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<a href="_transpose_convolution2d_end_to_end_test_impl_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_quantize_helper_8hpp.html">QuantizeHelper.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_permute_8hpp.html">armnnUtils/Permute.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_quantize_helper_8hpp.html">QuantizeHelper.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.html">ResolveType.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_common_test_utils_8hpp.html">backendsCommon/test/CommonTestUtils.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <map></span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> {</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> CreateTransposeConvolution2dNetwork(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">armnn::TransposeConvolution2dDescriptor</a>& descriptor,</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& inputInfo,</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& outputInfo,</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a>& weights,</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.html">armnn::Optional<armnn::ConstTensor></a>& biases)</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> {</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network(<a class="code" href="classarmnn_1_1_i_network.html#a706f7345af3f18f4b16e226a672214c6">INetwork::Create</a>());</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* input = network->AddInputLayer(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* transposeConvolution2d =</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  network->AddTransposeConvolution2dLayer(descriptor, weights, biases, <span class="stringliteral">"transposeConvolution2d"</span>);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* output = network->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, transposeConvolution2d, inputInfo, 0, 0);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(transposeConvolution2d, output, outputInfo, 0, 0);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> </div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">return</span> network;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> }</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> } <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="keyword">template</span><armnn::DataType ArmnnType, armnn::DataType ArmnnBType></div><div class="line"><a name="l00048"></a><span class="lineno"><a class="line" href="_transpose_convolution2d_end_to_end_test_impl_8hpp.html#a0349fffca581f50c343d517e709fb88e"> 48</a></span> <span class="keywordtype">void</span> <a class="code" href="_transpose_convolution2d_end_to_end_test_impl_8hpp.html#a0349fffca581f50c343d517e709fb88e">TransposeConvolution2dEndToEnd</a>(<span class="keyword">const</span> std::vector<armnn::BackendId>& backends,</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><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.html">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.html#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.html">TensorShape</a> inputShape = <a class="code" href="_common_test_utils_8cpp.html#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.html">TensorShape</a> outputShape = <a class="code" href="_common_test_utils_8cpp.html#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.html">TensorShape</a> weightsShape = <a class="code" href="_common_test_utils_8cpp.html#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.html">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.html">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.html">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.html">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.html">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.html#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.html#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.html#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.html#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.html#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.html#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.html#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.html#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.html#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.html">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.html#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.html#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnnUtils::Permute</a>(weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), 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.html#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnnUtils::Permute</a>(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), 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.html#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.html">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.html">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.html#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.html">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_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#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.html#l01111">Descriptors.hpp:1111</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">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.html#l00199">Tensor.hpp:199</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#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.html#l01109">Descriptors.hpp:1109</a></div></div>
<div class="ttc" id="classarmnn_1_1_permutation_vector_html"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00170">Types.hpp:170</a></div></div>
<div class="ttc" id="_permute_8hpp_html"><div class="ttname"><a href="_permute_8hpp.html">Permute.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_optional_html"><div class="ttname"><a href="classarmnn_1_1_optional.html">armnn::Optional< armnn::ConstTensor ></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="namespacearmnn_html_a0743ed5e860c316a20b68ca96301b411"><div class="ttname"><a href="namespacearmnn.html#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.html#l00066">ResolveType.hpp:66</a></div></div>
<div class="ttc" id="_resolve_type_8hpp_html"><div class="ttname"><a href="_resolve_type_8hpp.html">ResolveType.hpp</a></div></div>
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<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="_common_test_utils_8hpp_html"><div class="ttname"><a href="_common_test_utils_8hpp.html">CommonTestUtils.hpp</a></div></div>
<div class="ttc" id="_transpose_convolution2d_end_to_end_test_impl_8hpp_html_a0349fffca581f50c343d517e709fb88e"><div class="ttname"><a href="_transpose_convolution2d_end_to_end_test_impl_8hpp.html#a0349fffca581f50c343d517e709fb88e">TransposeConvolution2dEndToEnd</a></div><div class="ttdeci">void TransposeConvolution2dEndToEnd(const std::vector< armnn::BackendId > &backends, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_transpose_convolution2d_end_to_end_test_impl_8hpp_source.html#l00048">TransposeConvolution2dEndToEndTestImpl.hpp:48</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="classarmnn_1_1_i_network_html_a706f7345af3f18f4b16e226a672214c6"><div class="ttname"><a href="classarmnn_1_1_i_network.html#a706f7345af3f18f4b16e226a672214c6">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.html#l00048">Network.cpp:48</a></div></div>
<div class="ttc" id="_quantize_helper_8hpp_html"><div class="ttname"><a href="_quantize_helper_8hpp.html">QuantizeHelper.hpp</a></div></div>
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<div class="ttc" id="namespacearmnn_html_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.html#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.html#l00085">INetwork.hpp:85</a></div></div>
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<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="_test_utils_8cpp_html_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.html#l00012">TestUtils.cpp:12</a></div></div>
<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00048">Types.hpp:48</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="classarmnn_1_1_i_connectable_layer_html"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00061">INetwork.hpp:61</a></div></div>
<div class="ttc" id="namespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnn::LayerType::Permute</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_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00088">Tensor.hpp:88</a></div></div>
<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
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