3297</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> vIdx = 0; vIdx < numViews; ++vIdx)</div> +<div class="line"><a name="l03298"></a><span class="lineno"> 3298</span>  {</div> +<div class="line"><a name="l03299"></a><span class="lineno"> 3299</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[vIdx]);</div> +<div class="line"><a name="l03300"></a><span class="lineno"> 3300</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(vIdx).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03301"></a><span class="lineno"> 3301</span>  }</div> +<div class="line"><a name="l03302"></a><span class="lineno"> 3302</span>  </div> +<div class="line"><a name="l03303"></a><span class="lineno"> 3303</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03304"></a><span class="lineno"> 3304</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03305"></a><span class="lineno"> 3305</span> }</div> <div class="line"><a name="l03306"></a><span class="lineno"> 3306</span>  </div> -<div class="line"><a name="l03307"></a><span class="lineno"> 3307</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03308"></a><span class="lineno"> 3308</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 4);</div> -<div class="line"><a name="l03309"></a><span class="lineno"> 3309</span>  </div> -<div class="line"><a name="l03310"></a><span class="lineno"> 3310</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_LstmLayer();</div> -<div class="line"><a name="l03311"></a><span class="lineno"> 3311</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03312"></a><span class="lineno"> 3312</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> -<div class="line"><a name="l03313"></a><span class="lineno"> 3313</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div> -<div class="line"><a name="l03314"></a><span class="lineno"> 3314</span>  </div> -<div class="line"><a name="l03315"></a><span class="lineno"> 3315</span>  <span class="keyword">auto</span> lstmDescriptor = GetLstmDescriptor(flatBufferDescriptor);</div> -<div class="line"><a name="l03316"></a><span class="lineno"> 3316</span>  </div> -<div class="line"><a name="l03317"></a><span class="lineno"> 3317</span>  <a class="code" href="structarmnn_1_1_lstm_input_params.html">armnn::LstmInputParams</a> lstmInputParams;</div> +<div class="line"><a name="l03307"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af7bb02c61c6a5663121da024b7e042e8"> 3307</a></span> <a class="code" href="structarmnn_1_1_lstm_descriptor.html">armnn::LstmDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af7bb02c61c6a5663121da024b7e042e8">IDeserializer::DeserializerImpl::GetLstmDescriptor</a>(<a class="code" href="namespacearmnn_deserializer.html#a15397ee26bc4b7d3a459b05e457be428">LstmDescriptorPtr</a> lstmDescriptor)</div> +<div class="line"><a name="l03308"></a><span class="lineno"> 3308</span> {</div> +<div class="line"><a name="l03309"></a><span class="lineno"> 3309</span>  <a class="code" href="structarmnn_1_1_lstm_descriptor.html">armnn::LstmDescriptor</a> desc;</div> +<div class="line"><a name="l03310"></a><span class="lineno"> 3310</span>  </div> +<div class="line"><a name="l03311"></a><span class="lineno"> 3311</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = lstmDescriptor->activationFunc();</div> +<div class="line"><a name="l03312"></a><span class="lineno"> 3312</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = lstmDescriptor->clippingThresCell();</div> +<div class="line"><a name="l03313"></a><span class="lineno"> 3313</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a> = lstmDescriptor->clippingThresProj();</div> +<div class="line"><a name="l03314"></a><span class="lineno"> 3314</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = lstmDescriptor->cifgEnabled();</div> +<div class="line"><a name="l03315"></a><span class="lineno"> 3315</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = lstmDescriptor->peepholeEnabled();</div> +<div class="line"><a name="l03316"></a><span class="lineno"> 3316</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = lstmDescriptor->projectionEnabled();</div> +<div class="line"><a name="l03317"></a><span class="lineno"> 3317</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = lstmDescriptor->layerNormEnabled();</div> <div class="line"><a name="l03318"></a><span class="lineno"> 3318</span>  </div> -<div class="line"><a name="l03319"></a><span class="lineno"> 3319</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div> -<div class="line"><a name="l03320"></a><span class="lineno"> 3320</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div> -<div class="line"><a name="l03321"></a><span class="lineno"> 3321</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div> -<div class="line"><a name="l03322"></a><span class="lineno"> 3322</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div> -<div class="line"><a name="l03323"></a><span class="lineno"> 3323</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div> -<div class="line"><a name="l03324"></a><span class="lineno"> 3324</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div> -<div class="line"><a name="l03325"></a><span class="lineno"> 3325</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div> -<div class="line"><a name="l03326"></a><span class="lineno"> 3326</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellBias());</div> -<div class="line"><a name="l03327"></a><span class="lineno"> 3327</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div> +<div class="line"><a name="l03319"></a><span class="lineno"> 3319</span>  <span class="keywordflow">return</span> desc;</div> +<div class="line"><a name="l03320"></a><span class="lineno"> 3320</span> }</div> +<div class="line"><a name="l03321"></a><span class="lineno"> 3321</span>  </div> +<div class="line"><a name="l03322"></a><span class="lineno"> 3322</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseLstm(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03323"></a><span class="lineno"> 3323</span> {</div> +<div class="line"><a name="l03324"></a><span class="lineno"> 3324</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03325"></a><span class="lineno"> 3325</span>  </div> +<div class="line"><a name="l03326"></a><span class="lineno"> 3326</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03327"></a><span class="lineno"> 3327</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div> <div class="line"><a name="l03328"></a><span class="lineno"> 3328</span>  </div> -<div class="line"><a name="l03329"></a><span class="lineno"> 3329</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div> -<div class="line"><a name="l03330"></a><span class="lineno"> 3330</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div> -<div class="line"><a name="l03331"></a><span class="lineno"> 3331</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div> -<div class="line"><a name="l03332"></a><span class="lineno"> 3332</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div> -<div class="line"><a name="l03333"></a><span class="lineno"> 3333</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div> -<div class="line"><a name="l03334"></a><span class="lineno"> 3334</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div> -<div class="line"><a name="l03335"></a><span class="lineno"> 3335</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div> -<div class="line"><a name="l03336"></a><span class="lineno"> 3336</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div> -<div class="line"><a name="l03337"></a><span class="lineno"> 3337</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div> +<div class="line"><a name="l03329"></a><span class="lineno"> 3329</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03330"></a><span class="lineno"> 3330</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 4);</div> +<div class="line"><a name="l03331"></a><span class="lineno"> 3331</span>  </div> +<div class="line"><a name="l03332"></a><span class="lineno"> 3332</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_LstmLayer();</div> +<div class="line"><a name="l03333"></a><span class="lineno"> 3333</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03334"></a><span class="lineno"> 3334</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> +<div class="line"><a name="l03335"></a><span class="lineno"> 3335</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div> +<div class="line"><a name="l03336"></a><span class="lineno"> 3336</span>  </div> +<div class="line"><a name="l03337"></a><span class="lineno"> 3337</span>  <span class="keyword">auto</span> lstmDescriptor = GetLstmDescriptor(flatBufferDescriptor);</div> <div class="line"><a name="l03338"></a><span class="lineno"> 3338</span>  </div> -<div class="line"><a name="l03339"></a><span class="lineno"> 3339</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToInputWeights;</div> -<div class="line"><a name="l03340"></a><span class="lineno"> 3340</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToInputWeights;</div> -<div class="line"><a name="l03341"></a><span class="lineno"> 3341</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToInputWeights;</div> -<div class="line"><a name="l03342"></a><span class="lineno"> 3342</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputGateBias;</div> -<div class="line"><a name="l03343"></a><span class="lineno"> 3343</span>  <span class="keywordflow">if</span> (!lstmDescriptor.m_CifgEnabled)</div> -<div class="line"><a name="l03344"></a><span class="lineno"> 3344</span>  {</div> -<div class="line"><a name="l03345"></a><span class="lineno"> 3345</span>  inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div> -<div class="line"><a name="l03346"></a><span class="lineno"> 3346</span>  recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div> -<div class="line"><a name="l03347"></a><span class="lineno"> 3347</span>  cellToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToInputWeights());</div> -<div class="line"><a name="l03348"></a><span class="lineno"> 3348</span>  inputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div> -<div class="line"><a name="l03349"></a><span class="lineno"> 3349</span>  </div> -<div class="line"><a name="l03350"></a><span class="lineno"> 3350</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div> -<div class="line"><a name="l03351"></a><span class="lineno"> 3351</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div> -<div class="line"><a name="l03352"></a><span class="lineno"> 3352</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a> = &cellToInputWeights;</div> -<div class="line"><a name="l03353"></a><span class="lineno"> 3353</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div> -<div class="line"><a name="l03354"></a><span class="lineno"> 3354</span>  }</div> -<div class="line"><a name="l03355"></a><span class="lineno"> 3355</span>  </div> -<div class="line"><a name="l03356"></a><span class="lineno"> 3356</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionWeights;</div> -<div class="line"><a name="l03357"></a><span class="lineno"> 3357</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionBias;</div> -<div class="line"><a name="l03358"></a><span class="lineno"> 3358</span>  <span class="keywordflow">if</span> (lstmDescriptor.m_ProjectionEnabled)</div> -<div class="line"><a name="l03359"></a><span class="lineno"> 3359</span>  {</div> -<div class="line"><a name="l03360"></a><span class="lineno"> 3360</span>  projectionWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionWeights());</div> -<div class="line"><a name="l03361"></a><span class="lineno"> 3361</span>  projectionBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionBias());</div> -<div class="line"><a name="l03362"></a><span class="lineno"> 3362</span>  </div> -<div class="line"><a name="l03363"></a><span class="lineno"> 3363</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a> = &projectionWeights;</div> -<div class="line"><a name="l03364"></a><span class="lineno"> 3364</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a> = &projectionBias;</div> -<div class="line"><a name="l03365"></a><span class="lineno"> 3365</span>  }</div> -<div class="line"><a name="l03366"></a><span class="lineno"> 3366</span>  </div> -<div class="line"><a name="l03367"></a><span class="lineno"> 3367</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToForgetWeights;</div> -<div class="line"><a name="l03368"></a><span class="lineno"> 3368</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToOutputWeights;</div> -<div class="line"><a name="l03369"></a><span class="lineno"> 3369</span>  <span class="keywordflow">if</span> (lstmDescriptor.m_PeepholeEnabled)</div> -<div class="line"><a name="l03370"></a><span class="lineno"> 3370</span>  {</div> -<div class="line"><a name="l03371"></a><span class="lineno"> 3371</span>  cellToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToForgetWeights());</div> -<div class="line"><a name="l03372"></a><span class="lineno"> 3372</span>  cellToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToOutputWeights());</div> -<div class="line"><a name="l03373"></a><span class="lineno"> 3373</span>  </div> -<div class="line"><a name="l03374"></a><span class="lineno"> 3374</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> = &cellToForgetWeights;</div> -<div class="line"><a name="l03375"></a><span class="lineno"> 3375</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> = &cellToOutputWeights;</div> +<div class="line"><a name="l03339"></a><span class="lineno"> 3339</span>  <a class="code" href="structarmnn_1_1_lstm_input_params.html">armnn::LstmInputParams</a> lstmInputParams;</div> +<div class="line"><a name="l03340"></a><span class="lineno"> 3340</span>  </div> +<div class="line"><a name="l03341"></a><span class="lineno"> 3341</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div> +<div class="line"><a name="l03342"></a><span class="lineno"> 3342</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div> +<div class="line"><a name="l03343"></a><span class="lineno"> 3343</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div> +<div class="line"><a name="l03344"></a><span class="lineno"> 3344</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div> +<div class="line"><a name="l03345"></a><span class="lineno"> 3345</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div> +<div class="line"><a name="l03346"></a><span class="lineno"> 3346</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div> +<div class="line"><a name="l03347"></a><span class="lineno"> 3347</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div> +<div class="line"><a name="l03348"></a><span class="lineno"> 3348</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellBias());</div> +<div class="line"><a name="l03349"></a><span class="lineno"> 3349</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div> +<div class="line"><a name="l03350"></a><span class="lineno"> 3350</span>  </div> +<div class="line"><a name="l03351"></a><span class="lineno"> 3351</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div> +<div class="line"><a name="l03352"></a><span class="lineno"> 3352</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div> +<div class="line"><a name="l03353"></a><span class="lineno"> 3353</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div> +<div class="line"><a name="l03354"></a><span class="lineno"> 3354</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div> +<div class="line"><a name="l03355"></a><span class="lineno"> 3355</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div> +<div class="line"><a name="l03356"></a><span class="lineno"> 3356</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div> +<div class="line"><a name="l03357"></a><span class="lineno"> 3357</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div> +<div class="line"><a name="l03358"></a><span class="lineno"> 3358</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div> +<div class="line"><a name="l03359"></a><span class="lineno"> 3359</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div> +<div class="line"><a name="l03360"></a><span class="lineno"> 3360</span>  </div> +<div class="line"><a name="l03361"></a><span class="lineno"> 3361</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToInputWeights;</div> +<div class="line"><a name="l03362"></a><span class="lineno"> 3362</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToInputWeights;</div> +<div class="line"><a name="l03363"></a><span class="lineno"> 3363</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToInputWeights;</div> +<div class="line"><a name="l03364"></a><span class="lineno"> 3364</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputGateBias;</div> +<div class="line"><a name="l03365"></a><span class="lineno"> 3365</span>  <span class="keywordflow">if</span> (!lstmDescriptor.m_CifgEnabled)</div> +<div class="line"><a name="l03366"></a><span class="lineno"> 3366</span>  {</div> +<div class="line"><a name="l03367"></a><span class="lineno"> 3367</span>  inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div> +<div class="line"><a name="l03368"></a><span class="lineno"> 3368</span>  recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div> +<div class="line"><a name="l03369"></a><span class="lineno"> 3369</span>  cellToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToInputWeights());</div> +<div class="line"><a name="l03370"></a><span class="lineno"> 3370</span>  inputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div> +<div class="line"><a name="l03371"></a><span class="lineno"> 3371</span>  </div> +<div class="line"><a name="l03372"></a><span class="lineno"> 3372</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div> +<div class="line"><a name="l03373"></a><span class="lineno"> 3373</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div> +<div class="line"><a name="l03374"></a><span class="lineno"> 3374</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a> = &cellToInputWeights;</div> +<div class="line"><a name="l03375"></a><span class="lineno"> 3375</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div> <div class="line"><a name="l03376"></a><span class="lineno"> 3376</span>  }</div> <div class="line"><a name="l03377"></a><span class="lineno"> 3377</span>  </div> -<div class="line"><a name="l03378"></a><span class="lineno"> 3378</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputLayerNormWeights;</div> -<div class="line"><a name="l03379"></a><span class="lineno"> 3379</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetLayerNormWeights;</div> -<div class="line"><a name="l03380"></a><span class="lineno"> 3380</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellLayerNormWeights;</div> -<div class="line"><a name="l03381"></a><span class="lineno"> 3381</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputLayerNormWeights;</div> -<div class="line"><a name="l03382"></a><span class="lineno"> 3382</span>  <span class="keywordflow">if</span> (lstmDescriptor.m_LayerNormEnabled)</div> -<div class="line"><a name="l03383"></a><span class="lineno"> 3383</span>  {</div> -<div class="line"><a name="l03384"></a><span class="lineno"> 3384</span>  <span class="keywordflow">if</span> (!lstmDescriptor.m_CifgEnabled)</div> -<div class="line"><a name="l03385"></a><span class="lineno"> 3385</span>  {</div> -<div class="line"><a name="l03386"></a><span class="lineno"> 3386</span>  inputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputLayerNormWeights());</div> -<div class="line"><a name="l03387"></a><span class="lineno"> 3387</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a> = &inputLayerNormWeights;</div> -<div class="line"><a name="l03388"></a><span class="lineno"> 3388</span>  }</div> -<div class="line"><a name="l03389"></a><span class="lineno"> 3389</span>  forgetLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetLayerNormWeights());</div> -<div class="line"><a name="l03390"></a><span class="lineno"> 3390</span>  cellLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellLayerNormWeights());</div> -<div class="line"><a name="l03391"></a><span class="lineno"> 3391</span>  outputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputLayerNormWeights());</div> -<div class="line"><a name="l03392"></a><span class="lineno"> 3392</span>  </div> -<div class="line"><a name="l03393"></a><span class="lineno"> 3393</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a> = &forgetLayerNormWeights;</div> -<div class="line"><a name="l03394"></a><span class="lineno"> 3394</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a> = &cellLayerNormWeights;</div> -<div class="line"><a name="l03395"></a><span class="lineno"> 3395</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a> = &outputLayerNormWeights;</div> -<div class="line"><a name="l03396"></a><span class="lineno"> 3396</span>  }</div> -<div class="line"><a name="l03397"></a><span class="lineno"> 3397</span>  </div> -<div class="line"><a name="l03398"></a><span class="lineno"> 3398</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddLstmLayer(lstmDescriptor, lstmInputParams, layerName.c_str());</div> +<div class="line"><a name="l03378"></a><span class="lineno"> 3378</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionWeights;</div> +<div class="line"><a name="l03379"></a><span class="lineno"> 3379</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionBias;</div> +<div class="line"><a name="l03380"></a><span class="lineno"> 3380</span>  <span class="keywordflow">if</span> (lstmDescriptor.m_ProjectionEnabled)</div> +<div class="line"><a name="l03381"></a><span class="lineno"> 3381</span>  {</div> +<div class="line"><a name="l03382"></a><span class="lineno"> 3382</span>  projectionWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionWeights());</div> +<div class="line"><a name="l03383"></a><span class="lineno"> 3383</span>  projectionBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionBias());</div> +<div class="line"><a name="l03384"></a><span class="lineno"> 3384</span>  </div> +<div class="line"><a name="l03385"></a><span class="lineno"> 3385</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a> = &projectionWeights;</div> +<div class="line"><a name="l03386"></a><span class="lineno"> 3386</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a> = &projectionBias;</div> +<div class="line"><a name="l03387"></a><span class="lineno"> 3387</span>  }</div> +<div class="line"><a name="l03388"></a><span class="lineno"> 3388</span>  </div> +<div class="line"><a name="l03389"></a><span class="lineno"> 3389</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToForgetWeights;</div> +<div class="line"><a name="l03390"></a><span class="lineno"> 3390</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToOutputWeights;</div> +<div class="line"><a name="l03391"></a><span class="lineno"> 3391</span>  <span class="keywordflow">if</span> (lstmDescriptor.m_PeepholeEnabled)</div> +<div class="line"><a name="l03392"></a><span class="lineno"> 3392</span>  {</div> +<div class="line"><a name="l03393"></a><span class="lineno"> 3393</span>  cellToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToForgetWeights());</div> +<div class="line"><a name="l03394"></a><span class="lineno"> 3394</span>  cellToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToOutputWeights());</div> +<div class="line"><a name="l03395"></a><span class="lineno"> 3395</span>  </div> +<div class="line"><a name="l03396"></a><span class="lineno"> 3396</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> = &cellToForgetWeights;</div> +<div class="line"><a name="l03397"></a><span class="lineno"> 3397</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> = &cellToOutputWeights;</div> +<div class="line"><a name="l03398"></a><span class="lineno"> 3398</span>  }</div> <div class="line"><a name="l03399"></a><span class="lineno"> 3399</span>  </div> -<div class="line"><a name="l03400"></a><span class="lineno"> 3400</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo1 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03401"></a><span class="lineno"> 3401</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo1);</div> -<div class="line"><a name="l03402"></a><span class="lineno"> 3402</span>  </div> -<div class="line"><a name="l03403"></a><span class="lineno"> 3403</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo2 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> -<div class="line"><a name="l03404"></a><span class="lineno"> 3404</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo2);</div> -<div class="line"><a name="l03405"></a><span class="lineno"> 3405</span>  </div> -<div class="line"><a name="l03406"></a><span class="lineno"> 3406</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo3 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[2]);</div> -<div class="line"><a name="l03407"></a><span class="lineno"> 3407</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo3);</div> -<div class="line"><a name="l03408"></a><span class="lineno"> 3408</span>  </div> -<div class="line"><a name="l03409"></a><span class="lineno"> 3409</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo4 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[3]);</div> -<div class="line"><a name="l03410"></a><span class="lineno"> 3410</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(3).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo4);</div> -<div class="line"><a name="l03411"></a><span class="lineno"> 3411</span>  </div> -<div class="line"><a name="l03412"></a><span class="lineno"> 3412</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03413"></a><span class="lineno"> 3413</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03414"></a><span class="lineno"> 3414</span> }</div> -<div class="line"><a name="l03415"></a><span class="lineno"> 3415</span>  </div> -<div class="line"><a name="l03416"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a57e32d26ac8c87b118e77da920481123"> 3416</a></span> <a class="code" href="structarmnn_1_1_q_lstm_descriptor.html">armnn::QLstmDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a57e32d26ac8c87b118e77da920481123">IDeserializer::DeserializerImpl::GetQLstmDescriptor</a>(<a class="code" href="namespacearmnn_deserializer.html#a5cd994198e775b8e919853fd0da5b9c1">QLstmDescriptorPtr</a> qLstmDescriptor)</div> -<div class="line"><a name="l03417"></a><span class="lineno"> 3417</span> {</div> -<div class="line"><a name="l03418"></a><span class="lineno"> 3418</span>  <a class="code" href="structarmnn_1_1_q_lstm_descriptor.html">armnn::QLstmDescriptor</a> desc;</div> +<div class="line"><a name="l03400"></a><span class="lineno"> 3400</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputLayerNormWeights;</div> +<div class="line"><a name="l03401"></a><span class="lineno"> 3401</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetLayerNormWeights;</div> +<div class="line"><a name="l03402"></a><span class="lineno"> 3402</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellLayerNormWeights;</div> +<div class="line"><a name="l03403"></a><span class="lineno"> 3403</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputLayerNormWeights;</div> +<div class="line"><a name="l03404"></a><span class="lineno"> 3404</span>  <span class="keywordflow">if</span> (lstmDescriptor.m_LayerNormEnabled)</div> +<div class="line"><a name="l03405"></a><span class="lineno"> 3405</span>  {</div> +<div class="line"><a name="l03406"></a><span class="lineno"> 3406</span>  <span class="keywordflow">if</span> (!lstmDescriptor.m_CifgEnabled)</div> +<div class="line"><a name="l03407"></a><span class="lineno"> 3407</span>  {</div> +<div class="line"><a name="l03408"></a><span class="lineno"> 3408</span>  inputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputLayerNormWeights());</div> +<div class="line"><a name="l03409"></a><span class="lineno"> 3409</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a> = &inputLayerNormWeights;</div> +<div class="line"><a name="l03410"></a><span class="lineno"> 3410</span>  }</div> +<div class="line"><a name="l03411"></a><span class="lineno"> 3411</span>  forgetLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetLayerNormWeights());</div> +<div class="line"><a name="l03412"></a><span class="lineno"> 3412</span>  cellLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellLayerNormWeights());</div> +<div class="line"><a name="l03413"></a><span class="lineno"> 3413</span>  outputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputLayerNormWeights());</div> +<div class="line"><a name="l03414"></a><span class="lineno"> 3414</span>  </div> +<div class="line"><a name="l03415"></a><span class="lineno"> 3415</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a> = &forgetLayerNormWeights;</div> +<div class="line"><a name="l03416"></a><span class="lineno"> 3416</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a> = &cellLayerNormWeights;</div> +<div class="line"><a name="l03417"></a><span class="lineno"> 3417</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a> = &outputLayerNormWeights;</div> +<div class="line"><a name="l03418"></a><span class="lineno"> 3418</span>  }</div> <div class="line"><a name="l03419"></a><span class="lineno"> 3419</span>  </div> -<div class="line"><a name="l03420"></a><span class="lineno"> 3420</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = qLstmDescriptor->cifgEnabled();</div> -<div class="line"><a name="l03421"></a><span class="lineno"> 3421</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = qLstmDescriptor->peepholeEnabled();</div> -<div class="line"><a name="l03422"></a><span class="lineno"> 3422</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = qLstmDescriptor->projectionEnabled();</div> -<div class="line"><a name="l03423"></a><span class="lineno"> 3423</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = qLstmDescriptor->layerNormEnabled();</div> +<div class="line"><a name="l03420"></a><span class="lineno"> 3420</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddLstmLayer(lstmDescriptor, lstmInputParams, layerName.c_str());</div> +<div class="line"><a name="l03421"></a><span class="lineno"> 3421</span>  </div> +<div class="line"><a name="l03422"></a><span class="lineno"> 3422</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo1 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03423"></a><span class="lineno"> 3423</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo1);</div> <div class="line"><a name="l03424"></a><span class="lineno"> 3424</span>  </div> -<div class="line"><a name="l03425"></a><span class="lineno"> 3425</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#ac81fb0e66dc623dc37c77f219f53a6d3">m_CellClip</a> = qLstmDescriptor->cellClip();</div> -<div class="line"><a name="l03426"></a><span class="lineno"> 3426</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#aa6a518b65088f34803b3214334bdff61">m_ProjectionClip</a> = qLstmDescriptor->projectionClip();</div> +<div class="line"><a name="l03425"></a><span class="lineno"> 3425</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo2 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> +<div class="line"><a name="l03426"></a><span class="lineno"> 3426</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo2);</div> <div class="line"><a name="l03427"></a><span class="lineno"> 3427</span>  </div> -<div class="line"><a name="l03428"></a><span class="lineno"> 3428</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a09e1f097944f61cc901240f9300364cf">m_InputIntermediateScale</a> = qLstmDescriptor->inputIntermediateScale();</div> -<div class="line"><a name="l03429"></a><span class="lineno"> 3429</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#afec7f36158448f723b426a9527acb189">m_ForgetIntermediateScale</a> = qLstmDescriptor->forgetIntermediateScale();</div> -<div class="line"><a name="l03430"></a><span class="lineno"> 3430</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a0477ee1b44ace6090119178eea78cb0b">m_CellIntermediateScale</a> = qLstmDescriptor->cellIntermediateScale();</div> -<div class="line"><a name="l03431"></a><span class="lineno"> 3431</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#aa43409f9b457352c95c89f20ce5d844d">m_OutputIntermediateScale</a> = qLstmDescriptor->outputIntermediateScale();</div> -<div class="line"><a name="l03432"></a><span class="lineno"> 3432</span>  </div> -<div class="line"><a name="l03433"></a><span class="lineno"> 3433</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#af8f724af7210b52529216feefa993c98">m_HiddenStateScale</a> = qLstmDescriptor->hiddenStateScale();</div> -<div class="line"><a name="l03434"></a><span class="lineno"> 3434</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a4556cbd764d4848d8ad0637a9eed580d">m_HiddenStateZeroPoint</a> = qLstmDescriptor->hiddenStateZeroPoint();</div> -<div class="line"><a name="l03435"></a><span class="lineno"> 3435</span>  </div> -<div class="line"><a name="l03436"></a><span class="lineno"> 3436</span>  <span class="keywordflow">return</span> desc;</div> -<div class="line"><a name="l03437"></a><span class="lineno"> 3437</span> }</div> -<div class="line"><a name="l03438"></a><span class="lineno"> 3438</span>  </div> -<div class="line"><a name="l03439"></a><span class="lineno"> 3439</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseQLstm(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03440"></a><span class="lineno"> 3440</span> {</div> -<div class="line"><a name="l03441"></a><span class="lineno"> 3441</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03442"></a><span class="lineno"> 3442</span>  </div> -<div class="line"><a name="l03443"></a><span class="lineno"> 3443</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03444"></a><span class="lineno"> 3444</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div> -<div class="line"><a name="l03445"></a><span class="lineno"> 3445</span>  </div> -<div class="line"><a name="l03446"></a><span class="lineno"> 3446</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03447"></a><span class="lineno"> 3447</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 3);</div> -<div class="line"><a name="l03448"></a><span class="lineno"> 3448</span>  </div> -<div class="line"><a name="l03449"></a><span class="lineno"> 3449</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_QLstmLayer();</div> -<div class="line"><a name="l03450"></a><span class="lineno"> 3450</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03451"></a><span class="lineno"> 3451</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> -<div class="line"><a name="l03452"></a><span class="lineno"> 3452</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div> -<div class="line"><a name="l03453"></a><span class="lineno"> 3453</span>  </div> -<div class="line"><a name="l03454"></a><span class="lineno"> 3454</span>  <span class="keyword">auto</span> qLstmDescriptor = GetQLstmDescriptor(flatBufferDescriptor);</div> -<div class="line"><a name="l03455"></a><span class="lineno"> 3455</span>  <a class="code" href="structarmnn_1_1_lstm_input_params.html">armnn::LstmInputParams</a> qLstmInputParams;</div> -<div class="line"><a name="l03456"></a><span class="lineno"> 3456</span>  </div> -<div class="line"><a name="l03457"></a><span class="lineno"> 3457</span>  <span class="comment">// Mandatory params</span></div> -<div class="line"><a name="l03458"></a><span class="lineno"> 3458</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div> -<div class="line"><a name="l03459"></a><span class="lineno"> 3459</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div> -<div class="line"><a name="l03460"></a><span class="lineno"> 3460</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div> -<div class="line"><a name="l03461"></a><span class="lineno"> 3461</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div> -<div class="line"><a name="l03462"></a><span class="lineno"> 3462</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div> -<div class="line"><a name="l03463"></a><span class="lineno"> 3463</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div> -<div class="line"><a name="l03464"></a><span class="lineno"> 3464</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div> -<div class="line"><a name="l03465"></a><span class="lineno"> 3465</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellBias());</div> -<div class="line"><a name="l03466"></a><span class="lineno"> 3466</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div> +<div class="line"><a name="l03428"></a><span class="lineno"> 3428</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo3 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[2]);</div> +<div class="line"><a name="l03429"></a><span class="lineno"> 3429</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo3);</div> +<div class="line"><a name="l03430"></a><span class="lineno"> 3430</span>  </div> +<div class="line"><a name="l03431"></a><span class="lineno"> 3431</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo4 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[3]);</div> +<div class="line"><a name="l03432"></a><span class="lineno"> 3432</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(3).