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+<div class="title">TransposeConvolution2dTestImpl.hpp File Reference</div> </div>
+</div><!--header-->
+<div class="contents">
+<div class="textblock"><code>#include "<a class="el" href="_layer_test_result_8hpp_source.html">LayerTestResult.hpp</a>"</code><br />
+<code>#include <<a class="el" href="_resolve_type_8hpp_source.html">ResolveType.hpp</a>></code><br />
+<code>#include <<a class="el" href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.html">armnn/backends/IBackendInternal.hpp</a>></code><br />
+<code>#include <<a class="el" href="_workload_factory_8hpp_source.html">backendsCommon/WorkloadFactory.hpp</a>></code><br />
+</div>
+<p><a href="_transpose_convolution2d_test_impl_8hpp_source.html">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:aaab75bc035d8c526ed95a85893dfa8f4"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr>
+<tr class="memitem:aaab75bc035d8c526ed95a85893dfa8f4"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_transpose_convolution2d_test_impl_8hpp.html#aaab75bc035d8c526ed95a85893dfa8f4">SimpleTransposeConvolution2dTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, bool biasEnabled, const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr>
+<tr class="separator:aaab75bc035d8c526ed95a85893dfa8f4"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a1a0818bdef21773e58fc5d12e7aec147"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr>
+<tr class="memitem:a1a0818bdef21773e58fc5d12e7aec147"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_transpose_convolution2d_test_impl_8hpp.html#a1a0818bdef21773e58fc5d12e7aec147">PaddedTransposeConvolution2dTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, bool biasEnabled, const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr>
+<tr class="separator:a1a0818bdef21773e58fc5d12e7aec147"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a64e49b8f5d6e3a5888444b6b83dd9f1f"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr>
+<tr class="memitem:a64e49b8f5d6e3a5888444b6b83dd9f1f"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_transpose_convolution2d_test_impl_8hpp.html#a64e49b8f5d6e3a5888444b6b83dd9f1f">StridedTransposeConvolution2dTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, bool biasEnabled, const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr>
+<tr class="separator:a64e49b8f5d6e3a5888444b6b83dd9f1f"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a4d0af564c539e193020d5375adfb1c03"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr>
+<tr class="memitem:a4d0af564c539e193020d5375adfb1c03"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_transpose_convolution2d_test_impl_8hpp.html#a4d0af564c539e193020d5375adfb1c03">MultiChannelTransposeConvolution2dTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr>
+<tr class="separator:a4d0af564c539e193020d5375adfb1c03"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:afe35eec6fc46b9526db341d374e93653"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_transpose_convolution2d_test_impl_8hpp.html#afe35eec6fc46b9526db341d374e93653">TransposeConvolution2dPerAxisQuantTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr>
+<tr class="separator:afe35eec6fc46b9526db341d374e93653"><td class="memSeparator" colspan="2"> </td></tr>
+</table>
+<h2 class="groupheader">Function Documentation</h2>
+<a id="a4d0af564c539e193020d5375adfb1c03"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#a4d0af564c539e193020d5375adfb1c03">◆ </a></span>MultiChannelTransposeConvolution2dTest()</h2>
+
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><T, 4> MultiChannelTransposeConvolution2dTest </td>
+ <td>(</td>
+ <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">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.html#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="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td>
+ <td class="paramname"><em>layout</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="_transpose_convolution2d_test_impl_8cpp_source.html#l00483">483</a> of file <a class="el" href="_transpose_convolution2d_test_impl_8cpp_source.html">TransposeConvolution2dTestImpl.cpp</a>.</p>
+
+<p class="reference">References <a class="el" href="_descriptors_8hpp_source.html#l01117">TransposeConvolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.html#l01119">TransposeConvolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l01113">TransposeConvolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l01115">TransposeConvolution2dDescriptor::m_StrideY</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p>
+<div class="fragment"><div class="line"><a name="l00487"></a><span class="lineno"> 487</span> {</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> </div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape = { 1, 1, 2, 2 };</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape = { 1, 2, 5, 5 };</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span> </div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <span class="comment">// OIHW for NCHW; OHWI for NHWC</span></div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> weightsShape = { 2, 1, 3, 3 };</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> biasesShape = { 2 };</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span> </div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo(inputShape, ArmnnType);</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo(outputShape, ArmnnType);</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> weightsInfo(weightsShape, ArmnnType);</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> biasesInfo(biasesShape, ArmnnBType);</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span> </div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  std::vector<float> inputData =</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>  1.f, 2.f,</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  3.f, 4.f,</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  };</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span> </div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  std::vector<float> weightsData =</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  {</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  1.f, 3.f, 5.f,</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  7.f, 9.f, 11.f,</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  13.f, 15.f, 17.f,</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span> </div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  2.f, 4.f, 6.f,</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  8.f, 10.f, 12.f,</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  14.f, 16.f, 18.f</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  };</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span> </div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  std::vector<float> biasesData = { -1.5f, -2.0f };</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span> </div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  std::vector<float> expectedOutputData =</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  {</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  -0.5f, 1.5f, 5.5f, 4.5f, 8.5f,</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  5.5f, 7.5f, 23.5f, 