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<a href="_pooling2d_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>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_pooling2d_test_impl_8hpp.html">Pooling2dTestImpl.hpp</a>&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_quantize_helper_8hpp.html">QuantizeHelper.hpp</a>&gt;</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_resolve_type_8hpp.html">ResolveType.hpp</a>&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;</div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_layer_support_8hpp.html">armnn/LayerSupport.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_utils_8hpp.html">armnnUtils/TensorUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_data_layout_indexed_8hpp.html">armnnUtils/DataLayoutIndexed.hpp</a>&gt;</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_permute_8hpp.html">armnnUtils/Permute.hpp</a>&gt;</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="src_2backends_2backends_common_2_workload_info_8hpp.html">backendsCommon/WorkloadInfo.hpp</a>&gt;</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_copy_utils_8hpp.html">backendsCommon/test/TensorCopyUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_workload_test_utils_8hpp.html">backendsCommon/test/WorkloadTestUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_helpers_8hpp.html">test/TensorHelpers.hpp</a>&gt;</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#include &lt;boost/numeric/conversion/cast.hpp&gt;</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="keyword">namespace</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;{</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.html">armnnUtils</a>;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> SimplePooling2dTestImpl(</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor,</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; int32_t qOffset,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="keyword">const</span> boost::multi_array&lt;T, 4&gt;&amp; input,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="keyword">const</span> boost::multi_array&lt;T, 4&gt;&amp; outputExpected)</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;{</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; boost::ignore_unused(memoryManager);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a> dimensionIndices = dataLayout;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keyword">auto</span> heightIndex = dimensionIndices.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>();</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="keyword">auto</span> widthIndex = dimensionIndices.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>();</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keyword">auto</span> channelsIndex = dimensionIndices.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>();</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(input.shape()[heightIndex]);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(input.shape()[widthIndex]);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(input.shape()[channelsIndex]);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(input.shape()[0]);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(outputExpected.shape()[heightIndex]);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(outputExpected.shape()[widthIndex]);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(outputExpected.shape()[channelsIndex]);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputBatchSize = boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(outputExpected.shape()[0]);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo = <a class="code" href="namespacearmnn_utils.html#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; inputBatchSize, inputChannels, inputHeight, inputWidth, dataLayout, ArmnnType);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_utils.html#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; outputBatchSize, outputChannels, outputHeight, outputWidth, dataLayout, ArmnnType);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="keywordflow">if</span>(armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; {</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; inputTensorInfo.SetQuantizationScale(qScale);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; }</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> result(outputTensorInfo);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.html">armnn::Pooling2dQueueDescriptor</a> queueDescriptor;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a> = descriptor;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="comment">// Don&#39;t execute if Pooling is not supported, as an exception will be raised.</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <a class="code" href="classarmnn_1_1_backend_id.html">armnn::BackendId</a> backend = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a9f7e4296485d2812e7996089149c96d1">GetBackendId</a>();</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> reasonIfUnsupportedMaxLen = 255;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keywordtype">char</span> reasonIfUnsupported[reasonIfUnsupportedMaxLen+1];</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; result.supported = <a class="code" href="namespacearmnn.html#aea548aa1485adbeeb3e393a13bb6bff8">armnn::IsPooling2dSupported</a>(backend, inputTensorInfo, outputTensorInfo,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>,</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; reasonIfUnsupported, reasonIfUnsupportedMaxLen);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keywordflow">if</span> (!result.supported)</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; }</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a6e95afd9a55700cbf6f9e8db8089f2f2">CreatePooling2d</a>(queueDescriptor, workloadInfo);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; inputHandle-&gt;Allocate();</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; outputHandle-&gt;Allocate();</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &amp;input[0][0][0][0]);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; workload-&gt;Execute();</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;result.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; result.outputExpected = outputExpected;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160;}</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160;<span class="comment">// Tests max pooling with the following parameters:</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160;<span class="comment">// Pooling size: 3x3</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160;<span class="comment">// Stride: (2,4)</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160;<span class="comment">// input size: 8x13</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;<span class="comment">// channels: 2</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160;<span class="comment">// batch size: 2</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> SimpleMaxPooling2dSize3x3Stride2x4TestCommon(</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="keywordtype">bool</span> forceNoPadding,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160;{</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 3;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 4;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; <span class="comment">// forceNoPadding is mainly used for compatibility with ARM Compute.</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <span class="comment">// As of 16/05/2017, it errors if padX or padY are equal to or greater than the pool size.</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = forceNoPadding ? 