IVGCVSW-3726 Upload ArmNN Doxygen files
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+<a href="_batch_to_space_nd_test_impl_8hpp.xhtml">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">#pragma once</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="_layer_test_result_8hpp.xhtml">LayerTestResult.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="_resolve_type_8hpp.xhtml">ResolveType.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> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="include_2armnn_2backends_2_i_backend_internal_8hpp.xhtml">armnn/backends/IBackendInternal.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_workload_factory_8hpp.xhtml">backendsCommon/WorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_data_type_utils_8hpp.xhtml">backendsCommon/test/DataTypeUtils.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <<a class="code" href="_tensor_copy_utils_8hpp.xhtml">backendsCommon/test/TensorCopyUtils.hpp</a>></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="_workload_test_utils_8hpp.xhtml">backendsCommon/test/WorkloadTestUtils.hpp</a>></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <<a class="code" href="_tensor_helpers_8hpp.xhtml">test/TensorHelpers.hpp</a>></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> <span class="keyword">template</span><<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType,</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  std::size_t InputDim,</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  std::size_t OutputDim,</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keyword">typename</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, OutputDim></a> BatchToSpaceNdHelper(</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory,</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_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a>& dataLayout,</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *inputShape,</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keyword">const</span> std::vector<float> &inputData,</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keyword">const</span> std::vector<unsigned int> &blockShape,</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">const</span> std::vector<std::pair<unsigned int, unsigned int>> &crops,</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *outputShape,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keyword">const</span> std::vector<float> &outputData,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordtype">float</span> scale = 1.0f,</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  int32_t offset = 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>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo(InputDim, inputShape, ArmnnType);</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo(OutputDim, outputShape, ArmnnType);</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>  inputTensorInfo.SetQuantizationScale(scale);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  inputTensorInfo.SetQuantizationOffset(offset);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  outputTensorInfo.SetQuantizationScale(scale);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  outputTensorInfo.SetQuantizationOffset(offset);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">auto</span> input = MakeTensor<T, InputDim>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputData, inputTensorInfo));</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> </div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, OutputDim></a> result(outputTensorInfo);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  result.outputExpected = MakeTensor<T, OutputDim>(outputTensorInfo,</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  ConvertToDataType<ArmnnType>(outputData, outputTensorInfo));</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="structarmnn_1_1_batch_to_space_nd_queue_descriptor.xhtml">armnn::BatchToSpaceNdQueueDescriptor</a> data;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> = blockShape;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a3941f674c071c9503e00d2b59e92e454">m_Crops</a> = crops;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</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>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#af00ce13ef7dabd17cc4186d0a4991757">CreateBatchToSpaceNd</a>(data, info);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  inputHandle->Allocate();</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  outputHandle->Allocate();</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), input.origin());</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>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  workload->Execute();</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>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&result.output[0][0][0][0], outputHandle.get());</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>  <span class="keywordflow">return</span> result;</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> } <span class="comment">// anonymous namespace</span></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> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00088"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a5766a02d2acc065eaa6adf4bd515dcbd"> 88</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a5766a02d2acc065eaa6adf4bd515dcbd">BatchToSpaceNdNhwcTest1</a>(</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</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">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 2, 2, 1};</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 4, 4, 1};</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  std::vector<float> input({</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (1)</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  1.0f, 3.0f,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (1)</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  9.0f, 11.0f,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </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>  <span class="comment">// Batch 1, Height 0, Width (2) x Channel (1)</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  2.0f, 4.0f,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="comment">// Batch 1, Height 1, Width (2) x Channel (1)</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  10.0f, 12.0f,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </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">// Batch 2, Height 0, Width (2) x Channel (1)</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  5.0f, 7.0f,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// Batch 2, Height 1, Width (2) x Channel (1)</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  13.0f, 15.0f,</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">// Batch 3, Height 0, Width (2) x Channel (3)</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  6.0f, 8.0f,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="comment">// Batch 3, Height 1, Width (2) x Channel (1)</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  14.0f, 16.0f</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> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  std::vector<float> expectedOutput({</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  5.0f, 6.0f, 7.0f, 8.0f,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  9.0f, 10.0f, 11.0f, 12.0f,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  13.0f, 14.0f, 15.0f, 16.0f</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  });</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>  std::vector<unsigned int> blockShape {2, 2};</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> }</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00135"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#aca8aaef715d0d4b18c08641becf3a7e8"> 135</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#aca8aaef715d0d4b18c08641becf3a7e8">BatchToSpaceNdNhwcTest2</a>(</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> {</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 1, 1, 1};</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 2, 2, 1};</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>  std::vector<float> input({</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (1)</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  });</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f});</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>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> }</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00158"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#ac222455cb8669deb8c93f28ea7ef109a"> 158</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#ac222455cb8669deb8c93f28ea7ef109a">BatchToSpaceNdNhwcTest3</a>(</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> {</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 1, 1, 3};</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 2, 2, 3};</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f});</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f});</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> </div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  crops, outputShape, expectedOutput);</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> </div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00178"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a9945fb5c48fecb7d0609e98c87ec6ad5"> 178</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a9945fb5c48fecb7d0609e98c87ec6ad5">BatchToSpaceNdNhwcTest4</a>(</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> {</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {8, 1, 3, 1};</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {2, 2, 4, 1};</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  std::vector<float> input({</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  0.0f, 1.0f, 3.0f,</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  0.0f, 9.0f, 11.0f,</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  0.0f, 2.0f, 4.0f,</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  0.0f, 10.0f, 12.0f,</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  0.0f, 5.0f, 7.0f,</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  0.0f, 13.0f, 15.0f,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  0.0f, 6.0f, 8.0f,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  0.0f, 14.0f, 16.0f</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  });</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  std::vector<float> expectedOutput({</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  5.0f, 6.0f, 7.0f, 8.0f,</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  9.0f, 10.0f, 11.0f, 12.0f,</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  13.0f, 14.0f, 15.0f, 16.0f</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> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}};</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> </div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span> }</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> </div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00212"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a45f8dc539e9331ca47dd2d6ec44c92e6"> 212</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a45f8dc539e9331ca47dd2d6ec44c92e6">BatchToSpaceNdNhwcTest5</a>(</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</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>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 2, 2, 1};</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 4, 4, 1};</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16});</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  std::vector<float> expectedOutput({1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16});</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> </div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> </div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>, inputShape,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  input, blockShape, crops, outputShape, expectedOutput);</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> }</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> </div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00230"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a6342b2004b217eb0d2ec2a9306cd743c"> 230</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a6342b2004b217eb0d2ec2a9306cd743c">BatchToSpaceNdNhwcTest6</a>(</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> {</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 1, 1, 1};</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 2, 2, 1};</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  std::vector<float> input({</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (1)</span></div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  1, 2, 3, 4</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  });</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> </div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  std::vector<float> expectedOutput({1, 2, 3, 4});</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> </div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> }</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00253"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#af94eb1e55356e998b63f331356802d93"> 253</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#af94eb1e55356e998b63f331356802d93">BatchToSpaceNdNhwcTest7</a>(</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> {</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 1, 1, 3};</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 2, 2, 3};</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> </div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  std::vector<float> expectedOutput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});</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>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> </div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> }</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00273"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a165271263b4942e200709945e3bb33be"> 