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo4);</div> +<div class="line"><a name="l03433"></a><span class="lineno"> 3433</span>  </div> +<div class="line"><a name="l03434"></a><span class="lineno"> 3434</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03435"></a><span class="lineno"> 3435</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03436"></a><span class="lineno"> 3436</span> }</div> +<div class="line"><a name="l03437"></a><span class="lineno"> 3437</span>  </div> +<div class="line"><a name="l03438"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a57e32d26ac8c87b118e77da920481123"> 3438</a></span> <a class="code" href="structarmnn_1_1_q_lstm_descriptor.html">armnn::QLstmDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a57e32d26ac8c87b118e77da920481123">IDeserializer::DeserializerImpl::GetQLstmDescriptor</a>(<a class="code" href="namespacearmnn_deserializer.html#a5cd994198e775b8e919853fd0da5b9c1">QLstmDescriptorPtr</a> qLstmDescriptor)</div> +<div class="line"><a name="l03439"></a><span class="lineno"> 3439</span> {</div> +<div class="line"><a name="l03440"></a><span class="lineno"> 3440</span>  <a class="code" href="structarmnn_1_1_q_lstm_descriptor.html">armnn::QLstmDescriptor</a> desc;</div> +<div class="line"><a name="l03441"></a><span class="lineno"> 3441</span>  </div> +<div class="line"><a name="l03442"></a><span class="lineno"> 3442</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = qLstmDescriptor->cifgEnabled();</div> +<div class="line"><a name="l03443"></a><span class="lineno"> 3443</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = qLstmDescriptor->peepholeEnabled();</div> +<div class="line"><a name="l03444"></a><span class="lineno"> 3444</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = qLstmDescriptor->projectionEnabled();</div> +<div class="line"><a name="l03445"></a><span class="lineno"> 3445</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = qLstmDescriptor->layerNormEnabled();</div> +<div class="line"><a name="l03446"></a><span class="lineno"> 3446</span>  </div> +<div class="line"><a name="l03447"></a><span class="lineno"> 3447</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#ac81fb0e66dc623dc37c77f219f53a6d3">m_CellClip</a> = qLstmDescriptor->cellClip();</div> +<div class="line"><a name="l03448"></a><span class="lineno"> 3448</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#aa6a518b65088f34803b3214334bdff61">m_ProjectionClip</a> = qLstmDescriptor->projectionClip();</div> +<div class="line"><a name="l03449"></a><span class="lineno"> 3449</span>  </div> +<div class="line"><a name="l03450"></a><span class="lineno"> 3450</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a09e1f097944f61cc901240f9300364cf">m_InputIntermediateScale</a> = qLstmDescriptor->inputIntermediateScale();</div> +<div class="line"><a name="l03451"></a><span class="lineno"> 3451</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#afec7f36158448f723b426a9527acb189">m_ForgetIntermediateScale</a> = qLstmDescriptor->forgetIntermediateScale();</div> +<div class="line"><a name="l03452"></a><span class="lineno"> 3452</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a0477ee1b44ace6090119178eea78cb0b">m_CellIntermediateScale</a> = qLstmDescriptor->cellIntermediateScale();</div> +<div class="line"><a name="l03453"></a><span class="lineno"> 3453</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#aa43409f9b457352c95c89f20ce5d844d">m_OutputIntermediateScale</a> = qLstmDescriptor->outputIntermediateScale();</div> +<div class="line"><a name="l03454"></a><span class="lineno"> 3454</span>  </div> +<div class="line"><a name="l03455"></a><span class="lineno"> 3455</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#af8f724af7210b52529216feefa993c98">m_HiddenStateScale</a> = qLstmDescriptor->hiddenStateScale();</div> +<div class="line"><a name="l03456"></a><span class="lineno"> 3456</span>  desc.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.html#a4556cbd764d4848d8ad0637a9eed580d">m_HiddenStateZeroPoint</a> = qLstmDescriptor->hiddenStateZeroPoint();</div> +<div class="line"><a name="l03457"></a><span class="lineno"> 3457</span>  </div> +<div class="line"><a name="l03458"></a><span class="lineno"> 3458</span>  <span class="keywordflow">return</span> desc;</div> +<div class="line"><a name="l03459"></a><span class="lineno"> 3459</span> }</div> +<div class="line"><a name="l03460"></a><span class="lineno"> 3460</span>  </div> +<div class="line"><a name="l03461"></a><span class="lineno"> 3461</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseQLstm(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03462"></a><span class="lineno"> 3462</span> {</div> +<div class="line"><a name="l03463"></a><span class="lineno"> 3463</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03464"></a><span class="lineno"> 3464</span>  </div> +<div class="line"><a name="l03465"></a><span class="lineno"> 3465</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03466"></a><span class="lineno"> 3466</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div> <div class="line"><a name="l03467"></a><span class="lineno"> 3467</span>  </div> -<div class="line"><a name="l03468"></a><span class="lineno"> 3468</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div> -<div class="line"><a name="l03469"></a><span class="lineno"> 3469</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div> -<div class="line"><a name="l03470"></a><span class="lineno"> 3470</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div> -<div class="line"><a name="l03471"></a><span class="lineno"> 3471</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div> -<div class="line"><a name="l03472"></a><span class="lineno"> 3472</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div> -<div class="line"><a name="l03473"></a><span class="lineno"> 3473</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div> -<div class="line"><a name="l03474"></a><span class="lineno"> 3474</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div> -<div class="line"><a name="l03475"></a><span class="lineno"> 3475</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div> -<div class="line"><a name="l03476"></a><span class="lineno"> 3476</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div> -<div class="line"><a name="l03477"></a><span class="lineno"> 3477</span>  </div> -<div class="line"><a name="l03478"></a><span class="lineno"> 3478</span>  <span class="comment">// Optional CIFG params</span></div> -<div class="line"><a name="l03479"></a><span class="lineno"> 3479</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToInputWeights;</div> -<div class="line"><a name="l03480"></a><span class="lineno"> 3480</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToInputWeights;</div> -<div class="line"><a name="l03481"></a><span class="lineno"> 3481</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputGateBias;</div> -<div class="line"><a name="l03482"></a><span class="lineno"> 3482</span>  </div> -<div class="line"><a name="l03483"></a><span class="lineno"> 3483</span>  <span class="keywordflow">if</span> (!qLstmDescriptor.m_CifgEnabled)</div> -<div class="line"><a name="l03484"></a><span class="lineno"> 3484</span>  {</div> -<div class="line"><a name="l03485"></a><span class="lineno"> 3485</span>  inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div> -<div class="line"><a name="l03486"></a><span class="lineno"> 3486</span>  recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div> -<div class="line"><a name="l03487"></a><span class="lineno"> 3487</span>  inputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div> -<div class="line"><a name="l03488"></a><span class="lineno"> 3488</span>  </div> -<div class="line"><a name="l03489"></a><span class="lineno"> 3489</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div> -<div class="line"><a name="l03490"></a><span class="lineno"> 3490</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div> -<div class="line"><a name="l03491"></a><span class="lineno"> 3491</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div> -<div class="line"><a name="l03492"></a><span class="lineno"> 3492</span>  }</div> -<div class="line"><a name="l03493"></a><span class="lineno"> 3493</span>  </div> -<div class="line"><a name="l03494"></a><span class="lineno"> 3494</span>  <span class="comment">// Optional projection params</span></div> -<div class="line"><a name="l03495"></a><span class="lineno"> 3495</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionWeights;</div> -<div class="line"><a name="l03496"></a><span class="lineno"> 3496</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionBias;</div> -<div class="line"><a name="l03497"></a><span class="lineno"> 3497</span>  </div> -<div class="line"><a name="l03498"></a><span class="lineno"> 3498</span>  <span class="keywordflow">if</span> (qLstmDescriptor.m_ProjectionEnabled)</div> -<div class="line"><a name="l03499"></a><span class="lineno"> 3499</span>  {</div> -<div class="line"><a name="l03500"></a><span class="lineno"> 3500</span>  projectionWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionWeights());</div> -<div class="line"><a name="l03501"></a><span class="lineno"> 3501</span>  projectionBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionBias());</div> -<div class="line"><a name="l03502"></a><span class="lineno"> 3502</span>  </div> -<div class="line"><a name="l03503"></a><span class="lineno"> 3503</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a> = &projectionWeights;</div> -<div class="line"><a name="l03504"></a><span class="lineno"> 3504</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a> = &projectionBias;</div> -<div class="line"><a name="l03505"></a><span class="lineno"> 3505</span>  }</div> -<div class="line"><a name="l03506"></a><span class="lineno"> 3506</span>  </div> -<div class="line"><a name="l03507"></a><span class="lineno"> 3507</span>  <span class="comment">// Optional peephole params</span></div> -<div class="line"><a name="l03508"></a><span class="lineno"> 3508</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToInputWeights;</div> -<div class="line"><a name="l03509"></a><span class="lineno"> 3509</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToForgetWeights;</div> -<div class="line"><a name="l03510"></a><span class="lineno"> 3510</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToOutputWeights;</div> -<div class="line"><a name="l03511"></a><span class="lineno"> 3511</span>  </div> -<div class="line"><a name="l03512"></a><span class="lineno"> 3512</span>  <span class="keywordflow">if</span> (qLstmDescriptor.m_PeepholeEnabled)</div> -<div class="line"><a name="l03513"></a><span class="lineno"> 3513</span>  {</div> -<div class="line"><a name="l03514"></a><span class="lineno"> 3514</span>  <span class="keywordflow">if</span> (!qLstmDescriptor.m_CifgEnabled)</div> -<div class="line"><a name="l03515"></a><span class="lineno"> 3515</span>  {</div> -<div class="line"><a name="l03516"></a><span class="lineno"> 3516</span>  cellToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToInputWeights());</div> -<div class="line"><a name="l03517"></a><span class="lineno"> 3517</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a> = &cellToInputWeights;</div> -<div class="line"><a name="l03518"></a><span class="lineno"> 3518</span>  }</div> +<div class="line"><a name="l03468"></a><span class="lineno"> 3468</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03469"></a><span class="lineno"> 3469</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 3);</div> +<div class="line"><a name="l03470"></a><span class="lineno"> 3470</span>  </div> +<div class="line"><a name="l03471"></a><span class="lineno"> 3471</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_QLstmLayer();</div> +<div class="line"><a name="l03472"></a><span class="lineno"> 3472</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03473"></a><span class="lineno"> 3473</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> +<div class="line"><a name="l03474"></a><span class="lineno"> 3474</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div> +<div class="line"><a name="l03475"></a><span class="lineno"> 3475</span>  </div> +<div class="line"><a name="l03476"></a><span class="lineno"> 3476</span>  <span class="keyword">auto</span> qLstmDescriptor = GetQLstmDescriptor(flatBufferDescriptor);</div> +<div class="line"><a name="l03477"></a><span class="lineno"> 3477</span>  <a class="code" href="structarmnn_1_1_lstm_input_params.html">armnn::LstmInputParams</a> qLstmInputParams;</div> +<div class="line"><a name="l03478"></a><span class="lineno"> 3478</span>  </div> +<div class="line"><a name="l03479"></a><span class="lineno"> 3479</span>  <span class="comment">// Mandatory params</span></div> +<div class="line"><a name="l03480"></a><span class="lineno"> 3480</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div> +<div class="line"><a name="l03481"></a><span class="lineno"> 3481</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div> +<div class="line"><a name="l03482"></a><span class="lineno"> 3482</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div> +<div class="line"><a name="l03483"></a><span class="lineno"> 3483</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div> +<div class="line"><a name="l03484"></a><span class="lineno"> 3484</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div> +<div class="line"><a name="l03485"></a><span class="lineno"> 3485</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div> +<div class="line"><a name="l03486"></a><span class="lineno"> 3486</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div> +<div class="line"><a name="l03487"></a><span class="lineno"> 3487</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellBias());</div> +<div class="line"><a name="l03488"></a><span class="lineno"> 3488</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div> +<div class="line"><a name="l03489"></a><span class="lineno"> 3489</span>  </div> +<div class="line"><a name="l03490"></a><span class="lineno"> 3490</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div> +<div class="line"><a name="l03491"></a><span class="lineno"> 3491</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div> +<div class="line"><a name="l03492"></a><span class="lineno"> 3492</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div> +<div class="line"><a name="l03493"></a><span class="lineno"> 3493</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div> +<div class="line"><a name="l03494"></a><span class="lineno"> 3494</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div> +<div class="line"><a name="l03495"></a><span class="lineno"> 3495</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div> +<div class="line"><a name="l03496"></a><span class="lineno"> 3496</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div> +<div class="line"><a name="l03497"></a><span class="lineno"> 3497</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div> +<div class="line"><a name="l03498"></a><span class="lineno"> 3498</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div> +<div class="line"><a name="l03499"></a><span class="lineno"> 3499</span>  </div> +<div class="line"><a name="l03500"></a><span class="lineno"> 3500</span>  <span class="comment">// Optional CIFG params</span></div> +<div class="line"><a name="l03501"></a><span class="lineno"> 3501</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToInputWeights;</div> +<div class="line"><a name="l03502"></a><span class="lineno"> 3502</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToInputWeights;</div> +<div class="line"><a name="l03503"></a><span class="lineno"> 3503</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputGateBias;</div> +<div class="line"><a name="l03504"></a><span class="lineno"> 3504</span>  </div> +<div class="line"><a name="l03505"></a><span class="lineno"> 3505</span>  <span class="keywordflow">if</span> (!qLstmDescriptor.m_CifgEnabled)</div> +<div class="line"><a name="l03506"></a><span class="lineno"> 3506</span>  {</div> +<div class="line"><a name="l03507"></a><span class="lineno"> 3507</span>  inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div> +<div class="line"><a name="l03508"></a><span class="lineno"> 3508</span>  recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div> +<div class="line"><a name="l03509"></a><span class="lineno"> 3509</span>  inputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div> +<div class="line"><a name="l03510"></a><span class="lineno"> 3510</span>  </div> +<div class="line"><a name="l03511"></a><span class="lineno"> 3511</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div> +<div class="line"><a name="l03512"></a><span class="lineno"> 3512</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div> +<div class="line"><a name="l03513"></a><span class="lineno"> 3513</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div> +<div class="line"><a name="l03514"></a><span class="lineno"> 3514</span>  }</div> +<div class="line"><a name="l03515"></a><span class="lineno"> 3515</span>  </div> +<div class="line"><a name="l03516"></a><span class="lineno"> 3516</span>  <span class="comment">// Optional projection params</span></div> +<div class="line"><a name="l03517"></a><span class="lineno"> 3517</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionWeights;</div> +<div class="line"><a name="l03518"></a><span class="lineno"> 3518</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionBias;</div> <div class="line"><a name="l03519"></a><span class="lineno"> 3519</span>  </div> -<div class="line"><a name="l03520"></a><span class="lineno"> 3520</span>  cellToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToForgetWeights());</div> -<div class="line"><a name="l03521"></a><span class="lineno"> 3521</span>  cellToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToOutputWeights());</div> -<div class="line"><a name="l03522"></a><span class="lineno"> 3522</span>  </div> -<div class="line"><a name="l03523"></a><span class="lineno"> 3523</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> = &cellToForgetWeights;</div> -<div class="line"><a name="l03524"></a><span class="lineno"> 3524</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> = &cellToOutputWeights;</div> -<div class="line"><a name="l03525"></a><span class="lineno"> 3525</span>  }</div> -<div class="line"><a name="l03526"></a><span class="lineno"> 3526</span>  </div> -<div class="line"><a name="l03527"></a><span class="lineno"> 3527</span>  <span class="comment">// Optional layer norm params</span></div> -<div class="line"><a name="l03528"></a><span class="lineno"> 3528</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputLayerNormWeights;</div> -<div class="line"><a name="l03529"></a><span class="lineno"> 3529</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetLayerNormWeights;</div> -<div class="line"><a name="l03530"></a><span class="lineno"> 3530</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellLayerNormWeights;</div> -<div class="line"><a name="l03531"></a><span class="lineno"> 3531</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputLayerNormWeights;</div> -<div class="line"><a name="l03532"></a><span class="lineno"> 3532</span>  </div> -<div class="line"><a name="l03533"></a><span class="lineno"> 3533</span>  <span class="keywordflow">if</span> (qLstmDescriptor.m_LayerNormEnabled)</div> -<div class="line"><a name="l03534"></a><span class="lineno"> 3534</span>  {</div> -<div class="line"><a name="l03535"></a><span class="lineno"> 3535</span>  <span class="keywordflow">if</span> (!qLstmDescriptor.m_CifgEnabled)</div> -<div class="line"><a name="l03536"></a><span class="lineno"> 3536</span>  {</div> -<div class="line"><a name="l03537"></a><span class="lineno"> 3537</span>  inputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputLayerNormWeights());</div> -<div class="line"><a name="l03538"></a><span class="lineno"> 3538</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a> = &inputLayerNormWeights;</div> -<div class="line"><a name="l03539"></a><span class="lineno"> 3539</span>  }</div> -<div class="line"><a name="l03540"></a><span class="lineno"> 3540</span>  </div> -<div class="line"><a name="l03541"></a><span class="lineno"> 3541</span>  forgetLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetLayerNormWeights());</div> -<div class="line"><a name="l03542"></a><span class="lineno"> 3542</span>  cellLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellLayerNormWeights());</div> -<div class="line"><a name="l03543"></a><span class="lineno"> 3543</span>  outputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputLayerNormWeights());</div> +<div class="line"><a name="l03520"></a><span class="lineno"> 3520</span>  <span class="keywordflow">if</span> (qLstmDescriptor.m_ProjectionEnabled)</div> +<div class="line"><a name="l03521"></a><span class="lineno"> 3521</span>  {</div> +<div class="line"><a name="l03522"></a><span class="lineno"> 3522</span>  projectionWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionWeights());</div> +<div class="line"><a name="l03523"></a><span class="lineno"> 3523</span>  projectionBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionBias());</div> +<div class="line"><a name="l03524"></a><span class="lineno"> 3524</span>  </div> +<div class="line"><a name="l03525"></a><span class="lineno"> 3525</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a> = &projectionWeights;</div> +<div class="line"><a name="l03526"></a><span class="lineno"> 3526</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a> = &projectionBias;</div> +<div class="line"><a name="l03527"></a><span class="lineno"> 3527</span>  }</div> +<div class="line"><a name="l03528"></a><span class="lineno"> 3528</span>  </div> +<div class="line"><a name="l03529"></a><span class="lineno"> 3529</span>  <span class="comment">// Optional peephole params</span></div> +<div class="line"><a name="l03530"></a><span class="lineno"> 3530</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToInputWeights;</div> +<div class="line"><a name="l03531"></a><span class="lineno"> 3531</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToForgetWeights;</div> +<div class="line"><a name="l03532"></a><span class="lineno"> 3532</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToOutputWeights;</div> +<div class="line"><a name="l03533"></a><span class="lineno"> 3533</span>  </div> +<div class="line"><a name="l03534"></a><span class="lineno"> 3534</span>  <span class="keywordflow">if</span> (qLstmDescriptor.m_PeepholeEnabled)</div> +<div class="line"><a name="l03535"></a><span class="lineno"> 3535</span>  {</div> +<div class="line"><a name="l03536"></a><span class="lineno"> 3536</span>  <span class="keywordflow">if</span> (!qLstmDescriptor.m_CifgEnabled)</div> +<div class="line"><a name="l03537"></a><span class="lineno"> 3537</span>  {</div> +<div class="line"><a name="l03538"></a><span class="lineno"> 3538</span>  cellToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToInputWeights());</div> +<div class="line"><a name="l03539"></a><span class="lineno"> 3539</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a> = &cellToInputWeights;</div> +<div class="line"><a name="l03540"></a><span class="lineno"> 3540</span>  }</div> +<div class="line"><a name="l03541"></a><span class="lineno"> 3541</span>  </div> +<div class="line"><a name="l03542"></a><span class="lineno"> 3542</span>  cellToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToForgetWeights());</div> +<div class="line"><a name="l03543"></a><span class="lineno"> 3543</span>  cellToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToOutputWeights());</div> <div class="line"><a name="l03544"></a><span class="lineno"> 3544</span>  </div> -<div class="line"><a name="l03545"></a><span class="lineno"> 3545</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a> = &forgetLayerNormWeights;</div> -<div class="line"><a name="l03546"></a><span class="lineno"> 3546</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a> = &cellLayerNormWeights;</div> -<div class="line"><a name="l03547"></a><span class="lineno"> 3547</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a> = &outputLayerNormWeights;</div> -<div class="line"><a name="l03548"></a><span class="lineno"> 3548</span>  }</div> -<div class="line"><a name="l03549"></a><span class="lineno"> 3549</span>  </div> -<div class="line"><a name="l03550"></a><span class="lineno"> 3550</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddQLstmLayer(qLstmDescriptor, qLstmInputParams, layerName.c_str());</div> -<div class="line"><a name="l03551"></a><span class="lineno"> 3551</span>  </div> -<div class="line"><a name="l03552"></a><span class="lineno"> 3552</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputStateOutInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03553"></a><span class="lineno"> 3553</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputStateOutInfo);</div> +<div class="line"><a name="l03545"></a><span class="lineno"> 3545</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> = &cellToForgetWeights;</div> +<div class="line"><a name="l03546"></a><span class="lineno"> 3546</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> = &cellToOutputWeights;</div> +<div class="line"><a name="l03547"></a><span class="lineno"> 3547</span>  }</div> +<div class="line"><a name="l03548"></a><span class="lineno"> 3548</span>  </div> +<div class="line"><a name="l03549"></a><span class="lineno"> 3549</span>  <span class="comment">// Optional layer norm params</span></div> +<div class="line"><a name="l03550"></a><span class="lineno"> 3550</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputLayerNormWeights;</div> +<div class="line"><a name="l03551"></a><span class="lineno"> 3551</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetLayerNormWeights;</div> +<div class="line"><a name="l03552"></a><span class="lineno"> 3552</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellLayerNormWeights;</div> +<div class="line"><a name="l03553"></a><span class="lineno"> 3553</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputLayerNormWeights;</div> <div class="line"><a name="l03554"></a><span class="lineno"> 3554</span>  </div> -<div class="line"><a name="l03555"></a><span class="lineno"> 3555</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> cellStateOutInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> -<div class="line"><a name="l03556"></a><span class="lineno"> 3556</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(cellStateOutInfo);</div> -<div class="line"><a name="l03557"></a><span class="lineno"> 3557</span>  </div> -<div class="line"><a name="l03558"></a><span class="lineno"> 3558</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[2]);</div> -<div class="line"><a name="l03559"></a><span class="lineno"> 3559</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> -<div class="line"><a name="l03560"></a><span class="lineno"> 3560</span>  </div> -<div class="line"><a name="l03561"></a><span class="lineno"> 3561</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03562"></a><span class="lineno"> 3562</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03563"></a><span class="lineno"> 3563</span> }</div> -<div class="line"><a name="l03564"></a><span class="lineno"> 3564</span>  </div> -<div class="line"><a name="l03565"></a><span class="lineno"> 3565</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseQuantizedLstm(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03566"></a><span class="lineno"> 3566</span> {</div> -<div class="line"><a name="l03567"></a><span class="lineno"> 3567</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03568"></a><span class="lineno"> 3568</span>  </div> -<div class="line"><a name="l03569"></a><span class="lineno"> 3569</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03570"></a><span class="lineno"> 3570</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div> +<div class="line"><a name="l03555"></a><span class="lineno"> 3555</span>  <span class="keywordflow">if</span> (qLstmDescriptor.m_LayerNormEnabled)</div> +<div class="line"><a name="l03556"></a><span class="lineno"> 3556</span>  {</div> +<div class="line"><a name="l03557"></a><span class="lineno"> 3557</span>  <span class="keywordflow">if</span> (!qLstmDescriptor.m_CifgEnabled)</div> +<div class="line"><a name="l03558"></a><span class="lineno"> 3558</span>  {</div> +<div class="line"><a name="l03559"></a><span class="lineno"> 3559</span>  inputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputLayerNormWeights());</div> +<div class="line"><a name="l03560"></a><span class="lineno"> 3560</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a> = &inputLayerNormWeights;</div> +<div class="line"><a name="l03561"></a><span class="lineno"> 3561</span>  }</div> +<div class="line"><a name="l03562"></a><span class="lineno"> 3562</span>  </div> +<div class="line"><a name="l03563"></a><span class="lineno"> 3563</span>  forgetLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetLayerNormWeights());</div> +<div class="line"><a name="l03564"></a><span class="lineno"> 3564</span>  cellLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellLayerNormWeights());</div> +<div class="line"><a name="l03565"></a><span class="lineno"> 3565</span>  outputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputLayerNormWeights());</div> +<div class="line"><a name="l03566"></a><span class="lineno"> 3566</span>  </div> +<div class="line"><a name="l03567"></a><span class="lineno"> 3567</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a> = &forgetLayerNormWeights;</div> +<div class="line"><a name="l03568"></a><span class="lineno"> 3568</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a> = &cellLayerNormWeights;</div> +<div class="line"><a name="l03569"></a><span class="lineno"> 3569</span>  qLstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a> = &outputLayerNormWeights;</div> +<div class="line"><a name="l03570"></a><span class="lineno"> 3570</span>  }</div> <div class="line"><a name="l03571"></a><span class="lineno"> 3571</span>  </div> -<div class="line"><a name="l03572"></a><span class="lineno"> 3572</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03573"></a><span class="lineno"> 3573</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 2);</div> -<div class="line"><a name="l03574"></a><span class="lineno"> 3574</span>  </div> -<div class="line"><a name="l03575"></a><span class="lineno"> 3575</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_QuantizedLstmLayer();</div> -<div class="line"><a name="l03576"></a><span class="lineno"> 3576</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03577"></a><span class="lineno"> 3577</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div> -<div class="line"><a name="l03578"></a><span class="lineno"> 3578</span>  </div> -<div class="line"><a name="l03579"></a><span class="lineno"> 3579</span>  <a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html">armnn::QuantizedLstmInputParams</a> lstmInputParams;</div> -<div class="line"><a name="l03580"></a><span class="lineno"> 3580</span>  </div> -<div class="line"><a name="l03581"></a><span class="lineno"> 3581</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div> -<div class="line"><a name="l03582"></a><span class="lineno"> 3582</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div> -<div class="line"><a name="l03583"></a><span class="lineno"> 3583</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div> -<div class="line"><a name="l03584"></a><span class="lineno"> 3584</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div> -<div class="line"><a name="l03585"></a><span class="lineno"> 3585</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div> -<div class="line"><a name="l03586"></a><span class="lineno"> 3586</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div> -<div class="line"><a name="l03587"></a><span class="lineno"> 3587</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div> -<div class="line"><a name="l03588"></a><span class="lineno"> 3588</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div> -<div class="line"><a name="l03589"></a><span class="lineno"> 3589</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div> -<div class="line"><a name="l03590"></a><span class="lineno"> 3590</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div> -<div class="line"><a name="l03591"></a><span class="lineno"> 3591</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellBias());</div> -<div class="line"><a name="l03592"></a><span class="lineno"> 3592</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div> +<div class="line"><a name="l03572"></a><span class="lineno"> 3572</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddQLstmLayer(qLstmDescriptor, qLstmInputParams, layerName.c_str());</div> +<div class="line"><a name="l03573"></a><span class="lineno"> 3573</span>  </div> +<div class="line"><a name="l03574"></a><span class="lineno"> 3574</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputStateOutInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03575"></a><span class="lineno"> 3575</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputStateOutInfo);</div> +<div class="line"><a name="l03576"></a><span class="lineno"> 3576</span>  </div> +<div class="line"><a name="l03577"></a><span class="lineno"> 3577</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> cellStateOutInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> +<div class="line"><a name="l03578"></a><span class="lineno"> 3578</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(cellStateOutInfo);</div> +<div class="line"><a name="l03579"></a><span class="lineno"> 3579</span>  </div> +<div class="line"><a name="l03580"></a><span class="lineno"> 3580</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[2]);</div> +<div class="line"><a name="l03581"></a><span class="lineno"> 3581</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l03582"></a><span class="lineno"> 3582</span>  </div> +<div class="line"><a name="l03583"></a><span class="lineno"> 3583</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03584"></a><span class="lineno"> 3584</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03585"></a><span class="lineno"> 3585</span> }</div> +<div class="line"><a name="l03586"></a><span class="lineno"> 3586</span>  </div> +<div class="line"><a name="l03587"></a><span class="lineno"> 3587</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseQuantizedLstm(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03588"></a><span class="lineno"> 3588</span> {</div> +<div class="line"><a name="l03589"></a><span class="lineno"> 3589</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03590"></a><span class="lineno"> 3590</span>  </div> +<div class="line"><a name="l03591"></a><span class="lineno"> 3591</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03592"></a><span class="lineno"> 3592</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div> <div class="line"><a name="l03593"></a><span class="lineno"> 3593</span>  </div> -<div class="line"><a name="l03594"></a><span class="lineno"> 3594</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div> -<div class="line"><a name="l03595"></a><span class="lineno"> 3595</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div> -<div class="line"><a name="l03596"></a><span class="lineno"> 3596</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div> -<div class="line"><a name="l03597"></a><span class="lineno"> 3597</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div> -<div class="line"><a name="l03598"></a><span class="lineno"> 3598</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div> -<div class="line"><a name="l03599"></a><span class="lineno"> 3599</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div> -<div class="line"><a name="l03600"></a><span class="lineno"> 3600</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div> -<div class="line"><a name="l03601"></a><span class="lineno"> 3601</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div> -<div class="line"><a name="l03602"></a><span class="lineno"> 3602</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div> -<div class="line"><a name="l03603"></a><span class="lineno"> 3603</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div> -<div class="line"><a name="l03604"></a><span class="lineno"> 3604</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div> -<div class="line"><a name="l03605"></a><span class="lineno"> 3605</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div> -<div class="line"><a name="l03606"></a><span class="lineno"> 3606</span>  </div> -<div class="line"><a name="l03607"></a><span class="lineno"> 3607</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddQuantizedLstmLayer(lstmInputParams, layerName.c_str());</div> -<div class="line"><a name="l03608"></a><span class="lineno"> 3608</span>  </div> -<div class="line"><a name="l03609"></a><span class="lineno"> 3609</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo1 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03610"></a><span class="lineno"> 3610</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo1);</div> -<div class="line"><a name="l03611"></a><span class="lineno"> 3611</span>  </div> -<div class="line"><a name="l03612"></a><span class="lineno"> 3612</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo2 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> -<div class="line"><a name="l03613"></a><span class="lineno"> 3613</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo2);</div> -<div class="line"><a name="l03614"></a><span class="lineno"> 3614</span>  </div> -<div class="line"><a name="l03615"></a><span class="lineno"> 3615</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03616"></a><span class="lineno"> 3616</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03617"></a><span class="lineno"> 3617</span> }</div> -<div class="line"><a name="l03618"></a><span class="lineno"> 3618</span>  </div> -<div class="line"><a name="l03619"></a><span class="lineno"> 3619</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDequantize(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03620"></a><span class="lineno"> 3620</span> {</div> -<div class="line"><a name="l03621"></a><span class="lineno"> 3621</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03622"></a><span class="lineno"> 3622</span>  </div> -<div class="line"><a name="l03623"></a><span class="lineno"> 3623</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03624"></a><span class="lineno"> 3624</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l03625"></a><span class="lineno"> 3625</span>  </div> -<div class="line"><a name="l03626"></a><span class="lineno"> 3626</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03627"></a><span class="lineno"> 3627</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03594"></a><span class="lineno"> 3594</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03595"></a><span class="lineno"> 3595</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 2);</div> +<div class="line"><a name="l03596"></a><span class="lineno"> 3596</span>  </div> +<div class="line"><a name="l03597"></a><span class="lineno"> 3597</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_QuantizedLstmLayer();</div> +<div class="line"><a name="l03598"></a><span class="lineno"> 3598</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03599"></a><span class="lineno"> 3599</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div> +<div class="line"><a name="l03600"></a><span class="lineno"> 3600</span>  </div> +<div class="line"><a name="l03601"></a><span class="lineno"> 3601</span>  <a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html">armnn::QuantizedLstmInputParams</a> lstmInputParams;</div> +<div class="line"><a name="l03602"></a><span class="lineno"> 3602</span>  </div> +<div class="line"><a name="l03603"></a><span class="lineno"> 3603</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div> +<div class="line"><a name="l03604"></a><span class="lineno"> 3604</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div> +<div class="line"><a name="l03605"></a><span class="lineno"> 3605</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div> +<div class="line"><a name="l03606"></a><span class="lineno"> 3606</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div> +<div class="line"><a name="l03607"></a><span class="lineno"> 3607</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div> +<div class="line"><a name="l03608"></a><span class="lineno"> 3608</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div> +<div class="line"><a name="l03609"></a><span class="lineno"> 3609</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div> +<div class="line"><a name="l03610"></a><span class="lineno"> 3610</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div> +<div class="line"><a name="l03611"></a><span class="lineno"> 3611</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div> +<div class="line"><a name="l03612"></a><span class="lineno"> 3612</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div> +<div class="line"><a name="l03613"></a><span class="lineno"> 3613</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellBias());</div> +<div class="line"><a name="l03614"></a><span class="lineno"> 3614</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div> +<div class="line"><a name="l03615"></a><span class="lineno"> 3615</span>  </div> +<div class="line"><a name="l03616"></a><span class="lineno"> 3616</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div> +<div class="line"><a name="l03617"></a><span class="lineno"> 3617</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div> +<div class="line"><a name="l03618"></a><span class="lineno"> 3618</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div> +<div class="line"><a name="l03619"></a><span class="lineno"> 3619</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div> +<div class="line"><a name="l03620"></a><span class="lineno"> 3620</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div> +<div class="line"><a name="l03621"></a><span class="lineno"> 3621</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div> +<div class="line"><a name="l03622"></a><span class="lineno"> 3622</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div> +<div class="line"><a name="l03623"></a><span class="lineno"> 3623</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div> +<div class="line"><a name="l03624"></a><span class="lineno"> 3624</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div> +<div class="line"><a name="l03625"></a><span class="lineno"> 3625</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div> +<div class="line"><a name="l03626"></a><span class="lineno"> 3626</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div> +<div class="line"><a name="l03627"></a><span class="lineno"> 3627</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.html#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div> <div class="line"><a name="l03628"></a><span class="lineno"> 3628</span>  </div> -<div class="line"><a name="l03629"></a><span class="lineno"> 3629</span>  <span class="keyword">const</span> std::string layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03630"></a><span class="lineno"> 3630</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddDequantizeLayer(layerName.c_str());</div> -<div class="line"><a name="l03631"></a><span class="lineno"> 3631</span>  </div> -<div class="line"><a name="l03632"></a><span class="lineno"> 3632</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03633"></a><span class="lineno"> 3633</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03634"></a><span class="lineno"> 3634</span>  </div> -<div class="line"><a name="l03635"></a><span class="lineno"> 3635</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03636"></a><span class="lineno"> 3636</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03637"></a><span class="lineno"> 3637</span> }</div> -<div class="line"><a name="l03638"></a><span class="lineno"> 3638</span>  </div> -<div class="line"><a name="l03639"></a><span class="lineno"> 3639</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMerge(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03640"></a><span class="lineno"> 3640</span> {</div> -<div class="line"><a name="l03641"></a><span class="lineno"> 3641</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03642"></a><span class="lineno"> 3642</span>  </div> -<div class="line"><a name="l03643"></a><span class="lineno"> 3643</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03644"></a><span class="lineno"> 3644</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l03645"></a><span class="lineno"> 3645</span>  </div> -<div class="line"><a name="l03646"></a><span class="lineno"> 3646</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03647"></a><span class="lineno"> 3647</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03648"></a><span class="lineno"> 3648</span>  </div> -<div class="line"><a name="l03649"></a><span class="lineno"> 3649</span>  <span class="keyword">const</span> std::string layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03650"></a><span class="lineno"> 3650</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddMergeLayer(layerName.c_str());</div> -<div class="line"><a name="l03651"></a><span class="lineno"> 3651</span>  </div> -<div class="line"><a name="l03652"></a><span class="lineno"> 3652</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03653"></a><span class="lineno"> 3653</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03654"></a><span class="lineno"> 3654</span>  </div> -<div class="line"><a name="l03655"></a><span class="lineno"> 3655</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03656"></a><span class="lineno"> 3656</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03657"></a><span class="lineno"> 3657</span> }</div> -<div class="line"><a name="l03658"></a><span class="lineno"> 3658</span>  </div> -<div class="line"><a name="l03659"></a><span class="lineno"> 3659</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSwitch(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03660"></a><span class="lineno"> 3660</span> {</div> -<div class="line"><a name="l03661"></a><span class="lineno"> 3661</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03662"></a><span class="lineno"> 3662</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03663"></a><span class="lineno"> 3663</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l03664"></a><span class="lineno"> 3664</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l03665"></a><span class="lineno"> 3665</span>  </div> -<div class="line"><a name="l03666"></a><span class="lineno"> 3666</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03667"></a><span class="lineno"> 3667</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 2);</div> -<div class="line"><a name="l03668"></a><span class="lineno"> 3668</span>  </div> -<div class="line"><a name="l03669"></a><span class="lineno"> 3669</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03670"></a><span class="lineno"> 3670</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSwitchLayer(layerName.c_str());</div> -<div class="line"><a name="l03671"></a><span class="lineno"> 3671</span>  </div> -<div class="line"><a name="l03672"></a><span class="lineno"> 3672</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> output0TensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03673"></a><span class="lineno"> 3673</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(output0TensorInfo);</div> -<div class="line"><a name="l03674"></a><span class="lineno"> 3674</span>  </div> -<div class="line"><a name="l03675"></a><span class="lineno"> 3675</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> output1TensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> -<div class="line"><a name="l03676"></a><span class="lineno"> 3676</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(output1TensorInfo);</div> -<div class="line"><a name="l03677"></a><span class="lineno"> 3677</span>  </div> -<div class="line"><a name="l03678"></a><span class="lineno"> 3678</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03679"></a><span class="lineno"> 3679</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03680"></a><span class="lineno"> 3680</span> }</div> -<div class="line"><a name="l03681"></a><span class="lineno"> 3681</span>  </div> -<div class="line"><a name="l03682"></a><span class="lineno"> 3682</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseTile(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03683"></a><span class="lineno"> 3683</span> {</div> -<div class="line"><a name="l03684"></a><span class="lineno"> 3684</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03685"></a><span class="lineno"> 3685</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03686"></a><span class="lineno"> 3686</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l03687"></a><span class="lineno"> 3687</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l03688"></a><span class="lineno"> 3688</span>  </div> -<div class="line"><a name="l03689"></a><span class="lineno"> 3689</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03690"></a><span class="lineno"> 3690</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03691"></a><span class="lineno"> 3691</span>  </div> -<div class="line"><a name="l03692"></a><span class="lineno"> 3692</span>  <span class="keyword">auto</span> <a class="code" href="classarmnn_1_1_tile_layer.html">TileLayer</a> = graph->layers()->Get(layerIndex)->layer_as_TileLayer();</div> -<div class="line"><a name="l03693"></a><span class="lineno"> 3693</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03694"></a><span class="lineno"> 3694</span>  <span class="keyword">auto</span> flatBufferDescriptor = <a class="code" href="classarmnn_1_1_tile_layer.html">TileLayer</a>->descriptor();</div> -<div class="line"><a name="l03695"></a><span class="lineno"> 3695</span>  <span class="keyword">auto</span> flatBufferMultiples = flatBufferDescriptor->m_Multiples();</div> +<div class="line"><a name="l03629"></a><span class="lineno"> 3629</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddQuantizedLstmLayer(lstmInputParams, layerName.c_str());</div> +<div class="line"><a name="l03630"></a><span class="lineno"> 3630</span>  </div> +<div class="line"><a name="l03631"></a><span class="lineno"> 3631</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo1 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03632"></a><span class="lineno"> 3632</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo1);</div> +<div class="line"><a name="l03633"></a><span class="lineno"> 3633</span>  </div> +<div class="line"><a name="l03634"></a><span class="lineno"> 3634</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo2 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> +<div class="line"><a name="l03635"></a><span class="lineno"> 3635</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo2);</div> +<div class="line"><a name="l03636"></a><span class="lineno"> 3636</span>  </div> +<div class="line"><a name="l03637"></a><span class="lineno"> 3637</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03638"></a><span class="lineno"> 3638</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03639"></a><span class="lineno"> 3639</span> }</div> +<div class="line"><a name="l03640"></a><span class="lineno"> 3640</span>  </div> +<div class="line"><a name="l03641"></a><span class="lineno"> 3641</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseDequantize(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03642"></a><span class="lineno"> 3642</span> {</div> +<div class="line"><a name="l03643"></a><span class="lineno"> 3643</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03644"></a><span class="lineno"> 3644</span>  </div> +<div class="line"><a name="l03645"></a><span class="lineno"> 3645</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03646"></a><span class="lineno"> 3646</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03647"></a><span class="lineno"> 3647</span>  </div> +<div class="line"><a name="l03648"></a><span class="lineno"> 3648</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03649"></a><span class="lineno"> 3649</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03650"></a><span class="lineno"> 3650</span>  </div> +<div class="line"><a name="l03651"></a><span class="lineno"> 3651</span>  <span class="keyword">const</span> std::string layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03652"></a><span class="lineno"> 3652</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddDequantizeLayer(layerName.c_str());</div> +<div class="line"><a name="l03653"></a><span class="lineno"> 3653</span>  </div> +<div class="line"><a name="l03654"></a><span class="lineno"> 3654</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03655"></a><span class="lineno"> 3655</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03656"></a><span class="lineno"> 3656</span>  </div> +<div class="line"><a name="l03657"></a><span class="lineno"> 3657</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03658"></a><span class="lineno"> 3658</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03659"></a><span class="lineno"> 3659</span> }</div> +<div class="line"><a name="l03660"></a><span class="lineno"> 3660</span>  </div> +<div class="line"><a name="l03661"></a><span class="lineno"> 3661</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseMerge(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03662"></a><span class="lineno"> 3662</span> {</div> +<div class="line"><a name="l03663"></a><span class="lineno"> 3663</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03664"></a><span class="lineno"> 3664</span>  </div> +<div class="line"><a name="l03665"></a><span class="lineno"> 3665</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03666"></a><span class="lineno"> 3666</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l03667"></a><span class="lineno"> 3667</span>  </div> +<div class="line"><a name="l03668"></a><span class="lineno"> 3668</span>  <a class="code" href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03669"></a><span class="lineno"> 3669</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03670"></a><span class="lineno"> 3670</span>  </div> +<div class="line"><a name="l03671"></a><span class="lineno"> 3671</span>  <span class="keyword">const</span> std::string layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03672"></a><span class="lineno"> 3672</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddMergeLayer(layerName.c_str());</div> +<div class="line"><a name="l03673"></a><span class="lineno"> 3673</span>  </div> +<div class="line"><a name="l03674"></a><span class="lineno"> 3674</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03675"></a><span class="lineno"> 3675</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03676"></a><span class="lineno"> 3676</span>  </div> +<div class="line"><a name="l03677"></a><span class="lineno"> 3677</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03678"></a><span class="lineno"> 3678</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03679"></a><span class="lineno"> 3679</span> }</div> +<div class="line"><a name="l03680"></a><span class="lineno"> 3680</span>  </div> +<div class="line"><a name="l03681"></a><span class="lineno"> 3681</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseSwitch(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03682"></a><span class="lineno"> 3682</span> {</div> +<div class="line"><a name="l03683"></a><span class="lineno"> 3683</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03684"></a><span class="lineno"> 3684</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03685"></a><span class="lineno"> 3685</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l03686"></a><span class="lineno"> 3686</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> +<div class="line"><a name="l03687"></a><span class="lineno"> 3687</span>  </div> +<div class="line"><a name="l03688"></a><span class="lineno"> 3688</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03689"></a><span class="lineno"> 3689</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 2);</div> +<div class="line"><a name="l03690"></a><span class="lineno"> 3690</span>  </div> +<div class="line"><a name="l03691"></a><span class="lineno"> 3691</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03692"></a><span class="lineno"> 3692</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddSwitchLayer(layerName.c_str());</div> +<div class="line"><a name="l03693"></a><span class="lineno"> 3693</span>  </div> +<div class="line"><a name="l03694"></a><span class="lineno"> 3694</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> output0TensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03695"></a><span class="lineno"> 3695</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(output0TensorInfo);</div> <div class="line"><a name="l03696"></a><span class="lineno"> 3696</span>  </div> -<div class="line"><a name="l03697"></a><span class="lineno"> 3697</span>  <a class="code" href="structarmnn_1_1_tile_descriptor.html">armnn::TileDescriptor</a> tileDescriptor;</div> -<div class="line"><a name="l03698"></a><span class="lineno"> 3698</span>  tileDescriptor.<a class="code" href="structarmnn_1_1_tile_descriptor.html#a4e66396e5ed6ede8d87dc75103645def">m_Multiples</a> = std::vector<unsigned int>(flatBufferMultiples->begin(), flatBufferMultiples->end());</div> +<div class="line"><a name="l03697"></a><span class="lineno"> 3697</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> output1TensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> +<div class="line"><a name="l03698"></a><span class="lineno"> 3698</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(output1TensorInfo);</div> <div class="line"><a name="l03699"></a><span class="lineno"> 3699</span>  </div> -<div class="line"><a name="l03700"></a><span class="lineno"> 3700</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddTileLayer(tileDescriptor, layerName.c_str());</div> -<div class="line"><a name="l03701"></a><span class="lineno"> 3701</span>  </div> -<div class="line"><a name="l03702"></a><span class="lineno"> 3702</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> output0TensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03703"></a><span class="lineno"> 3703</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(output0TensorInfo);</div> -<div class="line"><a name="l03704"></a><span class="lineno"> 3704</span>  </div> -<div class="line"><a name="l03705"></a><span class="lineno"> 3705</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03706"></a><span class="lineno"> 3706</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03707"></a><span class="lineno"> 3707</span> }</div> -<div class="line"><a name="l03708"></a><span class="lineno"> 3708</span>  </div> -<div class="line"><a name="l03709"></a><span class="lineno"> 3709</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePrelu(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03710"></a><span class="lineno"> 3710</span> {</div> -<div class="line"><a name="l03711"></a><span class="lineno"> 3711</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03712"></a><span class="lineno"> 3712</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03713"></a><span class="lineno"> 3713</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> -<div class="line"><a name="l03714"></a><span class="lineno"> 3714</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> -<div class="line"><a name="l03715"></a><span class="lineno"> 3715</span>  </div> -<div class="line"><a name="l03716"></a><span class="lineno"> 3716</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03717"></a><span class="lineno"> 3717</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03700"></a><span class="lineno"> 3700</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03701"></a><span class="lineno"> 3701</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03702"></a><span class="lineno"> 3702</span> }</div> +<div class="line"><a name="l03703"></a><span class="lineno"> 3703</span>  </div> +<div class="line"><a name="l03704"></a><span class="lineno"> 3704</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseTile(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03705"></a><span class="lineno"> 3705</span> {</div> +<div class="line"><a name="l03706"></a><span class="lineno"> 3706</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03707"></a><span class="lineno"> 3707</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03708"></a><span class="lineno"> 3708</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l03709"></a><span class="lineno"> 3709</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03710"></a><span class="lineno"> 3710</span>  </div> +<div class="line"><a name="l03711"></a><span class="lineno"> 3711</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03712"></a><span class="lineno"> 3712</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03713"></a><span class="lineno"> 3713</span>  </div> +<div class="line"><a name="l03714"></a><span class="lineno"> 3714</span>  <span class="keyword">auto</span> <a class="code" href="classarmnn_1_1_tile_layer.html">TileLayer</a> = graph->layers()->Get(layerIndex)->layer_as_TileLayer();</div> +<div class="line"><a name="l03715"></a><span class="lineno"> 3715</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03716"></a><span class="lineno"> 3716</span>  <span class="keyword">auto</span> flatBufferDescriptor = <a class="code" href="classarmnn_1_1_tile_layer.html">TileLayer</a>->descriptor();</div> +<div class="line"><a name="l03717"></a><span class="lineno"> 3717</span>  <span class="keyword">auto</span> flatBufferMultiples = flatBufferDescriptor->m_Multiples();</div> <div class="line"><a name="l03718"></a><span class="lineno"> 3718</span>  </div> -<div class="line"><a name="l03719"></a><span class="lineno"> 3719</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03720"></a><span class="lineno"> 3720</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPreluLayer(layerName.c_str());</div> +<div class="line"><a name="l03719"></a><span class="lineno"> 3719</span>  <a class="code" href="structarmnn_1_1_tile_descriptor.html">armnn::TileDescriptor</a> tileDescriptor;</div> +<div class="line"><a name="l03720"></a><span class="lineno"> 3720</span>  tileDescriptor.