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+<a href="#func-members">Functions</a>  </div>
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+<div class="title">TransposeConvolution2dTestImpl.hpp File Reference</div>  </div>
+</div><!--header-->
+<div class="contents">
+<div class="textblock"><code>#include &quot;<a class="el" href="_layer_test_result_8hpp_source.html">LayerTestResult.hpp</a>&quot;</code><br />
+<code>#include &lt;<a class="el" href="_resolve_type_8hpp_source.html">ResolveType.hpp</a>&gt;</code><br />
+<code>#include &lt;<a class="el" href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.html">armnn/backends/IBackendInternal.hpp</a>&gt;</code><br />
+<code>#include &lt;<a class="el" href="_workload_factory_8hpp_source.html">backendsCommon/WorkloadFactory.hpp</a>&gt;</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&lt;armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T  = armnn::ResolveType&lt;ArmnnType&gt;&gt; </td></tr>
+<tr class="memitem:aaab75bc035d8c526ed95a85893dfa8f4"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; T, 4 &gt;&#160;</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> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;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">&#160;</td></tr>
+<tr class="memitem:a1a0818bdef21773e58fc5d12e7aec147"><td class="memTemplParams" colspan="2">template&lt;armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T  = armnn::ResolveType&lt;ArmnnType&gt;&gt; </td></tr>
+<tr class="memitem:a1a0818bdef21773e58fc5d12e7aec147"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; T, 4 &gt;&#160;</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> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;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">&#160;</td></tr>
+<tr class="memitem:a64e49b8f5d6e3a5888444b6b83dd9f1f"><td class="memTemplParams" colspan="2">template&lt;armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T  = armnn::ResolveType&lt;ArmnnType&gt;&gt; </td></tr>
+<tr class="memitem:a64e49b8f5d6e3a5888444b6b83dd9f1f"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; T, 4 &gt;&#160;</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> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;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">&#160;</td></tr>
+<tr class="memitem:a4d0af564c539e193020d5375adfb1c03"><td class="memTemplParams" colspan="2">template&lt;armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T  = armnn::ResolveType&lt;ArmnnType&gt;&gt; </td></tr>
+<tr class="memitem:a4d0af564c539e193020d5375adfb1c03"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; T, 4 &gt;&#160;</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> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr>
+<tr class="separator:a4d0af564c539e193020d5375adfb1c03"><td class="memSeparator" colspan="2">&#160;</td></tr>
+<tr class="memitem:afe35eec6fc46b9526db341d374e93653"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; uint8_t, 4 &gt;&#160;</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> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, const <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr>
+<tr class="separator:afe35eec6fc46b9526db341d374e93653"><td class="memSeparator" colspan="2">&#160;</td></tr>
+</table>
+<h2 class="groupheader">Function Documentation</h2>
+<a id="a4d0af564c539e193020d5375adfb1c03"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#a4d0af564c539e193020d5375adfb1c03">&#9670;&nbsp;</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>&lt;T, 4&gt; MultiChannelTransposeConvolution2dTest </td>
+          <td>(</td>
+          <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</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> &amp;&#160;</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>&#160;</td>
+          <td class="paramname"><em>layout</em>&#160;</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>&#160;{</div><div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;    <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>&#160;</div><div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;    <span class="comment">// OIHW for NCHW; OHWI for NHWC</span></div><div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;    std::vector&lt;float&gt; inputData =</div><div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;    {</div><div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;        1.f, 2.f,</div><div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;        3.f, 4.f,</div><div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;    };</div><div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;</div><div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;    std::vector&lt;float&gt; weightsData =</div><div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;    {</div><div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;         1.f,  3.f,  5.f,</div><div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;         7.f,  9.f, 11.f,</div><div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;        13.f, 15.f, 17.f,</div><div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;</div><div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;         2.f,  4.f,  6.f,</div><div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;         8.f, 10.f, 12.f,</div><div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;        14.f, 16.f, 18.f</div><div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;    };</div><div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;</div><div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;    std::vector&lt;float&gt; biasesData = { -1.5f, -2.0f };</div><div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;</div><div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160; 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        6.0f,  8.0f,  26.0f, 18.0f, 22.0f,</div><div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;        18.0f, 26.0f,  70.0f, 46.0f, 58.0f,</div><div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;        22.0f, 28.0f,  66.0f, 38.0f, 46.0f,</div><div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;        40.0f, 46.0f, 108.0f, 62.0f, 70.0f</div><div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;    };</div><div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;</div><div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;    <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>&#160;    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>&#160;    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>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;    <span class="comment">// swizzle data if needed</span></div><div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;    <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>&#160;    {</div><div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;        SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);</div><div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;    }</div><div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;</div><div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;    <span class="keywordflow">return</span> TransposeConvolution2dTest&lt;ArmnnType, ArmnnBType&gt;(workloadFactory,</div><div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;                                                             memoryManager,</div><div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;                                                             descriptor,</div><div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;                                                             inputInfo,</div><div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;                                                             inputData,</div><div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;                                                             outputInfo,</div><div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;                                                             expectedOutputData,</div><div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;                                                             weightsInfo,</div><div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;                                                             weightsData,</div><div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;                                                             biasesInfo,</div><div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;                                                             biasesData);</div><div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;}</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">&#9670;&nbsp;</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>&lt;T, 4&gt; PaddedTransposeConvolution2dTest </td>
