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diff --git a/20.02/_instance_normalization_end_to_end_test_impl_8cpp.xhtml b/20.02/_instance_normalization_end_to_end_test_impl_8cpp.xhtml new file mode 100644 index 0000000000..34fed3a17d --- /dev/null +++ b/20.02/_instance_normalization_end_to_end_test_impl_8cpp.xhtml @@ -0,0 +1,259 @@ +<!-- 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/InstanceNormalizationEndToEndTestImpl.cpp File 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init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_instance_normalization_end_to_end_test_impl_8cpp.xhtml','');}); +</script> +<div id="doc-content"> +<!-- window showing the filter options --> +<div id="MSearchSelectWindow" + onmouseover="return searchBox.OnSearchSelectShow()" + onmouseout="return searchBox.OnSearchSelectHide()" + onkeydown="return searchBox.OnSearchSelectKey(event)"> +</div> + +<!-- iframe showing the search results (closed by default) --> +<div id="MSearchResultsWindow"> +<iframe src="javascript:void(0)" frameborder="0" + name="MSearchResults" id="MSearchResults"> +</iframe> +</div> + +<div class="header"> + <div class="summary"> +<a href="#func-members">Functions</a> </div> + <div class="headertitle"> +<div class="title">InstanceNormalizationEndToEndTestImpl.cpp File Reference</div> </div> +</div><!--header--> +<div class="contents"> +<div class="textblock"><code>#include "<a class="el" href="_instance_normalization_end_to_end_test_impl_8hpp_source.xhtml">InstanceNormalizationEndToEndTestImpl.hpp</a>"</code><br /> +<code>#include "<a class="el" href="_end_to_end_test_impl_8hpp_source.xhtml">EndToEndTestImpl.hpp</a>"</code><br /> +<code>#include "<a class="el" href="_resolve_type_8hpp_source.xhtml">ResolveType.hpp</a>"</code><br /> +<code>#include <<a class="el" href="_permute_8hpp_source.xhtml">armnnUtils/Permute.hpp</a>></code><br /> +<code>#include <<a class="el" href="_data_layout_indexed_8hpp_source.xhtml">armnnUtils/DataLayoutIndexed.hpp</a>></code><br /> +<code>#include <<a class="el" href="_i_network_8hpp_source.xhtml">armnn/INetwork.hpp</a>></code><br /> +<code>#include <<a class="el" href="_data_layout_utils_8hpp_source.xhtml">backendsCommon/test/DataLayoutUtils.hpp</a>></code><br /> +<code>#include <<a class="el" href="_test_utils_8hpp_source.xhtml">test/TestUtils.hpp</a>></code><br /> +<code>#include <boost/test/unit_test.hpp></code><br /> +</div> +<p><a href="_instance_normalization_end_to_end_test_impl_8cpp_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:ae0bf53a96bad08ac5218f3c3747e5bed"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp.xhtml#ae0bf53a96bad08ac5218f3c3747e5bed">InstanceNormalizationNhwcEndToEndTest1</a> (const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > &<a class="el" href="_ref_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a>)</td></tr> +<tr class="separator:ae0bf53a96bad08ac5218f3c3747e5bed"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a120f2896c50cfa77409d16ef6b1628eb"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp.xhtml#a120f2896c50cfa77409d16ef6b1628eb">InstanceNormalizationNchwEndToEndTest1</a> (const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > &<a class="el" href="_ref_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a>)</td></tr> +<tr class="separator:a120f2896c50cfa77409d16ef6b1628eb"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a891c49c919ac2d170b7aa99e23e8871b"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp.xhtml#a891c49c919ac2d170b7aa99e23e8871b">InstanceNormalizationNhwcEndToEndTest2</a> (const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > &<a class="el" href="_ref_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a>)</td></tr> +<tr class="separator:a891c49c919ac2d170b7aa99e23e8871b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a3e262db2d488773b8824f73c4f6ab145"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp.xhtml#a3e262db2d488773b8824f73c4f6ab145">InstanceNormalizationNchwEndToEndTest2</a> (const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > &<a class="el" href="_ref_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a>)</td></tr> +<tr class="separator:a3e262db2d488773b8824f73c4f6ab145"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<h2 class="groupheader">Function Documentation</h2> +<a id="a120f2896c50cfa77409d16ef6b1628eb"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a120f2896c50cfa77409d16ef6b1628eb">◆ </a></span>InstanceNormalizationNchwEndToEndTest1()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void InstanceNormalizationNchwEndToEndTest1 </td> + <td>(</td> + <td class="paramtype">const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > & </td> + <td class="paramname"><em>defaultBackends</em></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp_source.xhtml#l00168">168</a> of file <a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp_source.xhtml">InstanceNormalizationEndToEndTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_cl_end_to_end_tests_8cpp_source.xhtml#l00175">BOOST_AUTO_TEST_CASE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> {</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> </div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> eps = 0.0001f;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> beta = 0.0f;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> gamma = 1.0f;</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape{2, 2, 2, 2};</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputTensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape{2, 2, 2, 2};</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputTensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> </div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  std::vector<float> inputData = std::vector<float>(</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  {</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  0.f, 1.f,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  0.f, 2.f,</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  0.f, 2.f,</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  0.f, 4.f,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> </div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  1.f, -1.f,</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  -1.f, 2.f,</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> </div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  -1.f, -2.f,</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  1.f, 4.f</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  });</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  std::vector<float> expectedOutputData = std::vector<float>(</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  {</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  0.f, -1.1470304f,</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  0.f, -0.22940612f,</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  0.f, -0.22940612f,</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  0.f, 1.6058424f,</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  0.99995005f, -0.7337929f,</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  -0.99995005f, 0.52413774f,</div><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">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  -0.99995005f, -1.1531031f,</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  0.99995005f, 1.3627582f</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> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> </div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  InstanceNormalizationEndToEnd(<a class="code" href="_cl_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a>,</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>,</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  