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+<a href="_pad_test_impl_8cpp.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> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_pad_test_impl_8hpp.html">PadTestImpl.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_quantize_helper_8hpp.html">QuantizeHelper.hpp</a>></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="_tensor_copy_utils_8hpp.html">backendsCommon/test/TensorCopyUtils.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_workload_test_utils_8hpp.html">backendsCommon/test/WorkloadTestUtils.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_tensor_helpers_8hpp.html">test/TensorHelpers.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="comment">//</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment">// Implementation templates</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment">//</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="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T></div><div class="line"><a name="l00020"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#a227a98a0681875f6a4af1b4e2154b1c0"> 20</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<T, 2></a> <a class="code" href="_pad_test_impl_8cpp.html#a2efccf857e77f59789d3c9c655943291">Pad2dTestCommon</a>(</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  int32_t qOffset,</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> customPaddingValue)</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> {</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  boost::ignore_unused(memoryManager);</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_tensor_shape.html">armnn::TensorShape</a> inputShape{ 3, 3 };</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_tensor_shape.html">armnn::TensorShape</a> outputShape{ 7, 7 };</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">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo(inputShape, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo(outputShape, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  std::vector<T> inputValues = armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="comment">// Height (3) x Width (3)</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  4, 8, 6,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  7, 4, 4,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  3, 2, 4</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  },</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  qScale, qOffset);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keyword">auto</span> p = customPaddingValue;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  std::vector<T> expectedOutputValues = armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  {</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  p, p, p, p, p, p, p,</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  p, p, p, p, p, p, p,</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  p, p, 4, 8, 6, p, p,</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  p, p, 7, 4, 4, p, p,</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  p, p, 3, 2, 4, p, p,</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  p, p, p, p, p, p, p,</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  p, p, p, p, p, p, p</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>  qScale, qOffset);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">auto</span> inputTensor = MakeTensor<T, 2>(inputTensorInfo, std::vector<T>(inputValues));</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="struct_layer_test_result.html">LayerTestResult<T, 2></a> result(outputTensorInfo);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  result.<a class="code" href="struct_layer_test_result.html#a73610ea6c776cc66e5a78dd842a39b8b">outputExpected</a> = MakeTensor<T, 2>(outputTensorInfo, std::vector<T>(expectedOutputValues));</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="structarmnn_1_1_pad_queue_descriptor.html">armnn::PadQueueDescriptor</a> descriptor;</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>  std::vector<std::pair<unsigned int, unsigned int>> padList;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  padList.push_back(std::pair<unsigned int, unsigned int>(2,2));</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  padList.push_back(std::pair<unsigned int, unsigned int>(2,2));</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>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pad_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a> = padList;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pad_descriptor.html#a410fa919f78af0f0f100bd1594eca4ab">m_PadValue</a> = customPaddingValue;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> info;</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#ab0c956e4a638d0a2777ecb71953f7e27">CreatePad</a>(descriptor, info);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  inputHandle->Allocate();</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  outputHandle->Allocate();</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &inputTensor[0][0]);</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>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  workload->Execute();</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>  <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&result.