+          <td>(</td>
+          <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</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> &amp;&#160;</td>
+          <td class="paramname"><em>memoryManager</em>, </td>
+        </tr>
+        <tr>
+          <td class="paramkey"></td>
+          <td></td>
+          <td class="paramtype">bool&#160;</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>&#160;</td>
+          <td class="paramname"><em>layout</em>&#160;</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>&#160;{</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;    <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>&#160;</div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;    std::vector&lt;float&gt; inputData =</div><div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;    {</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;       1.f, 3.f, 2.f, 1.f,</div><div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;       1.f, 3.f, 3.f, 1.f,</div><div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;       2.f, 1.f, 1.f, 3.f,</div><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;       3.f, 2.f, 3.f, 3.f</div><div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;    };</div><div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;</div><div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;    std::vector&lt;float&gt; weightsData =</div><div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;    {</div><div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;        1.f, 2.f, 3.f,</div><div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;        0.f, 1.f, 0.f,</div><div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;        2.f, 1.f, 2.f</div><div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;    };</div><div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;</div><div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;    std::vector&lt;float&gt; biasesData = { 1.f };</div><div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;</div><div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;    std::vector&lt;float&gt; expectedOutputData =</div><div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;    {</div><div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;         21.f, 21.f,</div><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;         28.f, 27.f</div><div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;    };</div><div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;</div><div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;    <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;    {</div><div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;        <span class="comment">// apply bias to expected output data</span></div><div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;        std::transform(expectedOutputData.begin(), expectedOutputData.end(), expectedOutputData.begin(),</div><div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;                       [&amp;](<span class="keywordtype">float</span> f) -&gt; <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>&#160;    }</div><div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;</div><div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;    <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>&#160;    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>&#160;    descriptor.m_PadRight    = 2;</div><div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;    descriptor.m_PadTop      = 2;</div><div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;    descriptor.m_PadBottom   = 2;</div><div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;    descriptor.m_StrideX     = 1;</div><div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;    descriptor.m_StrideY     = 1;</div><div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;    descriptor.m_BiasEnabled = biasEnabled;</div><div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;    descriptor.m_DataLayout  = layout;</div><div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;</div><div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;    <span class="comment">// swizzle data if needed</span></div><div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;    <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>&#160;    {</div><div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;        SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);</div><div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;    }</div><div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;</div><div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;    <span class="keywordflow">return</span> TransposeConvolution2dTest&lt;ArmnnType, ArmnnBType&gt;(workloadFactory,</div><div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;                                                             memoryManager,</div><div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;                                                             descriptor,</div><div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;                                                             inputInfo,</div><div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;                                                             inputData,</div><div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;                                                             outputInfo,</div><div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;                                                             expectedOutputData,</div><div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;                                                             weightsInfo,</div><div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;                                                             weightsData,</div><div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;                                                             biasesInfo,</div><div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;                                                             biasesData);</div><div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;}</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">&#9670;&nbsp;</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>&lt;T, 4&gt; SimpleTransposeConvolution2dTest </td>
+          <td>(</td>
+          <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</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> &amp;&#160;</td>
+          <td class="paramname"><em>memoryManager</em>, </td>
+        </tr>