0 : 3;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 8;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 13;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; 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(inputHeight + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a>) /</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 2;</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 2;</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160;</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; 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inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; }</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; std::vector&lt;float&gt; singleChannelData({</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; 0.0f, 4.0f, 8.0f, 1.0f, 6.0f, 4.0f, 5.0f, 8.0f,</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; 1.0f, 1.0f, 6.0f, 0.0f, 3.0f, 7.0f, 4.0f, 7.0f,</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; 8.0f, 5.0f, 0.0f, 0.0f, 8.0f, 3.0f, 4.0f, 3.0f,</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; 8.0f, 2.0f, 5.0f, 4.0f, 1.0f, 9.0f, 2.0f, 0.0f,</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; 5.0f, 4.0f, 5.0f, 0.0f, 0.0f, 0.0f, 7.0f, 2.0f,</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; 1.0f, 2.0f, 6.0f, 2.0f, 7.0f, 9.0f, 5.0f, 2.0f,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; 9.0f, 7.0f, 3.0f, 1.0f, 3.0f, 4.0f, 8.0f, 3.0f,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; 1.0f, 0.0f, 0.0f, 5.0f, 5.0f, 4.0f, 2.0f, 0.0f,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; 6.0f, 4.0f, 3.0f, 6.0f, 9.0f, 5.0f, 5.0f, 6.0f,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; 8.0f, 7.0f, 9.0f, 6.0f, 1.0f, 4.0f, 1.0f, 9.0f,</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; 7.0f, 1.0f, 9.0f, 2.0f, 9.0f, 9.0f, 8.0f, 1.0f,</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; 4.0f, 4.0f, 5.0f, 9.0f, 2.0f, 6.0f, 6.0f, 4.0f,</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; 3.0f, 5.0f, 4.0f, 0.0f, 1.0f, 5.0f, 9.0f, 7.0f,</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; });</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; <span class="comment">// Constructs input data.</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; std::vector&lt;float&gt; inputData;</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; <span class="keyword">auto</span> negator = [](<span class="keywordtype">float</span> f) { <span class="keywordflow">return</span> -f; 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},</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; }</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160;</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160;}</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160;</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> SimpleMaxPooling2dTestCommon(</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>,</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160;{</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; 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outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; }</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160;</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; std::vector&lt;T&gt; inputData(</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; 1.0f, 2.0f, 5.0f, 6.0f,</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; 3.0f, 4.0f, 7.0f, 8.0f,</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; 9.0f, 10.0f, 13.0f, 14.0f,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; 11.0f, 12.0f, 15.0f, 16.0f,</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160;</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; 17.0f, 18.0f, 21.0f, 22.0f,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; 19.0f, 20.0f, 23.0f, 24.0f,</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; 25.0f, 26.0f, 29.0f, 30.0f,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; 27.0f, 28.0f, 31.0f, 32.0f,</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; },</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160;</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; std::vector&lt;T&gt; outputData(</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; 4.0f, 8.0f,</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; 12.0f, 16.0f,</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160;</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; 20.0f, 24.0f,</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; 28.0f, 32.0f,</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; },</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160;</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a> NCHWToNHWC = { 0, 3, 1, 2 };</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; {</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; std::vector&lt;T&gt; tmp(inputData.size());</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, inputData.data(), tmp.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; inputData = tmp;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; std::vector&lt;T&gt; tmp1(outputData.size());</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, outputData.data(), tmp1.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; outputData = tmp1;</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; }</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo, inputData);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160;</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160; <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo, outputData);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160;</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160;}</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160;</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> SimpleAveragePooling2dTestCommon(</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; 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<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 2;</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo = <a class="code" href="namespacearmnn_utils.html#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(1, 2, 4, 4, dataLayout, ArmnnType);</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_utils.html#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(1, 2, 2, 2, dataLayout, ArmnnType);</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160;</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; <span class="keywordflow">if</span>(armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; {</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; }</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160;</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160; std::vector&lt;T&gt; inputData(</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160; 2.0f, 2.0f, 6.0f, 6.0f,</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160; 4.0f, 4.0f, 8.0f, 8.0f,</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160; 10.0f, 12.0f, 14.0f, 16.0f,</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160; 10.0f, 12.0f, 16.0f, 14.0f,</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>&#160;</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>&#160; 18.0f, 20.0f, 24.0f, 22.0f,</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>&#160; 20.0f, 18.0f, 22.0f, 24.0f,</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>&#160; 26.0f, 28.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>&#160; 26.0f, 28.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>&#160; },</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160;</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160; std::vector&lt;T&gt; outputData(</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>&#160; 3.0f, 7.0f,</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>&#160; 11.0f, 15.0f,</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>&#160;</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>&#160; 19.0f, 23.0f,</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>&#160; 27.0f, 0.0f,</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>&#160; },</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>&#160;</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a> NCHWToNHWC = { 0, 3, 1, 2 };</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>&#160; <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>&#160; {</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>&#160; std::vector&lt;T&gt; tmp(inputData.size());</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>&#160; <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, inputData.data(), tmp.