<a class="code" href="struct_layer_test_result.html#ac9d44d346bb7c89f7a7aa31d2bee947f">output</a>[0][0], outputHandle.get());</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordflow">return</span> result;</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> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T></div><div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#a106adefa1af15bdc68068403d7e93cd3"> 93</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<T, 3></a> <a class="code" href="_pad_test_impl_8cpp.html#a106adefa1af15bdc68068403d7e93cd3">Pad3dTestCommon</a>(</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  int32_t qOffset)</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> {</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  boost::ignore_unused(memoryManager);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputShape{ 2, 2, 2 };</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> outputShape{ 3, 5, 6 };</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo(inputShape, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo(outputShape, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  std::vector<T> inputValues = armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  {</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="comment">// Channel 0, Height (2) x Width (2)</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  0, 4,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  2, 5,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="comment">// Channel 1, Height (2) x Width (2)</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  6, 1,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  5, 2</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>  qScale, qOffset);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  std::vector<T> expectedOutputValues = armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  0, 0, 0, 4, 0, 0,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  0, 0, 2, 5, 0, 0,</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  0, 0, 6, 1, 0, 0,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  0, 0, 5, 2, 0, 0,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  0, 0, 0, 0, 0, 0,</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>  0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  0, 0, 0, 0, 0, 0</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  },</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  qScale, qOffset);</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>  <span class="keyword">auto</span> inputTensor = MakeTensor<T, 3>(inputTensorInfo, std::vector<T>(inputValues));</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> </div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="struct_layer_test_result.html">LayerTestResult<T, 3></a> result(outputTensorInfo);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  result.<a class="code" href="struct_layer_test_result.html#a73610ea6c776cc66e5a78dd842a39b8b">outputExpected</a> = MakeTensor<T, 3>(outputTensorInfo, std::vector<T>(expectedOutputValues));</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> </div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="structarmnn_1_1_pad_queue_descriptor.html">armnn::PadQueueDescriptor</a> descriptor;</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>  std::vector<std::pair<unsigned int, unsigned int>> PadList;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  PadList.push_back(std::pair<unsigned int, unsigned int>(0,1));</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  PadList.push_back(std::pair<unsigned int, unsigned int>(2,1));</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  PadList.push_back(std::pair<unsigned int, unsigned int>(2,2));</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> </div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pad_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a> = PadList;</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> info;</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#ab0c956e4a638d0a2777ecb71953f7e27">CreatePad</a>(descriptor, info);</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  inputHandle->Allocate();</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  outputHandle->Allocate();</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> </div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &inputTensor[0][0][0]);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  workload->Execute();</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&result.<a class="code" href="struct_layer_test_result.html#ac9d44d346bb7c89f7a7aa31d2bee947f">output</a>[0][0][0], outputHandle.get());</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> }</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T></div><div class="line"><a name="l00177"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#a878a628bade11abc79cf8160c518a244"> 177</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<T, 4></a> <a class="code" href="_pad_test_impl_8cpp.html#a878a628bade11abc79cf8160c518a244">Pad4dTestCommon</a>(</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  int32_t qOffset)</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> {</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  boost::ignore_unused(memoryManager);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputShape{ 2, 2, 3, 2 };</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> outputShape{ 4, 5, 7, 4 };</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo(inputShape, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo(outputShape, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  std::vector<T> inputValues = armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  {</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  0, 1,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  2, 3,</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  4, 5,</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  6, 7,</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  8, 9,</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  10, 11,</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="comment">// Batch 1, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  12, 13,</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  14, 15,</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  16, 17,</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="comment">// Batch 1, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  18, 19,</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  20, 21,</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  22, 23</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  },</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  