16.5f, 20.5f,</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  14.5f, 22.5f, 60.5f, 40.5f, 52.5f,</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  19.5f, 25.5f, 59.5f, 34.5f, 42.5f,</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  37.5f, 43.5f, 101.5f, 58.5f, 66.5f,</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span> </div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  0.0f, 2.0f, 8.0f, 6.0f, 10.0f,</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  6.0f, 8.0f, 26.0f, 18.0f, 22.0f,</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  18.0f, 26.0f, 70.0f, 46.0f, 58.0f,</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  22.0f, 28.0f, 66.0f, 38.0f, 46.0f,</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  40.0f, 46.0f, 108.0f, 62.0f, 70.0f</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> </div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">TransposeConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = layout;</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">// swizzle data if needed</span></div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  <span class="keywordflow">if</span> (layout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  {</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);</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> TransposeConvolution2dTest<ArmnnType, ArmnnBType>(workloadFactory,</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  memoryManager,</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  descriptor,</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  inputInfo,</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  inputData,</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  outputInfo,</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  expectedOutputData,</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  weightsInfo,</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  weightsData,</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  biasesInfo,</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  biasesData);</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::TransposeConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01119">Descriptors.hpp:1119</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01079">Descriptors.hpp:1079</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::TransposeConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01115">Descriptors.hpp:1115</a></div></div>
+<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::TransposeConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01113">Descriptors.hpp:1113</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::TransposeConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01117">Descriptors.hpp:1117</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
+</div><!-- fragment -->
+</div>
+</div>
+<a id="a1a0818bdef21773e58fc5d12e7aec147"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#a1a0818bdef21773e58fc5d12e7aec147">◆ </a></span>PaddedTransposeConvolution2dTest()</h2>
+
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><T, 4> PaddedTransposeConvolution2dTest </td>
+ <td>(</td>
+ <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">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.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td>
+ <td class="paramname"><em>memoryManager</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">bool </td>
+ <td class="paramname"><em>biasEnabled</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td>
+ <td class="paramname"><em>layout</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="_transpose_convolution2d_test_impl_8cpp_source.html#l00305">305</a> of file <a class="el" href="_transpose_convolution2d_test_impl_8cpp_source.html">TransposeConvolution2dTestImpl.cpp</a>.</p>
+
+<p class="reference">References <a class="el" href="_descriptors_8hpp_source.html#l01105">TransposeConvolution2dDescriptor::m_PadLeft</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p>
+<div class="fragment"><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> {</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batches = 1u;</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 1u;</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wInput = 4u;</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hInput = wInput;</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> </div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wOutput = 2u;</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hOutput = wOutput;</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wWeights = 3u;</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hWeights = wWeights;</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> </div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape = { batches, channels, hInput, wInput };</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape = { batches, channels, hOutput, wOutput };</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> weightsShape = { batches, channels, hWeights, wWeights };</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>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo(inputShape, ArmnnType);</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo(outputShape, ArmnnType);</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> weightsInfo(weightsShape, ArmnnType);</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> biasesInfo({ channels }, ArmnnBType);</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>  std::vector<float> inputData =</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>  1.f, 3.f, 2.f, 1.f,</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  1.f, 3.f, 3.f, 1.f,</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  2.f, 1.f, 1.f, 3.f,</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  3.f, 2.f, 3.f, 3.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> </div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  std::vector<float> weightsData =</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  {</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  1.f, 2.f, 3.f,</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  0.f, 1.f, 0.f,</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  2.f, 1.f, 2.f</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  };</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>  std::vector<float> biasesData = { 1.