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>&#160; inputData = tmp;</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>&#160;</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>&#160; std::vector&lt;T&gt; tmp1(outputData.size());</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>&#160; <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, outputData.data(), tmp1.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>&#160; outputData = tmp1;</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>&#160; }</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>&#160;</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo, inputData);</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>&#160;</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>&#160; <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo, outputData);</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>&#160;</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>&#160;}</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>&#160;</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> LargeTensorsAveragePooling2dTestCommon(</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>&#160;{</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 100;</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 5;</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 50;</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 50;</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>&#160; 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outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>&#160; }</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>&#160;</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>&#160; std::vector&lt;T&gt; inputVec;</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>&#160;</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0 ; i &lt; inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>().<a class="code" href="classarmnn_1_1_tensor_shape.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(); 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workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>&#160;}</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>&#160;</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> SimpleL2Pooling2dTestCommon(</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; 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descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>&#160;</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo = <a class="code" href="namespacearmnn_utils.html#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(1, 2, 4, 4, dataLayout, ArmnnType);</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_utils.html#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(1, 2, 2, 2, dataLayout, ArmnnType);</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>&#160;</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>&#160; std::vector&lt;T&gt; inputData(</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>&#160; 1.0f, 7.0f, 5.0f, 5.0f,</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>&#160; 1.0f, 7.0f, 5.0f, 5.0f,</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>&#160; 3.0f, 3.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>&#160; 3.0f, 3.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>&#160;</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>&#160; 1.0f, 7.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>&#160; 1.0f, 7.0f, 2.0f, 0.0f,</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>&#160; 0.0f, 2.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>&#160; 0.0f, 0.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>&#160; },</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>&#160;</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>&#160; std::vector&lt;T&gt; outputData(</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>&#160; 5.0f, 5.0f,</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>&#160; 3.0f, 1.0f,</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>&#160;</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>&#160; 5.0f, 1.0f,</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>&#160; 1.0f, 1.0f,</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>&#160; },</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>&#160;</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a> NCHWToNHWC = { 0, 3, 1, 2 };</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>&#160; <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>&#160; {</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>&#160; std::vector&lt;T&gt; tmp(inputData.size());</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>&#160; <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, inputData.data(), tmp.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>&#160; 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1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>&#160; 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f,</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>&#160; },</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>&#160;</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType);</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>&#160; <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>&#160; 3.0f, 3.0f, 3.0f,</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>&#160; 3.0f, 3.0f, 3.0f,</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>&#160; 3.0f, 3.0f, 3.0f,</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>&#160; },</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>&#160;</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>&#160;}</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>&#160;</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> L2Pooling2dSize3Stride4TestCommon(</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>&#160;{</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 3;</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 4;</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>&#160;</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo({ 1, 1, 7, 7 }, ArmnnType);</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>&#160; 2.0f, 1.0f, 5.0f, 0.0f, 2.0f, 1.0f, 5.0f,</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>&#160; 1.0f, 2.0f, 2.0f, 0.0f, 1.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>&#160; 5.0f, 4.0f, 1.0f, 0.0f, 5.0f, 4.0f, 1.0f,</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>&#160; 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>&#160; 2.0f, 1.0f, 5.0f, 0.0f, 2.0f, 1.0f, 5.0f,</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>&#160; 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3.0f, 3.0f,</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>&#160; 3.0f, 3.0f,</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>&#160; },</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>&#160;</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>&#160;}</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>&#160;</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> L2Pooling2dSize7TestCommon(</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>&#160;{</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>&#160; 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<a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>&#160;{</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 9;</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 9;</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>&#160;</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo({ 1, 1, 9, 9 }, ArmnnType);</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>&#160; 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f,</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>&#160; 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>&#160; 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f,</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>&#160; 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f,</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>&#160; 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>&#160; 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f,</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>&#160; 