<a class="code" href="structarmnn_1_1_tile_descriptor.html#a4e66396e5ed6ede8d87dc75103645def">m_Multiples</a> = std::vector<unsigned int>(flatBufferMultiples->begin(), flatBufferMultiples->end());</div> <div class="line"><a name="l03721"></a><span class="lineno"> 3721</span>  </div> -<div class="line"><a name="l03722"></a><span class="lineno"> 3722</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03723"></a><span class="lineno"> 3723</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03724"></a><span class="lineno"> 3724</span>  </div> -<div class="line"><a name="l03725"></a><span class="lineno"> 3725</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03726"></a><span class="lineno"> 3726</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03727"></a><span class="lineno"> 3727</span> }</div> -<div class="line"><a name="l03728"></a><span class="lineno"> 3728</span>  </div> -<div class="line"><a name="l03729"></a><span class="lineno"> 3729</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseTranspose(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03730"></a><span class="lineno"> 3730</span> {</div> -<div class="line"><a name="l03731"></a><span class="lineno"> 3731</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03732"></a><span class="lineno"> 3732</span>  </div> -<div class="line"><a name="l03733"></a><span class="lineno"> 3733</span>  <span class="keyword">auto</span> dimsMapping = graph->layers()->Get(layerIndex)->layer_as_TransposeLayer()->descriptor()->dimMappings();</div> -<div class="line"><a name="l03734"></a><span class="lineno"> 3734</span>  </div> -<div class="line"><a name="l03735"></a><span class="lineno"> 3735</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03736"></a><span class="lineno"> 3736</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03722"></a><span class="lineno"> 3722</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddTileLayer(tileDescriptor, layerName.c_str());</div> +<div class="line"><a name="l03723"></a><span class="lineno"> 3723</span>  </div> +<div class="line"><a name="l03724"></a><span class="lineno"> 3724</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> output0TensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03725"></a><span class="lineno"> 3725</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(output0TensorInfo);</div> +<div class="line"><a name="l03726"></a><span class="lineno"> 3726</span>  </div> +<div class="line"><a name="l03727"></a><span class="lineno"> 3727</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03728"></a><span class="lineno"> 3728</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03729"></a><span class="lineno"> 3729</span> }</div> +<div class="line"><a name="l03730"></a><span class="lineno"> 3730</span>  </div> +<div class="line"><a name="l03731"></a><span class="lineno"> 3731</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParsePrelu(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03732"></a><span class="lineno"> 3732</span> {</div> +<div class="line"><a name="l03733"></a><span class="lineno"> 3733</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03734"></a><span class="lineno"> 3734</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03735"></a><span class="lineno"> 3735</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l03736"></a><span class="lineno"> 3736</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div> <div class="line"><a name="l03737"></a><span class="lineno"> 3737</span>  </div> <div class="line"><a name="l03738"></a><span class="lineno"> 3738</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> <div class="line"><a name="l03739"></a><span class="lineno"> 3739</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03740"></a><span class="lineno"> 3740</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03741"></a><span class="lineno"> 3741</span>  </div> -<div class="line"><a name="l03742"></a><span class="lineno"> 3742</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03743"></a><span class="lineno"> 3743</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_descriptor.html">armnn::TransposeDescriptor</a> descriptor(<a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a>(dimsMapping->data(), dimsMapping->size()));</div> -<div class="line"><a name="l03744"></a><span class="lineno"> 3744</span>  </div> -<div class="line"><a name="l03745"></a><span class="lineno"> 3745</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddTransposeLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l03746"></a><span class="lineno"> 3746</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> -<div class="line"><a name="l03747"></a><span class="lineno"> 3747</span>  </div> -<div class="line"><a name="l03748"></a><span class="lineno"> 3748</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03749"></a><span class="lineno"> 3749</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03750"></a><span class="lineno"> 3750</span> }</div> -<div class="line"><a name="l03751"></a><span class="lineno"> 3751</span>  </div> -<div class="line"><a name="l03752"></a><span class="lineno"> 3752</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseTransposeConvolution2d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03753"></a><span class="lineno"> 3753</span> {</div> -<div class="line"><a name="l03754"></a><span class="lineno"> 3754</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03755"></a><span class="lineno"> 3755</span>  </div> -<div class="line"><a name="l03756"></a><span class="lineno"> 3756</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03757"></a><span class="lineno"> 3757</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> -<div class="line"><a name="l03758"></a><span class="lineno"> 3758</span>  </div> -<div class="line"><a name="l03759"></a><span class="lineno"> 3759</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03760"></a><span class="lineno"> 3760</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03761"></a><span class="lineno"> 3761</span>  </div> -<div class="line"><a name="l03762"></a><span class="lineno"> 3762</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_TransposeConvolution2dLayer();</div> -<div class="line"><a name="l03763"></a><span class="lineno"> 3763</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03764"></a><span class="lineno"> 3764</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> -<div class="line"><a name="l03765"></a><span class="lineno"> 3765</span>  </div> -<div class="line"><a name="l03766"></a><span class="lineno"> 3766</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">armnn::TransposeConvolution2dDescriptor</a> descriptor;</div> -<div class="line"><a name="l03767"></a><span class="lineno"> 3767</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = serializerDescriptor->padLeft();</div> -<div class="line"><a name="l03768"></a><span class="lineno"> 3768</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = serializerDescriptor->padRight();</div> -<div class="line"><a name="l03769"></a><span class="lineno"> 3769</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = serializerDescriptor->padTop();</div> -<div class="line"><a name="l03770"></a><span class="lineno"> 3770</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = serializerDescriptor->padBottom();</div> -<div class="line"><a name="l03771"></a><span class="lineno"> 3771</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = serializerDescriptor->strideX();</div> -<div class="line"><a name="l03772"></a><span class="lineno"> 3772</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = serializerDescriptor->strideY();;</div> -<div class="line"><a name="l03773"></a><span class="lineno"> 3773</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = serializerDescriptor->biasEnabled();;</div> -<div class="line"><a name="l03774"></a><span class="lineno"> 3774</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div> -<div class="line"><a name="l03775"></a><span class="lineno"> 3775</span>  </div> -<div class="line"><a name="l03776"></a><span class="lineno"> 3776</span>  <span class="comment">// weights & biases</span></div> -<div class="line"><a name="l03777"></a><span class="lineno"> 3777</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->weights());</div> -<div class="line"><a name="l03778"></a><span class="lineno"> 3778</span>  <a class="code" href="classarmnn_1_1_optional.html">armnn::Optional<armnn::ConstTensor></a> optionalBiases;</div> -<div class="line"><a name="l03779"></a><span class="lineno"> 3779</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div> -<div class="line"><a name="l03780"></a><span class="lineno"> 3780</span>  {</div> -<div class="line"><a name="l03781"></a><span class="lineno"> 3781</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> biases = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->biases());</div> -<div class="line"><a name="l03782"></a><span class="lineno"> 3782</span>  optionalBiases = armnn::MakeOptional<armnn::ConstTensor>(biases);</div> -<div class="line"><a name="l03783"></a><span class="lineno"> 3783</span>  }</div> -<div class="line"><a name="l03784"></a><span class="lineno"> 3784</span>  </div> -<div class="line"><a name="l03785"></a><span class="lineno"> 3785</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddTransposeConvolution2dLayer(descriptor,</div> -<div class="line"><a name="l03786"></a><span class="lineno"> 3786</span>  weights,</div> -<div class="line"><a name="l03787"></a><span class="lineno"> 3787</span>  optionalBiases,</div> -<div class="line"><a name="l03788"></a><span class="lineno"> 3788</span>  layerName.c_str());</div> -<div class="line"><a name="l03789"></a><span class="lineno"> 3789</span>  </div> -<div class="line"><a name="l03790"></a><span class="lineno"> 3790</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03791"></a><span class="lineno"> 3791</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03792"></a><span class="lineno"> 3792</span>  </div> -<div class="line"><a name="l03793"></a><span class="lineno"> 3793</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03794"></a><span class="lineno"> 3794</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03795"></a><span class="lineno"> 3795</span> }</div> -<div class="line"><a name="l03796"></a><span class="lineno"> 3796</span>  </div> -<div class="line"><a name="l03797"></a><span class="lineno"> 3797</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseStack(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03798"></a><span class="lineno"> 3798</span> {</div> -<div class="line"><a name="l03799"></a><span class="lineno"> 3799</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03800"></a><span class="lineno"> 3800</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03801"></a><span class="lineno"> 3801</span>  </div> -<div class="line"><a name="l03802"></a><span class="lineno"> 3802</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03803"></a><span class="lineno"> 3803</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> -<div class="line"><a name="l03804"></a><span class="lineno"> 3804</span>  </div> -<div class="line"><a name="l03805"></a><span class="lineno"> 3805</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_StackLayer()->descriptor();</div> -<div class="line"><a name="l03806"></a><span class="lineno"> 3806</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis = flatBufferDescriptor->axis();</div> -<div class="line"><a name="l03807"></a><span class="lineno"> 3807</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = flatBufferDescriptor->numInputs();</div> -<div class="line"><a name="l03808"></a><span class="lineno"> 3808</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> -<div class="line"><a name="l03809"></a><span class="lineno"> 3809</span>  </div> -<div class="line"><a name="l03810"></a><span class="lineno"> 3810</span>  <span class="keyword">auto</span> flatBufferInputShape = flatBufferDescriptor->inputShape();</div> -<div class="line"><a name="l03811"></a><span class="lineno"> 3811</span>  std::vector<uint32_t> vectorInputShape(flatBufferInputShape->begin(),</div> -<div class="line"><a name="l03812"></a><span class="lineno"> 3812</span>  flatBufferInputShape->begin() + flatBufferInputShape->size());</div> -<div class="line"><a name="l03813"></a><span class="lineno"> 3813</span>  </div> -<div class="line"><a name="l03814"></a><span class="lineno"> 3814</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape(<span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(vectorInputShape.size()), vectorInputShape.data());</div> -<div class="line"><a name="l03815"></a><span class="lineno"> 3815</span>  <a class="code" href="structarmnn_1_1_stack_descriptor.html">armnn::StackDescriptor</a> descriptor(axis, numInputs, inputShape);</div> -<div class="line"><a name="l03816"></a><span class="lineno"> 3816</span>  </div> -<div class="line"><a name="l03817"></a><span class="lineno"> 3817</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<inputs.size(); ++i)</div> -<div class="line"><a name="l03818"></a><span class="lineno"> 3818</span>  {</div> -<div class="line"><a name="l03819"></a><span class="lineno"> 3819</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputShape = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(inputs[i]).<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> -<div class="line"><a name="l03820"></a><span class="lineno"> 3820</span>  <span class="keywordflow">if</span> (descriptor.m_InputShape != inputShape)</div> -<div class="line"><a name="l03821"></a><span class="lineno"> 3821</span>  {</div> -<div class="line"><a name="l03822"></a><span class="lineno"> 3822</span>  std::stringstream ss;</div> -<div class="line"><a name="l03823"></a><span class="lineno"> 3823</span>  ss << <span class="stringliteral">"Shape of input "</span></div> -<div class="line"><a name="l03824"></a><span class="lineno"> 3824</span>  << i</div> -<div class="line"><a name="l03825"></a><span class="lineno"> 3825</span>  << <span class="stringliteral">" "</span></div> -<div class="line"><a name="l03826"></a><span class="lineno"> 3826</span>  << inputShape</div> -<div class="line"><a name="l03827"></a><span class="lineno"> 3827</span>  << <span class="stringliteral">" does not equal defined input shape "</span></div> -<div class="line"><a name="l03828"></a><span class="lineno"> 3828</span>  << descriptor.m_InputShape</div> -<div class="line"><a name="l03829"></a><span class="lineno"> 3829</span>  << <span class="stringliteral">": "</span></div> -<div class="line"><a name="l03830"></a><span class="lineno"> 3830</span>  << <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString();</div> -<div class="line"><a name="l03831"></a><span class="lineno"> 3831</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(ss.str());</div> -<div class="line"><a name="l03832"></a><span class="lineno"> 3832</span>  }</div> -<div class="line"><a name="l03833"></a><span class="lineno"> 3833</span>  }</div> -<div class="line"><a name="l03834"></a><span class="lineno"> 3834</span>  </div> -<div class="line"><a name="l03835"></a><span class="lineno"> 3835</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03836"></a><span class="lineno"> 3836</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddStackLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l03837"></a><span class="lineno"> 3837</span>  </div> -<div class="line"><a name="l03838"></a><span class="lineno"> 3838</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03839"></a><span class="lineno"> 3839</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> -<div class="line"><a name="l03840"></a><span class="lineno"> 3840</span>  </div> -<div class="line"><a name="l03841"></a><span class="lineno"> 3841</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03842"></a><span class="lineno"> 3842</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03843"></a><span class="lineno"> 3843</span> }</div> -<div class="line"><a name="l03844"></a><span class="lineno"> 3844</span>  </div> -<div class="line"><a name="l03845"></a><span class="lineno"> 3845</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseStandIn(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03846"></a><span class="lineno"> 3846</span> {</div> -<div class="line"><a name="l03847"></a><span class="lineno"> 3847</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03848"></a><span class="lineno"> 3848</span>  </div> -<div class="line"><a name="l03849"></a><span class="lineno"> 3849</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03850"></a><span class="lineno"> 3850</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03851"></a><span class="lineno"> 3851</span>  </div> -<div class="line"><a name="l03852"></a><span class="lineno"> 3852</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_StandInLayer();</div> -<div class="line"><a name="l03853"></a><span class="lineno"> 3853</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> -<div class="line"><a name="l03854"></a><span class="lineno"> 3854</span>  </div> -<div class="line"><a name="l03855"></a><span class="lineno"> 3855</span>  <a class="code" href="structarmnn_1_1_stand_in_descriptor.html">armnn::StandInDescriptor</a> descriptor;</div> -<div class="line"><a name="l03856"></a><span class="lineno"> 3856</span>  descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#aed6086070440ceb94129bef06f70173f">m_NumInputs</a> = fbDescriptor->numInputs();</div> -<div class="line"><a name="l03857"></a><span class="lineno"> 3857</span>  descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a> = fbDescriptor->numOutputs();</div> -<div class="line"><a name="l03858"></a><span class="lineno"> 3858</span>  </div> -<div class="line"><a name="l03859"></a><span class="lineno"> 3859</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#aed6086070440ceb94129bef06f70173f">m_NumInputs</a>);</div> -<div class="line"><a name="l03860"></a><span class="lineno"> 3860</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a>);</div> -<div class="line"><a name="l03861"></a><span class="lineno"> 3861</span>  </div> -<div class="line"><a name="l03862"></a><span class="lineno"> 3862</span>  <span class="keyword">const</span> std::string layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03863"></a><span class="lineno"> 3863</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer = m_Network->AddStandInLayer(descriptor, layerName.c_str());</div> -<div class="line"><a name="l03864"></a><span class="lineno"> 3864</span>  </div> -<div class="line"><a name="l03865"></a><span class="lineno"> 3865</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a>; ++i)</div> -<div class="line"><a name="l03866"></a><span class="lineno"> 3866</span>  {</div> -<div class="line"><a name="l03867"></a><span class="lineno"> 3867</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[i]);</div> -<div class="line"><a name="l03868"></a><span class="lineno"> 3868</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(i).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> -<div class="line"><a name="l03869"></a><span class="lineno"> 3869</span>  }</div> +<div class="line"><a name="l03740"></a><span class="lineno"> 3740</span>  </div> +<div class="line"><a name="l03741"></a><span class="lineno"> 3741</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03742"></a><span class="lineno"> 3742</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddPreluLayer(layerName.c_str());</div> +<div class="line"><a name="l03743"></a><span class="lineno"> 3743</span>  </div> +<div class="line"><a name="l03744"></a><span class="lineno"> 3744</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03745"></a><span class="lineno"> 3745</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03746"></a><span class="lineno"> 3746</span>  </div> +<div class="line"><a name="l03747"></a><span class="lineno"> 3747</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03748"></a><span class="lineno"> 3748</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03749"></a><span class="lineno"> 3749</span> }</div> +<div class="line"><a name="l03750"></a><span class="lineno"> 3750</span>  </div> +<div class="line"><a name="l03751"></a><span class="lineno"> 3751</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseTranspose(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03752"></a><span class="lineno"> 3752</span> {</div> +<div class="line"><a name="l03753"></a><span class="lineno"> 3753</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03754"></a><span class="lineno"> 3754</span>  </div> +<div class="line"><a name="l03755"></a><span class="lineno"> 3755</span>  <span class="keyword">auto</span> dimsMapping = graph->layers()->Get(layerIndex)->layer_as_TransposeLayer()->descriptor()->dimMappings();</div> +<div class="line"><a name="l03756"></a><span class="lineno"> 3756</span>  </div> +<div class="line"><a name="l03757"></a><span class="lineno"> 3757</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03758"></a><span class="lineno"> 3758</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03759"></a><span class="lineno"> 3759</span>  </div> +<div class="line"><a name="l03760"></a><span class="lineno"> 3760</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03761"></a><span class="lineno"> 3761</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03762"></a><span class="lineno"> 3762</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03763"></a><span class="lineno"> 3763</span>  </div> +<div class="line"><a name="l03764"></a><span class="lineno"> 3764</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03765"></a><span class="lineno"> 3765</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_descriptor.html">armnn::TransposeDescriptor</a> descriptor(<a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a>(dimsMapping->data(), dimsMapping->size()));</div> +<div class="line"><a name="l03766"></a><span class="lineno"> 3766</span>  </div> +<div class="line"><a name="l03767"></a><span class="lineno"> 3767</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddTransposeLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03768"></a><span class="lineno"> 3768</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l03769"></a><span class="lineno"> 3769</span>  </div> +<div class="line"><a name="l03770"></a><span class="lineno"> 3770</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03771"></a><span class="lineno"> 3771</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03772"></a><span class="lineno"> 3772</span> }</div> +<div class="line"><a name="l03773"></a><span class="lineno"> 3773</span>  </div> +<div class="line"><a name="l03774"></a><span class="lineno"> 3774</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseTransposeConvolution2d(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03775"></a><span class="lineno"> 3775</span> {</div> +<div class="line"><a name="l03776"></a><span class="lineno"> 3776</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03777"></a><span class="lineno"> 3777</span>  </div> +<div class="line"><a name="l03778"></a><span class="lineno"> 3778</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03779"></a><span class="lineno"> 3779</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div> +<div class="line"><a name="l03780"></a><span class="lineno"> 3780</span>  </div> +<div class="line"><a name="l03781"></a><span class="lineno"> 3781</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03782"></a><span class="lineno"> 3782</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03783"></a><span class="lineno"> 3783</span>  </div> +<div class="line"><a name="l03784"></a><span class="lineno"> 3784</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_TransposeConvolution2dLayer();</div> +<div class="line"><a name="l03785"></a><span class="lineno"> 3785</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03786"></a><span class="lineno"> 3786</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div> +<div class="line"><a name="l03787"></a><span class="lineno"> 3787</span>  </div> +<div class="line"><a name="l03788"></a><span class="lineno"> 3788</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">armnn::TransposeConvolution2dDescriptor</a> descriptor;</div> +<div class="line"><a name="l03789"></a><span class="lineno"> 3789</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = serializerDescriptor->padLeft();</div> +<div class="line"><a name="l03790"></a><span class="lineno"> 3790</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = serializerDescriptor->padRight();</div> +<div class="line"><a name="l03791"></a><span class="lineno"> 3791</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = serializerDescriptor->padTop();</div> +<div class="line"><a name="l03792"></a><span class="lineno"> 3792</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = serializerDescriptor->padBottom();</div> +<div class="line"><a name="l03793"></a><span class="lineno"> 3793</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = serializerDescriptor->strideX();</div> +<div class="line"><a name="l03794"></a><span class="lineno"> 3794</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = serializerDescriptor->strideY();;</div> +<div class="line"><a name="l03795"></a><span class="lineno"> 3795</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = serializerDescriptor->biasEnabled();;</div> +<div class="line"><a name="l03796"></a><span class="lineno"> 3796</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div> +<div class="line"><a name="l03797"></a><span class="lineno"> 3797</span>  </div> +<div class="line"><a name="l03798"></a><span class="lineno"> 3798</span>  <span class="comment">// weights & biases</span></div> +<div class="line"><a name="l03799"></a><span class="lineno"> 3799</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->weights());</div> +<div class="line"><a name="l03800"></a><span class="lineno"> 3800</span>  <a class="code" href="classarmnn_1_1_optional.html">armnn::Optional<armnn::ConstTensor></a> optionalBiases;</div> +<div class="line"><a name="l03801"></a><span class="lineno"> 3801</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div> +<div class="line"><a name="l03802"></a><span class="lineno"> 3802</span>  {</div> +<div class="line"><a name="l03803"></a><span class="lineno"> 3803</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> biases = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(serializerLayer->biases());</div> +<div class="line"><a name="l03804"></a><span class="lineno"> 3804</span>  optionalBiases = armnn::MakeOptional<armnn::ConstTensor>(biases);</div> +<div class="line"><a name="l03805"></a><span class="lineno"> 3805</span>  }</div> +<div class="line"><a name="l03806"></a><span class="lineno"> 3806</span>  </div> +<div class="line"><a name="l03807"></a><span class="lineno"> 3807</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddTransposeConvolution2dLayer(descriptor,</div> +<div class="line"><a name="l03808"></a><span class="lineno"> 3808</span>  weights,</div> +<div class="line"><a name="l03809"></a><span class="lineno"> 3809</span>  optionalBiases,</div> +<div class="line"><a name="l03810"></a><span class="lineno"> 3810</span>  layerName.c_str());</div> +<div class="line"><a name="l03811"></a><span class="lineno"> 3811</span>  </div> +<div class="line"><a name="l03812"></a><span class="lineno"> 3812</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03813"></a><span class="lineno"> 3813</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03814"></a><span class="lineno"> 3814</span>  </div> +<div class="line"><a name="l03815"></a><span class="lineno"> 3815</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03816"></a><span class="lineno"> 3816</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03817"></a><span class="lineno"> 3817</span> }</div> +<div class="line"><a name="l03818"></a><span class="lineno"> 3818</span>  </div> +<div class="line"><a name="l03819"></a><span class="lineno"> 3819</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseStack(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03820"></a><span class="lineno"> 3820</span> {</div> +<div class="line"><a name="l03821"></a><span class="lineno"> 3821</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03822"></a><span class="lineno"> 3822</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03823"></a><span class="lineno"> 3823</span>  </div> +<div class="line"><a name="l03824"></a><span class="lineno"> 3824</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03825"></a><span class="lineno"> 3825</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l03826"></a><span class="lineno"> 3826</span>  </div> +<div class="line"><a name="l03827"></a><span class="lineno"> 3827</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_StackLayer()->descriptor();</div> +<div class="line"><a name="l03828"></a><span class="lineno"> 3828</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis = flatBufferDescriptor->axis();</div> +<div class="line"><a name="l03829"></a><span class="lineno"> 3829</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = flatBufferDescriptor->numInputs();</div> +<div class="line"><a name="l03830"></a><span class="lineno"> 3830</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div> +<div class="line"><a name="l03831"></a><span class="lineno"> 3831</span>  </div> +<div class="line"><a name="l03832"></a><span class="lineno"> 3832</span>  <span class="keyword">auto</span> flatBufferInputShape = flatBufferDescriptor->inputShape();</div> +<div class="line"><a name="l03833"></a><span class="lineno"> 3833</span>  std::vector<uint32_t> vectorInputShape(flatBufferInputShape->begin(),</div> +<div class="line"><a name="l03834"></a><span class="lineno"> 3834</span>  flatBufferInputShape->begin() + flatBufferInputShape->size());</div> +<div class="line"><a name="l03835"></a><span class="lineno"> 3835</span>  </div> +<div class="line"><a name="l03836"></a><span class="lineno"> 3836</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape(<span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(vectorInputShape.size()), vectorInputShape.data());</div> +<div class="line"><a name="l03837"></a><span class="lineno"> 3837</span>  <a class="code" href="structarmnn_1_1_stack_descriptor.html">armnn::StackDescriptor</a> descriptor(axis, numInputs, inputShape);</div> +<div class="line"><a name="l03838"></a><span class="lineno"> 3838</span>  </div> +<div class="line"><a name="l03839"></a><span class="lineno"> 3839</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<inputs.size(); ++i)</div> +<div class="line"><a name="l03840"></a><span class="lineno"> 3840</span>  {</div> +<div class="line"><a name="l03841"></a><span class="lineno"> 3841</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputShape = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(inputs[i]).<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> +<div class="line"><a name="l03842"></a><span class="lineno"> 3842</span>  <span class="keywordflow">if</span> (descriptor.m_InputShape != inputShape)</div> +<div class="line"><a name="l03843"></a><span class="lineno"> 3843</span>  {</div> +<div class="line"><a name="l03844"></a><span class="lineno"> 3844</span>  std::stringstream ss;</div> +<div class="line"><a name="l03845"></a><span class="lineno"> 3845</span>  ss << <span class="stringliteral">"Shape of input "</span></div> +<div class="line"><a name="l03846"></a><span class="lineno"> 3846</span>  << i</div> +<div class="line"><a name="l03847"></a><span class="lineno"> 3847</span>  << <span class="stringliteral">" "</span></div> +<div class="line"><a name="l03848"></a><span class="lineno"> 3848</span>  << inputShape</div> +<div class="line"><a name="l03849"></a><span class="lineno"> 3849</span>  << <span class="stringliteral">" does not equal defined input shape "</span></div> +<div class="line"><a name="l03850"></a><span class="lineno"> 3850</span>  << descriptor.m_InputShape</div> +<div class="line"><a name="l03851"></a><span class="lineno"> 3851</span>  << <span class="stringliteral">": "</span></div> +<div class="line"><a name="l03852"></a><span class="lineno"> 3852</span>  << <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString();</div> +<div class="line"><a name="l03853"></a><span class="lineno"> 3853</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.html">ParseException</a>(ss.str());</div> +<div class="line"><a name="l03854"></a><span class="lineno"> 3854</span>  }</div> +<div class="line"><a name="l03855"></a><span class="lineno"> 3855</span>  }</div> +<div class="line"><a name="l03856"></a><span class="lineno"> 3856</span>  </div> +<div class="line"><a name="l03857"></a><span class="lineno"> 3857</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03858"></a><span class="lineno"> 3858</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddStackLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03859"></a><span class="lineno"> 3859</span>  </div> +<div class="line"><a name="l03860"></a><span class="lineno"> 3860</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l03861"></a><span class="lineno"> 3861</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div> +<div class="line"><a name="l03862"></a><span class="lineno"> 3862</span>  </div> +<div class="line"><a name="l03863"></a><span class="lineno"> 3863</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03864"></a><span class="lineno"> 3864</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03865"></a><span class="lineno"> 3865</span> }</div> +<div class="line"><a name="l03866"></a><span class="lineno"> 3866</span>  </div> +<div class="line"><a name="l03867"></a><span class="lineno"> 3867</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseStandIn(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03868"></a><span class="lineno"> 3868</span> {</div> +<div class="line"><a name="l03869"></a><span class="lineno"> 3869</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> <div class="line"><a name="l03870"></a><span class="lineno"> 3870</span>  </div> -<div class="line"><a name="l03871"></a><span class="lineno"> 3871</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03872"></a><span class="lineno"> 3872</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l03873"></a><span class="lineno"> 3873</span> }</div> -<div class="line"><a name="l03874"></a><span class="lineno"> 3874</span>  </div> -<div class="line"><a name="l03875"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ad04b4361ec1ded6b9334dae64c7c4579"> 3875</a></span> <a class="code" href="structarmnn_1_1_lstm_descriptor.html">armnn::UnidirectionalSequenceLstmDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ad04b4361ec1ded6b9334dae64c7c4579">IDeserializer::DeserializerImpl::GetUnidirectionalSequenceLstmDescriptor</a>(</div> -<div class="line"><a name="l03876"></a><span class="lineno"> 3876</span>  <a class="code" href="namespacearmnn_deserializer.html#a9eb5db921d6fa5015a57916a5d0c7cd9">UnidirectionalSequenceLstmDescriptorPtr</a> descriptor)</div> -<div class="line"><a name="l03877"></a><span class="lineno"> 3877</span> {</div> -<div class="line"><a name="l03878"></a><span class="lineno"> 3878</span>  <a class="code" href="structarmnn_1_1_lstm_descriptor.html">armnn::UnidirectionalSequenceLstmDescriptor</a> desc;</div> -<div class="line"><a name="l03879"></a><span class="lineno"> 3879</span>  </div> -<div class="line"><a name="l03880"></a><span class="lineno"> 3880</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = descriptor->activationFunc();</div> -<div class="line"><a name="l03881"></a><span class="lineno"> 3881</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = descriptor->clippingThresCell();</div> -<div class="line"><a name="l03882"></a><span class="lineno"> 3882</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a> = descriptor->clippingThresProj();</div> -<div class="line"><a name="l03883"></a><span class="lineno"> 3883</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = descriptor->cifgEnabled();</div> -<div class="line"><a name="l03884"></a><span class="lineno"> 3884</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = descriptor->peepholeEnabled();</div> -<div class="line"><a name="l03885"></a><span class="lineno"> 3885</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = descriptor->projectionEnabled();</div> -<div class="line"><a name="l03886"></a><span class="lineno"> 3886</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = descriptor->layerNormEnabled();</div> -<div class="line"><a name="l03887"></a><span class="lineno"> 3887</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = descriptor->timeMajor();</div> -<div class="line"><a name="l03888"></a><span class="lineno"> 3888</span>  </div> -<div class="line"><a name="l03889"></a><span class="lineno"> 3889</span>  <span class="keywordflow">return</span> desc;</div> -<div class="line"><a name="l03890"></a><span class="lineno"> 3890</span> }</div> -<div class="line"><a name="l03891"></a><span class="lineno"> 3891</span>  </div> -<div class="line"><a name="l03892"></a><span class="lineno"> 3892</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseUnidirectionalSequenceLstm(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> -<div class="line"><a name="l03893"></a><span class="lineno"> 3893</span> {</div> -<div class="line"><a name="l03894"></a><span class="lineno"> 3894</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> -<div class="line"><a name="l03895"></a><span class="lineno"> 3895</span>  </div> -<div class="line"><a name="l03896"></a><span class="lineno"> 3896</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> -<div class="line"><a name="l03897"></a><span class="lineno"> 3897</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div> -<div class="line"><a name="l03898"></a><span class="lineno"> 3898</span>  </div> -<div class="line"><a name="l03899"></a><span class="lineno"> 3899</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> -<div class="line"><a name="l03900"></a><span class="lineno"> 3900</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 3);</div> +<div class="line"><a name="l03871"></a><span class="lineno"> 3871</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03872"></a><span class="lineno"> 3872</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03873"></a><span class="lineno"> 3873</span>  </div> +<div class="line"><a name="l03874"></a><span class="lineno"> 3874</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_StandInLayer();</div> +<div class="line"><a name="l03875"></a><span class="lineno"> 3875</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div> +<div class="line"><a name="l03876"></a><span class="lineno"> 3876</span>  </div> +<div class="line"><a name="l03877"></a><span class="lineno"> 3877</span>  <a class="code" href="structarmnn_1_1_stand_in_descriptor.html">armnn::StandInDescriptor</a> descriptor;</div> +<div class="line"><a name="l03878"></a><span class="lineno"> 3878</span>  descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#aed6086070440ceb94129bef06f70173f">m_NumInputs</a> = fbDescriptor->numInputs();</div> +<div class="line"><a name="l03879"></a><span class="lineno"> 3879</span>  descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a> = fbDescriptor->numOutputs();</div> +<div class="line"><a name="l03880"></a><span class="lineno"> 3880</span>  </div> +<div class="line"><a name="l03881"></a><span class="lineno"> 3881</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#aed6086070440ceb94129bef06f70173f">m_NumInputs</a>);</div> +<div class="line"><a name="l03882"></a><span class="lineno"> 3882</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a>);</div> +<div class="line"><a name="l03883"></a><span class="lineno"> 3883</span>  </div> +<div class="line"><a name="l03884"></a><span class="lineno"> 3884</span>  <span class="keyword">const</span> std::string layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03885"></a><span class="lineno"> 3885</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer = m_Network->AddStandInLayer(descriptor, layerName.c_str());</div> +<div class="line"><a name="l03886"></a><span class="lineno"> 3886</span>  </div> +<div class="line"><a name="l03887"></a><span class="lineno"> 3887</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.html#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a>; ++i)</div> +<div class="line"><a name="l03888"></a><span class="lineno"> 3888</span>  {</div> +<div class="line"><a name="l03889"></a><span class="lineno"> 3889</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[i]);</div> +<div class="line"><a name="l03890"></a><span class="lineno"> 3890</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(i).