qScale, qOffset);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> </div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  std::vector<T> expectedOutputValues = armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  {</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  0, 0, 0, 0,</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  0, 0, 0, 0,</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  0, 0, 0, 0,</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  0, 0, 0, 0,</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  0, 0, 0, 0,</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  0, 0, 0, 0,</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  0, 0, 0, 0,</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> </div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  0, 0, 0, 0,</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  0, 0, 0, 0,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  0, 0, 0, 0,</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  0, 0, 0, 0,</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  0, 0, 0, 0,</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  0, 0, 0, 0,</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  0, 0, 0, 0,</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  0, 0, 0, 0,</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  0, 0, 0, 0,</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  0, 0, 0, 0,</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  0, 0, 0, 0,</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  0, 0, 0, 0,</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  0, 0, 0, 0,</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  0, 0, 0, 0,</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  0, 0, 0, 0,</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  0, 0, 0, 0,</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  0, 0, 0, 0,</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  0, 0, 0, 0,</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  0, 0, 0, 0,</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  0, 0, 0, 0,</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  0, 0, 0, 0,</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> </div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  0, 0, 0, 0,</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  0, 0, 0, 0,</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  0, 0, 0, 0,</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  0, 0, 0, 0,</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  0, 0, 0, 0,</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  0, 0, 0, 0,</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  0, 0, 0, 0,</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> </div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  0, 0, 0, 0,</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  0, 0, 0, 0,</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  0, 0, 0, 0,</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  0, 0, 0, 0,</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  0, 0, 0, 0,</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  0, 0, 0, 0,</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  0, 0, 0, 0,</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> </div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  0, 0, 0, 0,</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  0, 0, 0, 0,</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  0, 0, 0, 0,</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  0, 0, 0, 0,</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  0, 0, 0, 0,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  0, 0, 0, 0,</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  0, 0, 0, 0,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  0, 0, 0, 0,</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  0, 0, 0, 0,</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  0, 0, 0, 0,</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  0, 0, 1, 0,</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  0, 2, 3, 0,</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  0, 4, 5, 0,</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  0, 0, 0, 0,</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> </div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  0, 0, 0, 0,</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  0, 0, 0, 0,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  0, 0, 0, 0,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  0, 6, 7, 0,</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  0, 8, 9, 0,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  0, 10, 11, 0,</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  0, 0, 0, 0,</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> </div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  0, 0, 0, 0,</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  0, 0, 0, 0,</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  0, 0, 0, 0,</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  0, 0, 0, 0,</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  0, 0, 0, 0,</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  0, 0, 0, 0,</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  0, 0, 0, 0,</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> </div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  0, 0, 0, 0,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  0, 0, 0, 0,</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  0, 0, 0, 0,</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  0, 0, 0, 0,</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  0, 0, 0, 0,</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  0, 0, 0, 0,</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  0, 0, 0, 0,</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span> </div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  0, 0, 0, 0,</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  0, 0, 0, 0,</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  0, 0, 0, 0,</div><div class="line"><a name="l00307"></a><span class="lineno"> 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0</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  },</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  qScale, qOffset);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keyword">auto</span> inputTensor = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>(inputValues));</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> </div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <a class="code" href="struct_layer_test_result.html">LayerTestResult<T, 4></a> result(outputTensorInfo);</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  result.