273</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a165271263b4942e200709945e3bb33be">BatchToSpaceNdNchwTest1</a>(</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory,</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> {</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 3, 1, 1};</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 3, 2, 2};</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>  std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f});</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  std::vector<float> expectedOutput({</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <span class="comment">// Batch 0, Channel 0, Height (2) x Width (2)</span></div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  1.0f, 4.0f,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  7.0f, 10.0f,</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="comment">// Batch 0, Channel 1, Height (2) x Width (2)</span></div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  2.0f, 5.0f,</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  8.0f, 11.0f,</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> </div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="comment">// Batch 0, Channel 2, Height (2) x Width (2)</span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  3.0f, 6.0f,</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  9.0f, 12.0f,</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  });</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>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> }</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> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00305"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#acca2cfa16ec45fd21784087c38a64348"> 305</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#acca2cfa16ec45fd21784087c38a64348">BatchToSpaceNdNchwTest2</a>(</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> {</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 1, 1, 1};</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 1, 2, 2};</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> </div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  std::vector<float> input({</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (1)</span></div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  });</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> </div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f});</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> </div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> }</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> </div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00328"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a991e5ed989f6b8171e9d0c30dd493271"> 328</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a991e5ed989f6b8171e9d0c30dd493271">BatchToSpaceNdNchwTest3</a>(</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> {</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 3, 1, 1};</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 3, 2, 2};</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> </div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  std::vector<float> input({1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f});</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> </div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  std::vector<float> expectedOutput({</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="comment">// Batch 0, Channel 0, Height (2) x Width (2)</span></div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  1.0f, 7.0f,</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  2.0f, 8.0f,</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="comment">// Batch 0, Channel 1, Height (2) x Width (2)</span></div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  3.0f, 9.0f,</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  4.0f, 10.0f,</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="comment">// Batch 0, Channel 2, Height (2) x Width (2)</span></div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  5.0f, 11.0f,</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  6.0f, 12.0f,</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  });</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span> </div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> </div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> }</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> </div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00360"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#ae75d415c280469d41e76370ae8af874b"> 360</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#ae75d415c280469d41e76370ae8af874b">BatchToSpaceNdNchwTest4</a>(</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory,</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> {</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 3, 1, 1};</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 3, 2, 2};</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> </div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> </div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  std::vector<float> expectedOutput({</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="comment">// Batch 0, Channel 0, Height (2) x Width (2)</span></div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  1, 4,</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  7, 10,</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> </div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="comment">// Batch 0, Channel 1, Height (2) x Width (2)</span></div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  2, 5,</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  8, 11,</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="comment">// Batch 0, Channel 2, Height (2) x Width (2)</span></div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  3, 6,</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  9, 12,</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  });</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::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</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>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span> }</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span> </div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00392"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a457cfa0045885dcecb6cfe8c14be777f"> 392</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a457cfa0045885dcecb6cfe8c14be777f">BatchToSpaceNdNchwTest5</a>(</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> {</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 1, 1, 1};</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 1, 2, 2};</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> </div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  