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f,</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span>&#160; 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span>&#160; 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f,</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>&#160; },</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>&#160;</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo({ 1, 1, 1, 1 }, ArmnnType);</div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>&#160; <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>&#160; 3.0f,</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span>&#160; },</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>&#160;</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>&#160;}</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>&#160;</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> AsymmetricNonSquarePooling2dTestCommon(</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>&#160;{</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo({ 1, 1, 1, 3 }, ArmnnType);</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType);</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>&#160;</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>&#160; descriptor.m_PoolWidth = 2;</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>&#160; descriptor.m_PoolHeight = 3;</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>&#160; descriptor.m_StrideX = 2;</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>&#160; descriptor.m_StrideY = 1;</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>&#160; descriptor.m_PadLeft = 2;</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>&#160; descriptor.m_PadRight = 0;</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>&#160; descriptor.m_PadTop = 1;</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>&#160; descriptor.m_PadBottom = 2;</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>&#160; descriptor.m_OutputShapeRounding = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>&#160; descriptor.m_PaddingMethod = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>&#160;</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>&#160; <span class="comment">// Construct input data.</span></div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>&#160; 1.0f, 3.0f, 4.0f,</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>&#160; },</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>&#160;</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>&#160; <span class="comment">// These were calculated manually.</span></div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>&#160; <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>&#160; 0.0f, 3.0f, 0.0f, 3.0f,</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>&#160; },</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>&#160;</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>&#160;}</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>&#160;</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> ComparePooling2dTestCommon(</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; refWorkloadFactory,</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>&#160; <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a> poolingType,</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>&#160;{</div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>&#160; boost::ignore_unused(memoryManager);</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 16;</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 32;</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelCount = 2;</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 5;</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>&#160;</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>&#160; 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outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>&#160; }</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>&#160;</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>&#160; boost::multi_array&lt;T, 4&gt; input = MakeRandomTensor&lt;T, 4&gt;(inputTensorInfo, 81715);</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>&#160;</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>&#160; <a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> comparisonResult(outputTensorInfo);</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>&#160;</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>&#160;</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.html">armnn::Pooling2dQueueDescriptor</a> data;</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>&#160; AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>&#160; AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = poolingType;</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = poolSize;</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = poolSize;</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = strideX;</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = strideY;</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = padX;</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = padX;</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = padY;</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = padY;</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>&#160;</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandleRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandleRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>&#160;</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>&#160; <span class="comment">// Don&#39;t execute if Pooling is not supported, as an exception will be raised.</span></div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>&#160; <a class="code" href="classarmnn_1_1_backend_id.html">armnn::BackendId</a> backend = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a9f7e4296485d2812e7996089149c96d1">GetBackendId</a>();</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> reasonIfUnsupportedMaxLen = 255;</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>&#160; <span class="keywordtype">char</span> reasonIfUnsupported[reasonIfUnsupportedMaxLen+1];</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>&#160; comparisonResult.supported = <a class="code" href="namespacearmnn.html#aea548aa1485adbeeb3e393a13bb6bff8">armnn::IsPooling2dSupported</a>(backend, inputTensorInfo, outputTensorInfo,</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>,</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>&#160; reasonIfUnsupported, reasonIfUnsupportedMaxLen);</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>&#160; <span class="keywordflow">if</span> (!comparisonResult.supported)</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>&#160; {</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>&#160; <span class="keywordflow">return</span> comparisonResult;</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>&#160; }</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>&#160;</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.html">armnn::Pooling2dQueueDescriptor</a> refData = data;</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> refInfo = info;</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>&#160; SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get());</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>&#160; SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get());</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span>&#160;</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a6e95afd9a55700cbf6f9e8db8089f2f2">CreatePooling2d</a>(data, info);</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workloadRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a6e95afd9a55700cbf6f9e8db8089f2f2">CreatePooling2d</a>(refData, refInfo);</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>&#160;</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span>&#160; outputHandleRef-&gt;Allocate();</div><div class="line"><a name="l00822"></a><span class="lineno"> 822</span>&#160; inputHandleRef-&gt;Allocate();</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>&#160; inputHandle-&gt;Allocate();</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>&#160; outputHandle-&gt;Allocate();</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span>&#160;</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &amp;input[0][0][0][0]);</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandleRef.get(), &amp;input[0][0][0][0]);</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>&#160;</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span>&#160; workload-&gt;Execute();</div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span>&#160; workloadRef-&gt;Execute();</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span>&#160;</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;comparisonResult.