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div> +<div class="line"><a name="l03891"></a><span class="lineno"> 3891</span>  }</div> +<div class="line"><a name="l03892"></a><span class="lineno"> 3892</span>  </div> +<div class="line"><a name="l03893"></a><span class="lineno"> 3893</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03894"></a><span class="lineno"> 3894</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l03895"></a><span class="lineno"> 3895</span> }</div> +<div class="line"><a name="l03896"></a><span class="lineno"> 3896</span>  </div> +<div class="line"><a name="l03897"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ad04b4361ec1ded6b9334dae64c7c4579"> 3897</a></span> <a class="code" href="structarmnn_1_1_lstm_descriptor.html">armnn::UnidirectionalSequenceLstmDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ad04b4361ec1ded6b9334dae64c7c4579">IDeserializer::DeserializerImpl::GetUnidirectionalSequenceLstmDescriptor</a>(</div> +<div class="line"><a name="l03898"></a><span class="lineno"> 3898</span>  <a class="code" href="namespacearmnn_deserializer.html#a9eb5db921d6fa5015a57916a5d0c7cd9">UnidirectionalSequenceLstmDescriptorPtr</a> descriptor)</div> +<div class="line"><a name="l03899"></a><span class="lineno"> 3899</span> {</div> +<div class="line"><a name="l03900"></a><span class="lineno"> 3900</span>  <a class="code" href="structarmnn_1_1_lstm_descriptor.html">armnn::UnidirectionalSequenceLstmDescriptor</a> desc;</div> <div class="line"><a name="l03901"></a><span class="lineno"> 3901</span>  </div> -<div class="line"><a name="l03902"></a><span class="lineno"> 3902</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_UnidirectionalSequenceLstmLayer();</div> -<div class="line"><a name="l03903"></a><span class="lineno"> 3903</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> -<div class="line"><a name="l03904"></a><span class="lineno"> 3904</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> -<div class="line"><a name="l03905"></a><span class="lineno"> 3905</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div> -<div class="line"><a name="l03906"></a><span class="lineno"> 3906</span>  </div> -<div class="line"><a name="l03907"></a><span class="lineno"> 3907</span>  <span class="keyword">auto</span> descriptor = GetUnidirectionalSequenceLstmDescriptor(flatBufferDescriptor);</div> -<div class="line"><a name="l03908"></a><span class="lineno"> 3908</span>  </div> -<div class="line"><a name="l03909"></a><span class="lineno"> 3909</span>  <a class="code" href="structarmnn_1_1_lstm_input_params.html">armnn::LstmInputParams</a> lstmInputParams;</div> +<div class="line"><a name="l03902"></a><span class="lineno"> 3902</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = descriptor->activationFunc();</div> +<div class="line"><a name="l03903"></a><span class="lineno"> 3903</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = descriptor->clippingThresCell();</div> +<div class="line"><a name="l03904"></a><span class="lineno"> 3904</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a> = descriptor->clippingThresProj();</div> +<div class="line"><a name="l03905"></a><span class="lineno"> 3905</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = descriptor->cifgEnabled();</div> +<div class="line"><a name="l03906"></a><span class="lineno"> 3906</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = descriptor->peepholeEnabled();</div> +<div class="line"><a name="l03907"></a><span class="lineno"> 3907</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = descriptor->projectionEnabled();</div> +<div class="line"><a name="l03908"></a><span class="lineno"> 3908</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = descriptor->layerNormEnabled();</div> +<div class="line"><a name="l03909"></a><span class="lineno"> 3909</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = descriptor->timeMajor();</div> <div class="line"><a name="l03910"></a><span class="lineno"> 3910</span>  </div> -<div class="line"><a name="l03911"></a><span class="lineno"> 3911</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div> -<div class="line"><a name="l03912"></a><span class="lineno"> 3912</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div> -<div class="line"><a name="l03913"></a><span class="lineno"> 3913</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div> -<div class="line"><a name="l03914"></a><span class="lineno"> 3914</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div> -<div class="line"><a name="l03915"></a><span class="lineno"> 3915</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div> -<div class="line"><a name="l03916"></a><span class="lineno"> 3916</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div> -<div class="line"><a name="l03917"></a><span class="lineno"> 3917</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div> -<div class="line"><a name="l03918"></a><span class="lineno"> 3918</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellBias());</div> -<div class="line"><a name="l03919"></a><span class="lineno"> 3919</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div> +<div class="line"><a name="l03911"></a><span class="lineno"> 3911</span>  <span class="keywordflow">return</span> desc;</div> +<div class="line"><a name="l03912"></a><span class="lineno"> 3912</span> }</div> +<div class="line"><a name="l03913"></a><span class="lineno"> 3913</span>  </div> +<div class="line"><a name="l03914"></a><span class="lineno"> 3914</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseUnidirectionalSequenceLstm(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l03915"></a><span class="lineno"> 3915</span> {</div> +<div class="line"><a name="l03916"></a><span class="lineno"> 3916</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l03917"></a><span class="lineno"> 3917</span>  </div> +<div class="line"><a name="l03918"></a><span class="lineno"> 3918</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l03919"></a><span class="lineno"> 3919</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div> <div class="line"><a name="l03920"></a><span class="lineno"> 3920</span>  </div> -<div class="line"><a name="l03921"></a><span class="lineno"> 3921</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div> -<div class="line"><a name="l03922"></a><span class="lineno"> 3922</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div> -<div class="line"><a name="l03923"></a><span class="lineno"> 3923</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div> -<div class="line"><a name="l03924"></a><span class="lineno"> 3924</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div> -<div class="line"><a name="l03925"></a><span class="lineno"> 3925</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div> -<div class="line"><a name="l03926"></a><span class="lineno"> 3926</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div> -<div class="line"><a name="l03927"></a><span class="lineno"> 3927</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div> -<div class="line"><a name="l03928"></a><span class="lineno"> 3928</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div> -<div class="line"><a name="l03929"></a><span class="lineno"> 3929</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div> +<div class="line"><a name="l03921"></a><span class="lineno"> 3921</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l03922"></a><span class="lineno"> 3922</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 3);</div> +<div class="line"><a name="l03923"></a><span class="lineno"> 3923</span>  </div> +<div class="line"><a name="l03924"></a><span class="lineno"> 3924</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_UnidirectionalSequenceLstmLayer();</div> +<div class="line"><a name="l03925"></a><span class="lineno"> 3925</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l03926"></a><span class="lineno"> 3926</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div> +<div class="line"><a name="l03927"></a><span class="lineno"> 3927</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div> +<div class="line"><a name="l03928"></a><span class="lineno"> 3928</span>  </div> +<div class="line"><a name="l03929"></a><span class="lineno"> 3929</span>  <span class="keyword">auto</span> descriptor = GetUnidirectionalSequenceLstmDescriptor(flatBufferDescriptor);</div> <div class="line"><a name="l03930"></a><span class="lineno"> 3930</span>  </div> -<div class="line"><a name="l03931"></a><span class="lineno"> 3931</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToInputWeights;</div> -<div class="line"><a name="l03932"></a><span class="lineno"> 3932</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToInputWeights;</div> -<div class="line"><a name="l03933"></a><span class="lineno"> 3933</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToInputWeights;</div> -<div class="line"><a name="l03934"></a><span class="lineno"> 3934</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputGateBias;</div> -<div class="line"><a name="l03935"></a><span class="lineno"> 3935</span>  <span class="keywordflow">if</span> (!descriptor.m_CifgEnabled)</div> -<div class="line"><a name="l03936"></a><span class="lineno"> 3936</span>  {</div> -<div class="line"><a name="l03937"></a><span class="lineno"> 3937</span>  inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div> -<div class="line"><a name="l03938"></a><span class="lineno"> 3938</span>  recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div> -<div class="line"><a name="l03939"></a><span class="lineno"> 3939</span>  inputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div> -<div class="line"><a name="l03940"></a><span class="lineno"> 3940</span>  </div> -<div class="line"><a name="l03941"></a><span class="lineno"> 3941</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div> -<div class="line"><a name="l03942"></a><span class="lineno"> 3942</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div> -<div class="line"><a name="l03943"></a><span class="lineno"> 3943</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div> -<div class="line"><a name="l03944"></a><span class="lineno"> 3944</span>  </div> -<div class="line"><a name="l03945"></a><span class="lineno"> 3945</span>  <span class="keywordflow">if</span> (descriptor.m_PeepholeEnabled)</div> -<div class="line"><a name="l03946"></a><span class="lineno"> 3946</span>  {</div> -<div class="line"><a name="l03947"></a><span class="lineno"> 3947</span>  cellToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToInputWeights());</div> -<div class="line"><a name="l03948"></a><span class="lineno"> 3948</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a> = &cellToInputWeights;</div> -<div class="line"><a name="l03949"></a><span class="lineno"> 3949</span>  }</div> -<div class="line"><a name="l03950"></a><span class="lineno"> 3950</span>  }</div> -<div class="line"><a name="l03951"></a><span class="lineno"> 3951</span>  </div> -<div class="line"><a name="l03952"></a><span class="lineno"> 3952</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionWeights;</div> -<div class="line"><a name="l03953"></a><span class="lineno"> 3953</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionBias;</div> -<div class="line"><a name="l03954"></a><span class="lineno"> 3954</span>  <span class="keywordflow">if</span> (descriptor.m_ProjectionEnabled)</div> -<div class="line"><a name="l03955"></a><span class="lineno"> 3955</span>  {</div> -<div class="line"><a name="l03956"></a><span class="lineno"> 3956</span>  projectionWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionWeights());</div> -<div class="line"><a name="l03957"></a><span class="lineno"> 3957</span>  projectionBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionBias());</div> -<div class="line"><a name="l03958"></a><span class="lineno"> 3958</span>  </div> -<div class="line"><a name="l03959"></a><span class="lineno"> 3959</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a> = &projectionWeights;</div> -<div class="line"><a name="l03960"></a><span class="lineno"> 3960</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a> = &projectionBias;</div> -<div class="line"><a name="l03961"></a><span class="lineno"> 3961</span>  }</div> +<div class="line"><a name="l03931"></a><span class="lineno"> 3931</span>  <a class="code" href="structarmnn_1_1_lstm_input_params.html">armnn::LstmInputParams</a> lstmInputParams;</div> +<div class="line"><a name="l03932"></a><span class="lineno"> 3932</span>  </div> +<div class="line"><a name="l03933"></a><span class="lineno"> 3933</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div> +<div class="line"><a name="l03934"></a><span class="lineno"> 3934</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div> +<div class="line"><a name="l03935"></a><span class="lineno"> 3935</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div> +<div class="line"><a name="l03936"></a><span class="lineno"> 3936</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div> +<div class="line"><a name="l03937"></a><span class="lineno"> 3937</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div> +<div class="line"><a name="l03938"></a><span class="lineno"> 3938</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div> +<div class="line"><a name="l03939"></a><span class="lineno"> 3939</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div> +<div class="line"><a name="l03940"></a><span class="lineno"> 3940</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellBias());</div> +<div class="line"><a name="l03941"></a><span class="lineno"> 3941</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div> +<div class="line"><a name="l03942"></a><span class="lineno"> 3942</span>  </div> +<div class="line"><a name="l03943"></a><span class="lineno"> 3943</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div> +<div class="line"><a name="l03944"></a><span class="lineno"> 3944</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div> +<div class="line"><a name="l03945"></a><span class="lineno"> 3945</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div> +<div class="line"><a name="l03946"></a><span class="lineno"> 3946</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div> +<div class="line"><a name="l03947"></a><span class="lineno"> 3947</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div> +<div class="line"><a name="l03948"></a><span class="lineno"> 3948</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div> +<div class="line"><a name="l03949"></a><span class="lineno"> 3949</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div> +<div class="line"><a name="l03950"></a><span class="lineno"> 3950</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div> +<div class="line"><a name="l03951"></a><span class="lineno"> 3951</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div> +<div class="line"><a name="l03952"></a><span class="lineno"> 3952</span>  </div> +<div class="line"><a name="l03953"></a><span class="lineno"> 3953</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputToInputWeights;</div> +<div class="line"><a name="l03954"></a><span class="lineno"> 3954</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> recurrentToInputWeights;</div> +<div class="line"><a name="l03955"></a><span class="lineno"> 3955</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToInputWeights;</div> +<div class="line"><a name="l03956"></a><span class="lineno"> 3956</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputGateBias;</div> +<div class="line"><a name="l03957"></a><span class="lineno"> 3957</span>  <span class="keywordflow">if</span> (!descriptor.m_CifgEnabled)</div> +<div class="line"><a name="l03958"></a><span class="lineno"> 3958</span>  {</div> +<div class="line"><a name="l03959"></a><span class="lineno"> 3959</span>  inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div> +<div class="line"><a name="l03960"></a><span class="lineno"> 3960</span>  recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div> +<div class="line"><a name="l03961"></a><span class="lineno"> 3961</span>  inputGateBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div> <div class="line"><a name="l03962"></a><span class="lineno"> 3962</span>  </div> -<div class="line"><a name="l03963"></a><span class="lineno"> 3963</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToForgetWeights;</div> -<div class="line"><a name="l03964"></a><span class="lineno"> 3964</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToOutputWeights;</div> -<div class="line"><a name="l03965"></a><span class="lineno"> 3965</span>  <span class="keywordflow">if</span> (descriptor.m_PeepholeEnabled)</div> -<div class="line"><a name="l03966"></a><span class="lineno"> 3966</span>  {</div> -<div class="line"><a name="l03967"></a><span class="lineno"> 3967</span>  cellToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToForgetWeights());</div> -<div class="line"><a name="l03968"></a><span class="lineno"> 3968</span>  cellToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToOutputWeights());</div> -<div class="line"><a name="l03969"></a><span class="lineno"> 3969</span>  </div> -<div class="line"><a name="l03970"></a><span class="lineno"> 3970</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> = &cellToForgetWeights;</div> -<div class="line"><a name="l03971"></a><span class="lineno"> 3971</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> = &cellToOutputWeights;</div> +<div class="line"><a name="l03963"></a><span class="lineno"> 3963</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div> +<div class="line"><a name="l03964"></a><span class="lineno"> 3964</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div> +<div class="line"><a name="l03965"></a><span class="lineno"> 3965</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div> +<div class="line"><a name="l03966"></a><span class="lineno"> 3966</span>  </div> +<div class="line"><a name="l03967"></a><span class="lineno"> 3967</span>  <span class="keywordflow">if</span> (descriptor.m_PeepholeEnabled)</div> +<div class="line"><a name="l03968"></a><span class="lineno"> 3968</span>  {</div> +<div class="line"><a name="l03969"></a><span class="lineno"> 3969</span>  cellToInputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToInputWeights());</div> +<div class="line"><a name="l03970"></a><span class="lineno"> 3970</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a> = &cellToInputWeights;</div> +<div class="line"><a name="l03971"></a><span class="lineno"> 3971</span>  }</div> <div class="line"><a name="l03972"></a><span class="lineno"> 3972</span>  }</div> <div class="line"><a name="l03973"></a><span class="lineno"> 3973</span>  </div> -<div class="line"><a name="l03974"></a><span class="lineno"> 3974</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputLayerNormWeights;</div> -<div class="line"><a name="l03975"></a><span class="lineno"> 3975</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetLayerNormWeights;</div> -<div class="line"><a name="l03976"></a><span class="lineno"> 3976</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellLayerNormWeights;</div> -<div class="line"><a name="l03977"></a><span class="lineno"> 3977</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputLayerNormWeights;</div> -<div class="line"><a name="l03978"></a><span class="lineno"> 3978</span>  <span class="keywordflow">if</span> (descriptor.m_LayerNormEnabled)</div> -<div class="line"><a name="l03979"></a><span class="lineno"> 3979</span>  {</div> -<div class="line"><a name="l03980"></a><span class="lineno"> 3980</span>  <span class="keywordflow">if</span> (!descriptor.m_CifgEnabled)</div> -<div class="line"><a name="l03981"></a><span class="lineno"> 3981</span>  {</div> -<div class="line"><a name="l03982"></a><span class="lineno"> 3982</span>  inputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputLayerNormWeights());</div> -<div class="line"><a name="l03983"></a><span class="lineno"> 3983</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a> = &inputLayerNormWeights;</div> -<div class="line"><a name="l03984"></a><span class="lineno"> 3984</span>  }</div> -<div class="line"><a name="l03985"></a><span class="lineno"> 3985</span>  forgetLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetLayerNormWeights());</div> -<div class="line"><a name="l03986"></a><span class="lineno"> 3986</span>  cellLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellLayerNormWeights());</div> -<div class="line"><a name="l03987"></a><span class="lineno"> 3987</span>  outputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputLayerNormWeights());</div> -<div class="line"><a name="l03988"></a><span class="lineno"> 3988</span>  </div> -<div class="line"><a name="l03989"></a><span class="lineno"> 3989</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a> = &forgetLayerNormWeights;</div> -<div class="line"><a name="l03990"></a><span class="lineno"> 3990</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a> = &cellLayerNormWeights;</div> -<div class="line"><a name="l03991"></a><span class="lineno"> 3991</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a> = &outputLayerNormWeights;</div> -<div class="line"><a name="l03992"></a><span class="lineno"> 3992</span>  }</div> -<div class="line"><a name="l03993"></a><span class="lineno"> 3993</span>  </div> -<div class="line"><a name="l03994"></a><span class="lineno"> 3994</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddUnidirectionalSequenceLstmLayer(descriptor,</div> -<div class="line"><a name="l03995"></a><span class="lineno"> 3995</span>  lstmInputParams,</div> -<div class="line"><a name="l03996"></a><span class="lineno"> 3996</span>  layerName.c_str());</div> -<div class="line"><a name="l03997"></a><span class="lineno"> 3997</span>  </div> -<div class="line"><a name="l03998"></a><span class="lineno"> 3998</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo0 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> -<div class="line"><a name="l03999"></a><span class="lineno"> 3999</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo0);</div> -<div class="line"><a name="l04000"></a><span class="lineno"> 4000</span>  </div> -<div class="line"><a name="l04001"></a><span class="lineno"> 4001</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo1 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> -<div class="line"><a name="l04002"></a><span class="lineno"> 4002</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo1);</div> -<div class="line"><a name="l04003"></a><span class="lineno"> 4003</span>  </div> -<div class="line"><a name="l04004"></a><span class="lineno"> 4004</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo2 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[2]);</div> -<div class="line"><a name="l04005"></a><span class="lineno"> 4005</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo2);</div> -<div class="line"><a name="l04006"></a><span class="lineno"> 4006</span>  </div> -<div class="line"><a name="l04007"></a><span class="lineno"> 4007</span>  RegisterInputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l04008"></a><span class="lineno"> 4008</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> -<div class="line"><a name="l04009"></a><span class="lineno"> 4009</span> }</div> +<div class="line"><a name="l03974"></a><span class="lineno"> 3974</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionWeights;</div> +<div class="line"><a name="l03975"></a><span class="lineno"> 3975</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> projectionBias;</div> +<div class="line"><a name="l03976"></a><span class="lineno"> 3976</span>  <span class="keywordflow">if</span> (descriptor.m_ProjectionEnabled)</div> +<div class="line"><a name="l03977"></a><span class="lineno"> 3977</span>  {</div> +<div class="line"><a name="l03978"></a><span class="lineno"> 3978</span>  projectionWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionWeights());</div> +<div class="line"><a name="l03979"></a><span class="lineno"> 3979</span>  projectionBias = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->projectionBias());</div> +<div class="line"><a name="l03980"></a><span class="lineno"> 3980</span>  </div> +<div class="line"><a name="l03981"></a><span class="lineno"> 3981</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a> = &projectionWeights;</div> +<div class="line"><a name="l03982"></a><span class="lineno"> 3982</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a> = &projectionBias;</div> +<div class="line"><a name="l03983"></a><span class="lineno"> 3983</span>  }</div> +<div class="line"><a name="l03984"></a><span class="lineno"> 3984</span>  </div> +<div class="line"><a name="l03985"></a><span class="lineno"> 3985</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToForgetWeights;</div> +<div class="line"><a name="l03986"></a><span class="lineno"> 3986</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellToOutputWeights;</div> +<div class="line"><a name="l03987"></a><span class="lineno"> 3987</span>  <span class="keywordflow">if</span> (descriptor.m_PeepholeEnabled)</div> +<div class="line"><a name="l03988"></a><span class="lineno"> 3988</span>  {</div> +<div class="line"><a name="l03989"></a><span class="lineno"> 3989</span>  cellToForgetWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToForgetWeights());</div> +<div class="line"><a name="l03990"></a><span class="lineno"> 3990</span>  cellToOutputWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellToOutputWeights());</div> +<div class="line"><a name="l03991"></a><span class="lineno"> 3991</span>  </div> +<div class="line"><a name="l03992"></a><span class="lineno"> 3992</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> = &cellToForgetWeights;</div> +<div class="line"><a name="l03993"></a><span class="lineno"> 3993</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> = &cellToOutputWeights;</div> +<div class="line"><a name="l03994"></a><span class="lineno"> 3994</span>  }</div> +<div class="line"><a name="l03995"></a><span class="lineno"> 3995</span>  </div> +<div class="line"><a name="l03996"></a><span class="lineno"> 3996</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> inputLayerNormWeights;</div> +<div class="line"><a name="l03997"></a><span class="lineno"> 3997</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> forgetLayerNormWeights;</div> +<div class="line"><a name="l03998"></a><span class="lineno"> 3998</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> cellLayerNormWeights;</div> +<div class="line"><a name="l03999"></a><span class="lineno"> 3999</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> outputLayerNormWeights;</div> +<div class="line"><a name="l04000"></a><span class="lineno"> 4000</span>  <span class="keywordflow">if</span> (descriptor.m_LayerNormEnabled)</div> +<div class="line"><a name="l04001"></a><span class="lineno"> 4001</span>  {</div> +<div class="line"><a name="l04002"></a><span class="lineno"> 4002</span>  <span class="keywordflow">if</span> (!descriptor.m_CifgEnabled)</div> +<div class="line"><a name="l04003"></a><span class="lineno"> 4003</span>  {</div> +<div class="line"><a name="l04004"></a><span class="lineno"> 4004</span>  inputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->inputLayerNormWeights());</div> +<div class="line"><a name="l04005"></a><span class="lineno"> 4005</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a> = &inputLayerNormWeights;</div> +<div class="line"><a name="l04006"></a><span class="lineno"> 4006</span>  }</div> +<div class="line"><a name="l04007"></a><span class="lineno"> 4007</span>  forgetLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->forgetLayerNormWeights());</div> +<div class="line"><a name="l04008"></a><span class="lineno"> 4008</span>  cellLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->cellLayerNormWeights());</div> +<div class="line"><a name="l04009"></a><span class="lineno"> 4009</span>  outputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">ToConstTensor</a>(flatBufferInputParams->outputLayerNormWeights());</div> <div class="line"><a name="l04010"></a><span class="lineno"> 4010</span>  </div> -<div class="line"><a name="l04011"></a><span class="lineno"> 4011</span> } <span class="comment">// namespace armnnDeserializer</span></div> +<div class="line"><a name="l04011"></a><span class="lineno"> 4011</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a> = &forgetLayerNormWeights;</div> +<div class="line"><a name="l04012"></a><span class="lineno"> 4012</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a> = &cellLayerNormWeights;</div> +<div class="line"><a name="l04013"></a><span class="lineno"> 4013</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.html#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a> = &outputLayerNormWeights;</div> +<div class="line"><a name="l04014"></a><span class="lineno"> 4014</span>  }</div> +<div class="line"><a name="l04015"></a><span class="lineno"> 4015</span>  </div> +<div class="line"><a name="l04016"></a><span class="lineno"> 4016</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddUnidirectionalSequenceLstmLayer(descriptor,</div> +<div class="line"><a name="l04017"></a><span class="lineno"> 4017</span>  lstmInputParams,</div> +<div class="line"><a name="l04018"></a><span class="lineno"> 4018</span>  layerName.c_str());</div> +<div class="line"><a name="l04019"></a><span class="lineno"> 4019</span>  </div> +<div class="line"><a name="l04020"></a><span class="lineno"> 4020</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo0 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l04021"></a><span class="lineno"> 4021</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo0);</div> +<div class="line"><a name="l04022"></a><span class="lineno"> 4022</span>  </div> +<div class="line"><a name="l04023"></a><span class="lineno"> 4023</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo1 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[1]);</div> +<div class="line"><a name="l04024"></a><span class="lineno"> 4024</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo1);</div> +<div class="line"><a name="l04025"></a><span class="lineno"> 4025</span>  </div> +<div class="line"><a name="l04026"></a><span class="lineno"> 4026</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo2 = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[2]);</div> +<div class="line"><a name="l04027"></a><span class="lineno"> 4027</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo2);</div> +<div class="line"><a name="l04028"></a><span class="lineno"> 4028</span>  </div> +<div class="line"><a name="l04029"></a><span class="lineno"> 4029</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l04030"></a><span class="lineno"> 4030</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l04031"></a><span class="lineno"> 4031</span> }</div> +<div class="line"><a name="l04032"></a><span class="lineno"> 4032</span>  </div> +<div class="line"><a name="l04033"></a><span class="lineno"> 4033</span> <span class="keywordtype">void</span> IDeserializer::DeserializerImpl::ParseScatterNd(<a class="code" href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div> +<div class="line"><a name="l04034"></a><span class="lineno"> 4034</span> {</div> +<div class="line"><a name="l04035"></a><span class="lineno"> 4035</span>  <a class="code" href="_deserializer_8cpp.html#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div> +<div class="line"><a name="l04036"></a><span class="lineno"> 4036</span>  <span class="keyword">auto</span> inputs = GetInputs(graph, layerIndex);</div> +<div class="line"><a name="l04037"></a><span class="lineno"> 4037</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div> +<div class="line"><a name="l04038"></a><span class="lineno"> 4038</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div> +<div class="line"><a name="l04039"></a><span class="lineno"> 4039</span>  </div> +<div class="line"><a name="l04040"></a><span class="lineno"> 4040</span>  <span class="keyword">auto</span> outputs = GetOutputs(graph, layerIndex);</div> +<div class="line"><a name="l04041"></a><span class="lineno"> 4041</span>  <a class="code" href="_verification_helpers_8hpp.html#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div> +<div class="line"><a name="l04042"></a><span class="lineno"> 4042</span>  </div> +<div class="line"><a name="l04043"></a><span class="lineno"> 4043</span>  <span class="keyword">auto</span> <a class="code" href="classarmnn_1_1_scatter_nd_layer.html">ScatterNdLayer</a> = graph->layers()->Get(layerIndex)->layer_as_ScatterNdLayer();</div> +<div class="line"><a name="l04044"></a><span class="lineno"> 4044</span>  <span class="keyword">auto</span> layerName = GetLayerName(graph, layerIndex);</div> +<div class="line"><a name="l04045"></a><span class="lineno"> 4045</span>  <span class="keyword">auto</span> flatBufferDescriptor = <a class="code" href="classarmnn_1_1_scatter_nd_layer.html">ScatterNdLayer</a>->descriptor();</div> +<div class="line"><a name="l04046"></a><span class="lineno"> 4046</span>  </div> +<div class="line"><a name="l04047"></a><span class="lineno"> 4047</span>  <a class="code" href="structarmnn_1_1_scatter_nd_descriptor.html">armnn::ScatterNdDescriptor</a> scatterNdDescriptor;</div> +<div class="line"><a name="l04048"></a><span class="lineno"> 4048</span>  scatterNdDescriptor.