<a class="code" href="struct_layer_test_result.html#a73610ea6c776cc66e5a78dd842a39b8b">outputExpected</a> = MakeTensor<T, 4>(outputTensorInfo, std::vector<T>(expectedOutputValues));</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> </div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <a class="code" href="structarmnn_1_1_pad_queue_descriptor.html">armnn::PadQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> </div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  std::vector<std::pair<unsigned int, unsigned int>> PadList;</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  PadList.push_back(std::pair<unsigned int, unsigned int>(1,1));</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  PadList.push_back(std::pair<unsigned int, unsigned int>(2,1));</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  PadList.push_back(std::pair<unsigned int, unsigned int>(3,1));</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  PadList.push_back(std::pair<unsigned int, unsigned int>(1,1));</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> </div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pad_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a> = PadList;</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> info;</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span> </div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> </div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#ab0c956e4a638d0a2777ecb71953f7e27">CreatePad</a>(descriptor, info);</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> </div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  inputHandle->Allocate();</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  outputHandle->Allocate();</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> </div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &inputTensor[0][0][0][0]);</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span> </div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  workload->Execute();</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> </div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&result.<a class="code" href="struct_layer_test_result.html#ac9d44d346bb7c89f7a7aa31d2bee947f">output</a>[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> </div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span> }</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> </div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> <span class="comment">//</span></div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span> <span class="comment">// Explicit template specializations</span></div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> <span class="comment">//</span></div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> </div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> <span class="keyword">template</span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16></a>, 2></div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span> Pad2dTestCommon<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  int32_t qOffset,</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> customPaddingValue);</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> </div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> <span class="keyword">template</span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16></a>, 3></div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> Pad3dTestCommon<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  int32_t qOffset);</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span> </div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span> <span class="keyword">template</span> LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4></div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span> Pad4dTestCommon<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  int32_t qOffset);</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span> </div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span> <span class="comment">//</span></div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span> <span class="comment">// Implementation functions</span></div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span> <span class="comment">//</span></div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span> </div><div class="line"><a name="l00445"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#af9c6d2cdf6ad5b749e618ccc6fb43311"> 445</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<uint8_t, 2></a> <a class="code" href="_pad_test_impl_8cpp.html#af9c6d2cdf6ad5b749e618ccc6fb43311">PadUint82dTest</a>(</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span> {</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <span class="keywordflow">return</span> Pad2dTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, 1.0f, 0);</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span> }</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> </div><div class="line"><a name="l00452"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#a07b74f034f52a7c5dae44a74efb8019e"> 452</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<uint8_t, 2></a> <a