+        <tr>
+          <td class="paramkey"></td>
+          <td></td>
+          <td class="paramtype">bool&#160;</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>&#160;</td>
+          <td class="paramname"><em>layout</em>&#160;</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>&#160;{</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    <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>&#160;</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    std::vector&lt;float&gt; inputData =</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;    {</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;       1.f, 1.f, 1.f,</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;       1.f, 1.f, 1.f,</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;       1.f, 1.f, 1.f</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    };</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    std::vector&lt;float&gt; weightsData =</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;    {</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;        1.f, 2.f, 3.f,</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;        4.f, 5.f, 6.f,</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;        7.f, 8.f, 9.f</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;    };</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    std::vector&lt;float&gt; biasesData = { 1.f };</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;</div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;    std::vector&lt;float&gt; expectedOutputData =</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;    {</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;         1.f,  3.f,  6.f,  5.f,  3.f,</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;         5.f, 12.f, 21.f, 16.f,  9.f,</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;        12.f, 27.f, 45.f, 33.f, 18.f,</div><div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;        11.f, 24.f, 39.f, 28.f, 15.f,</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;         7.f, 15.f, 24.f, 17.f,  9.f</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    };</div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;    <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;    {</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;        <span class="comment">// apply bias to expected output data</span></div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        std::transform(expectedOutputData.begin(), expectedOutputData.end(), expectedOutputData.begin(),</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;                       [&amp;](<span class="keywordtype">float</span> f) -&gt; <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>&#160;    }</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;    <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>&#160;    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>&#160;    descriptor.m_StrideY     = 1;</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;    descriptor.m_BiasEnabled = biasEnabled;</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;    descriptor.m_DataLayout  = layout;</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;    <span class="comment">// swizzle data if needed</span></div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;    <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>&#160;    {</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;       SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;    }</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;    <span class="keywordflow">return</span> TransposeConvolution2dTest&lt;ArmnnType, ArmnnBType&gt;(workloadFactory,</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;                                                             memoryManager,</div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;                                                             descriptor,</div><div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;                                                             inputInfo,</div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;                                                             inputData,</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;                                                             outputInfo,</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;                                                             expectedOutputData,</div><div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;                                                             weightsInfo,</div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;                                                             weightsData,</div><div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;                                                             biasesInfo,</div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;                                                             biasesData);</div><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;}</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">&#9670;&nbsp;</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>&lt;T, 4&gt; StridedTransposeConvolution2dTest </td>
+          <td>(</td>
+          <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</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> &amp;&#160;</td>
+          <td class="paramname"><em>memoryManager</em>, </td>
+        </tr>
+        <tr>
+          <td class="paramkey"></td>
+          <td></td>
+          <td class="paramtype">bool&#160;</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>&#160;</td>
+          <td class="paramname"><em>layout</em>&#160;</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>&#160;{</div><div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;    <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>&#160;</div><div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;    std::vector&lt;float&gt; inputData =</div><div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;    {</div><div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;        1.f, 1.f, 1.f,</div><div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;        1.f, 1.f, 1.f,</div><div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;        1.f, 1.f, 1.f</div><div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;    };</div><div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;</div><div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;    std::vector&lt;float&gt; weightsData =</div><div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;    {</div><div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;        1.f, 2.f, 3.f,</div><div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;        4.f, 5.f, 6.f,</div><div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;        7.f, 8.f, 9.f</div><div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;    };</div><div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;</div><div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;    std::vector&lt;float&gt; biasesData = { 1.f };</div><div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;</div><div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;    std::vector&lt;float&gt; expectedOutputData =</div><div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;    {</div><div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;        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>&#160;        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>&#160;        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>&#160;        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>&#160;        