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author | Nikhil Raj <nikhil.raj@arm.com> | 2022-05-24 11:32:07 +0100 |
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committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-05-24 11:32:07 +0100 |
commit | 549b9600a6eaf0727fa084465a75f173edf8f381 (patch) | |
tree | 9c9b054417504444fff067b74eaa1811b74e6d06 /22.05/_batch_normalization_test_impl_8hpp.xhtml | |
parent | f4019872c1134c6fcc1d6993e5746f55c1e79208 (diff) | |
download | armnn-549b9600a6eaf0727fa084465a75f173edf8f381.tar.gz |
Update 22.05 Doxygen Docs after updates to main Readme
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I56711772406a41ff81fa136a5fb6c59c9b9cf504
Diffstat (limited to '22.05/_batch_normalization_test_impl_8hpp.xhtml')
-rw-r--r-- | 22.05/_batch_normalization_test_impl_8hpp.xhtml | 554 |
1 files changed, 554 insertions, 0 deletions
diff --git a/22.05/_batch_normalization_test_impl_8hpp.xhtml b/22.05/_batch_normalization_test_impl_8hpp.xhtml new file mode 100644 index 0000000000..54856be833 --- /dev/null +++ b/22.05/_batch_normalization_test_impl_8hpp.xhtml @@ -0,0 +1,554 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.hpp File Reference</title> +<link href="tabs.css" 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href="#func-members">Functions</a> </div> + <div class="headertitle"> +<div class="title">BatchNormalizationTestImpl.hpp File Reference</div> </div> +</div><!--header--> +<div class="contents"> +<div class="textblock"><code>#include <<a class="el" href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml">armnnTestUtils/LayerTestResult.hpp</a>></code><br /> +<code>#include <<a class="el" href="_half_8hpp_source.xhtml">Half.hpp</a>></code><br /> +<code>#include <<a class="el" href="_i_backend_internal_8hpp_source.xhtml">armnn/backends/IBackendInternal.hpp</a>></code><br /> +<code>#include <<a class="el" href="include_2armnn_2backends_2_workload_factory_8hpp_source.xhtml">armnn/backends/WorkloadFactory.hpp</a>></code><br /> +</div> +<p><a href="_batch_normalization_test_impl_8hpp_source.xhtml">Go to the source code of this file.</a></p> +<table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> +Functions</h2></td></tr> +<tr class="memitem:aa14c8756f74be01bacef39bcb85fa6e8"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8hpp.xhtml#aa14c8756f74be01bacef39bcb85fa6e8">BatchNormFloat32Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:aa14c8756f74be01bacef39bcb85fa6e8"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a4fcbc56f59eb2024f846912cbc92622b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8hpp.xhtml#a4fcbc56f59eb2024f846912cbc92622b">BatchNormFloat32NhwcTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:a4fcbc56f59eb2024f846912cbc92622b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a66306097520bd1b7a064f1b76cd4100b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< <a class="el" href="namespacearmnn.xhtml#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a>, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8hpp.xhtml#a66306097520bd1b7a064f1b76cd4100b">BatchNormFloat16Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:a66306097520bd1b7a064f1b76cd4100b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a22bfc4c479226d9b844e374d34cdbb21"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< <a class="el" href="namespacearmnn.xhtml#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a>, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8hpp.xhtml#a22bfc4c479226d9b844e374d34cdbb21">BatchNormFloat16NhwcTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:a22bfc4c479226d9b844e374d34cdbb21"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aa7076e3baf52b2283390d6241a1000f4"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8hpp.xhtml#aa7076e3baf52b2283390d6241a1000f4">BatchNormUint8Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:aa7076e3baf52b2283390d6241a1000f4"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a1d1b1f74e7df3f3097b94ba4f9d437cb"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8hpp.xhtml#a1d1b1f74e7df3f3097b94ba4f9d437cb">BatchNormUint8NhwcTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:a1d1b1f74e7df3f3097b94ba4f9d437cb"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aded633c2a9fd6c778c11af1604703843"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8hpp.xhtml#aded633c2a9fd6c778c11af1604703843">BatchNormInt16Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:aded633c2a9fd6c778c11af1604703843"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aa72195e53db1180ecce721ff83c19480"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8hpp.xhtml#aa72195e53db1180ecce721ff83c19480">BatchNormInt16NhwcTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:aa72195e53db1180ecce721ff83c19480"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a4f9bc9429cb69d93753208a42d25b637"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8hpp.xhtml#a4f9bc9429cb69d93753208a42d25b637">CompareBatchNormTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &refWorkloadFactory, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &refTensorHandleFactory)</td></tr> +<tr class="separator:a4f9bc9429cb69d93753208a42d25b637"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<h2 class="groupheader">Function Documentation</h2> +<a id="a22bfc4c479226d9b844e374d34cdbb21"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a22bfc4c479226d9b844e374d34cdbb21">◆ </a></span>BatchNormFloat16NhwcTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><<a class="el" href="namespacearmnn.xhtml#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a>, 4> BatchNormFloat16NhwcTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml#l00364">364</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml">BatchNormalizationTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> {</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> </div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 1, 3, 2, 2 };</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  std::vector<float> inputValues</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  {</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  1.f, 1.f,</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  4.f, 1.f,</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  4.f, 4.f,</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  2.f, 1.f,</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span> </div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  1.f, -2.f,</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  6.f, 4.f</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  };</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  {</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  1.f, 3.f,</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  4.f, 3.f,</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  4.f, 4.f,</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  2.f, 3.f,</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> </div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  1.f, 2.f,</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  6.f, 4.f</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  };</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> </div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::Float16>(</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  workloadFactory,</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  memoryManager,</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  tensorHandleFactory,</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  inputOutputShape,</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  inputValues,</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  expectedOutputValues,</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  0.f,</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  0,</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>);</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a66306097520bd1b7a064f1b76cd4100b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a66306097520bd1b7a064f1b76cd4100b">◆ </a></span>BatchNormFloat16Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><<a class="el" href="namespacearmnn.xhtml#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a>, 4> BatchNormFloat16Test </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml#l00316">316</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml">BatchNormalizationTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> {</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> </div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 1, 2, 3, 2 };</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  std::vector<float> inputValues</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  {</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  1.f, 4.f,</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  4.f, 2.f,</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  1.f, 