inputTensorInfo,</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  outputTensorInfo,</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  inputData,</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  expectedOutputData,</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  gamma,</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  beta,</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  eps);</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> }</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#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></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="_cl_end_to_end_tests_8cpp_xhtml_ab59caffe2ee6be46c08766c055420f17"><div class="ttname"><a href="_cl_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a></div><div class="ttdeci">std::vector< armnn::BackendId > defaultBackends</div><div class="ttdef"><b>Definition:</b> <a href="_cl_end_to_end_tests_8cpp_source.xhtml#l00025">ClEndToEndTests.cpp:25</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="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a3e262db2d488773b8824f73c4f6ab145"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a3e262db2d488773b8824f73c4f6ab145">◆ </a></span>InstanceNormalizationNchwEndToEndTest2()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void InstanceNormalizationNchwEndToEndTest2 </td> + <td>(</td> + <td class="paramtype">const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > & </td> + <td class="paramname"><em>defaultBackends</em></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp_source.xhtml#l00310">310</a> of file <a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp_source.xhtml">InstanceNormalizationEndToEndTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_cl_end_to_end_tests_8cpp_source.xhtml#l00185">BOOST_AUTO_TEST_CASE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> {</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> </div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> eps = 0.0001f;</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> beta = 10.0f;</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> gamma = 2.0f;</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> </div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape{2, 2, 2, 2};</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape{2, 2, 2, 2};</div><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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputTensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputTensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> </div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  std::vector<float> inputData = std::vector<float>(</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="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  0.f, 1.f,</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  0.f, 2.f,</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span> </div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  0.f, 2.f,</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  0.f, 4.f,</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> </div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  1.f, -1.f,</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  -1.f, 2.f,</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 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  -1.f, -2.f,</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  1.f, 4.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> </div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  std::vector<float> expectedOutputData = std::vector<float>(</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  {</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  10.f, 7.7059393f,</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  10.f, 9.541187f,</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> </div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  10.f, 9.541187f,</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  10.f, 13.211685f,</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> </div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  11.9999f, 8.532414f,</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  8.0001f, 11.048275f,</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> </div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  8.0001f, 7.693794f,</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  11.9999f, 12.725516f</div><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> </div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  InstanceNormalizationEndToEnd(<a class="code" href="_cl_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a>,</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>,</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  inputTensorInfo,</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  outputTensorInfo,</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  inputData,</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  expectedOutputData,</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  gamma,</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  beta,</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  eps);</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> }</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#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></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="_cl_end_to_end_tests_8cpp_xhtml_ab59caffe2ee6be46c08766c055420f17"><div class="ttname"><a href="_cl_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a></div><div class="ttdeci">std::vector< armnn::BackendId > defaultBackends</div><div class="ttdef"><b>Definition:</b> <a href="_cl_end_to_end_tests_8cpp_source.xhtml#l00025">ClEndToEndTests.cpp:25</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="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="ae0bf53a96bad08ac5218f3c3747e5bed"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ae0bf53a96bad08ac5218f3c3747e5bed">◆ </a></span>InstanceNormalizationNhwcEndToEndTest1()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void InstanceNormalizationNhwcEndToEndTest1 </td> + <td>(</td> + <td class="paramtype">const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > & </td> + <td class="paramname"><em>defaultBackends</em></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp_source.xhtml#l00098">98</a> of file <a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp_source.xhtml">InstanceNormalizationEndToEndTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_cl_end_to_end_tests_8cpp_source.xhtml#l00170">BOOST_AUTO_TEST_CASE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> {</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> eps = 0.0001f;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> beta = 0.0f;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> gamma = 1.0f;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape{2, 2, 2, 2};</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputTensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape{2, 2, 2, 2};</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputTensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  std::vector<float> inputData = std::vector<float>(</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  {</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  0.f, 1.f,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  0.f, 2.f,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  0.f, 2.f,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  0.f, 4.f,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  1.f, -1.f,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  -1.f, 2.f,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  -1.f, -2.f,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  1.f, 4.f</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  });</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  std::vector<float> expectedOutputData = std::vector<float>(</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  {</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  0.f, -1.1470304f,</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  0.f, -0.22940612f,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  0.f, -0.22940612f,</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  0.f, 1.6058424f,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  0.99995005f, -0.7337929f,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  -0.99995005f, 0.52413774f,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  -0.99995005f, -1.1531031f,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  0.99995005f, 1.3627582f</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  });</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  InstanceNormalizationEndToEnd(<a class="code" href="_cl_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a>,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  inputTensorInfo,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  outputTensorInfo,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  inputData,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  expectedOutputData,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  gamma,</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  beta,</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  eps);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> }</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#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></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="_cl_end_to_end_tests_8cpp_xhtml_ab59caffe2ee6be46c08766c055420f17"><div class="ttname"><a href="_cl_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a></div><div class="ttdeci">std::vector< armnn::BackendId > defaultBackends</div><div class="ttdef"><b>Definition:</b> <a href="_cl_end_to_end_tests_8cpp_source.xhtml#l00025">ClEndToEndTests.cpp:25</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="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a891c49c919ac2d170b7aa99e23e8871b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a891c49c919ac2d170b7aa99e23e8871b">◆ </a></span>InstanceNormalizationNhwcEndToEndTest2()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void InstanceNormalizationNhwcEndToEndTest2 </td> + <td>(</td> + <td class="paramtype">const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > & </td> + <td class="paramname"><em>defaultBackends</em></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp_source.xhtml#l00239">239</a> of file <a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp_source.xhtml">InstanceNormalizationEndToEndTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_cl_end_to_end_tests_8cpp_source.xhtml#l00180">BOOST_AUTO_TEST_CASE()</a>.</p> +<div class="fragment"><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="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> </div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> eps = 0.0001f;</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> beta = 10.0f;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> gamma = 2.0f;</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> </div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape{2, 2, 2, 2};</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape{2, 2, 2, 2};</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputTensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputTensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> </div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  std::vector<float> inputData = std::vector<float>(</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  {</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  0.f, 1.f,</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  0.f, 2.f,</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> </div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  0.f, 2.f,</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  0.f, 4.f,</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> </div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  1.f, -1.f,</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  -1.f, 2.f,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> </div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  -1.f, -2.f,</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  1.f, 4.f</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  });</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> </div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  std::vector<float> expectedOutputData = std::vector<float>(</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  {</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  10.f, 7.7059393f,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  10.f, 9.541187f,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> </div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  10.f, 9.541187f,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  10.f, 13.211685f,</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> </div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  11.9999f, 8.532414f,</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  8.0001f, 11.048275f,</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> </div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  8.0001f, 7.693794f,</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  11.9999f, 12.725516f</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  });</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>  InstanceNormalizationEndToEnd(<a class="code" href="_cl_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a>,</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>,</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  inputTensorInfo,</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  outputTensorInfo,</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  inputData,</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  expectedOutputData,</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  gamma,</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  beta,</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  eps);</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> }</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#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></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="_cl_end_to_end_tests_8cpp_xhtml_ab59caffe2ee6be46c08766c055420f17"><div class="ttname"><a href="_cl_end_to_end_tests_8cpp.xhtml#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a></div><div class="ttdeci">std::vector< armnn::BackendId > defaultBackends</div><div class="ttdef"><b>Definition:</b> <a href="_cl_end_to_end_tests_8cpp_source.xhtml#l00025">ClEndToEndTests.cpp:25</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="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +</div><!-- fragment --> +</div> +</div> +</div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.xhtml">backendsCommon</a></li><li class="navelem"><a class="el" href="dir_28bfe507f7e135bdae07c2a6b7f66696.xhtml">test</a></li><li class="navelem"><a class="el" href="_instance_normalization_end_to_end_test_impl_8cpp.xhtml">InstanceNormalizationEndToEndTestImpl.cpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:14 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> +</div> +</body> +</html> |