<a class="code" href="structarmnn_1_1_scatter_nd_descriptor.html#a2beb2331d0aff8e24d17f16cca34784c">m_Function</a> = <a class="code" href="namespacearmnn_deserializer.html#ada48fd59da09885ff0c4273b303c28f5">ToScatterNdFunction</a>(flatBufferDescriptor->m_Function());</div> +<div class="line"><a name="l04049"></a><span class="lineno"> 4049</span>  scatterNdDescriptor.<a class="code" href="structarmnn_1_1_scatter_nd_descriptor.html#a12501f4f1f889d0b63f8a6067cdaad4a">m_InputEnabled</a> = flatBufferDescriptor->m_InputEnabled();</div> +<div class="line"><a name="l04050"></a><span class="lineno"> 4050</span>  scatterNdDescriptor.<a class="code" href="structarmnn_1_1_scatter_nd_descriptor.html#a35d11c7d509d1adbae1ae01c58394a7f">m_Axis</a> = flatBufferDescriptor->m_Axis();</div> +<div class="line"><a name="l04051"></a><span class="lineno"> 4051</span>  scatterNdDescriptor.<a class="code" href="structarmnn_1_1_scatter_nd_descriptor.html#a96a5cc69bb69aea9cb10cdf17f74fbd4">m_AxisEnabled</a> = flatBufferDescriptor->m_AxisEnabled();</div> +<div class="line"><a name="l04052"></a><span class="lineno"> 4052</span>  </div> +<div class="line"><a name="l04053"></a><span class="lineno"> 4053</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* layer = m_Network->AddScatterNdLayer(scatterNdDescriptor, layerName.c_str());</div> +<div class="line"><a name="l04054"></a><span class="lineno"> 4054</span>  </div> +<div class="line"><a name="l04055"></a><span class="lineno"> 4055</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> output0TensorInfo = <a class="code" href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">ToTensorInfo</a>(outputs[0]);</div> +<div class="line"><a name="l04056"></a><span class="lineno"> 4056</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(output0TensorInfo);</div> +<div class="line"><a name="l04057"></a><span class="lineno"> 4057</span>  </div> +<div class="line"><a name="l04058"></a><span class="lineno"> 4058</span>  RegisterInputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l04059"></a><span class="lineno"> 4059</span>  RegisterOutputSlots(graph, layerIndex, layer);</div> +<div class="line"><a name="l04060"></a><span class="lineno"> 4060</span> }</div> +<div class="line"><a name="l04061"></a><span class="lineno"> 4061</span>  </div> +<div class="line"><a name="l04062"></a><span class="lineno"> 4062</span> } <span class="comment">// namespace armnnDeserializer</span></div> </div><!-- fragment --></div><!-- contents --> </div><!-- doc-content --> <div class="ttc" id="astructarmnn_1_1_batch_normalization_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.html">armnn::BatchNormalizationDescriptor</a></div><div class="ttdoc">A BatchNormalizationDescriptor for the BatchNormalizationLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00828">Descriptors.hpp:828</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">armnn::Convolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00570">Descriptors.hpp:570</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a8fb47fe218330370a5c9c066ac1571ea"><div class="ttname"><a href="namespacearmnn_deserializer.html#a8fb47fe218330370a5c9c066ac1571ea">armnnDeserializer::ToArgMinMaxFunction</a></div><div class="ttdeci">armnn::ArgMinMaxFunction ToArgMinMaxFunction(armnnSerializer::ArgMinMaxFunction function)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00512">Deserializer.cpp:512</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a8fb47fe218330370a5c9c066ac1571ea"><div class="ttname"><a href="namespacearmnn_deserializer.html#a8fb47fe218330370a5c9c066ac1571ea">armnnDeserializer::ToArgMinMaxFunction</a></div><div class="ttdeci">armnn::ArgMinMaxFunction ToArgMinMaxFunction(armnnSerializer::ArgMinMaxFunction function)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00515">Deserializer.cpp:515</a></div></div> <div class="ttc" id="anamespacearmnn_html_ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::ArgMinMaxFunction::Max</a></div><div class="ttdeci">@ Max</div></div> <div class="ttc" id="anamespacearmnn_html_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00339">INetwork.hpp:339</a></div></div> <div class="ttc" id="astructarmnn_1_1_instance_normalization_descriptor_html_a8275d51ef9a584feb95726ea0522f6e5"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">armnn::InstanceNormalizationDescriptor::m_Beta</a></div><div class="ttdeci">float m_Beta</div><div class="ttdoc">Beta, the offset scalar value applied for the normalized tensor. Defaults to 1.0.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00867">Descriptors.hpp:867</a></div></div> <div class="ttc" id="anamespacearmnn_html_a14d24d90ab4ba2956e92e27890ba4c91af334649ef5e5d0ffe200751d07012626"><div class="ttname"><a href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91af334649ef5e5d0ffe200751d07012626">armnn::PaddingMode::Symmetric</a></div><div class="ttdeci">@ Symmetric</div></div> <div class="ttc" id="astructarmnn_1_1_slice_descriptor_html_a4939f00778f08d6c6fec6f74c0a59b7e"><div class="ttname"><a href="structarmnn_1_1_slice_descriptor.html#a4939f00778f08d6c6fec6f74c0a59b7e">armnn::SliceDescriptor::m_Begin</a></div><div class="ttdeci">std::vector< unsigned int > m_Begin</div><div class="ttdoc">Beginning indices of the slice in each dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01244">Descriptors.hpp:1244</a></div></div> <div class="ttc" id="anamespacearmnn_html_a280670a263dc4fd40491f6d0a2737f44"><div class="ttname"><a href="namespacearmnn.html#a280670a263dc4fd40491f6d0a2737f44">armnn::BindingPointInfo</a></div><div class="ttdeci">std::pair< armnn::LayerBindingId, armnn::TensorInfo > BindingPointInfo</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00276">Tensor.hpp:276</a></div></div> -<div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::Convolution3dDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdoc">Get the number of views/inputs.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00464">Descriptors.cpp:464</a></div></div> +<div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::Convolution3dDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdoc">Get the number of views/inputs.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00465">Descriptors.cpp:465</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_ae83131e16df1cace69395a5f99bc5ecb"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#ae83131e16df1cace69395a5f99bc5ecb">armnn::LstmInputParams::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00045">LstmParams.hpp:45</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a8b51e137fab21d758b965c6c6e3b02f3"><div class="ttname"><a href="namespacearmnn_deserializer.html#a8b51e137fab21d758b965c6c6e3b02f3">armnnDeserializer::ToResizeMethod</a></div><div class="ttdeci">armnn::ResizeMethod ToResizeMethod(armnnSerializer::ResizeMethod method)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00641">Deserializer.cpp:641</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a8b51e137fab21d758b965c6c6e3b02f3"><div class="ttname"><a href="namespacearmnn_deserializer.html#a8b51e137fab21d758b965c6c6e3b02f3">armnnDeserializer::ToResizeMethod</a></div><div class="ttdeci">armnn::ResizeMethod ToResizeMethod(armnnSerializer::ResizeMethod method)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00663">Deserializer.cpp:663</a></div></div> <div class="ttc" id="astructarmnn_1_1_channel_shuffle_descriptor_html_ab218de7805899c8412d75d1fd1d846d2"><div class="ttname"><a href="structarmnn_1_1_channel_shuffle_descriptor.html#ab218de7805899c8412d75d1fd1d846d2">armnn::ChannelShuffleDescriptor::m_Axis</a></div><div class="ttdeci">uint32_t m_Axis</div><div class="ttdoc">Axis to apply channel shuffle operation on.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01580">Descriptors.hpp:1580</a></div></div> <div class="ttc" id="anamespacearmnn_html_ac4f8557279754ed7b3f749d55b0e3047a62b6d55816cf737bfc6f42e60df1a3f2"><div class="ttname"><a href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a62b6d55816cf737bfc6f42e60df1a3f2">armnn::BinaryOperation::Mul</a></div><div class="ttdeci">@ Mul</div></div> <div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a></div><div class="ttdeci">@ Boolean</div></div> @@ -4138,12 +4189,13 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_fully_connected_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.html">armnn::FullyConnectedDescriptor</a></div><div class="ttdoc">A FullyConnectedDescriptor for the FullyConnectedLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00507">Descriptors.hpp:507</a></div></div> <div class="ttc" id="anamespacearmnn_html_ac4f8557279754ed7b3f749d55b0e3047aec211f7c20af43e742bf2570c3cb84f9"><div class="ttname"><a href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aec211f7c20af43e742bf2570c3cb84f9">armnn::BinaryOperation::Add</a></div><div class="ttdeci">@ Add</div></div> <div class="ttc" id="astructarmnn_1_1_detection_post_process_descriptor_html_ae64523937ea910030ad66fee6fddd51f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html#ae64523937ea910030ad66fee6fddd51f">armnn::DetectionPostProcessDescriptor::m_ScaleX</a></div><div class="ttdeci">float m_ScaleX</div><div class="ttdoc">Center size encoding scale x.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00759">Descriptors.hpp:759</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_ac33cddeda1d847c4a17d679ea1dab6be"><div class="ttname"><a href="namespacearmnn_deserializer.html#ac33cddeda1d847c4a17d679ea1dab6be">armnnDeserializer::ToPaddingMode</a></div><div class="ttdeci">armnn::PaddingMode ToPaddingMode(armnnSerializer::PaddingMode paddingMode)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00628">Deserializer.cpp:628</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_ac33cddeda1d847c4a17d679ea1dab6be"><div class="ttname"><a href="namespacearmnn_deserializer.html#ac33cddeda1d847c4a17d679ea1dab6be">armnnDeserializer::ToPaddingMode</a></div><div class="ttdeci">armnn::PaddingMode ToPaddingMode(armnnSerializer::PaddingMode paddingMode)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00650">Deserializer.cpp:650</a></div></div> <div class="ttc" id="aclassarmnn_1_1_base_tensor_html_aa81f67ac64f0c249e26499600c45d996"><div class="ttname"><a href="classarmnn_1_1_base_tensor.html#aa81f67ac64f0c249e26499600c45d996">armnn::BaseTensor::GetMemoryArea</a></div><div class="ttdeci">MemoryType GetMemoryArea() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00307">Tensor.hpp:307</a></div></div> <div class="ttc" id="anamespacearmnn_html_a2d299363c9fc33334c571fa29ca4f58caa4cbdbb6070a5abb35fc95ecf1e22c14"><div class="ttname"><a href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58caa4cbdbb6070a5abb35fc95ecf1e22c14">armnn::ComparisonOperation::LessOrEqual</a></div><div class="ttdeci">@ LessOrEqual</div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_afcc87bf0e20779861dd5d01a4bedcda9"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#afcc87bf0e20779861dd5d01a4bedcda9">armnnDeserializer::IDeserializer::DeserializerImpl::GetBindingLayerInfo</a></div><div class="ttdeci">static int32_t GetBindingLayerInfo(const GraphPtr &graphPtr, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00448">Deserializer.cpp:448</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_afcc87bf0e20779861dd5d01a4bedcda9"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#afcc87bf0e20779861dd5d01a4bedcda9">armnnDeserializer::IDeserializer::DeserializerImpl::GetBindingLayerInfo</a></div><div class="ttdeci">static int32_t GetBindingLayerInfo(const GraphPtr &graphPtr, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00451">Deserializer.cpp:451</a></div></div> <div class="ttc" id="anamespacearmnn_deserializer_html_a97b50f22cd99f0e09e6e48d20a35f6b2"><div class="ttname"><a href="namespacearmnn_deserializer.html#a97b50f22cd99f0e09e6e48d20a35f6b2">armnnDeserializer::CheckShape</a></div><div class="ttdeci">bool CheckShape(const armnn::TensorShape &actual, const std::vector< uint32_t > &expected)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00188">Deserializer.cpp:188</a></div></div> <div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.html">armnn::QLstmDescriptor</a></div><div class="ttdoc">A QLstmDescriptor for the QLstmLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01380">Descriptors.hpp:1380</a></div></div> +<div class="ttc" id="anamespacearmnn_html_a75ca90884e15396a70b0cb722a877b4aa78d811e98514cd165dda532286610fd2"><div class="ttname"><a href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aa78d811e98514cd165dda532286610fd2">armnn::ScatterNdFunction::Min</a></div><div class="ttdeci">@ Min</div></div> <div class="ttc" id="aclassarmnn_1_1_tensor_info_html_abcbdfb544ece4c31d0b37715ad0f3be0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#abcbdfb544ece4c31d0b37715ad0f3be0">armnn::TensorInfo::GetNumBytes</a></div><div class="ttdeci">unsigned int GetNumBytes() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00427">Tensor.cpp:427</a></div></div> <div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::TransposeConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01477">Descriptors.hpp:1477</a></div></div> <div class="ttc" id="aclassarmnn_1_1_optional_html"><div class="ttname"><a href="classarmnn_1_1_optional.html">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00270">Optional.hpp:270</a></div></div> @@ -4159,16 +4211,17 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="anamespacearmnn_html_a9a2af2f8c4af4f9efa8e79417d505ac4"><div class="ttname"><a href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4">armnn::ResizeMethod</a></div><div class="ttdeci">ResizeMethod</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00166">Types.hpp:166</a></div></div> <div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00062">Types.hpp:62</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling3d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_pooling3d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">armnn::Pooling3dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00479">Descriptors.hpp:479</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_ac337f5478049cba1da222da655be49cc"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac337f5478049cba1da222da655be49cc">armnnDeserializer::IDeserializer::DeserializerImpl::GetInputs</a></div><div class="ttdeci">static TensorRawPtrVector GetInputs(const GraphPtr &graph, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00803">Deserializer.cpp:803</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_ac337f5478049cba1da222da655be49cc"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac337f5478049cba1da222da655be49cc">armnnDeserializer::IDeserializer::DeserializerImpl::GetInputs</a></div><div class="ttdeci">static TensorRawPtrVector GetInputs(const GraphPtr &graph, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00825">Deserializer.cpp:825</a></div></div> <div class="ttc" id="a_descriptors_8hpp_html"><div class="ttname"><a href="_descriptors_8hpp.html">Descriptors.hpp</a></div></div> <div class="ttc" id="astructarmnn_1_1_space_to_batch_nd_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::SpaceToBatchNdDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01071">Descriptors.hpp:1071</a></div></div> <div class="ttc" id="anamespacearmnn_deserializer_html"><div class="ttname"><a href="namespacearmnn_deserializer.html">armnnDeserializer</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_deserializer_8hpp_source.html#l00016">IDeserializer.hpp:16</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a2ccbea2c0078ba1d34c2ac48a8bdd342"><div class="ttname"><a href="namespacearmnn_deserializer.html#a2ccbea2c0078ba1d34c2ac48a8bdd342">armnnDeserializer::ToLogicalBinaryOperation</a></div><div class="ttdeci">armnn::LogicalBinaryOperation ToLogicalBinaryOperation(armnnSerializer::LogicalBinaryOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00563">Deserializer.cpp:563</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a2ccbea2c0078ba1d34c2ac48a8bdd342"><div class="ttname"><a href="namespacearmnn_deserializer.html#a2ccbea2c0078ba1d34c2ac48a8bdd342">armnnDeserializer::ToLogicalBinaryOperation</a></div><div class="ttdeci">armnn::LogicalBinaryOperation ToLogicalBinaryOperation(armnnSerializer::LogicalBinaryOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00585">Deserializer.cpp:585</a></div></div> <div class="ttc" id="astructarmnn_1_1_fully_connected_descriptor_html_a281fcaec86e17c97f7b8402633f6b55a"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.html#a281fcaec86e17c97f7b8402633f6b55a">armnn::FullyConnectedDescriptor::m_TransposeWeightMatrix</a></div><div class="ttdeci">bool m_TransposeWeightMatrix</div><div class="ttdoc">Enable/disable transpose weight matrix.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00528">Descriptors.hpp:528</a></div></div> <div class="ttc" id="astructarmnn_1_1_resize_descriptor_html_a46c3fa15c46fb0d1dcdc24d0ea5cb5cd"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">armnn::ResizeDescriptor::m_TargetHeight</a></div><div class="ttdeci">uint32_t m_TargetHeight</div><div class="ttdoc">Target height value.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01009">Descriptors.hpp:1009</a></div></div> <div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00708">Descriptors.hpp:708</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling2d_descriptor_html_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">armnn::Pooling2dDescriptor::m_PoolHeight</a></div><div class="ttdeci">uint32_t m_PoolHeight</div><div class="ttdoc">Pooling height value.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00417">Descriptors.hpp:417</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_a44b0e6b16708df7f0d2bbab141688aaa"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#a44b0e6b16708df7f0d2bbab141688aaa">armnn::LstmInputParams::m_ProjectionBias</a></div><div class="ttdeci">const ConstTensor * m_ProjectionBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00056">LstmParams.hpp:56</a></div></div> +<div class="ttc" id="anamespacearmnn_html_a75ca90884e15396a70b0cb722a877b4aae80155eceb940c89e2de63ad05868db2"><div class="ttname"><a href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aae80155eceb940c89e2de63ad05868db2">armnn::ScatterNdFunction::Sub</a></div><div class="ttdeci">@ Sub</div></div> <div class="ttc" id="astructarmnn_1_1_detection_post_process_descriptor_html_a7a2156ec7d9c012ce00bbcc6afcb9028"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html#a7a2156ec7d9c012ce00bbcc6afcb9028">armnn::DetectionPostProcessDescriptor::m_ScaleY</a></div><div class="ttdeci">float m_ScaleY</div><div class="ttdoc">Center size encoding scale y.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00761">Descriptors.hpp:761</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling3d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_pooling3d_descriptor.html">armnn::Pooling3dDescriptor</a></div><div class="ttdoc">A Pooling3dDescriptor for the Pooling3dLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00431">Descriptors.hpp:431</a></div></div> <div class="ttc" id="astructarmnn_1_1_detection_post_process_descriptor_html_ae72089bcab60ac175557f4241b16a014"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html#ae72089bcab60ac175557f4241b16a014">armnn::DetectionPostProcessDescriptor::m_MaxDetections</a></div><div class="ttdeci">uint32_t m_MaxDetections</div><div class="ttdoc">Maximum numbers of detections.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00745">Descriptors.hpp:745</a></div></div> @@ -4184,11 +4237,12 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_instance_normalization_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.html">armnn::InstanceNormalizationDescriptor</a></div><div class="ttdoc">An InstanceNormalizationDescriptor for InstanceNormalizationLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00847">Descriptors.hpp:847</a></div></div> <div class="ttc" id="astructarmnn_1_1_check_location_html_a46e3b4b140e2c550342337b5fcceb9c6"><div class="ttname"><a href="structarmnn_1_1_check_location.html#a46e3b4b140e2c550342337b5fcceb9c6">armnn::CheckLocation::m_Function</a></div><div class="ttdeci">const char * m_Function</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00016">Exceptions.hpp:16</a></div></div> <div class="ttc" id="astructarmnn_1_1_softmax_descriptor_html_a8275d51ef9a584feb95726ea0522f6e5"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">armnn::SoftmaxDescriptor::m_Beta</a></div><div class="ttdeci">float m_Beta</div><div class="ttdoc">Exponentiation value.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00190">Descriptors.hpp:190</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a32a96909bc8a8ee9076bd4d5c1028301"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a32a96909bc8a8ee9076bd4d5c1028301">armnnDeserializer::IDeserializer::DeserializerImpl::CreateNetworkFromBinary</a></div><div class="ttdeci">armnn::INetworkPtr CreateNetworkFromBinary(const std::vector< uint8_t > &binaryContent)</div><div class="ttdoc">Create an input network from binary file contents.</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00854">Deserializer.cpp:854</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a32a96909bc8a8ee9076bd4d5c1028301"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a32a96909bc8a8ee9076bd4d5c1028301">armnnDeserializer::IDeserializer::DeserializerImpl::CreateNetworkFromBinary</a></div><div class="ttdeci">armnn::INetworkPtr CreateNetworkFromBinary(const std::vector< uint8_t > &binaryContent)</div><div class="ttdoc">Create an input network from binary file contents.</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00876">Deserializer.cpp:876</a></div></div> <div class="ttc" id="astructarmnn_1_1_gather_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_gather_descriptor.html">armnn::GatherDescriptor</a></div><div class="ttdoc">A GatherDescriptor for the GatherLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00965">Descriptors.hpp:965</a></div></div> <div class="ttc" id="a_types_utils_8hpp_html"><div class="ttname"><a href="_types_utils_8hpp.html">TypesUtils.hpp</a></div></div> <div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00710">Descriptors.hpp:710</a></div></div> <div class="ttc" id="anamespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::ActivationFunction::Sqrt</a></div><div class="ttdeci">@ Sqrt</div></div> +<div class="ttc" id="astructarmnn_1_1_scatter_nd_descriptor_html_a12501f4f1f889d0b63f8a6067cdaad4a"><div class="ttname"><a href="structarmnn_1_1_scatter_nd_descriptor.html#a12501f4f1f889d0b63f8a6067cdaad4a">armnn::ScatterNdDescriptor::m_InputEnabled</a></div><div class="ttdeci">bool m_InputEnabled</div><div class="ttdoc">Flag to show if input tensor is accepted.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01722">Descriptors.hpp:1722</a></div></div> <div class="ttc" id="astructarmnn_1_1_l2_normalization_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::L2NormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00824">Descriptors.hpp:824</a></div></div> <div class="ttc" id="aclassarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00152">Tensor.hpp:152</a></div></div> <div class="ttc" id="astructarmnn_1_1_l2_normalization_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.html">armnn::L2NormalizationDescriptor</a></div><div class="ttdoc">A L2NormalizationDescriptor for the L2NormalizationLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00809">Descriptors.hpp:809</a></div></div> @@ -4242,7 +4296,7 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_pooling2d_descriptor_html_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">armnn::Pooling2dDescriptor::m_PoolWidth</a></div><div class="ttdeci">uint32_t m_PoolWidth</div><div class="ttdoc">Pooling width value.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00415">Descriptors.hpp:415</a></div></div> <div class="ttc" id="anamespacearmnn_html_a1cfaa710db2a54673b21d2ea2da757c8afb278fa5defd7e699fcbc930c3e76ccd"><div class="ttname"><a href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8afb278fa5defd7e699fcbc930c3e76ccd">armnn::UnaryOperation::Neg</a></div><div class="ttdeci">@ Neg</div></div> <div class="ttc" id="astructarmnn_1_1_stand_in_descriptor_html_aed6086070440ceb94129bef06f70173f"><div class="ttname"><a href="structarmnn_1_1_stand_in_descriptor.html#aed6086070440ceb94129bef06f70173f">armnn::StandInDescriptor::m_NumInputs</a></div><div class="ttdeci">uint32_t m_NumInputs</div><div class="ttdoc">Number of input tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01297">Descriptors.hpp:1297</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a57e32d26ac8c87b118e77da920481123"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a57e32d26ac8c87b118e77da920481123">armnnDeserializer::IDeserializer::DeserializerImpl::GetQLstmDescriptor</a></div><div class="ttdeci">static armnn::QLstmDescriptor GetQLstmDescriptor(QLstmDescriptorPtr qLstmDescriptorPtr)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l03416">Deserializer.cpp:3416</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a57e32d26ac8c87b118e77da920481123"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a57e32d26ac8c87b118e77da920481123">armnnDeserializer::IDeserializer::DeserializerImpl::GetQLstmDescriptor</a></div><div class="ttdeci">static armnn::QLstmDescriptor GetQLstmDescriptor(QLstmDescriptorPtr qLstmDescriptorPtr)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l03438">Deserializer.cpp:3438</a></div></div> <div class="ttc" id="anamespacearmnn_html_a2da4db0140d1a6dc69c9c82e9ef5379e"><div class="ttname"><a href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379e">armnn::LogicalBinaryOperation</a></div><div class="ttdeci">LogicalBinaryOperation</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00119">Types.hpp:119</a></div></div> <div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html">armnnDeserializer::IDeserializer::DeserializerImpl</a></div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.html#l00034">Deserializer.hpp:34</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling3d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_pooling3d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Pooling3dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCDHW, NDHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00503">Descriptors.hpp:503</a></div></div> @@ -4263,17 +4317,18 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="anamespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaaf48cca1c6deaa6a1c34e4ee46954cf0b"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaf48cca1c6deaa6a1c34e4ee46954cf0b">armnn::ActivationFunction::Gelu</a></div><div class="ttdeci">@ Gelu</div></div> <div class="ttc" id="astructarmnn_1_1_normalization_descriptor_html_a05945f080edf694b631960728b87aadb"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.html#a05945f080edf694b631960728b87aadb">armnn::NormalizationDescriptor::m_NormMethodType</a></div><div class="ttdeci">NormalizationAlgorithmMethod m_NormMethodType</div><div class="ttdoc">Normalization method algorithm to use (LocalBrightness, LocalContrast).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00795">Descriptors.hpp:795</a></div></div> <div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::TransposeConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01475">Descriptors.hpp:1475</a></div></div> +<div class="ttc" id="astructarmnn_1_1_scatter_nd_descriptor_html_a96a5cc69bb69aea9cb10cdf17f74fbd4"><div class="ttname"><a href="structarmnn_1_1_scatter_nd_descriptor.html#a96a5cc69bb69aea9cb10cdf17f74fbd4">armnn::ScatterNdDescriptor::m_AxisEnabled</a></div><div class="ttdeci">bool m_AxisEnabled</div><div class="ttdoc">Flag for ScatterElement, will be set to false by default, we do not support m_AxisEnable = true for n...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01728">Descriptors.hpp:1728</a></div></div> <div class="ttc" id="a_numeric_cast_8hpp_html"><div class="ttname"><a href="_numeric_cast_8hpp.html">NumericCast.hpp</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_ace7a1f1f1041b412b7d8ef82b95ff352"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#ace7a1f1f1041b412b7d8ef82b95ff352">armnn::LstmInputParams::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensor * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00052">LstmParams.hpp:52</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling3d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling3d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Pooling3dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00495">Descriptors.hpp:495</a></div></div> <div class="ttc" id="anamespacearmnn_html_abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc"><div class="ttname"><a href="namespacearmnn.html#abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc">armnn::NormalizationAlgorithmChannel::Across</a></div><div class="ttdeci">@ Across</div></div> <div class="ttc" id="astructarmnn_1_1_reduce_descriptor_html_aa57c67b1da0011b1abb30170146e870f"><div class="ttname"><a href="structarmnn_1_1_reduce_descriptor.html#aa57c67b1da0011b1abb30170146e870f">armnn::ReduceDescriptor::m_ReduceOperation</a></div><div class="ttdeci">ReduceOperation m_ReduceOperation</div><div class="ttdoc">Specifies the reduction operation to execute.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01558">Descriptors.hpp:1558</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a5de68e32eabd643f55a35f288ba10294"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a5de68e32eabd643f55a35f288ba10294">armnnDeserializer::IDeserializer::DeserializerImpl::GetNetworkInputBindingInfo</a></div><div class="ttdeci">BindingPointInfo GetNetworkInputBindingInfo(unsigned int layerId, const std::string &name) const</div><div class="ttdoc">Retrieve binding info (layer id and tensor info) for the network input identified by the given layer ...</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00939">Deserializer.cpp:939</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a5de68e32eabd643f55a35f288ba10294"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a5de68e32eabd643f55a35f288ba10294">armnnDeserializer::IDeserializer::DeserializerImpl::GetNetworkInputBindingInfo</a></div><div class="ttdeci">BindingPointInfo GetNetworkInputBindingInfo(unsigned int layerId, const std::string &name) const</div><div class="ttdoc">Retrieve binding info (layer id and tensor info) for the network input identified by the given layer ...