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<div class="textblock"><code>#include "<a class="el" href="_quantize_helper_8hpp_source.xhtml">QuantizeHelper.hpp</a>"</code><br />
<code>#include <<a class="el" href="_permute_8hpp_source.xhtml">armnnUtils/Permute.hpp</a>></code><br />
<code>#include <<a class="el" href="_resolve_type_8hpp_source.xhtml">ResolveType.hpp</a>></code><br />
<code>#include <<a class="el" href="_common_test_utils_8hpp_source.xhtml">backendsCommon/test/CommonTestUtils.hpp</a>></code><br />
<code>#include <boost/test/unit_test.hpp></code><br />
<code>#include <map></code><br />
<code>#include <vector></code><br />
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<tr class="memitem:a0349fffca581f50c343d517e709fb88e"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType> </td></tr>
<tr class="memitem:a0349fffca581f50c343d517e709fb88e"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_transpose_convolution2d_end_to_end_test_impl_8hpp.xhtml#a0349fffca581f50c343d517e709fb88e">TransposeConvolution2dEndToEnd</a> (const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > &backends, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</td></tr>
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<h2 class="memtitle"><span class="permalink"><a href="#a0349fffca581f50c343d517e709fb88e">◆ </a></span>TransposeConvolution2dEndToEnd()</h2>
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<td class="memname">void TransposeConvolution2dEndToEnd </td>
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<td class="paramtype">const std::vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > & </td>
<td class="paramname"><em>backends</em>, </td>
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<td class="paramtype"><a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td>
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<p class="definition">Definition at line <a class="el" href="_transpose_convolution2d_end_to_end_test_impl_8hpp_source.xhtml#l00048">48</a> of file <a class="el" href="_transpose_convolution2d_end_to_end_test_impl_8hpp_source.xhtml">TransposeConvolution2dEndToEndTestImpl.hpp</a>.</p>
<p class="reference">References <a class="el" href="_tensor_8hpp_source.xhtml#l00187">TensorInfo::GetShape()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01254">TransposeConvolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01256">TransposeConvolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01248">TransposeConvolution2dDescriptor::m_PadBottom</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01242">TransposeConvolution2dDescriptor::m_PadLeft</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01244">TransposeConvolution2dDescriptor::m_PadRight</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01246">TransposeConvolution2dDescriptor::m_PadTop</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01250">TransposeConvolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01252">TransposeConvolution2dDescriptor::m_StrideY</a>, <a class="el" href="_common_test_utils_8cpp_source.xhtml#l00054">MakeTensorShape()</a>, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>, and <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnn::Permute</a>.</p>
<div class="fragment"><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">using</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">ResolveType<ArmnnType></a>;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batches = 1u;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 1u;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wInput = 3u;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hInput = wInput;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wOutput = 5u;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hOutput = wOutput;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> wWeights = 3u;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> hWeights = wWeights;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = <a class="code" href="_common_test_utils_8cpp.xhtml#a46d07efd379e728fc3df18a88ec878b0">MakeTensorShape</a>(batches, channels, hInput, wInput, dataLayout);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = <a class="code" href="_common_test_utils_8cpp.xhtml#a46d07efd379e728fc3df18a88ec878b0">MakeTensorShape</a>(batches, channels, hOutput, wOutput, dataLayout);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> weightsShape = <a class="code" href="_common_test_utils_8cpp.xhtml#a46d07efd379e728fc3df18a88ec878b0">MakeTensorShape</a>(batches, channels, hWeights, wWeights, dataLayout);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> qScale = IsQuantizedType<T>() ? 0.25f : 1.0f;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">const</span> int32_t qOffset = IsQuantizedType<T>() ? 50 : 0;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo(inputShape, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo(outputShape, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> weightsInfo(weightsShape, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> biasesInfo({ channels }, ArmnnBType, qScale * qScale, 0);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  std::vector<float> inputData =</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  1.f, 1.f, 1.f,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  1.f, 1.f, 1.f,</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  1.f, 1.f, 1.f</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  };</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  std::vector<float> weightsData =</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  {</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  1.f, 2.f, 3.f,</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  4.f, 5.f, 6.f,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  7.f, 8.f, 9.f</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  };</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  std::vector<float> biasesData = { 1.f };</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  std::vector<float> expectedOutputData =</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  {</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  6.f, 11.f, 6.f, 11.f, 6.f,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  11.f, 21.f, 11.f, 21.f, 11.f,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  6.f, 11.f, 6.f, 11.f, 