std::vector<float> input({</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (1)</span></div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  1, 2, 3, 4</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  });</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> </div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  std::vector<float> expectedOutput({1, 2, 3, 4});</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span> </div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span> </div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span> }</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> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00415"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a9cf96226764fc0bef5d2a59a99758cd6"> 415</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a9cf96226764fc0bef5d2a59a99758cd6">BatchToSpaceNdNchwTest6</a>(</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</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">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {4, 3, 1, 1};</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 3, 2, 2};</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  std::vector<float> input({1, 3, 5, 7, 9, 11, 2, 4, 6, 8, 10, 12});</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span> </div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  std::vector<float> expectedOutput({</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  <span class="comment">// Batch 0, Channel 0, Height (2) x Width (2)</span></div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  1, 7,</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  2, 8,</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> </div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="comment">// Batch 0, Channel 1, Height (2) x Width (2)</span></div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  3, 9,</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  4, 10,</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> </div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="comment">// Batch 0, Channel 2, Height (2) x Width (2)</span></div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  5, 11,</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  6, 12,</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  });</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span> </div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</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="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span> }</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span> </div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00447"></a><span class="lineno"><a class="line" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a3827710219ac619b26223505d33182e3"> 447</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_batch_to_space_nd_test_impl_8hpp.xhtml#a3827710219ac619b26223505d33182e3">BatchToSpaceNdNchwTest7</a>(</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</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>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {8, 1, 1, 3};</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {2, 1, 2, 4};</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span> </div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  std::vector<float> input({</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  0, 1, 3, 0, 9, 11,</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  0, 2, 4, 0, 10, 12,</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  0, 5, 7, 0, 13, 15,</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  0, 6, 8, 0, 14, 16</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  });</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span> </div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  std::vector<float> expectedOutput({</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  1, 2, 3, 4,</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  5, 6, 7, 8,</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  9, 10, 11, 12,</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  13, 14, 15, 16</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  });</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span> </div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  std::vector<unsigned int> blockShape({2, 2});</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}};</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span> </div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keywordflow">return</span> BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>, inputShape, input, blockShape,</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  crops, outputShape, expectedOutput);</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span> }</div><div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_a991e5ed989f6b8171e9d0c30dd493271"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#a991e5ed989f6b8171e9d0c30dd493271">BatchToSpaceNdNchwTest3</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNchwTest3(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00328">BatchToSpaceNdTestImpl.hpp:328</a></div></div>
+<div class="ttc" id="_tensor_copy_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_copy_utils_8hpp.xhtml">TensorCopyUtils.hpp</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_acca2cfa16ec45fd21784087c38a64348"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#acca2cfa16ec45fd21784087c38a64348">BatchToSpaceNdNchwTest2</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNchwTest2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00305">BatchToSpaceNdTestImpl.hpp:305</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_a9cf96226764fc0bef5d2a59a99758cd6"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#a9cf96226764fc0bef5d2a59a99758cd6">BatchToSpaceNdNchwTest6</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNchwTest6(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00415">BatchToSpaceNdTestImpl.hpp:415</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_a457cfa0045885dcecb6cfe8c14be777f"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#a457cfa0045885dcecb6cfe8c14be777f">BatchToSpaceNdNchwTest5</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNchwTest5(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00392">BatchToSpaceNdTestImpl.hpp:392</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_af00ce13ef7dabd17cc4186d0a4991757"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#af00ce13ef7dabd17cc4186d0a4991757">armnn::IWorkloadFactory::CreateBatchToSpaceNd</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateBatchToSpaceNd(const BatchToSpaceNdQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01123">WorkloadFactory.cpp:1123</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00049">Types.hpp:49</a></div></div>
+<div class="ttc" id="_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_workload_factory_8hpp.xhtml">WorkloadFactory.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.xhtml#l00021">WorkloadFactory.hpp:21</a></div></div>