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>&#160;        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>&#160;        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>&#160;    };</div><div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;</div><div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;    <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;    {</div><div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;        <span class="comment">// apply bias to expected output data</span></div><div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;        std::transform(expectedOutputData.begin(), expectedOutputData.end(), expectedOutputData.begin(),</div><div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;                    [&amp;](<span class="keywordtype">float</span> f) -&gt; <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>&#160;    }</div><div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;</div><div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;    <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>&#160;    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>&#160;    descriptor.m_StrideY     = 2;</div><div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;    descriptor.m_BiasEnabled = biasEnabled;</div><div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;    descriptor.m_DataLayout  = layout;</div><div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;</div><div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;    <span class="comment">// swizzle data if needed</span></div><div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;    <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>&#160;    {</div><div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;        SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);</div><div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;    }</div><div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;</div><div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;    <span class="keywordflow">return</span> TransposeConvolution2dTest&lt;ArmnnType, ArmnnBType&gt;(workloadFactory,</div><div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;                                                             memoryManager,</div><div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;                                                             descriptor,</div><div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;                                                             inputInfo,</div><div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;                                                             inputData,</div><div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;                                                             outputInfo,</div><div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;                                                             expectedOutputData,</div><div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;                                                             weightsInfo,</div><div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;                                                             weightsData,</div><div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;                                                             biasesInfo,</div><div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;                                                             biasesData);</div><div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;}</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">&#9670;&nbsp;</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>&lt;uint8_t, 4&gt; TransposeConvolution2dPerAxisQuantTest </td>
+          <td>(</td>
+          <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</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> &amp;&#160;</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>&#160;</td>
+          <td class="paramname"><em>layout</em>&#160;</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&lt; LayerDescriptor &gt;::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&lt; T, n &gt;::output</a>, <a class="el" href="_layer_test_result_8hpp_source.html#l00041">LayerTestResult&lt; T, n &gt;::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>&#160;{</div><div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;   <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>&#160;</div><div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;    <span class="keyword">const</span> std::vector&lt;float&gt; 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   std::vector&lt;uint8_t&gt; inputData =</div><div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;    {</div><div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;        12, 14,</div><div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;        16, 18</div><div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;    };</div><div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;</div><div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;    std::vector&lt;int8_t&gt; kernelData =</div><div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;    {</div><div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;         4, 12, 20,</div><div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;        28, 36, 44,</div><div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160; 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       <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>&#160;    }</div><div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;</div><div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160;    <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>&#160;    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>&#160;    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>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160;    std::unique_ptr&lt;ITensorHandle&gt; 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>&#160;    std::unique_ptr&lt;ITensorHandle&gt; 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>&#160;</div><div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160; 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   AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get());</div><div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;</div><div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;    std::unique_ptr&lt;IWorkload&gt; 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>&#160;    inputHandle-&gt;Allocate();</div><div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;    outputHandle-&gt;Allocate();</div><div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;</div><div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;    <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>&#160;</div><div class="line"><a name="l00654"></a><span class="lineno">  654</span>&#160; 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+<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&lt; ITensorHandle &gt; CreateTensorHandle(const TensorInfo &amp;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>
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+<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>
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+<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 &amp;tensorInfo, std::vector&lt; T &gt; &amp;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&lt; IWorkload &gt; CreateTransposeConvolution2d(const TransposeConvolution2dQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;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>
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