6.f,</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  11.f, 21.f, 11.f, 21.f, 11.f,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  6.f, 11.f, 6.f, 11.f, 6.f</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  };</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">TransposeConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 1;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 1;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 1;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 1;</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="comment">// swizzle data if needed</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  {</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  constexpr <span class="keywordtype">size_t</span> dataTypeSize = <span class="keyword">sizeof</span>(float);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> nchwToNhwc = { 0, 3, 1, 2 };</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  std::vector<float> tmp(inputData.size());</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnnUtils::Permute</a>(inputInfo.GetShape(), nchwToNhwc, inputData.data(), tmp.data(), dataTypeSize);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  inputData = tmp;</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> </div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  tmp.resize(weightsData.size());</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnnUtils::Permute</a>(weightsInfo.GetShape(), nchwToNhwc, weightsData.data(), tmp.data(), dataTypeSize);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  weightsData = tmp;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> </div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  tmp.resize(expectedOutputData.size());</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnnUtils::Permute</a>(outputInfo.GetShape(), nchwToNhwc, expectedOutputData.data(), tmp.data(), dataTypeSize);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  expectedOutputData = tmp;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  }</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="comment">// quantize data</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  std::vector<T> qInputData = armnnUtils::QuantizedVector<T>(inputData, qScale, qOffset);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  std::vector<T> qWeightsData = armnnUtils::QuantizedVector<T>(weightsData, qScale, qOffset);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  std::vector<T> qExpectedOutputData = armnnUtils::QuantizedVector<T>(expectedOutputData, qScale, qOffset);</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keyword">using</span> BT = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">ResolveType<ArmnnBType></a>;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  std::vector<BT> qBiasesData = armnnUtils::QuantizedVector<BT>(biasesData, qScale * qScale, 0);</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> weights(weightsInfo, qWeightsData);</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> biases(biasesInfo, qBiasesData);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = CreateTransposeConvolution2dNetwork(descriptor,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  inputInfo,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  outputInfo,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  weights,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a>(biases));</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> </div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network),</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  { { 0, qInputData } },</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  { { 0, qExpectedOutputData } },</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  backends);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> }</div><div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01213">Descriptors.hpp:1213</a></div></div>
<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00270">Optional.hpp:270</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#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.xhtml#l01254">Descriptors.hpp:1254</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a0743ed5e860c316a20b68ca96301b411"><div class="ttname"><a href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a></div><div class="ttdeci">typename ResolveTypeImpl< DT >::Type ResolveType</div><div class="ttdef"><b>Definition:</b> <a href="_resolve_type_8hpp_source.xhtml#l00073">ResolveType.hpp:73</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::TransposeConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01248">Descriptors.hpp:1248</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnn::LayerType::Permute</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::TransposeConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01246">Descriptors.hpp:1246</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#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.xhtml#l01256">Descriptors.hpp:1256</a></div></div>
<div class="ttc" id="classarmnn_1_1_permutation_vector_xhtml"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00212">Types.hpp:212</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#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.xhtml#l01242">Descriptors.hpp:1242</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#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.xhtml#l01250">Descriptors.hpp:1250</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#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.xhtml#l01252">Descriptors.hpp:1252</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::TransposeConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01244">Descriptors.hpp:1244</a></div></div>
<div class="ttc" id="_common_test_utils_8cpp_xhtml_a46d07efd379e728fc3df18a88ec878b0"><div class="ttname"><a href="_common_test_utils_8cpp.xhtml#a46d07efd379e728fc3df18a88ec878b0">MakeTensorShape</a></div><div class="ttdeci">armnn::TensorShape MakeTensorShape(unsigned int batches, unsigned int channels, unsigned int height, unsigned int width, armnn::DataLayout layout)</div><div class="ttdef"><b>Definition:</b> <a href="_common_test_utils_8cpp_source.xhtml#l00054">CommonTestUtils.cpp:54</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
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