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;comparisonResult.outputExpected[0][0][0][0], outputHandleRef.get());</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>&#160;</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>&#160; <span class="keywordflow">return</span> comparisonResult;</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>&#160;}</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>&#160;</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span>&#160;<span class="comment">// Tests max pooling with the following parameters:</span></div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>&#160;<span class="comment">// Pooling size: 2x2</span></div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>&#160;<span class="comment">// Stride: (2,2)</span></div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>&#160;<span class="comment">// input size: 4x4</span></div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>&#160;<span class="comment">// channels: 1</span></div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>&#160;<span class="comment">// batch size: 1</span></div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> SimpleMaxPooling2dSize2x2Stride2x2TestCommon(</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>&#160; <span class="keywordtype">bool</span> forceNoPadding,</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>&#160;{</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 2;</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = forceNoPadding ? 0 : 3;</div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>&#160;</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>&#160;</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 4;</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>&#160;</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 4;</div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>&#160;</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth =</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>&#160; (inputWidth + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a>) /</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>;</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight =</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span>&#160; (inputHeight + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a>) /</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>;</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 1;</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 1;</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span>&#160;</div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span>&#160; std::vector&lt;float&gt; inputData = {</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span>&#160; 510.0f, 222.0f, 780.0f, 654.0f,</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span>&#160; 141.0f, 276.0f, 15.0f, 546.0f,</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>&#160; 303.0f, 618.0f, 582.0f, 339.0f,</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>&#160; 438.0f, 564.0f, 573.0f, 402.0f</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>&#160; };</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span>&#160;</div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span>&#160; <span class="comment">// Note that left and right edges will be 0.f, due to the 2x2 max pooling only accessing zeros here.</span></div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>&#160; std::vector&lt;float&gt; expectedOutputDataWithPadding = {</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>&#160; 0.0f, 510.0f, 780.0f, 654.0f, 0.0f,</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span>&#160; 0.0f, 438.0f, 618.0f, 402.0f, 0.0f</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>&#160; };</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>&#160;</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>&#160; std::vector&lt;float&gt; expectedOutputDataNoPadding = {</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>&#160; 510.0f, 780.0f,</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span>&#160; 618.0f, 582.0f</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>&#160; };</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>&#160;</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType);</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>&#160;</div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span>&#160; <span class="comment">// Scale and offset should match input - we&#39;re just calculating maximum values.</span></div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, ArmnnType);</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span>&#160;</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>&#160; <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>&#160; <span class="keywordflow">if</span>(armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>&#160; {</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span>&#160; inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>&#160; inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>&#160; }</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>&#160;</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo, QuantizedVector&lt;T&gt;(inputData, qScale, qOffset));</div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>&#160;</div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>&#160; <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>&#160; forceNoPadding ? 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<a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span>&#160; <span class="keywordtype">bool</span> forceNoPadding,</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>&#160; <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>&#160; int32_t qOffset = 0)</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>&#160;{</div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = 3;</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 2;</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = (forceNoPadding) ? 0 : 1;</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>;</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 0;</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a>;</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>&#160;</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 3;</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 2;</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth =</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>&#160; (inputWidth + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a>) /</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>;</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight =</div><div class="line"><a name="l00957"></a><span class="lineno"> 957</span>&#160; (inputHeight + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a>) /</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>;</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>&#160; 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6.0f, 8.0f,</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>&#160; };</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>&#160;</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>&#160; std::vector&lt;float&gt; expectedOutputDataNoPadding = {</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>&#160; 10.5f,</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>&#160; };</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>&#160;</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType);</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>&#160;</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span>&#160; <span class="comment">// Scale and offset should match input - we&#39;re just calculating average values.