</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00961">Deserializer.cpp:961</a></div></div> <div class="ttc" id="anamespacearmnn_html_a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96"><div class="ttname"><a href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96">armnn::ComparisonOperation::NotEqual</a></div><div class="ttdeci">@ NotEqual</div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_a484bafa2f8453a7c5a4a00b92a61b006"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#a484bafa2f8453a7c5a4a00b92a61b006">armnn::LstmInputParams::m_CellToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_CellToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00048">LstmParams.hpp:48</a></div></div> <div class="ttc" id="anamespacearmnn_html_a2d299363c9fc33334c571fa29ca4f58ca6f2f0aefb3d22da0f3839453add5f937"><div class="ttname"><a href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca6f2f0aefb3d22da0f3839453add5f937">armnn::ComparisonOperation::GreaterOrEqual</a></div><div class="ttdeci">@ GreaterOrEqual</div></div> <div class="ttc" id="astructarmnn_1_1_mean_descriptor_html_a28e0548abfc4e79c48f29a3d11a062e9"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.html#a28e0548abfc4e79c48f29a3d11a062e9">armnn::MeanDescriptor::m_KeepDims</a></div><div class="ttdeci">bool m_KeepDims</div><div class="ttdoc">Enable/disable keep dimensions. If true, then the reduced dimensions that are of length 1 are kept.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01192">Descriptors.hpp:1192</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a9f1aae5d3ce2b27d619725fb3cee38da"><div class="ttname"><a href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">armnnDeserializer::ToConstTensor</a></div><div class="ttdeci">armnn::ConstTensor ToConstTensor(ConstTensorRawPtr constTensorPtr)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00760">Deserializer.cpp:760</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a9f1aae5d3ce2b27d619725fb3cee38da"><div class="ttname"><a href="namespacearmnn_deserializer.html#a9f1aae5d3ce2b27d619725fb3cee38da">armnnDeserializer::ToConstTensor</a></div><div class="ttdeci">armnn::ConstTensor ToConstTensor(ConstTensorRawPtr constTensorPtr)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00782">Deserializer.cpp:782</a></div></div> <div class="ttc" id="a_logging_8hpp_html_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.html#l00212">Logging.hpp:212</a></div></div> <div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a4dd0194b114cbf51da5b3a72569863ef"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a4dd0194b114cbf51da5b3a72569863ef">armnn::DataLayout::NDHWC</a></div><div class="ttdeci">@ NDHWC</div></div> <div class="ttc" id="astructarmnn_1_1_fill_descriptor_html_ab3ebc5cf4a617d43371a4cb7fecdeb32"><div class="ttname"><a href="structarmnn_1_1_fill_descriptor.html#ab3ebc5cf4a617d43371a4cb7fecdeb32">armnn::FillDescriptor::m_Value</a></div><div class="ttdeci">float m_Value</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00940">Descriptors.hpp:940</a></div></div> @@ -4290,37 +4345,38 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="aclassarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::Convolution3dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00631">Descriptors.hpp:631</a></div></div> <div class="ttc" id="a_verification_helpers_8hpp_html"><div class="ttname"><a href="_verification_helpers_8hpp.html">VerificationHelpers.hpp</a></div></div> +<div class="ttc" id="astructarmnn_1_1_scatter_nd_descriptor_html_a35d11c7d509d1adbae1ae01c58394a7f"><div class="ttname"><a href="structarmnn_1_1_scatter_nd_descriptor.html#a35d11c7d509d1adbae1ae01c58394a7f">armnn::ScatterNdDescriptor::m_Axis</a></div><div class="ttdeci">int32_t m_Axis</div><div class="ttdoc">Extra attribute for ScatterElement, will be set to 0 by default, we do not support axis !...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01725">Descriptors.hpp:1725</a></div></div> <div class="ttc" id="astructarmnn_1_1_normalization_descriptor_html_afe1f0f09d49ad2befc01f8789187b7dd"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.html#afe1f0f09d49ad2befc01f8789187b7dd">armnn::NormalizationDescriptor::m_NormChannelType</a></div><div class="ttdeci">NormalizationAlgorithmChannel m_NormChannelType</div><div class="ttdoc">Normalization channel algorithm to use (Across, Within).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00793">Descriptors.hpp:793</a></div></div> <div class="ttc" id="a_lstm_params_8hpp_html"><div class="ttname"><a href="_lstm_params_8hpp.html">LstmParams.hpp</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a2ee1264a9803ff8dc1323a26f1f4c986"><div class="ttname"><a href="namespacearmnn_deserializer.html#a2ee1264a9803ff8dc1323a26f1f4c986">armnnDeserializer::ToActivationFunction</a></div><div class="ttdeci">armnn::ActivationFunction ToActivationFunction(armnnSerializer::ActivationFunction function)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00479">Deserializer.cpp:479</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a2ee1264a9803ff8dc1323a26f1f4c986"><div class="ttname"><a href="namespacearmnn_deserializer.html#a2ee1264a9803ff8dc1323a26f1f4c986">armnnDeserializer::ToActivationFunction</a></div><div class="ttdeci">armnn::ActivationFunction ToActivationFunction(armnnSerializer::ActivationFunction function)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00482">Deserializer.cpp:482</a></div></div> <div class="ttc" id="aclassarmnn_1_1_i_output_slot_html"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.html">armnn::IOutputSlot</a></div><div class="ttdoc">An output connection slot for a layer.</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00053">INetwork.hpp:53</a></div></div> <div class="ttc" id="anamespacearmnn_html_ac4f8557279754ed7b3f749d55b0e3047a8321e79c278ec510f63675c040594892"><div class="ttname"><a href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a8321e79c278ec510f63675c040594892">armnn::BinaryOperation::Maximum</a></div><div class="ttdeci">@ Maximum</div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_a35b112e30c3eb153806a2a8c16d178e3"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#a35b112e30c3eb153806a2a8c16d178e3">armnn::LstmInputParams::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00049">LstmParams.hpp:49</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a2f66de823cd61765a40407fee754655e"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a2f66de823cd61765a40407fee754655e">armnnDeserializer::IDeserializer::DeserializerImpl::GetNetworkOutputBindingInfo</a></div><div class="ttdeci">BindingPointInfo GetNetworkOutputBindingInfo(unsigned int layerId, const std::string &name) const</div><div class="ttdoc">Retrieve binding info (layer id and tensor info) for the network output identified by the given layer...</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00955">Deserializer.cpp:955</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a9069127d4430d97fe0f2c53fb2c32ab9"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a9069127d4430d97fe0f2c53fb2c32ab9">armnnDeserializer::IDeserializer::DeserializerImpl::GetOutputs</a></div><div class="ttdeci">static TensorRawPtrVector GetOutputs(const GraphPtr &graph, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00820">Deserializer.cpp:820</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a2f66de823cd61765a40407fee754655e"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a2f66de823cd61765a40407fee754655e">armnnDeserializer::IDeserializer::DeserializerImpl::GetNetworkOutputBindingInfo</a></div><div class="ttdeci">BindingPointInfo GetNetworkOutputBindingInfo(unsigned int layerId, const std::string &name) const</div><div class="ttdoc">Retrieve binding info (layer id and tensor info) for the network output identified by the given layer...</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00977">Deserializer.cpp:977</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a9069127d4430d97fe0f2c53fb2c32ab9"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a9069127d4430d97fe0f2c53fb2c32ab9">armnnDeserializer::IDeserializer::DeserializerImpl::GetOutputs</a></div><div class="ttdeci">static TensorRawPtrVector GetOutputs(const GraphPtr &graph, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00842">Deserializer.cpp:842</a></div></div> <div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div><div class="ttdeci">@ Float16</div></div> <div class="ttc" id="astructarmnn_1_1_check_location_html"><div class="ttname"><a href="structarmnn_1_1_check_location.html">armnn::CheckLocation</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00014">Exceptions.hpp:14</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a1467999b659959577bb2efc8fc62e15a"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a1467999b659959577bb2efc8fc62e15a">armnnDeserializer::IDeserializer::DeserializerImpl::GetPooling3dDescriptor</a></div><div class="ttdeci">static armnn::Pooling3dDescriptor GetPooling3dDescriptor(Pooling3dDescriptor pooling3dDescriptor, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02456">Deserializer.cpp:2456</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a1467999b659959577bb2efc8fc62e15a"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a1467999b659959577bb2efc8fc62e15a">armnnDeserializer::IDeserializer::DeserializerImpl::GetPooling3dDescriptor</a></div><div class="ttdeci">static armnn::Pooling3dDescriptor GetPooling3dDescriptor(Pooling3dDescriptor pooling3dDescriptor, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02478">Deserializer.cpp:2478</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_a435d3651482bbfcc11263b4e4e0c900f"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#a435d3651482bbfcc11263b4e4e0c900f">armnn::LstmInputParams::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00044">LstmParams.hpp:44</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_descriptor_html_a86e88bef0df4df96df752b4b8955a3af"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.html#a86e88bef0df4df96df752b4b8955a3af">armnn::LstmDescriptor::m_ClippingThresProj</a></div><div class="ttdeci">float m_ClippingThresProj</div><div class="ttdoc">Clipping threshold value for the projection.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01144">Descriptors.hpp:1144</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling3d_descriptor_html_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling3d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">armnn::Pooling3dDescriptor::m_PoolWidth</a></div><div class="ttdeci">uint32_t m_PoolWidth</div><div class="ttdoc">Pooling width value.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00487">Descriptors.hpp:487</a></div></div> <div class="ttc" id="anamespacearmnn_html_ac4f8557279754ed7b3f749d55b0e3047a2d17ea57d7f86acde5c60cef8e123a53"><div class="ttname"><a href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a2d17ea57d7f86acde5c60cef8e123a53">armnn::BinaryOperation::SqDiff</a></div><div class="ttdeci">@ SqDiff</div></div> <div class="ttc" id="astructarmnn_1_1_pooling2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Pooling2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00427">Descriptors.hpp:427</a></div></div> -<div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::Convolution2dDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00469">Descriptors.cpp:469</a></div></div> +<div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::Convolution2dDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00470">Descriptors.cpp:470</a></div></div> <div class="ttc" id="anamespacearmnn_html_a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4"><div class="ttname"><a href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4">armnn::UnaryOperation::Rsqrt</a></div><div class="ttdeci">@ Rsqrt</div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_affcee5f4ab5994a21bee3b78b4e43de3"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#affcee5f4ab5994a21bee3b78b4e43de3">armnn::LstmInputParams::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00040">LstmParams.hpp:40</a></div></div> <div class="ttc" id="aclassarmnn_1_1_tensor_shape_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdoc">Function that returns the tensor rank.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00174">Tensor.cpp:174</a></div></div> <div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_html_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">armnn::DepthwiseConvolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation factor value for height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00706">Descriptors.hpp:706</a></div></div> <div class="ttc" id="anamespacearmnn_html_a2d299363c9fc33334c571fa29ca4f58ca1cfdf0e8d0c87a228c1f40d9bee7888b"><div class="ttname"><a href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca1cfdf0e8d0c87a228c1f40d9bee7888b">armnn::ComparisonOperation::Less</a></div><div class="ttdeci">@ Less</div></div> <div class="ttc" id="anamespacearmnn_html_a1cfaa710db2a54673b21d2ea2da757c8aae77f3ad25595e35b327334d89410054"><div class="ttname"><a href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8aae77f3ad25595e35b327334d89410054">armnn::UnaryOperation::Sqrt</a></div><div class="ttdeci">@ Sqrt</div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a8752c2b994619ae67201a297c2c76be2"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a8752c2b994619ae67201a297c2c76be2">armnnDeserializer::IDeserializer::DeserializerImpl::OutputShapeOfReshape</a></div><div class="ttdeci">static armnn::TensorInfo OutputShapeOfReshape(const armnn::TensorInfo &inputTensorInfo, const std::vector< uint32_t > &targetDimsIn)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02616">Deserializer.cpp:2616</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a8752c2b994619ae67201a297c2c76be2"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a8752c2b994619ae67201a297c2c76be2">armnnDeserializer::IDeserializer::DeserializerImpl::OutputShapeOfReshape</a></div><div class="ttdeci">static armnn::TensorInfo OutputShapeOfReshape(const armnn::TensorInfo &inputTensorInfo, const std::vector< uint32_t > &targetDimsIn)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02638">Deserializer.cpp:2638</a></div></div> <div class="ttc" id="anamespacearmnn_html_a1cfaa710db2a54673b21d2ea2da757c8a2a25ebd8c909241e3f7818389b804ecc"><div class="ttname"><a href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a2a25ebd8c909241e3f7818389b804ecc">armnn::UnaryOperation::LogicalNot</a></div><div class="ttdeci">@ LogicalNot</div></div> <div class="ttc" id="astructarmnn_1_1_quantized_lstm_input_params_html_a56b81ca8ba4b4937e0787e4951f043fc"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">armnn::QuantizedLstmInputParams::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.html#l00041">QuantizedLstmParams.hpp:41</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::Pooling2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00413">Descriptors.hpp:413</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_a56b81ca8ba4b4937e0787e4951f043fc"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#a56b81ca8ba4b4937e0787e4951f043fc">armnn::LstmInputParams::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00047">LstmParams.hpp:47</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling3d_descriptor_html_a8c29d6ea9b4186d69aad5961c910939c"><div class="ttname"><a href="structarmnn_1_1_pooling3d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">armnn::Pooling3dDescriptor::m_PaddingMethod</a></div><div class="ttdeci">PaddingMethod m_PaddingMethod</div><div class="ttdoc">The padding method to be used. (Exclude, IgnoreValue).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00501">Descriptors.hpp:501</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::Pooling2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00409">Descriptors.hpp:409</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a9c11dfb7a73226061b83ecd995b91582"><div class="ttname"><a href="namespacearmnn_deserializer.html#a9c11dfb7a73226061b83ecd995b91582">armnnDeserializer::ToElementwiseUnaryOperation</a></div><div class="ttdeci">armnn::UnaryOperation ToElementwiseUnaryOperation(armnnSerializer::UnaryOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00601">Deserializer.cpp:601</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a9c11dfb7a73226061b83ecd995b91582"><div class="ttname"><a href="namespacearmnn_deserializer.html#a9c11dfb7a73226061b83ecd995b91582">armnnDeserializer::ToElementwiseUnaryOperation</a></div><div class="ttdeci">armnn::UnaryOperation ToElementwiseUnaryOperation(armnnSerializer::UnaryOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00623">Deserializer.cpp:623</a></div></div> <div class="ttc" id="astructarmnn_1_1_fully_connected_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::FullyConnectedDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00526">Descriptors.hpp:526</a></div></div> <div class="ttc" id="a_logging_8hpp_html"><div class="ttname"><a href="_logging_8hpp.html">Logging.hpp</a></div></div> <div class="ttc" id="astructarmnn_1_1_logical_binary_descriptor_html_a32c95d929d2e2e0fa7fc1a3a25865eb0"><div class="ttname"><a href="structarmnn_1_1_logical_binary_descriptor.html#a32c95d929d2e2e0fa7fc1a3a25865eb0">armnn::LogicalBinaryDescriptor::m_Operation</a></div><div class="ttdeci">LogicalBinaryOperation m_Operation</div><div class="ttdoc">Specifies the logical operation to execute.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01534">Descriptors.hpp:1534</a></div></div> @@ -4328,7 +4384,7 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="anamespacearmnn_html_a1cfaa710db2a54673b21d2ea2da757c8acad39a154bffb61175f674d6eefaf6d0"><div class="ttname"><a href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8acad39a154bffb61175f674d6eefaf6d0">armnn::UnaryOperation::Exp</a></div><div class="ttdeci">@ Exp</div></div> <div class="ttc" id="anamespacearmnn_deserializer_html_a2a282cf18fcfe848b47e946327ca1048"><div class="ttname"><a href="namespacearmnn_deserializer.html#a2a282cf18fcfe848b47e946327ca1048">armnnDeserializer::NormalizationDescriptorPtr</a></div><div class="ttdeci">const armnnSerializer::NormalizationDescriptor * NormalizationDescriptorPtr</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.html#l00023">Deserializer.hpp:23</a></div></div> <div class="ttc" id="aclassarmnn_1_1_i_output_slot_html_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a28f896fb78cdf6607b61c196c98b2570"><div class="ttname"><a href="namespacearmnn_deserializer.html#a28f896fb78cdf6607b61c196c98b2570">armnnDeserializer::ToComparisonOperation</a></div><div class="ttdeci">armnn::ComparisonOperation ToComparisonOperation(armnnSerializer::ComparisonOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00524">Deserializer.cpp:524</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a28f896fb78cdf6607b61c196c98b2570"><div class="ttname"><a href="namespacearmnn_deserializer.html#a28f896fb78cdf6607b61c196c98b2570">armnnDeserializer::ToComparisonOperation</a></div><div class="ttdeci">armnn::ComparisonOperation ToComparisonOperation(armnnSerializer::ComparisonOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00546">Deserializer.cpp:546</a></div></div> <div class="ttc" id="astructarmnn_1_1_transpose_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_transpose_descriptor.html">armnn::TransposeDescriptor</a></div><div class="ttdoc">A TransposeDescriptor for the TransposeLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01490">Descriptors.hpp:1490</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html_a16543bce17aa2e4d6e81c88f74227192"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html#a16543bce17aa2e4d6e81c88f74227192">armnn::Convolution3dDescriptor::m_DilationZ</a></div><div class="ttdeci">uint32_t m_DilationZ</div><div class="ttdoc">Dilation along z axis.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00651">Descriptors.hpp:651</a></div></div> <div class="ttc" id="astructarmnn_1_1_detection_post_process_descriptor_html_a3a04b0ccee4bb2f21721ee5045e83df4"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html#a3a04b0ccee4bb2f21721ee5045e83df4">armnn::DetectionPostProcessDescriptor::m_NumClasses</a></div><div class="ttdeci">uint32_t m_NumClasses</div><div class="ttdoc">Number of classes.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00755">Descriptors.hpp:755</a></div></div> @@ -4345,10 +4401,11 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="anamespacearmnn_html_a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a"><div class="ttname"><a href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a></div><div class="ttdeci">@ IgnoreValue</div><div class="ttdoc">The padding fields count, but are ignored.</div></div> <div class="ttc" id="astructarmnn_1_1_reshape_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.html">armnn::ReshapeDescriptor</a></div><div class="ttdoc">A ReshapeDescriptor for the ReshapeLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01023">Descriptors.hpp:1023</a></div></div> <div class="ttc" id="aclassarmnn_1_1_invalid_argument_exception_html"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00080">Exceptions.hpp:80</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_aede2265569640ae0af1c5520c8a66829"><div class="ttname"><a href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">armnnDeserializer::ToDataLayout</a></div><div class="ttdeci">armnn::DataLayout ToDataLayout(armnnSerializer::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00463">Deserializer.cpp:463</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_aede2265569640ae0af1c5520c8a66829"><div class="ttname"><a href="namespacearmnn_deserializer.html#aede2265569640ae0af1c5520c8a66829">armnnDeserializer::ToDataLayout</a></div><div class="ttdeci">armnn::DataLayout ToDataLayout(armnnSerializer::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00466">Deserializer.cpp:466</a></div></div> <div class="ttc" id="anamespacearmnn_html_a1cfaa710db2a54673b21d2ea2da757c8a0986d137604183312e6d3599578bc6cd"><div class="ttname"><a href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a0986d137604183312e6d3599578bc6cd">armnn::UnaryOperation::Sin</a></div><div class="ttdeci">@ Sin</div></div> <div class="ttc" id="anamespacearmnn_html_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a></div><div class="ttdeci">int LayerBindingId</div><div class="ttdoc">Type of identifiers for bindable layers (inputs, outputs).</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00309">Types.hpp:309</a></div></div> <div class="ttc" id="anamespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b">armnn::ActivationFunction::Linear</a></div><div class="ttdeci">@ Linear</div></div> +<div class="ttc" id="anamespacearmnn_html_a75ca90884e15396a70b0cb722a877b4a"><div class="ttname"><a href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4a">armnn::ScatterNdFunction</a></div><div class="ttdeci">ScatterNdFunction</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00500">Types.hpp:500</a></div></div> <div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::DepthwiseConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00694">Descriptors.hpp:694</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Convolution3dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00629">Descriptors.hpp:629</a></div></div> <div class="ttc" id="astructarmnn_1_1_activation_descriptor_html_af10fa7883e3579950f477bee92a64844"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.html#af10fa7883e3579950f477bee92a64844">armnn::ActivationDescriptor::m_Function</a></div><div class="ttdeci">ActivationFunction m_Function</div><div class="ttdoc">The activation function to use (Sigmoid, TanH, Linear, ReLu, BoundedReLu, SoftReLu,...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00059">Descriptors.hpp:59</a></div></div> @@ -4364,17 +4421,19 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_gather_descriptor_html_a35d11c7d509d1adbae1ae01c58394a7f"><div class="ttname"><a href="structarmnn_1_1_gather_descriptor.html#a35d11c7d509d1adbae1ae01c58394a7f">armnn::GatherDescriptor::m_Axis</a></div><div class="ttdeci">int32_t m_Axis</div><div class="ttdoc">The axis in params to gather indices from.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00981">Descriptors.hpp:981</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Convolution3dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00641">Descriptors.hpp:641</a></div></div> <div class="ttc" id="astructarmnn_1_1_space_to_batch_nd_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.html">armnn::SpaceToBatchNdDescriptor</a></div><div class="ttdoc">A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01043">Descriptors.hpp:1043</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a920251d49a8f32085d458ba23f776800"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a920251d49a8f32085d458ba23f776800">armnnDeserializer::IDeserializer::DeserializerImpl::GetNormalizationDescriptor</a></div><div class="ttdeci">static armnn::NormalizationDescriptor GetNormalizationDescriptor(NormalizationDescriptorPtr normalizationDescriptor, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02950">Deserializer.cpp:2950</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a920251d49a8f32085d458ba23f776800"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a920251d49a8f32085d458ba23f776800">armnnDeserializer::IDeserializer::DeserializerImpl::GetNormalizationDescriptor</a></div><div class="ttdeci">static armnn::NormalizationDescriptor GetNormalizationDescriptor(NormalizationDescriptorPtr normalizationDescriptor, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02972">Deserializer.cpp:2972</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::Convolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00572">Descriptors.hpp:572</a></div></div> <div class="ttc" id="aclassarmnn_1_1_permutation_vector_html"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00314">Types.hpp:314</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html">armnn::Convolution3dDescriptor</a></div><div class="ttdoc">A Convolution3dDescriptor for the Convolution3dLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00588">Descriptors.hpp:588</a></div></div> <div class="ttc" id="astructarmnn_1_1_reshape_descriptor_html_a1178f4dafdda81f59c15145ec327f7d9"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.html#a1178f4dafdda81f59c15145ec327f7d9">armnn::ReshapeDescriptor::m_TargetShape</a></div><div class="ttdeci">TensorShape m_TargetShape</div><div class="ttdoc">Target shape value.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01039">Descriptors.hpp:1039</a></div></div> <div class="ttc" id="aclassarmnn_1_1_exception_html"><div class="ttname"><a href="classarmnn_1_1_exception.html">armnn::Exception</a></div><div class="ttdoc">Base class for all ArmNN exceptions so that users can filter to just those.</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00046">Exceptions.hpp:46</a></div></div> +<div class="ttc" id="anamespacearmnn_html_a75ca90884e15396a70b0cb722a877b4aaec211f7c20af43e742bf2570c3cb84f9"><div class="ttname"><a href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aaec211f7c20af43e742bf2570c3cb84f9">armnn::ScatterNdFunction::Add</a></div><div class="ttdeci">@ Add</div></div> <div class="ttc" id="astructarmnn_1_1_quantized_lstm_input_params_html_a31da1ead6794dd64571afdd0b6efc771"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">armnn::QuantizedLstmInputParams::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.html#l00034">QuantizedLstmParams.hpp:34</a></div></div> <div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::TransposeConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01479">Descriptors.hpp:1479</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_ada48fd59da09885ff0c4273b303c28f5"><div class="ttname"><a href="namespacearmnn_deserializer.html#ada48fd59da09885ff0c4273b303c28f5">armnnDeserializer::ToScatterNdFunction</a></div><div class="ttdeci">armnn::ScatterNdFunction ToScatterNdFunction(armnnSerializer::ScatterNdFunction function)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00527">Deserializer.cpp:527</a></div></div> <div class="ttc" id="anamespacearmnn_deserializer_html_abd8bee7fb9b86485a60bc7ee05114270"><div class="ttname"><a href="namespacearmnn_deserializer.html#abd8bee7fb9b86485a60bc7ee05114270">armnnDeserializer::TensorRawPtrVector</a></div><div class="ttdeci">std::vector< TensorRawPtr > TensorRawPtrVector</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.html#l00028">Deserializer.hpp:28</a></div></div> <div class="ttc" id="anamespacearmnn_html_a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f"><div class="ttname"><a href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a></div><div class="ttdeci">@ NearestNeighbor</div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_ac17b9b154461bfa49ff7ade08f3c4bdf"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac17b9b154461bfa49ff7ade08f3c4bdf">armnnDeserializer::IDeserializer::DeserializerImpl::GetPooling2dDescriptor</a></div><div class="ttdeci">static armnn::Pooling2dDescriptor GetPooling2dDescriptor(Pooling2dDescriptor pooling2dDescriptor, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02361">Deserializer.cpp:2361</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_ac17b9b154461bfa49ff7ade08f3c4bdf"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ac17b9b154461bfa49ff7ade08f3c4bdf">armnnDeserializer::IDeserializer::DeserializerImpl::GetPooling2dDescriptor</a></div><div class="ttdeci">static armnn::Pooling2dDescriptor GetPooling2dDescriptor(Pooling2dDescriptor pooling2dDescriptor, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02383">Deserializer.cpp:2383</a></div></div> <div class="ttc" id="aclassarmnn_1_1_base_tensor_html_a8aeddebdcf02e1832b22203c08a6b678"><div class="ttname"><a href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">const TensorInfo & GetInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00297">Tensor.hpp:297</a></div></div> <div class="ttc" id="a_parser_helper_8hpp_html"><div class="ttname"><a href="_parser_helper_8hpp.html">ParserHelper.hpp</a></div></div> <div class="ttc" id="astructarmnn_1_1_quantized_lstm_input_params_html_a8c0f6d48705f40c5590dde09be262222"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.html#a8c0f6d48705f40c5590dde09be262222">armnn::QuantizedLstmInputParams::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensor * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.html#l00046">QuantizedLstmParams.hpp:46</a></div></div> @@ -4385,7 +4444,7 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="anamespacearmnn_html_ac4f8557279754ed7b3f749d55b0e3047add4fe0cc913f704600b97d1f5dd285de"><div class="ttname"><a href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047add4fe0cc913f704600b97d1f5dd285de">armnn::BinaryOperation::Power</a></div><div class="ttdeci">@ Power</div></div> <div class="ttc" id="a_deserializer_8cpp_html_aa6fd9c6c98bdd08620d75cac3a2e17e6"><div class="ttname"><a href="_deserializer_8cpp.html#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a></div><div class="ttdeci">#define CHECK_CONST_TENSOR_SIZE(CONST_TENSOR_SIZE, TENSOR_SIZE)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00175">Deserializer.cpp:175</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling3d_descriptor_html_a83ca447892f460dabaa2f87d3dc3db61"><div class="ttname"><a href="structarmnn_1_1_pooling3d_descriptor.html#a83ca447892f460dabaa2f87d3dc3db61">armnn::Pooling3dDescriptor::m_PadFront</a></div><div class="ttdeci">uint32_t m_PadFront</div><div class="ttdoc">Padding front value in the depth dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00483">Descriptors.hpp:483</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_af7bb02c61c6a5663121da024b7e042e8"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af7bb02c61c6a5663121da024b7e042e8">armnnDeserializer::IDeserializer::DeserializerImpl::GetLstmDescriptor</a></div><div class="ttdeci">static armnn::LstmDescriptor GetLstmDescriptor(LstmDescriptorPtr lstmDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l03285">Deserializer.cpp:3285</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_af7bb02c61c6a5663121da024b7e042e8"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af7bb02c61c6a5663121da024b7e042e8">armnnDeserializer::IDeserializer::DeserializerImpl::GetLstmDescriptor</a></div><div class="ttdeci">static armnn::LstmDescriptor GetLstmDescriptor(LstmDescriptorPtr lstmDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l03307">Deserializer.cpp:3307</a></div></div> <div class="ttc" id="anamespacearmnn_html_a1cfaa710db2a54673b21d2ea2da757c8"><div class="ttname"><a href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8">armnn::UnaryOperation</a></div><div class="ttdeci">UnaryOperation</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00125">Types.hpp:125</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00574">Descriptors.hpp:574</a></div></div> <div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_html_aa43409f9b457352c95c89f20ce5d844d"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.html#aa43409f9b457352c95c89f20ce5d844d">armnn::QLstmDescriptor::m_OutputIntermediateScale</a></div><div class="ttdeci">float m_OutputIntermediateScale</div><div class="ttdoc">Output intermediate quantization scale.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01432">Descriptors.hpp:1432</a></div></div> @@ -4393,8 +4452,9 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="aclassarmnn_1_1_tensor_info_html_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00200">Tensor.hpp:200</a></div></div> <div class="ttc" id="anamespacearmnn_html_a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021"><div class="ttname"><a href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a></div><div class="ttdeci">@ Average</div></div> <div class="ttc" id="astructarmnn_1_1_detection_post_process_descriptor_html_a7e2f87544b8bc7e497e1dec8d3ca4055"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html#a7e2f87544b8bc7e497e1dec8d3ca4055">armnn::DetectionPostProcessDescriptor::m_DetectionsPerClass</a></div><div class="ttdeci">uint32_t m_DetectionsPerClass</div><div class="ttdoc">Detections per classes, used in Regular NMS.