class="code" href="_pad_test_impl_8cpp.html#a07b74f034f52a7c5dae44a74efb8019e">PadUint82dCustomPaddingTest</a>(</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span> {</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="keywordflow">return</span> Pad2dTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, 1.0f, 0, 1.0f);</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span> }</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span> </div><div class="line"><a name="l00459"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#abffbd2fd1db993ecf50344cf530c21b5"> 459</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<uint8_t, 3></a> <a class="code" href="_pad_test_impl_8cpp.html#abffbd2fd1db993ecf50344cf530c21b5">PadUint83dTest</a>(</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span> {</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keywordflow">return</span> Pad3dTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, 1.0f, 0);</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span> }</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span> </div><div class="line"><a name="l00466"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#a00264a85539177528b812af3df9a664a"> 466</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<uint8_t, 4></a> <a class="code" href="_pad_test_impl_8cpp.html#a00264a85539177528b812af3df9a664a">PadUint84dTest</a>(</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span> {</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keywordflow">return</span> Pad4dTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, 1.0f, 0);</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span> }</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span> </div><div class="line"><a name="l00473"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#a25fabb1639914c21d6704cb4d38a9c84"> 473</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<float, 2></a> <a class="code" href="_pad_test_impl_8cpp.html#a25fabb1639914c21d6704cb4d38a9c84">PadFloat322dTest</a>(</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span> {</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  <span class="keywordflow">return</span> Pad2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0);</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span> }</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span> </div><div class="line"><a name="l00480"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#aaa52b691f1734bf8ed1b983a4ccb9e7c"> 480</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<float, 2></a> <a class="code" href="_pad_test_impl_8cpp.html#aaa52b691f1734bf8ed1b983a4ccb9e7c">PadFloat322dCustomPaddingTest</a>(</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span> {</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keywordflow">return</span> Pad2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0, 1.0f);</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span> }</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span> </div><div class="line"><a name="l00487"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#affbb9e1924205682a80918a3ee91df3f"> 487</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<float, 3></a> <a class="code" href="_pad_test_impl_8cpp.html#affbb9e1924205682a80918a3ee91df3f">PadFloat323dTest</a>(</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span> {</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="keywordflow">return</span> Pad3dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0);</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span> }</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span> </div><div class="line"><a name="l00494"></a><span class="lineno"><a class="line" href="_pad_test_impl_8hpp.html#a154b1f8adf21e8e368d27882d02c0abd"> 494</a></span> <a class="code" href="struct_layer_test_result.html">LayerTestResult<float, 4></a> <a class="code" href="_pad_test_impl_8cpp.html#a154b1f8adf21e8e368d27882d02c0abd">PadFloat324dTest</a>(</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span> {</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keywordflow">return</span> Pad4dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0);</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span> }</div><div class="ttc" id="_pad_test_impl_8cpp_html_a07b74f034f52a7c5dae44a74efb8019e"><div class="ttname"><a href="_pad_test_impl_8cpp.html#a07b74f034f52a7c5dae44a74efb8019e">PadUint82dCustomPaddingTest</a></div><div class="ttdeci">LayerTestResult< uint8_t, 2 > PadUint82dCustomPaddingTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00452">PadTestImpl.cpp:452</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_html"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.html#l00021">WorkloadFactory.hpp:21</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_ab0c956e4a638d0a2777ecb71953f7e27"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#ab0c956e4a638d0a2777ecb71953f7e27">armnn::IWorkloadFactory::CreatePad</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreatePad(const PadQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01311">WorkloadFactory.cpp:1311</a></div></div>
+<div class="ttc" id="_pad_test_impl_8cpp_html_a2efccf857e77f59789d3c9c655943291"><div class="ttname"><a href="_pad_test_impl_8cpp.html#a2efccf857e77f59789d3c9c655943291">Pad2dTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 2 > Pad2dTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, float qScale, int32_t qOffset, const float customPaddingValue)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00020">PadTestImpl.cpp:20</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="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="_pad_test_impl_8cpp_html_affbb9e1924205682a80918a3ee91df3f"><div class="ttname"><a href="_pad_test_impl_8cpp.html#affbb9e1924205682a80918a3ee91df3f">PadFloat323dTest</a></div><div class="ttdeci">LayerTestResult< float, 3 > PadFloat323dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00487">PadTestImpl.cpp:487</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div>