</span></div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>&#160; 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inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>&#160; }</div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>&#160;</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>&#160; 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-1.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>&#160; 1.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>&#160; 1.0f, 2.0f, -4.0f,</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>&#160; },</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>&#160; qScale, qOffset));</div><div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>&#160;</div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>&#160;}</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>&#160;</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> IgnorePaddingMaxPooling2dSize3TestCommon(</div><div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>&#160; 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-1.0f, 3.0f, 4.0f, 4.0f,</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>&#160; 2.0f, 3.0f, 4.0f, 4.0f,</div><div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>&#160; 2.0f, 3.0f, 4.0f, 4.0f,</div><div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>&#160; 2.0f, 2.0f, 2.0f, -3.0f,</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>&#160; },</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>&#160; qScale, qOffset));</div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>&#160;</div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>&#160;}</div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>&#160;</div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> IgnorePaddingSimpleAveragePooling2dTestCommon(</div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>&#160; 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inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>&#160; }</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>&#160;</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>&#160; 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3.0f, 13.0f, 10.0f,</div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>&#160; 6.0f, 26.0f, 20.0f,</div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>&#160; 3.0f, 13.0f, 10.0f,</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>&#160; },</div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>&#160; qScale, qOffset));</div><div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>&#160;</div><div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>&#160;}</div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>&#160;</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T, 4&gt;</a> IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon(</div><div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>&#160; 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descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 3;</div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 0;</div><div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 0;</div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 0;</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a>;</div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">armnn::OutputShapeRounding::Ceiling</a>;</div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>&#160;</div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo({ 1, 1, 4, 4}, ArmnnType);</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType);</div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>&#160;</div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>&#160; <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>&#160; <span class="keywordflow">if</span>(armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>&#160; {</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>&#160; inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>&#160; inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>&#160; 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inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01278"></a><span class="lineno"> 1278</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l01279"></a><span class="lineno"> 1279</span>&#160; }</div><div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>&#160;</div><div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l01282"></a><span class="lineno"> 1282</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>&#160; 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inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01328"></a><span class="lineno"> 1328</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>&#160; }</div><div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>&#160;</div><div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>&#160; 1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>&#160; 1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>&#160; 1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>&#160; 1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>&#160; },</div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>&#160; qScale, qOffset));</div><div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>&#160;</div><div class="line"><a name="l01340"></a><span class="lineno"> 1340</span>&#160; <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>&#160; QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>&#160; 1.0540f, 1.7638f, 2.5385f, 2.3570f,</div><div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>&#160; 1.2909f, 2.1602f, 3.1091f, 2.8867f,</div><div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>&#160; 1.2909f, 2.1602f, 3.1091f, 2.8867f,</div><div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>&#160; 1.0540f, 1.7638f, 2.5385f, 2.3570f,</div><div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>&#160; },</div><div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>&#160; qScale, qOffset));</div><div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>&#160;</div><div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>&#160; <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>&#160; workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>&#160;}</div><div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>&#160;</div><div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>&#160;} <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>&#160;</div><div class="line"><a name="l01355"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a0f8bd9f2e91b9b2aad21e2728bb655e3"> 1355</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a0f8bd9f2e91b9b2aad21e2728bb655e3">SimpleMaxPooling2dSize2x2Stride2x2Test</a>(</div><div class="line"><a name="l01356"></a><span class="lineno"> 1356</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>&#160; <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>&#160;{</div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>&#160; <span class="keywordflow">return</span> SimpleMaxPooling2dSize2x2Stride2x2TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>&#160; workloadFactory, memoryManager, forceNoPadding);</div><div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>&#160;}</div><div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>&#160;</div><div class="line"><a name="l01364"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a6f4185540ddce123892c799e516ee50d"> 1364</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a6f4185540ddce123892c799e516ee50d">SimpleMaxPooling2dSize2x2Stride2x2Uint8Test</a>(</div><div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01366"></a><span class="lineno"> 1366</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>&#160; <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01368"></a><span class="lineno"> 1368</span>&#160;{</div><div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>&#160; <span class="keywordflow">return</span> SimpleMaxPooling2dSize2x2Stride2x2TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>&#160; workloadFactory, memoryManager, forceNoPadding, 