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>  std::vector<float> expectedOutputData =</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  {</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  21.f, 21.f,</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  28.f, 27.f</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  };</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> </div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="keywordflow">if</span> (biasEnabled)</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">// apply bias to expected output data</span></div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  std::transform(expectedOutputData.begin(), expectedOutputData.end(), expectedOutputData.begin(),</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  [&](<span class="keywordtype">float</span> f) -> <span class="keywordtype">float</span> { <span class="keywordflow">return</span> f + biasesData[0]; });</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  }</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>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">TransposeConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 2;</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  descriptor.m_PadRight = 2;</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  descriptor.m_PadTop = 2;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  descriptor.m_PadBottom = 2;</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  descriptor.m_StrideX = 1;</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  descriptor.m_StrideY = 1;</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  descriptor.m_BiasEnabled = biasEnabled;</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  descriptor.m_DataLayout = layout;</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="comment">// swizzle data if needed</span></div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordflow">if</span> (layout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</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>  SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  }</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> </div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keywordflow">return</span> TransposeConvolution2dTest<ArmnnType, ArmnnBType>(workloadFactory,</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  memoryManager,</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  descriptor,</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  inputInfo,</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  inputData,</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  outputInfo,</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  expectedOutputData,</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  weightsInfo,</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  weightsData,</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  biasesInfo,</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  biasesData);</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01079">Descriptors.hpp:1079</a></div></div>
+<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::TransposeConvolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01105">Descriptors.hpp:1105</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
+</div><!-- fragment -->
+</div>
+</div>
+<a id="aaab75bc035d8c526ed95a85893dfa8f4"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#aaab75bc035d8c526ed95a85893dfa8f4">◆ </a></span>SimpleTransposeConvolution2dTest()</h2>
+
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><T, 4> SimpleTransposeConvolution2dTest </td>
+ <td>(</td>
+ <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">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.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td>
+ <td class="paramname"><em>memoryManager</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">bool </td>
+ <td class="paramname"><em>biasEnabled</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td>
+ <td class="paramname"><em>layout</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="_transpose_convolution2d_test_impl_8cpp_source.html#l00218">218</a> of file <a class="el" href="_transpose_convolution2d_test_impl_8cpp_source.html">TransposeConvolution2dTestImpl.cpp</a>.</p>
+
+<p class="reference">References <a class="el" href="_descriptors_8hpp_source.html#l01113">TransposeConvolution2dDescriptor::m_StrideX</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p>
+<div class="fragment"><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> {</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</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>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batches = 1u;</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 1u;</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>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wInput = 3u;</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hInput = wInput;</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wOutput = 5u;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hOutput = wOutput;</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> </div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wWeights = 3u;</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hWeights = wWeights;</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape = { batches, channels, hInput, wInput };</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape = { batches, channels, hOutput, wOutput };</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> weightsShape = { batches, channels, hWeights, wWeights };</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> </div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo(inputShape, ArmnnType);</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo(outputShape, ArmnnType);</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> weightsInfo(weightsShape, ArmnnType);</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> biasesInfo({ channels }, ArmnnBType);</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>  std::vector<float> inputData =</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  {</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  1.f, 1.f, 1.f,</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  1.f, 1.f, 1.f,</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  1.f, 1.f, 1.f</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> </div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  std::vector<float> weightsData =</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  {</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  1.f, 2.f, 3.f,</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  4.f, 5.f, 6.f,</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  7.f, 8.f, 9.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> </div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  std::vector<float> biasesData = { 1.f };</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> </div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  std::vector<float> expectedOutputData =</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>  1.f, 3.f, 6.f, 5.f, 3.f,</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  5.f, 12.f, 21.f, 16.f, 9.f,</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  12.f, 27.f, 45.f, 33.f, 18.f,</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  11.f, 24.f, 39.f, 28.f, 15.f,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  7.f, 15.f, 24.f, 17.f, 9.f</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  };</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keywordflow">if</span> (biasEnabled)</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="comment">// apply bias to expected output data</span></div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  std::transform(expectedOutputData.begin(), expectedOutputData.end(), expectedOutputData.begin(),</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  [&](<span class="keywordtype">float</span> f) -> <span class="keywordtype">float</span> { <span class="keywordflow">return</span> f + biasesData[0]; });</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> </div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">TransposeConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  descriptor.m_StrideY = 1;</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  descriptor.m_BiasEnabled = biasEnabled;</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  descriptor.m_DataLayout = layout;</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">// swizzle data if needed</span></div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keywordflow">if</span> (layout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</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>  SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  }</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> </div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keywordflow">return</span> TransposeConvolution2dTest<ArmnnType, ArmnnBType>(workloadFactory,</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  memoryManager,</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  descriptor,</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  inputInfo,</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  inputData,</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  outputInfo,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  expectedOutputData,</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  weightsInfo,</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  weightsData,</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  biasesInfo,</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  biasesData);</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01079">Descriptors.hpp:1079</a></div></div>
+<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::TransposeConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01113">Descriptors.hpp:1113</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
+</div><!-- fragment -->
+</div>
+</div>
+<a id="a64e49b8f5d6e3a5888444b6b83dd9f1f"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#a64e49b8f5d6e3a5888444b6b83dd9f1f">◆ </a></span>StridedTransposeConvolution2dTest()</h2>
+
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><T, 4> StridedTransposeConvolution2dTest </td>
+ <td>(</td>
+ <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">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.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td>
+ <td class="paramname"><em>memoryManager</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">bool </td>
+ <td class="paramname"><em>biasEnabled</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td>
+ <td class="paramname"><em>layout</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="_transpose_convolution2d_test_impl_8cpp_source.html#l00394">394</a> of file <a class="el" href="_transpose_convolution2d_test_impl_8cpp_source.html">TransposeConvolution2dTestImpl.cpp</a>.</p>
+
+<p class="reference">References <a class="el" href="_descriptors_8hpp_source.html#l01113">TransposeConvolution2dDescriptor::m_StrideX</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p>
+<div class="fragment"><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> {</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> </div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batches = 1u;</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 1u;</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> </div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wInput = 3u;</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hInput = wInput;</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span> </div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wOutput = 7u;</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hOutput = wOutput;</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span> </div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wWeights = 3u;</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hWeights = wWeights;</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span> </div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape = { batches, channels, hInput, wInput };</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape = { batches, channels, hOutput, wOutput };</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> weightsShape = { batches, channels, hWeights, wWeights };</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> </div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo(inputShape, ArmnnType);</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo(outputShape, ArmnnType);</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> weightsInfo(weightsShape, ArmnnType);</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> biasesInfo({ channels }, ArmnnBType);</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span> </div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  std::vector<float> inputData =</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  {</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  1.f, 1.f, 1.f,</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  1.f, 1.f, 1.f,</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  1.f, 1.f, 1.f</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> </div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  std::vector<float> weightsData =</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  {</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  1.f, 2.f, 3.f,</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  4.f, 5.f, 6.f,</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  7.f, 8.f, 9.f</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  };</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  std::vector<float> biasesData = { 1.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> expectedOutputData =</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>  1.f, 2.f, 4.f, 2.f, 4.f, 2.f, 3.f,</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  4.f, 5.f, 10.f, 5.f, 10.f, 5.f, 6.f,</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  8.f, 10.f, 20.f, 10.f, 20.f, 10.f, 12.f,</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  4.f, 5.f, 10.f, 5.f, 10.f, 5.f, 6.f,</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  8.f, 10.f, 20.f, 10.f, 20.f, 10.f, 12.f,</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  4.f, 5.f, 10.f, 5.f, 10.f, 5.f, 6.f,</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  7.f, 8.f, 16.f, 8.f, 16.f, 8.f, 9.f</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  };</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span> </div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <span class="keywordflow">if</span> (biasEnabled)</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="comment">// apply bias to expected output data</span></div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  std::transform(expectedOutputData.begin(), expectedOutputData.end(), expectedOutputData.begin(),</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  [&](<span class="keywordtype">float</span> f) -> <span class="keywordtype">float</span> { <span class="keywordflow">return</span> f + biasesData[0]; });</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  }</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">TransposeConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  descriptor.m_StrideY = 2;</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  descriptor.m_BiasEnabled = biasEnabled;</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  descriptor.m_DataLayout = layout;</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span> </div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="comment">// swizzle data if needed</span></div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <span class="keywordflow">if</span> (layout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  {</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  }</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> </div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="keywordflow">return</span> TransposeConvolution2dTest<ArmnnType, ArmnnBType>(workloadFactory,</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  memoryManager,</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  descriptor,</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  inputInfo,</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  inputData,</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  outputInfo,</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  expectedOutputData,</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  weightsInfo,</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  weightsData,</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  biasesInfo,</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  biasesData);</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01079">Descriptors.hpp:1079</a></div></div>
+<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::TransposeConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01113">Descriptors.hpp:1113</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
+</div><!-- fragment -->
+</div>
+</div>
+<a id="afe35eec6fc46b9526db341d374e93653"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#afe35eec6fc46b9526db341d374e93653">◆ </a></span>TransposeConvolution2dPerAxisQuantTest()</h2>
+
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><uint8_t, 4> TransposeConvolution2dPerAxisQuantTest </td>
+ <td>(</td>
+ <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">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.html#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="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td>
+ <td class="paramname"><em>layout</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="_transpose_convolution2d_test_impl_8cpp_source.html#l00561">561</a> of file <a class="el" href="_transpose_convolution2d_test_impl_8cpp_source.html">TransposeConvolution2dTestImpl.cpp</a>.</p>
+
+<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.html#l01431">IWorkloadFactory::CreateTransposeConvolution2d()</a>, <a class="el" href="_descriptors_8hpp_source.html#l01117">TransposeConvolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.html#l01119">TransposeConvolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_workload_data_8hpp_source.html#l00049">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.html#l01113">TransposeConvolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l01115">TransposeConvolution2dDescriptor::m_StrideY</a>, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>, <a class="el" href="_layer_test_result_8hpp_source.html#l00040">LayerTestResult< T, n >::output</a>, <a class="el" href="_layer_test_result_8hpp_source.html#l00041">LayerTestResult< T, n >::outputExpected</a>, <a class="el" href="_data_layout_utils_8hpp_source.html#l00014">PermuteTensorNchwToNhwc()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::QAsymmU8</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::QSymmS8</a>, and <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p>
+
+<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.html#l01413">BOOST_AUTO_TEST_CASE()</a>.</p>
+<div class="fragment"><div class="line"><a name="l00565"></a><span class="lineno"> 565</span> {</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span> </div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> inputType = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>;</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> kernelType = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>;</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> biasType = <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>;</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span> </div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo ({ 1, 1, 2, 2 }, inputType, 0.50f, 10);</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo({ 1, 2, 5, 5 }, inputType, 0.50f, 10);</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span> </div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <span class="keyword">const</span> std::vector<float> quantScales{ 0.25f, 0.5f };</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantDimension = 0;</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span> </div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> kernelInfo({ 2, 1, 3, 3 }, kernelType, quantScales, quantDimension);</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span> </div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <span class="keyword">const</span> std::vector<float> biasQuantScales{ 0.125f, 0.25f };</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> biasInfo({ 2 }, biasType, biasQuantScales, quantDimension);</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span> </div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  std::vector<uint8_t> inputData =</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>  12, 14,</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  16, 18</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  };</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span> </div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  std::vector<int8_t> kernelData =</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>  4, 12, 20,</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  28, 36, 44,</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  52, 60, 68,</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>  4, 8, 12,</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  16, 20, 24,</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  28, 32, 36</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>  std::vector<int32_t> biasData = { -12, -8 };</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span> </div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  std::vector<uint8_t> expectedOutputData =</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  {</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  9, 13, 21, 19, 27,</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  21, 25, 57, 43, 51,</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  39, 55, 131, 91, 115,</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  49, 61, 129, 79, 95,</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  85, 97, 213, 127, 143,</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span> </div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  10, 14, 26, 22, 30,</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  22, 26, 62, 