6.f,</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> </div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  1.f, 1.f,</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  4.f, 1.f,</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  -2.f, 4.f</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  };</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  {</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  1.f, 4.f,</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  4.f, 2.f,</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  1.f, 6.f,</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  3.f, 3.f,</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  4.f, 3.f,</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  2.f, 4.f</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  };</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> </div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::Float16>(</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  workloadFactory,</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  memoryManager,</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  tensorHandleFactory,</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  inputOutputShape,</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  inputValues,</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  expectedOutputValues,</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  0.f,</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  0,</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>);</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a4fcbc56f59eb2024f846912cbc92622b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a4fcbc56f59eb2024f846912cbc92622b">◆ </a></span>BatchNormFloat32NhwcTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 4> BatchNormFloat32NhwcTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml#l00264">264</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml">BatchNormalizationTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_cl_layer_tests_8cpp_source.xhtml#l00027">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> {</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 1, 3, 2, 2 };</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  std::vector<float> inputValues</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  {</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  1.f, 1.f,</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  4.f, 1.f,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> </div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  4.f, 4.f,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  2.f, 1.f,</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>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  1.f, -2.f,</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  6.f, 4.f</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>  std::vector<float> expectedOutputValues</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="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  1.f, 3.f,</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  4.f, 3.f,</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  4.f, 4.f,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  2.f, 3.f,</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  1.f, 2.f,</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  6.f, 4.f</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  };</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span> </div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  workloadFactory,</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  memoryManager,</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  tensorHandleFactory,</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  inputOutputShape,</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  inputValues,</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  expectedOutputValues,</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  0.f,</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  0,</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aa14c8756f74be01bacef39bcb85fa6e8"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aa14c8756f74be01bacef39bcb85fa6e8">◆ </a></span>BatchNormFloat32Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 4> BatchNormFloat32Test </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml#l00216">216</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml">BatchNormalizationTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_cl_layer_tests_8cpp_source.xhtml#l00027">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> {</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 1, 2, 3, 2 };</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  std::vector<float> inputValues</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  {</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  1.f, 4.f,</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  4.f, 2.f,</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  1.f, 6.f,</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> </div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  1.f, 1.f,</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  4.f, 1.f,</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  -2.f, 4.f</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  };</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  {</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  1.f, 4.f,</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  4.f, 2.f,</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  1.f, 6.f,</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> </div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  3.f, 3.f,</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  4.f, 3.f,</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  2.f, 4.f</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  };</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  workloadFactory,</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  memoryManager,</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  tensorHandleFactory,</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  inputOutputShape,</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  inputValues,</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  expectedOutputValues,</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  0.f,</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  0,</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aa72195e53db1180ecce721ff83c19480"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aa72195e53db1180ecce721ff83c19480">◆ </a></span>BatchNormInt16NhwcTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><int16_t, 4> BatchNormInt16NhwcTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml#l00560">560</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml">BatchNormalizationTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><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="comment">// BatchSize: 1</span></div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <span class="comment">// Channels: 2</span></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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 1, 3, 2, 2 };</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  std::vector<float> inputValues</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  {</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  1.f, 1.f,</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  4.f, 1.f,</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span> </div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  4.f, 4.f,</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  2.f, 1.f,</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span> </div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  1.f, -2.f,</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  6.f, 4.f</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  };</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  std::vector<float> expectedOutputValues</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="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  1.f, 3.f,</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  4.f, 3.f,</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span> </div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  4.f, 4.f,</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  2.f, 3.f,</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span> </div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  1.f, 2.f,</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  6.f, 4.f</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>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  workloadFactory,</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  memoryManager,</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  tensorHandleFactory,</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  inputOutputShape,</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  