3.0f, -5);</div><div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>&#160;}</div><div class="line"><a name="l01372"></a><span class="lineno"> 1372</span>&#160;</div><div class="line"><a name="l01373"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a50dff405960b48e03ee0d296f72743df"> 1373</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a50dff405960b48e03ee0d296f72743df">SimpleMaxPooling2dSize2x2Stride2x2Int16Test</a>(</div><div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>&#160; <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>&#160;{</div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>&#160; <span class="keywordflow">return</span> SimpleMaxPooling2dSize2x2Stride2x2TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01379"></a><span class="lineno"> 1379</span>&#160; workloadFactory, memoryManager, forceNoPadding);</div><div class="line"><a name="l01380"></a><span class="lineno"> 1380</span>&#160;}</div><div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>&#160;</div><div class="line"><a name="l01382"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a2f7ec646738a0e279cfbb77afb3e41bd"> 1382</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a2f7ec646738a0e279cfbb77afb3e41bd">SimpleMaxPooling2dSize3x3Stride2x4Test</a>(</div><div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>&#160; <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>&#160;{</div><div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>&#160; <span class="keywordflow">return</span> SimpleMaxPooling2dSize3x3Stride2x4TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01388"></a><span class="lineno"> 1388</span>&#160; workloadFactory, memoryManager, forceNoPadding);</div><div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>&#160;}</div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>&#160;</div><div class="line"><a name="l01391"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#aacd91233b18641d11b190969bcd93057"> 1391</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#aacd91233b18641d11b190969bcd93057">SimpleMaxPooling2dSize3x3Stride2x4Uint8Test</a>(</div><div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>&#160; <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>&#160;{</div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>&#160; <span class="keywordflow">return</span> SimpleMaxPooling2dSize3x3Stride2x4TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>&#160; workloadFactory, memoryManager, forceNoPadding, 0.1f, 128);</div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>&#160;}</div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>&#160;</div><div class="line"><a name="l01400"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#ae398f1e979dd0ad467a8f5182b9101ee"> 1400</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#ae398f1e979dd0ad467a8f5182b9101ee">SimpleMaxPooling2dSize3x3Stride2x4Int16Test</a>(</div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>&#160; <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>&#160;{</div><div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>&#160; <span class="keywordflow">return</span> SimpleMaxPooling2dSize3x3Stride2x4TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>&#160; workloadFactory, memoryManager, forceNoPadding);</div><div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>&#160;}</div><div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>&#160;</div><div class="line"><a name="l01409"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a2783cdc0a074cbdfbf2f91e116c92c97"> 1409</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a2783cdc0a074cbdfbf2f91e116c92c97">SimpleMaxPooling2dTest</a>(</div><div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>&#160;{</div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>&#160; <span class="keywordflow">return</span> SimpleMaxPooling2dTestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>&#160;}</div><div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>&#160;</div><div class="line"><a name="l01417"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a807ea3c4451f81f5b91b7db53eb0a138"> 1417</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a807ea3c4451f81f5b91b7db53eb0a138">SimpleMaxPooling2dUint8Test</a>(</div><div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>&#160;{</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>&#160; <span class="keywordflow">return</span> SimpleMaxPooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>&#160;}</div><div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>&#160;</div><div class="line"><a name="l01425"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a5ff218665f1e7dc5b90c395027573e8c"> 1425</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a5ff218665f1e7dc5b90c395027573e8c">SimpleMaxPooling2dInt16Test</a>(</div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>&#160;{</div><div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>&#160; <span class="keywordflow">return</span> SimpleMaxPooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>&#160;}</div><div class="line"><a name="l01432"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a2008735411bf96a7febef693c41a4ff5"> 1432</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a2008735411bf96a7febef693c41a4ff5">IgnorePaddingSimpleMaxPooling2dTest</a>(</div><div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>&#160;{</div><div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleMaxPooling2dTestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>&#160;}</div><div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>&#160;</div><div class="line"><a name="l01439"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a3789eb1689edeed1aae83c773e75607c"> 1439</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a3789eb1689edeed1aae83c773e75607c">IgnorePaddingSimpleMaxPooling2dUint8Test</a>(</div><div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01441"></a><span class="lineno"> 1441</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>&#160;{</div><div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleMaxPooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>&#160; workloadFactory, memoryManager, 1.0f, -5);</div><div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>&#160;}</div><div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>&#160;</div><div class="line"><a name="l01447"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#af0a9b7e26de79a55506a3cd3d36a83a7"> 1447</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#af0a9b7e26de79a55506a3cd3d36a83a7">IgnorePaddingSimpleMaxPooling2dInt16Test</a>(</div><div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>&#160;{</div><div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleMaxPooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>&#160;}</div><div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>&#160;</div><div class="line"><a name="l01455"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a08f2f1d9a1f69a5799294a881dbb24b4"> 1455</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a08f2f1d9a1f69a5799294a881dbb24b4">IgnorePaddingMaxPooling2dSize3Test</a>(</div><div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>&#160;{</div><div class="line"><a name="l01459"></a><span class="lineno"> 1459</span>&#160; <span class="keywordflow">return</span> IgnorePaddingMaxPooling2dSize3TestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>&#160;}</div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>&#160;</div><div class="line"><a name="l01462"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a7f7147713ac3346b30c1071bf14fb374"> 1462</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a7f7147713ac3346b30c1071bf14fb374">IgnorePaddingMaxPooling2dSize3Uint8Test</a>(</div><div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>&#160;{</div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>&#160; <span class="keywordflow">return</span> IgnorePaddingMaxPooling2dSize3TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>&#160; workloadFactory, memoryManager, 1.0f, -5);</div><div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>&#160;}</div><div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>&#160;</div><div class="line"><a