46, 54,</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  46, 62, 150, 102, 126,</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  54, 66, 142, 86, 102,</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  90, 102, 226, 134, 150</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  };</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span> </div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <span class="keywordflow">if</span> (layout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><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="_data_layout_utils_8hpp.html#a2f264435e93ad5aab7ac9e1dec4a4e93">PermuteTensorNchwToNhwc</a>(inputInfo, inputData);</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  <a class="code" href="_data_layout_utils_8hpp.html#a2f264435e93ad5aab7ac9e1dec4a4e93">PermuteTensorNchwToNhwc</a>(kernelInfo, kernelData);</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  <a class="code" href="_data_layout_utils_8hpp.html#a2f264435e93ad5aab7ac9e1dec4a4e93">PermuteTensorNchwToNhwc</a>(outputInfo, expectedOutputData);</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  }</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span> </div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">TransposeConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = layout;</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span> </div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  std::unique_ptr<ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputInfo);</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputInfo);</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span> </div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <a class="code" href="structarmnn_1_1_workload_info.html">WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.html">ScopedCpuTensorHandle</a> weightTensor(kernelInfo);</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.html">ScopedCpuTensorHandle</a> biasTensor(biasInfo);</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span> </div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&weightTensor, kernelData.data());</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&biasTensor, biasData.data());</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span> </div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_queue_descriptor.html">TransposeConvolution2dQueueDescriptor</a> queueDescriptor;</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a> = descriptor;</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  queueDescriptor.m_Weight = &weightTensor;</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  queueDescriptor.m_Bias = &biasTensor;</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span> </div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get());</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get());</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span> </div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  std::unique_ptr<IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a12cccba82124cc4993868a3173a65167">CreateTransposeConvolution2d</a>(queueDescriptor, workloadInfo);</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  inputHandle->Allocate();</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  outputHandle->Allocate();</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="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputData.data());</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span> </div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  ExecuteWorkload(*workload, memoryManager);</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span> </div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <a class="code" href="struct_layer_test_result.html">LayerTestResult<uint8_t, 4></a> ret(outputInfo);</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(ret.output.origin(), outputHandle.get());</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  ret.outputExpected = MakeTensor<uint8_t, 4>(outputInfo, expectedOutputData);</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span> </div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span> }</div><div class="ttc" id="_tensor_copy_utils_8cpp_html_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00019">TensorCopyUtils.cpp:19</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_queue_descriptor.html">armnn::TransposeConvolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00494">WorkloadData.hpp:494</a></div></div>
+<div class="ttc" id="_tensor_copy_utils_8cpp_html_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00009">TensorCopyUtils.cpp:9</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
+<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_html_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00049">WorkloadData.hpp:49</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div>
+<div class="ttc" id="struct_layer_test_result_html"><div class="ttname"><a href="struct_layer_test_result.html">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.html#l00029">LayerTestResult.hpp:29</a></div></div>
+<div class="ttc" id="_tensor_copy_utils_8cpp_html_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.html#l00014">TensorCopyUtils.cpp:14</a></div></div>
+<div class="ttc" id="structarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::TransposeConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01119">Descriptors.hpp:1119</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01079">Descriptors.hpp:1079</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::TransposeConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01115">Descriptors.hpp:1115</a></div></div>
+<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::TransposeConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01113">Descriptors.hpp:1113</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00032">Types.hpp:32</a></div></div>
+<div class="ttc" id="_data_layout_utils_8hpp_html_a2f264435e93ad5aab7ac9e1dec4a4e93"><div class="ttname"><a href="_data_layout_utils_8hpp.html#a2f264435e93ad5aab7ac9e1dec4a4e93">PermuteTensorNchwToNhwc</a></div><div class="ttdeci">void PermuteTensorNchwToNhwc(armnn::TensorInfo &tensorInfo, std::vector< T > &tensorData)</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_utils_8hpp_source.html#l00014">DataLayoutUtils.hpp:14</a></div></div>
+<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::TransposeConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01117">Descriptors.hpp:1117</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a12cccba82124cc4993868a3173a65167"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a12cccba82124cc4993868a3173a65167">armnn::IWorkloadFactory::CreateTransposeConvolution2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateTransposeConvolution2d(const TransposeConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01431">WorkloadFactory.cpp:1431</a></div></div>
+<div class="ttc" id="classarmnn_1_1_scoped_cpu_tensor_handle_html"><div class="ttname"><a href="classarmnn_1_1_scoped_cpu_tensor_handle.html">armnn::ScopedCpuTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.html#l00106">CpuTensorHandle.hpp:106</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
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