inputValues,</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  expectedOutputValues,</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  1.f / 20.f,</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  50,</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>);</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aded633c2a9fd6c778c11af1604703843"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aded633c2a9fd6c778c11af1604703843">◆ </a></span>BatchNormInt16Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><int16_t, 4> BatchNormInt16Test </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml#l00512">512</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml">BatchNormalizationTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><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="comment">// BatchSize: 1</span></div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <span class="comment">// Width: 2</span></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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 1, 2, 3, 2 };</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  std::vector<float> inputValues</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>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  1.f, 4.f,</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  4.f, 2.f,</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  1.f, 6.f,</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span> </div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  1.f, 1.f,</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  4.f, 1.f,</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  -2.f, 4.f</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  };</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  {</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  1.f, 4.f,</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  4.f, 2.f,</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  1.f, 6.f,</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>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  3.f, 3.f,</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  4.f, 3.f,</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  2.f, 4.f</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  };</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">return</span> BatchNormTestImpl<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  workloadFactory,</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  memoryManager,</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  tensorHandleFactory,</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  inputOutputShape,</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  inputValues,</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  expectedOutputValues,</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  1.f / 20.f,</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  50,</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>);</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a1d1b1f74e7df3f3097b94ba4f9d437cb"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a1d1b1f74e7df3f3097b94ba4f9d437cb">◆ </a></span>BatchNormUint8NhwcTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><uint8_t, 4> BatchNormUint8NhwcTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml#l00464">464</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml">BatchNormalizationTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> {</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span> </div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 1, 3, 2, 2 };</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  std::vector<float> inputValues</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>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  1.f, 1.f,</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  4.f, 1.f,</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="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  4.f, 4.f,</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  2.f, 1.f,</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span> </div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  1.f, -2.f,</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  6.f, 4.f</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  };</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  {</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  1.f, 3.f,</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  4.f, 3.f,</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span> </div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  4.f, 4.f,</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  2.f, 3.f,</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span> </div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  1.f, 2.f,</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  6.f, 4.f</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  };</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span> </div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  workloadFactory,</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  memoryManager,</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  tensorHandleFactory,</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  inputOutputShape, inputValues, expectedOutputValues,</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  1.f/20.f, 50, <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>);</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aa7076e3baf52b2283390d6241a1000f4"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aa7076e3baf52b2283390d6241a1000f4">◆ </a></span>BatchNormUint8Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><uint8_t, 4> BatchNormUint8Test </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml#l00416">416</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml">BatchNormalizationTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00420"></a><span class="lineno"> 420</span> {</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span> </div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 1, 2, 3, 2 };</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  std::vector<float> inputValues</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  {</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  1.f, 4.f,</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  4.f, 2.f,</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  1.f, 6.f,</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span> </div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  1.f, 1.f,</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  4.f, 1.f,</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  -2.f, 4.f</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>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  {</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  1.f, 4.f,</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  4.f, 2.f,</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  1.f, 6.f,</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="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  3.f, 3.f,</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  4.f, 3.f,</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  2.f, 4.f</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  };</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">return</span> BatchNormTestImpl<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  workloadFactory,</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  memoryManager,</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  tensorHandleFactory,</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  inputOutputShape,</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  inputValues,</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  expectedOutputValues,</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  1.f / 20.f,</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  50,</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>);</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a4f9bc9429cb69d93753208a42d25b637"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a4f9bc9429cb69d93753208a42d25b637">◆ </a></span>CompareBatchNormTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 4> CompareBatchNormTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>refWorkloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>refTensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml#l00612">612</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.xhtml">BatchNormalizationTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e">armnn::BatchNormalization</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01559">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00196">TensorInfo::GetNumElements()</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00191">TensorInfo::GetShape()</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00345">BatchNormalizationQueueDescriptor::m_Beta</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00806">BatchNormalizationDescriptor::m_Eps</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00346">BatchNormalizationQueueDescriptor::m_Gamma</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00343">BatchNormalizationQueueDescriptor::m_Mean</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00066">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, and <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00344">BatchNormalizationQueueDescriptor::m_Variance</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_cl_layer_tests_8cpp_source.xhtml#l00027">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00618"></a><span class="lineno"> 618</span> {</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 2;</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 3;</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 5;</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 3;</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo;</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span> </div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = {batchSize, channels, height, width};</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> tensorShape[] = {channels};</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>  inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  tensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(1, tensorShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span> </div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  <span class="keyword">auto</span> input = MakeRandomTensor<float>(inputTensorInfo, 21312);</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span> </div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <span class="keyword">auto</span> mean = MakeRandomTensor<float>(tensorInfo, 123);</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  <span class="keyword">auto</span> variance = MakeRandomTensor<float>(tensorInfo, 234, 0.0f);</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <span class="keyword">auto</span> beta = MakeRandomTensor<float>(tensorInfo, 123);</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  <span class="keyword">auto</span> gamma = MakeRandomTensor<float>(tensorInfo, 345);</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>  std::vector<float> actualOutput(outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  std::vector<float> expectedOutput(outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span> </div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</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>  std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</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>  <a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">armnn::BatchNormalizationQueueDescriptor</a> data;</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> meanTensor(tensorInfo);</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> varianceTensor(tensorInfo);</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> betaTensor(tensorInfo);</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> gammaTensor(tensorInfo);</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>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&meanTensor, &mean[0]);</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&varianceTensor, &variance[0]);</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&betaTensor, &beta[0]);</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&gammaTensor, &gamma[0]);</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span> </div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  data.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a0ae7224f556b0d008d060f847c8f8901">m_Mean</a> = &meanTensor;</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  data.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a744e5178444c4b7bc4d516f4bbee8fcd">m_Variance</a> = &varianceTensor;</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  data.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#addb90eb7f4baa493fce64fdb7f140018">m_Beta</a> = &betaTensor;</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  data.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a96ee5ab4a7d2d8a4634b77d4eb9a949f">m_Gamma</a> = &gammaTensor;</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a> = 0.01f;</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span> </div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  <a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">armnn::BatchNormalizationQueueDescriptor</a> refData = data;</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> refInfo = info;</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get());</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get());</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span> </div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  std::unique_ptr<armnn::IWorkload> workload</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e">armnn::LayerType::BatchNormalization</a>, data, info);</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  std::unique_ptr<armnn::IWorkload> workloadRef</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e">armnn::LayerType::BatchNormalization</a>, refData, refInfo);</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span> </div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  inputHandle->Allocate();</div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  outputHandle->Allocate();</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  inputHandleRef->Allocate();</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  outputHandleRef->Allocate();</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span> </div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), input.data());</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandleRef.get(), input.data());</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span> </div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  workload->Execute();</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  workloadRef->PostAllocationConfigure();</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  workloadRef->Execute();</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span> </div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(expectedOutput.data(), outputHandleRef.get());</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>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a>(actualOutput,</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  expectedOutput,</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  outputHandle->GetShape(),</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>());</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00191">Tensor.hpp:191</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml_a744e5178444c4b7bc4d516f4bbee8fcd"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a744e5178444c4b7bc4d516f4bbee8fcd">armnn::BatchNormalizationQueueDescriptor::m_Variance</a></div><div class="ttdeci">const ConstTensorHandle * m_Variance</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00344">WorkloadData.hpp:344</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#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.xhtml#l00806">Descriptors.hpp:806</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00066">WorkloadData.hpp:66</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml_a96ee5ab4a7d2d8a4634b77d4eb9a949f"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a96ee5ab4a7d2d8a4634b77d4eb9a949f">armnn::BatchNormalizationQueueDescriptor::m_Gamma</a></div><div class="ttdeci">const ConstTensorHandle * m_Gamma</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00346">WorkloadData.hpp:346</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">armnn::BatchNormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00333">WorkloadData.hpp:333</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e">armnn::LayerType::BatchNormalization</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml_a0ae7224f556b0d008d060f847c8f8901"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a0ae7224f556b0d008d060f847c8f8901">armnn::BatchNormalizationQueueDescriptor::m_Mean</a></div><div class="ttdeci">const ConstTensorHandle * m_Mean</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00343">WorkloadData.hpp:343</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01559">WorkloadFactory.cpp:1559</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml_addb90eb7f4baa493fce64fdb7f140018"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#addb90eb7f4baa493fce64fdb7f140018">armnn::BatchNormalizationQueueDescriptor::m_Beta</a></div><div class="ttdeci">const ConstTensorHandle * m_Beta</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00345">WorkloadData.hpp:345</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00196">Tensor.hpp:196</a></div></div> +</div><!-- fragment --> +</div> 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