+<div class="ttc" id="struct_layer_test_result_html"><div class="ttname"><a href="struct_layer_test_result.html">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.html#l00029">LayerTestResult.hpp:29</a></div></div>
+<div class="ttc" id="_tensor_copy_utils_8cpp_html_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.html#l00014">TensorCopyUtils.cpp:14</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_backend_internal_html_a693b40e6b94e958836aeb0410ca186bd"><div class="ttname"><a href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a></div><div class="ttdeci">std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.html#l00090">IBackendInternal.hpp:90</a></div></div>
+<div class="ttc" id="struct_layer_test_result_html_ac9d44d346bb7c89f7a7aa31d2bee947f"><div class="ttname"><a href="struct_layer_test_result.html#ac9d44d346bb7c89f7a7aa31d2bee947f">LayerTestResult::output</a></div><div class="ttdeci">boost::multi_array< T, n > output</div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.html#l00040">LayerTestResult.hpp:40</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_pad_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_pad_queue_descriptor.html">armnn::PadQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00252">WorkloadData.hpp:252</a></div></div>
+<div class="ttc" id="_pad_test_impl_8hpp_html"><div class="ttname"><a href="_pad_test_impl_8hpp.html">PadTestImpl.hpp</a></div></div>
+<div class="ttc" id="_pad_test_impl_8cpp_html_a154b1f8adf21e8e368d27882d02c0abd"><div class="ttname"><a href="_pad_test_impl_8cpp.html#a154b1f8adf21e8e368d27882d02c0abd">PadFloat324dTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > PadFloat324dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00494">PadTestImpl.cpp:494</a></div></div>
+<div class="ttc" id="_pad_test_impl_8cpp_html_a878a628bade11abc79cf8160c518a244"><div class="ttname"><a href="_pad_test_impl_8cpp.html#a878a628bade11abc79cf8160c518a244">Pad4dTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > Pad4dTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00177">PadTestImpl.cpp:177</a></div></div>
+<div class="ttc" id="_pad_test_impl_8cpp_html_af9c6d2cdf6ad5b749e618ccc6fb43311"><div class="ttname"><a href="_pad_test_impl_8cpp.html#af9c6d2cdf6ad5b749e618ccc6fb43311">PadUint82dTest</a></div><div class="ttdeci">LayerTestResult< uint8_t, 2 > PadUint82dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00445">PadTestImpl.cpp:445</a></div></div>
+<div class="ttc" id="struct_layer_test_result_html_a73610ea6c776cc66e5a78dd842a39b8b"><div class="ttname"><a href="struct_layer_test_result.html#a73610ea6c776cc66e5a78dd842a39b8b">LayerTestResult::outputExpected</a></div><div class="ttdeci">boost::multi_array< T, n > outputExpected</div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.html#l00041">LayerTestResult.hpp:41</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>
+<div class="ttc" id="_workload_test_utils_8hpp_html"><div class="ttname"><a href="_workload_test_utils_8hpp.html">WorkloadTestUtils.hpp</a></div></div>
+<div class="ttc" id="_pad_test_impl_8cpp_html_aaa52b691f1734bf8ed1b983a4ccb9e7c"><div class="ttname"><a href="_pad_test_impl_8cpp.html#aaa52b691f1734bf8ed1b983a4ccb9e7c">PadFloat322dCustomPaddingTest</a></div><div class="ttdeci">LayerTestResult< float, 2 > PadFloat322dCustomPaddingTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00480">PadTestImpl.cpp:480</a></div></div>
+<div class="ttc" id="structarmnn_1_1_pad_descriptor_html_a410fa919f78af0f0f100bd1594eca4ab"><div class="ttname"><a href="structarmnn_1_1_pad_descriptor.html#a410fa919f78af0f0f100bd1594eca4ab">armnn::PadDescriptor::m_PadValue</a></div><div class="ttdeci">float m_PadValue</div><div class="ttdoc">Optional value to use for padding, defaults to 0. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00923">Descriptors.hpp:923</a></div></div>
+<div class="ttc" id="structarmnn_1_1_pad_descriptor_html_a85f98c94e11f65a6b73f831735c040f3"><div class="ttname"><a href="structarmnn_1_1_pad_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">armnn::PadDescriptor::m_PadList</a></div><div class="ttdeci">std::vector< std::pair< unsigned int, unsigned int > > m_PadList</div><div class="ttdoc">Specifies the padding for input dimension. First is the number of values to add before the tensor in ...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00920">Descriptors.hpp:920</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="_pad_test_impl_8cpp_html_a106adefa1af15bdc68068403d7e93cd3"><div class="ttname"><a href="_pad_test_impl_8cpp.html#a106adefa1af15bdc68068403d7e93cd3">Pad3dTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 3 > Pad3dTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00093">PadTestImpl.cpp:93</a></div></div>
+<div class="ttc" id="_pad_test_impl_8cpp_html_abffbd2fd1db993ecf50344cf530c21b5"><div class="ttname"><a href="_pad_test_impl_8cpp.html#abffbd2fd1db993ecf50344cf530c21b5">PadUint83dTest</a></div><div class="ttdeci">LayerTestResult< uint8_t, 3 > PadUint83dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00459">PadTestImpl.cpp:459</a></div></div>
+<div class="ttc" id="_pad_test_impl_8cpp_html_a00264a85539177528b812af3df9a664a"><div class="ttname"><a href="_pad_test_impl_8cpp.html#a00264a85539177528b812af3df9a664a">PadUint84dTest</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > PadUint84dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00466">PadTestImpl.cpp:466</a></div></div>
+<div class="ttc" id="_tensor_copy_utils_8hpp_html"><div class="ttname"><a href="_tensor_copy_utils_8hpp.html">TensorCopyUtils.hpp</a></div></div>
+<div class="ttc" id="_pad_test_impl_8cpp_html_a25fabb1639914c21d6704cb4d38a9c84"><div class="ttname"><a href="_pad_test_impl_8cpp.html#a25fabb1639914c21d6704cb4d38a9c84">PadFloat322dTest</a></div><div class="ttdeci">LayerTestResult< float, 2 > PadFloat322dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pad_test_impl_8cpp_source.html#l00473">PadTestImpl.cpp:473</a></div></div>
+<div class="ttc" id="_tensor_helpers_8hpp_html"><div class="ttname"><a href="_tensor_helpers_8hpp.html">TensorHelpers.hpp</a></div></div>
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