+<div class="ttc" id="_workload_test_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_test_utils_8hpp.xhtml">WorkloadTestUtils.hpp</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_a45f8dc539e9331ca47dd2d6ec44c92e6"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#a45f8dc539e9331ca47dd2d6ec44c92e6">BatchToSpaceNdNhwcTest5</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNhwcTest5(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00212">BatchToSpaceNdTestImpl.hpp:212</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_a5766a02d2acc065eaa6adf4bd515dcbd"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#a5766a02d2acc065eaa6adf4bd515dcbd">BatchToSpaceNdNhwcTest1</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNhwcTest1(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00088">BatchToSpaceNdTestImpl.hpp:88</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_aca8aaef715d0d4b18c08641becf3a7e8"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#aca8aaef715d0d4b18c08641becf3a7e8">BatchToSpaceNdNhwcTest2</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNhwcTest2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00135">BatchToSpaceNdTestImpl.hpp:135</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_a165271263b4942e200709945e3bb33be"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#a165271263b4942e200709945e3bb33be">BatchToSpaceNdNchwTest1</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNchwTest1(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00273">BatchToSpaceNdTestImpl.hpp:273</a></div></div>
+<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchToSpaceNdDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00684">Descriptors.hpp:684</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a0743ed5e860c316a20b68ca96301b411"><div class="ttname"><a href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a></div><div class="ttdeci">typename ResolveTypeImpl< DT >::Type ResolveType</div><div class="ttdef"><b>Definition:</b> <a href="_resolve_type_8hpp_source.xhtml#l00073">ResolveType.hpp:73</a></div></div>
+<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_a6342b2004b217eb0d2ec2a9306cd743c"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#a6342b2004b217eb0d2ec2a9306cd743c">BatchToSpaceNdNhwcTest6</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNhwcTest6(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00230">BatchToSpaceNdTestImpl.hpp:230</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div>
+<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_queue_descriptor.xhtml">armnn::BatchToSpaceNdQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00420">WorkloadData.hpp:420</a></div></div>
+<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#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.xhtml#l00049">WorkloadData.hpp:49</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_a3827710219ac619b26223505d33182e3"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#a3827710219ac619b26223505d33182e3">BatchToSpaceNdNchwTest7</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNchwTest7(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00447">BatchToSpaceNdTestImpl.hpp:447</a></div></div>
+<div class="ttc" id="_layer_test_result_8hpp_xhtml"><div class="ttname"><a href="_layer_test_result_8hpp.xhtml">LayerTestResult.hpp</a></div></div>
+<div class="ttc" id="_tensor_helpers_8hpp_xhtml"><div class="ttname"><a href="_tensor_helpers_8hpp.xhtml">TensorHelpers.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div>
+<div class="ttc" id="include_2armnn_2backends_2_i_backend_internal_8hpp_xhtml"><div class="ttname"><a href="include_2armnn_2backends_2_i_backend_internal_8hpp.xhtml">IBackendInternal.hpp</a></div></div>
+<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a02e143524aefddd40b485fcf7dea6696"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">armnn::BatchToSpaceNdDescriptor::m_BlockShape</a></div><div class="ttdeci">std::vector< unsigned int > m_BlockShape</div><div class="ttdoc">Block shape values. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00680">Descriptors.hpp:680</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_backend_internal_xhtml_a693b40e6b94e958836aeb0410ca186bd"><div class="ttname"><a href="classarmnn_1_1_i_backend_internal.xhtml#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.xhtml#l00090">IBackendInternal.hpp:90</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_af94eb1e55356e998b63f331356802d93"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#af94eb1e55356e998b63f331356802d93">BatchToSpaceNdNhwcTest7</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNhwcTest7(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00253">BatchToSpaceNdTestImpl.hpp:253</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_a9945fb5c48fecb7d0609e98c87ec6ad5"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#a9945fb5c48fecb7d0609e98c87ec6ad5">BatchToSpaceNdNhwcTest4</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNhwcTest4(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00178">BatchToSpaceNdTestImpl.hpp:178</a></div></div>
+<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#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.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#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="_batch_to_space_nd_test_impl_8hpp_xhtml_ac222455cb8669deb8c93f28ea7ef109a"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#ac222455cb8669deb8c93f28ea7ef109a">BatchToSpaceNdNhwcTest3</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNhwcTest3(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00158">BatchToSpaceNdTestImpl.hpp:158</a></div></div>
+<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a3941f674c071c9503e00d2b59e92e454"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a3941f674c071c9503e00d2b59e92e454">armnn::BatchToSpaceNdDescriptor::m_Crops</a></div><div class="ttdeci">std::vector< std::pair< unsigned int, unsigned int > > m_Crops</div><div class="ttdoc">The values to crop from the input dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00682">Descriptors.hpp:682</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
+<div class="ttc" id="_data_type_utils_8hpp_xhtml"><div class="ttname"><a href="_data_type_utils_8hpp.xhtml">DataTypeUtils.hpp</a></div></div>
+<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div>
+<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div>
+<div class="ttc" id="_batch_to_space_nd_test_impl_8hpp_xhtml_ae75d415c280469d41e76370ae8af874b"><div class="ttname"><a href="_batch_to_space_nd_test_impl_8hpp.xhtml#ae75d415c280469d41e76370ae8af874b">BatchToSpaceNdNchwTest4</a></div><div class="ttdeci">LayerTestResult< T, 4 > BatchToSpaceNdNchwTest4(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_test_impl_8hpp_source.xhtml#l00360">BatchToSpaceNdTestImpl.hpp:360</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
+<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#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.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div>
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