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00749">Descriptors.hpp:749</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_scatter_nd_layer_html"><div class="ttname"><a href="classarmnn_1_1_scatter_nd_layer.html">armnn::ScatterNdLayer</a></div><div class="ttdoc">This layer represents a ScatterNd operator.</div><div class="ttdef"><b>Definition:</b> <a href="_scatter_nd_layer_8hpp_source.html#l00014">ScatterNdLayer.hpp:14</a></div></div> <div class="ttc" id="astructarmnn_1_1_detection_post_process_descriptor_html_aa61510cbd529870182e918ac6e8b9d72"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html#aa61510cbd529870182e918ac6e8b9d72">armnn::DetectionPostProcessDescriptor::m_ScaleH</a></div><div class="ttdeci">float m_ScaleH</div><div class="ttdoc">Center size encoding scale height.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00765">Descriptors.hpp:765</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a0bab2006e8fafc4a7fd02efa536f2828"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a0bab2006e8fafc4a7fd02efa536f2828">armnnDeserializer::IDeserializer::DeserializerImpl::LoadGraphFromBinary</a></div><div class="ttdeci">static GraphPtr LoadGraphFromBinary(const uint8_t *binaryContent, size_t len)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00877">Deserializer.cpp:877</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_a0bab2006e8fafc4a7fd02efa536f2828"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#a0bab2006e8fafc4a7fd02efa536f2828">armnnDeserializer::IDeserializer::DeserializerImpl::LoadGraphFromBinary</a></div><div class="ttdeci">static GraphPtr LoadGraphFromBinary(const uint8_t *binaryContent, size_t len)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00899">Deserializer.cpp:899</a></div></div> <div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div><div class="ttdeci">@ Signed32</div></div> <div class="ttc" id="anamespacearmnn_html_a1cfaa710db2a54673b21d2ea2da757c8ab95a01ffffa8fcdd2a9af961937c097c"><div class="ttname"><a href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8ab95a01ffffa8fcdd2a9af961937c097c">armnn::UnaryOperation::Ceil</a></div><div class="ttdeci">@ Ceil</div></div> <div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_html"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer.html">armnnDeserializer::IDeserializer</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_deserializer_8hpp_source.html#l00027">IDeserializer.hpp:27</a></div></div> @@ -4422,7 +4482,7 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_resize_descriptor_html_adcf5037208faac36c0788239a073f75c"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#adcf5037208faac36c0788239a073f75c">armnn::ResizeDescriptor::m_TargetWidth</a></div><div class="ttdeci">uint32_t m_TargetWidth</div><div class="ttdoc">Target width value.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01007">Descriptors.hpp:1007</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling3d_descriptor_html_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling3d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">armnn::Pooling3dDescriptor::m_PoolHeight</a></div><div class="ttdeci">uint32_t m_PoolHeight</div><div class="ttdoc">Pooling height value.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00489">Descriptors.hpp:489</a></div></div> <div class="ttc" id="anamespacearmnn_html_a2da4db0140d1a6dc69c9c82e9ef5379ea103aa83df42877d5f9baeafdbf620b55"><div class="ttname"><a href="namespacearmnn.html#a2da4db0140d1a6dc69c9c82e9ef5379ea103aa83df42877d5f9baeafdbf620b55">armnn::LogicalBinaryOperation::LogicalAnd</a></div><div class="ttdeci">@ LogicalAnd</div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a948b8c615ff06defa3b80d2352259ff2"><div class="ttname"><a href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">armnnDeserializer::ToTensorInfo</a></div><div class="ttdeci">armnn::TensorInfo ToTensorInfo(TensorRawPtr tensorPtr)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00654">Deserializer.cpp:654</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a948b8c615ff06defa3b80d2352259ff2"><div class="ttname"><a href="namespacearmnn_deserializer.html#a948b8c615ff06defa3b80d2352259ff2">armnnDeserializer::ToTensorInfo</a></div><div class="ttdeci">armnn::TensorInfo ToTensorInfo(TensorRawPtr tensorPtr)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00676">Deserializer.cpp:676</a></div></div> <div class="ttc" id="astructarmnn_1_1_instance_normalization_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::InstanceNormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00871">Descriptors.hpp:871</a></div></div> <div class="ttc" id="a_transpose_8hpp_html"><div class="ttname"><a href="_transpose_8hpp.html">Transpose.hpp</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.html">armnn::LstmDescriptor</a></div><div class="ttdoc">An LstmDescriptor for the LstmLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01102">Descriptors.hpp:1102</a></div></div> @@ -4456,12 +4516,14 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_html_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.html#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::QLstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable CIFG (coupled input & forget gate).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01418">Descriptors.hpp:1418</a></div></div> <div class="ttc" id="aclassarmnn_1_1_i_input_slot_html_ac8591a782840b802efd266f2743efe2e"><div class="ttname"><a href="classarmnn_1_1_i_input_slot.html#ac8591a782840b802efd266f2743efe2e">armnn::IInputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo tensorInfo)=0</div><div class="ttdoc">Sets the TensorInfo for this InputSlot.</div></div> <div class="ttc" id="astructarmnn_1_1_elementwise_binary_descriptor_html_a7e4ece533ef2cb0f251e11c47a17371c"><div class="ttname"><a href="structarmnn_1_1_elementwise_binary_descriptor.html#a7e4ece533ef2cb0f251e11c47a17371c">armnn::ElementwiseBinaryDescriptor::m_Operation</a></div><div class="ttdeci">BinaryOperation m_Operation</div><div class="ttdoc">Specifies the elementwiseBinary operation to execute.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00125">Descriptors.hpp:125</a></div></div> +<div class="ttc" id="anamespacearmnn_html_a75ca90884e15396a70b0cb722a877b4aa06933067aafd48425d67bcb01bba5cb6"><div class="ttname"><a href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aa06933067aafd48425d67bcb01bba5cb6">armnn::ScatterNdFunction::Update</a></div><div class="ttdeci">@ Update</div></div> <div class="ttc" id="anamespacearmnn_html_ac4f8557279754ed7b3f749d55b0e3047aa1d0ec6d56f8833a078b5a7ac4caf2d4"><div class="ttname"><a href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aa1d0ec6d56f8833a078b5a7ac4caf2d4">armnn::BinaryOperation::Minimum</a></div><div class="ttdeci">@ Minimum</div></div> <div class="ttc" id="anamespacearmnn_deserializer_html_a6713b8a83104db317823b5367b195d2e"><div class="ttname"><a href="namespacearmnn_deserializer.html#a6713b8a83104db317823b5367b195d2e">armnnDeserializer::Pooling3dDescriptor</a></div><div class="ttdeci">const armnnSerializer::Pooling3dDescriptor * Pooling3dDescriptor</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.html#l00022">Deserializer.hpp:22</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">armnn::Convolution3dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation along y axis.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00649">Descriptors.hpp:649</a></div></div> <div class="ttc" id="astructarmnn_1_1_origins_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_origins_descriptor.html">armnn::OriginsDescriptor</a></div><div class="ttdoc">An OriginsDescriptor for the ConcatLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00201">Descriptors.hpp:201</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_ab03e6e1514f74427916c892f473fe04c"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#ab03e6e1514f74427916c892f473fe04c">armnn::LstmInputParams::m_ProjectionWeights</a></div><div class="ttdeci">const ConstTensor * m_ProjectionWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00055">LstmParams.hpp:55</a></div></div> -<div class="ttc" id="astructarmnn_1_1_fully_connected_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::FullyConnectedDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdoc">Get the number of inputs.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00474">Descriptors.cpp:474</a></div></div> +<div class="ttc" id="anamespacearmnn_html_a75ca90884e15396a70b0cb722a877b4aa6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.html#a75ca90884e15396a70b0cb722a877b4aa6a061313d22e51e0f25b7cd4dc065233">armnn::ScatterNdFunction::Max</a></div><div class="ttdeci">@ Max</div></div> +<div class="ttc" id="astructarmnn_1_1_fully_connected_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::FullyConnectedDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdoc">Get the number of inputs.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00475">Descriptors.cpp:475</a></div></div> <div class="ttc" id="anamespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559">armnn::ActivationFunction::ReLu</a></div><div class="ttdeci">@ ReLu</div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_a31da1ead6794dd64571afdd0b6efc771"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#a31da1ead6794dd64571afdd0b6efc771">armnn::LstmInputParams::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00041">LstmParams.hpp:41</a></div></div> <div class="ttc" id="aclassarmnn_1_1_tensor_info_html_abe8889e8150beef5fd204b2d87b49298"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">armnn::TensorInfo::SetShape</a></div><div class="ttdeci">void SetShape(const TensorShape &newShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00195">Tensor.hpp:195</a></div></div> @@ -4478,6 +4540,7 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html_a5164336f6a1b15be0d434a6bbf7289da"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html#a5164336f6a1b15be0d434a6bbf7289da">armnn::Convolution3dDescriptor::m_StrideZ</a></div><div class="ttdeci">uint32_t m_StrideZ</div><div class="ttdoc">Stride value when proceeding through input for the depth dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00645">Descriptors.hpp:645</a></div></div> <div class="ttc" id="a_quantized_lstm_params_8hpp_html"><div class="ttname"><a href="_quantized_lstm_params_8hpp.html">QuantizedLstmParams.hpp</a></div></div> <div class="ttc" id="astructarmnn_1_1_detection_post_process_descriptor_html_a7ed9bc7c26df67d274d5dd4cd83adf0f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html#a7ed9bc7c26df67d274d5dd4cd83adf0f">armnn::DetectionPostProcessDescriptor::m_UseRegularNms</a></div><div class="ttdeci">bool m_UseRegularNms</div><div class="ttdoc">Use Regular NMS.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00757">Descriptors.hpp:757</a></div></div> +<div class="ttc" id="astructarmnn_1_1_scatter_nd_descriptor_html_a2beb2331d0aff8e24d17f16cca34784c"><div class="ttname"><a href="structarmnn_1_1_scatter_nd_descriptor.html#a2beb2331d0aff8e24d17f16cca34784c">armnn::ScatterNdDescriptor::m_Function</a></div><div class="ttdeci">ScatterNdFunction m_Function</div><div class="ttdoc">Specify if the function is update, add, sub, max or min.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01719">Descriptors.hpp:1719</a></div></div> <div class="ttc" id="anamespacearmnn_html_a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a></div><div class="ttdeci">@ Max</div></div> <div class="ttc" id="anamespacearmnn_deserializer_html_a68b76ee033fdd629404369171c3d4f90"><div class="ttname"><a href="namespacearmnn_deserializer.html#a68b76ee033fdd629404369171c3d4f90">armnnDeserializer::ConstTensorRawPtr</a></div><div class="ttdeci">const armnnSerializer::ConstTensor * ConstTensorRawPtr</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.html#l00018">Deserializer.hpp:18</a></div></div> <div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_html_af8f724af7210b52529216feefa993c98"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.html#af8f724af7210b52529216feefa993c98">armnn::QLstmDescriptor::m_HiddenStateScale</a></div><div class="ttdeci">float m_HiddenStateScale</div><div class="ttdoc">Hidden State quantization scale.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01436">Descriptors.hpp:1436</a></div></div> @@ -4485,7 +4548,7 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_normalization_descriptor_html_a8526ea7cf860d8e7f8340e9f9354f9f0"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.html#a8526ea7cf860d8e7f8340e9f9354f9f0">armnn::NormalizationDescriptor::m_K</a></div><div class="ttdeci">float m_K</div><div class="ttdoc">Kappa value used for the across channel normalization equation.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00803">Descriptors.hpp:803</a></div></div> <div class="ttc" id="anamespacearmnn_html_a1cfaa710db2a54673b21d2ea2da757c8a1e34af023adeb7d5f484f8eb4b9826b6"><div class="ttname"><a href="namespacearmnn.html#a1cfaa710db2a54673b21d2ea2da757c8a1e34af023adeb7d5f484f8eb4b9826b6">armnn::UnaryOperation::Abs</a></div><div class="ttdeci">@ Abs</div></div> <div class="ttc" id="astructarmnn_1_1_lstm_descriptor_html_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.html#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01150">Descriptors.hpp:1150</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_ab3dff510bec873d3e4ffe5cdfa71f1cd"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ab3dff510bec873d3e4ffe5cdfa71f1cd">armnnDeserializer::IDeserializer::DeserializerImpl::GetBaseLayer</a></div><div class="ttdeci">static LayerBaseRawPtr GetBaseLayer(const GraphPtr &graphPtr, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00285">Deserializer.cpp:285</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_ab3dff510bec873d3e4ffe5cdfa71f1cd"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ab3dff510bec873d3e4ffe5cdfa71f1cd">armnnDeserializer::IDeserializer::DeserializerImpl::GetBaseLayer</a></div><div class="ttdeci">static LayerBaseRawPtr GetBaseLayer(const GraphPtr &graphPtr, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00286">Deserializer.cpp:286</a></div></div> <div class="ttc" id="anamespacearmnn_html_abc05539fc6e7907f32ef0fb242e3b3b0a78d811e98514cd165dda532286610fd2"><div class="ttname"><a href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a78d811e98514cd165dda532286610fd2">armnn::ReduceOperation::Min</a></div><div class="ttdeci">@ Min</div></div> <div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_html_aaa88c7afbe8e8f777d05f99a2a540a99"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer.html#aaa88c7afbe8e8f777d05f99a2a540a99">armnnDeserializer::IDeserializer::CreateNetworkFromBinary</a></div><div class="ttdeci">armnn::INetworkPtr CreateNetworkFromBinary(const std::vector< uint8_t > &binaryContent)</div><div class="ttdoc">Create an input network from binary file contents.</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00057">Deserializer.cpp:57</a></div></div> <div class="ttc" id="aclassarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00329">Tensor.hpp:329</a></div></div> @@ -4493,8 +4556,8 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="aclassarmnn_1_1_i_connectable_layer_html"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00080">INetwork.hpp:80</a></div></div> <div class="ttc" id="aclassarmnn_1_1_i_input_slot_html"><div class="ttname"><a href="classarmnn_1_1_i_input_slot.html">armnn::IInputSlot</a></div><div class="ttdoc">An input connection slot for a layer.</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00025">INetwork.hpp:25</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling2d_descriptor_html_affb5b68b3eba3ed45a06c7cde7781962"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">armnn::Pooling2dDescriptor::m_OutputShapeRounding</a></div><div class="ttdeci">OutputShapeRounding m_OutputShapeRounding</div><div class="ttdoc">The rounding method for the output shape. (Floor, Ceiling).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00423">Descriptors.hpp:423</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_af2e5b4595b6abc056779ecd12bd271c2"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af2e5b4595b6abc056779ecd12bd271c2">armnnDeserializer::IDeserializer::DeserializerImpl::GetLayerName</a></div><div class="ttdeci">static std::string GetLayerName(const GraphPtr &graph, unsigned int index)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00441">Deserializer.cpp:441</a></div></div> -<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_ad04b4361ec1ded6b9334dae64c7c4579"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ad04b4361ec1ded6b9334dae64c7c4579">armnnDeserializer::IDeserializer::DeserializerImpl::GetUnidirectionalSequenceLstmDescriptor</a></div><div class="ttdeci">static armnn::UnidirectionalSequenceLstmDescriptor GetUnidirectionalSequenceLstmDescriptor(UnidirectionalSequenceLstmDescriptorPtr descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l03875">Deserializer.cpp:3875</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_af2e5b4595b6abc056779ecd12bd271c2"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#af2e5b4595b6abc056779ecd12bd271c2">armnnDeserializer::IDeserializer::DeserializerImpl::GetLayerName</a></div><div class="ttdeci">static std::string GetLayerName(const GraphPtr &graph, unsigned int index)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00444">Deserializer.cpp:444</a></div></div> +<div class="ttc" id="aclassarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl_html_ad04b4361ec1ded6b9334dae64c7c4579"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer_1_1_deserializer_impl.html#ad04b4361ec1ded6b9334dae64c7c4579">armnnDeserializer::IDeserializer::DeserializerImpl::GetUnidirectionalSequenceLstmDescriptor</a></div><div class="ttdeci">static armnn::UnidirectionalSequenceLstmDescriptor GetUnidirectionalSequenceLstmDescriptor(UnidirectionalSequenceLstmDescriptorPtr descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l03897">Deserializer.cpp:3897</a></div></div> <div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::TransposeConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01481">Descriptors.hpp:1481</a></div></div> <div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_html_ac81fb0e66dc623dc37c77f219f53a6d3"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.html#ac81fb0e66dc623dc37c77f219f53a6d3">armnn::QLstmDescriptor::m_CellClip</a></div><div class="ttdeci">float m_CellClip</div><div class="ttdoc">Clipping threshold value for the cell state.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01414">Descriptors.hpp:1414</a></div></div> <div class="ttc" id="astructarmnn_1_1_detection_post_process_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00713">Descriptors.hpp:713</a></div></div> @@ -4502,7 +4565,7 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_channel_shuffle_descriptor_html_a1953d00371489c32ebded5a42eabc0cf"><div class="ttname"><a href="structarmnn_1_1_channel_shuffle_descriptor.html#a1953d00371489c32ebded5a42eabc0cf">armnn::ChannelShuffleDescriptor::m_NumGroups</a></div><div class="ttdeci">uint32_t m_NumGroups</div><div class="ttdoc">Number of groups for the channel shuffle operation.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01578">Descriptors.hpp:1578</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution3d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Convolution3dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NDHWC, NCDHW).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00655">Descriptors.hpp:655</a></div></div> <div class="ttc" id="astructarmnn_1_1_l2_normalization_descriptor_html_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">armnn::L2NormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Used to avoid dividing by zero.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00822">Descriptors.hpp:822</a></div></div> -<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8ffca1e21bdfa7f945617acd606aac91"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">armnn::TensorInfo::SetConstant</a></div><div class="ttdeci">void SetConstant(const bool IsConstant=true)</div><div class="ttdoc">Marks the data corresponding to this tensor info as constant.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00514">Tensor.cpp:514</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8ffca1e21bdfa7f945617acd606aac91"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">armnn::TensorInfo::SetConstant</a></div><div class="ttdeci">void SetConstant(const bool IsConstant=true)</div><div class="ttdoc">Marks the data corresponding to this tensor info as constant.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00518">Tensor.cpp:518</a></div></div> <div class="ttc" id="anamespacearmnn_html_ac4f8557279754ed7b3f749d55b0e3047a43d11850893d2fe84a1e618121c1cc0a"><div class="ttname"><a href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a43d11850893d2fe84a1e618121c1cc0a">armnn::BinaryOperation::Div</a></div><div class="ttdeci">@ Div</div></div> <div class="ttc" id="anamespacearmnn_html_adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb"><div class="ttname"><a href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">armnn::OutputShapeRounding::Ceiling</a></div><div class="ttdeci">@ Ceiling</div></div> <div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d">armnn::DataType::Signed64</a></div><div class="ttdeci">@ Signed64</div></div> @@ -4514,13 +4577,14 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_batch_to_space_nd_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::BatchToSpaceNdDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00902">Descriptors.hpp:902</a></div></div> <div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00659">Descriptors.hpp:659</a></div></div> <div class="ttc" id="anamespacearmnn_html_a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5"><div class="ttname"><a href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">armnn::ComparisonOperation::Equal</a></div><div class="ttdeci">@ Equal</div></div> +<div class="ttc" id="astructarmnn_1_1_scatter_nd_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_scatter_nd_descriptor.html">armnn::ScatterNdDescriptor</a></div><div class="ttdoc">A ScatterNdDescriptor for the ScatterNdLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01679">Descriptors.hpp:1679</a></div></div> <div class="ttc" id="astructarmnn_1_1_reduce_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_reduce_descriptor.html">armnn::ReduceDescriptor</a></div><div class="ttdoc">A ReduceDescriptor for the REDUCE operators.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01538">Descriptors.hpp:1538</a></div></div> <div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_html_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::DepthwiseConvolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation factor value for width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00704">Descriptors.hpp:704</a></div></div> <div class="ttc" id="astructarmnn_1_1_batch_normalization_descriptor_html_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">armnn::BatchNormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Value to add to the variance. Used to avoid dividing by zero.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00841">Descriptors.hpp:841</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_descriptor_html_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.html#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01142">Descriptors.hpp:1142</a></div></div> <div class="ttc" id="anamespacearmnn_html_ad605d1661fa0d8c7fea651d82fbe11c9aa94d2fcabc6b001015aeddfa19266e6f"><div class="ttname"><a href="namespacearmnn.html#ad605d1661fa0d8c7fea651d82fbe11c9aa94d2fcabc6b001015aeddfa19266e6f">armnn::NormalizationAlgorithmMethod::LocalContrast</a></div><div class="ttdeci">@ LocalContrast</div><div class="ttdoc">Jarret 2009: Local Contrast Normalization.</div></div> <div class="ttc" id="astructarmnn_1_1_pooling3d_descriptor_html_acc978b36fd5d949bc781d7638e6e08b9"><div class="ttname"><a href="structarmnn_1_1_pooling3d_descriptor.html#acc978b36fd5d949bc781d7638e6e08b9">armnn::Pooling3dDescriptor::m_PoolDepth</a></div><div class="ttdeci">uint32_t m_PoolDepth</div><div class="ttdoc">Pooling depth value.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00491">Descriptors.hpp:491</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a3bb16a8c4f68fd2dfde128f1dc623571"><div class="ttname"><a href="namespacearmnn_deserializer.html#a3bb16a8c4f68fd2dfde128f1dc623571">armnnDeserializer::ToElementwiseBinaryOperation</a></div><div class="ttdeci">armnn::BinaryOperation ToElementwiseBinaryOperation(armnnSerializer::BinaryOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00576">Deserializer.cpp:576</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a3bb16a8c4f68fd2dfde128f1dc623571"><div class="ttname"><a href="namespacearmnn_deserializer.html#a3bb16a8c4f68fd2dfde128f1dc623571">armnnDeserializer::ToElementwiseBinaryOperation</a></div><div class="ttdeci">armnn::BinaryOperation ToElementwiseBinaryOperation(armnnSerializer::BinaryOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00598">Deserializer.cpp:598</a></div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html">armnn::LstmInputParams</a></div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00013">LstmParams.hpp:13</a></div></div> <div class="ttc" id="anamespacearmnn_html_a14d24d90ab4ba2956e92e27890ba4c91a74de3e45e4491e956e8dc18d841d9b00"><div class="ttname"><a href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91a74de3e45e4491e956e8dc18d841d9b00">armnn::PaddingMode::Reflect</a></div><div class="ttdeci">@ Reflect</div></div> <div class="ttc" id="astructarmnn_1_1_lstm_input_params_html_ad0b8c32bb5381f4cc999093ba3b98b43"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.html#ad0b8c32bb5381f4cc999093ba3b98b43">armnn::LstmInputParams::m_CellLayerNormWeights</a></div><div class="ttdeci">const ConstTensor * m_CellLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.html#l00059">LstmParams.hpp:59</a></div></div> @@ -4529,20 +4593,20 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div class="ttc" id="astructarmnn_1_1_quantized_lstm_input_params_html"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.html">armnn::QuantizedLstmInputParams</a></div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.html#l00013">QuantizedLstmParams.hpp:13</a></div></div> <div class="ttc" id="astructarmnn_1_1_check_location_html_ac1184445a1323e07e0da084a54aec535"><div class="ttname"><a href="structarmnn_1_1_check_location.html#ac1184445a1323e07e0da084a54aec535">armnn::CheckLocation::FileLine</a></div><div class="ttdeci">std::string FileLine() const</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00037">Exceptions.hpp:37</a></div></div> <div class="ttc" id="astructarmnn_1_1_tile_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_tile_descriptor.html">armnn::TileDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01640">Descriptors.hpp:1640</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_afa869143574c5885c6ad75f5a6f0333d"><div class="ttname"><a href="namespacearmnn_deserializer.html#afa869143574c5885c6ad75f5a6f0333d">armnnDeserializer::ToReduceOperation</a></div><div class="ttdeci">armnn::ReduceOperation ToReduceOperation(armnnSerializer::ReduceOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00544">Deserializer.cpp:544</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_afa869143574c5885c6ad75f5a6f0333d"><div class="ttname"><a href="namespacearmnn_deserializer.html#afa869143574c5885c6ad75f5a6f0333d">armnnDeserializer::ToReduceOperation</a></div><div class="ttdeci">armnn::ReduceOperation ToReduceOperation(armnnSerializer::ReduceOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00566">Deserializer.cpp:566</a></div></div> <div class="ttc" id="anamespacearmnn_html_a14d24d90ab4ba2956e92e27890ba4c91acb17869fe51048b5a5c4c6106551a255"><div class="ttname"><a href="namespacearmnn.html#a14d24d90ab4ba2956e92e27890ba4c91acb17869fe51048b5a5c4c6106551a255">armnn::PaddingMode::Constant</a></div><div class="ttdeci">@ Constant</div></div> <div class="ttc" id="astructarmnn_1_1_softmax_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.html">armnn::SoftmaxDescriptor</a></div><div class="ttdoc">A SoftmaxDescriptor for the SoftmaxLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00177">Descriptors.hpp:177</a></div></div> <div class="ttc" id="astructarmnn_1_1_pooling2d_descriptor_html_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">armnn::Pooling2dDescriptor::m_PoolType</a></div><div class="ttdeci">PoolingAlgorithm m_PoolType</div><div class="ttdoc">The pooling algorithm to use (Max. Average, L2).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00405">Descriptors.hpp:405</a></div></div> <div class="ttc" id="astructarmnn_1_1_quantized_lstm_input_params_html_a49e11acda22742cbaf6f1b259ead0d84"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.html#a49e11acda22742cbaf6f1b259ead0d84">armnn::QuantizedLstmInputParams::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.html#l00035">QuantizedLstmParams.hpp:35</a></div></div> <div class="ttc" id="astructarmnn_1_1_instance_normalization_descriptor_html_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">armnn::InstanceNormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Epsilon, small scalar value added to variance to avoid dividing by zero. Defaults to 1e-12f.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00869">Descriptors.hpp:869</a></div></div> <div class="ttc" id="a_deserializer_8cpp_html_ab90eef134463f7b44cd4c9cfb2529825"><div class="ttname"><a href="_deserializer_8cpp.html#ab90eef134463f7b44cd4c9cfb2529825">CHECK_GRAPH</a></div><div class="ttdeci">#define CHECK_GRAPH(GRAPH, LAYERS_INDEX)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l00184">Deserializer.cpp:184</a></div></div> -<div class="ttc" id="anamespacearmnn_deserializer_html_a63d3841a5ebb0a5ce572cfb4cb634376"><div class="ttname"><a href="namespacearmnn_deserializer.html#a63d3841a5ebb0a5ce572cfb4cb634376">armnnDeserializer::GetOriginsDescriptor</a></div><div class="ttdeci">const armnnSerializer::OriginsDescriptor * GetOriginsDescriptor(const armnnSerializer::SerializedGraph *graph, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02033">Deserializer.cpp:2033</a></div></div> +<div class="ttc" id="anamespacearmnn_deserializer_html_a63d3841a5ebb0a5ce572cfb4cb634376"><div class="ttname"><a href="namespacearmnn_deserializer.html#a63d3841a5ebb0a5ce572cfb4cb634376">armnnDeserializer::GetOriginsDescriptor</a></div><div class="ttdeci">const armnnSerializer::OriginsDescriptor * GetOriginsDescriptor(const armnnSerializer::SerializedGraph *graph, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.html#l02055">Deserializer.cpp:2055</a></div></div> <div class="ttc" id="astructarmnn_1_1_space_to_depth_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.html">armnn::SpaceToDepthDescriptor</a></div><div class="ttdoc">A SpaceToDepthDescriptor for the SpaceToDepthLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01075">Descriptors.hpp:1075</a></div></div> <div class="ttc" id="anamespacearmnn_deserializer_html_a7e75f47f676327bce37149932aa4a011"><div class="ttname"><a href="namespacearmnn_deserializer.html#a7e75f47f676327bce37149932aa4a011">armnnDeserializer::Pooling2dDescriptor</a></div><div class="ttdeci">const armnnSerializer::Pooling2dDescriptor * Pooling2dDescriptor</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.html#l00021">Deserializer.hpp:21</a></div></div> <div class="ttc" id="anamespacearmnn_html_abc05539fc6e7907f32ef0fb242e3b3b0a6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.html#abc05539fc6e7907f32ef0fb242e3b3b0a6a061313d22e51e0f25b7cd4dc065233">armnn::ReduceOperation::Max</a></div><div class="ttdeci">@ Max</div></div> <div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div><div class="ttdeci">@ NCHW</div></div> <div class="ttc" id="anamespacearmnn_deserializer_html_a38c1f8ba8e51364802669c968cf98ff5"><div class="ttname"><a href="namespacearmnn_deserializer.html#a38c1f8ba8e51364802669c968cf98ff5">armnnDeserializer::GraphPtr</a></div><div class="ttdeci">const armnnSerializer::SerializedGraph * GraphPtr</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.html#l00019">Deserializer.hpp:19</a></div></div> -<div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::DepthwiseConvolution2dDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdoc">Get the number of views/inputs.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00479">Descriptors.cpp:479</a></div></div> +<div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::DepthwiseConvolution2dDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdoc">Get the number of views/inputs.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00480">Descriptors.cpp:480</a></div></div> <div class="ttc" id="anamespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a></div><div class="ttdeci">@ Sigmoid</div></div> <div class="ttc" id="astructarmnn_1_1_space_to_depth_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::SpaceToDepthDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01095">Descriptors.hpp:1095</a></div></div> <div class="ttc" id="anamespacearmnn_html_a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a"><div class="ttname"><a href="namespacearmnn.html#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">armnn::ComparisonOperation::Greater</a></div><div class="ttdeci">@ Greater</div></div> @@ -4552,7 +4616,7 @@ $(document).ready(function(){initNavTree('_deserializer_8cpp_source.html',''); i <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li 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