name="l01470"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#acf9c19888a6f2139b355052d542920bb"> 1470</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#acf9c19888a6f2139b355052d542920bb">IgnorePaddingMaxPooling2dSize3Int16Test</a>(</div><div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>&#160;{</div><div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>&#160; <span class="keywordflow">return</span> IgnorePaddingMaxPooling2dSize3TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>&#160;}</div><div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>&#160;</div><div class="line"><a name="l01478"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a12f407a57b0a6ae541ad67275e398788"> 1478</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a12f407a57b0a6ae541ad67275e398788">SimpleAveragePooling2dTest</a>(</div><div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>&#160;{</div><div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>&#160; <span class="keywordflow">return</span> SimpleAveragePooling2dTestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>&#160;}</div><div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>&#160;</div><div class="line"><a name="l01486"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a1b114f8624e335814f7a17856669ada2"> 1486</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a1b114f8624e335814f7a17856669ada2">SimpleAveragePooling2dUint8Test</a>(</div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>&#160; 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<a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>&#160; <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>&#160;{</div><div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>&#160; <span class="keywordflow">return</span> IgnorePaddingAveragePooling2dSize3x2Stride2x2TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>&#160; workloadFactory, memoryManager, forceNoPadding);</div><div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>&#160;}</div><div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>&#160;</div><div class="line"><a name="l01513"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a3929c1959366adb6236ad41acee93b19"> 1513</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a3929c1959366adb6236ad41acee93b19">LargeTensorsAveragePooling2dTest</a>(</div><div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>&#160;{</div><div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>&#160; <span class="keywordflow">return</span> LargeTensorsAveragePooling2dTestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>&#160;}</div><div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>&#160;</div><div class="line"><a name="l01520"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a6b0562007adce4063f111fa1e90e4344"> 1520</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a6b0562007adce4063f111fa1e90e4344">LargeTensorsAveragePooling2dUint8Test</a>(</div><div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>&#160; 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<a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>&#160;{</div><div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>&#160; <span class="keywordflow">return</span> LargeTensorsAveragePooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>&#160;}</div><div class="line"><a name="l01535"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a5103df4c034f9679776cd55e81cd93a4"> 1535</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a5103df4c034f9679776cd55e81cd93a4">IgnorePaddingSimpleAveragePooling2dTest</a>(</div><div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>&#160;{</div><div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dTestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01540"></a><span class="lineno"> 1540</span>&#160;}</div><div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>&#160;</div><div class="line"><a name="l01542"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#afdc8b9898475e00425b125447eb0bf3e"> 1542</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#afdc8b9898475e00425b125447eb0bf3e">IgnorePaddingSimpleAveragePooling2dUint8Test</a>(</div><div class="line"><a name="l01543"></a><span class="lineno"> 1543</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>&#160;{</div><div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>&#160;}</div><div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>&#160;</div><div class="line"><a name="l01550"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a13ccef523e801fb5fdc2868fae871a26"> 1550</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a13ccef523e801fb5fdc2868fae871a26">IgnorePaddingSimpleAveragePooling2dInt16Test</a>(</div><div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>&#160;{</div><div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>&#160;}</div><div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>&#160;</div><div class="line"><a name="l01558"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a19f29e6ac7af2f7ee8316048c6638aff"> 1558</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a19f29e6ac7af2f7ee8316048c6638aff">IgnorePaddingSimpleAveragePooling2dNoPaddingTest</a>(</div><div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>&#160;{</div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>&#160;}</div><div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>&#160;</div><div class="line"><a name="l01566"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#abdb3d542a8c5a5e6a42cb91e3ebce21f"> 1566</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#abdb3d542a8c5a5e6a42cb91e3ebce21f">IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test</a>(</div><div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>&#160;{</div><div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>&#160;}</div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>&#160;</div><div class="line"><a name="l01574"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a7c0c120c3d2c63941fd2dec93b7d9564"> 1574</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a7c0c120c3d2c63941fd2dec93b7d9564">IgnorePaddingSimpleAveragePooling2dNoPaddingInt16Test</a>(</div><div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>&#160;{</div><div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>&#160;}</div><div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>&#160;</div><div class="line"><a name="l01582"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a01264032fbe8272556bf1142b7cd74b1"> 1582</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a01264032fbe8272556bf1142b7cd74b1">IgnorePaddingAveragePooling2dSize3Test</a>(</div><div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>&#160;{</div><div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>&#160; <span class="keywordflow">return</span> IgnorePaddingAveragePooling2dSize3TestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>&#160;}</div><div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>&#160;</div><div class="line"><a name="l01589"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#ad5690176a9dd35986a5e895f1378efc0"> 1589</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#ad5690176a9dd35986a5e895f1378efc0">IgnorePaddingAveragePooling2dSize3Uint8Test</a>(</div><div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01592"></a><span class="lineno"> 1592</span>&#160;{</div><div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>&#160; <span class="keywordflow">return</span> IgnorePaddingAveragePooling2dSize3TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01595"></a><span class="lineno"> 1595</span>&#160;}</div><div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>&#160;</div><div class="line"><a name="l01597"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a3a693fe529564ec9bdf6b66965b0083e"> 1597</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a3a693fe529564ec9bdf6b66965b0083e">IgnorePaddingAveragePooling2dSize3Int16Test</a>(</div><div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>&#160;{</div><div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>&#160; <span class="keywordflow">return</span> IgnorePaddingAveragePooling2dSize3TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>&#160; workloadFactory, memoryManager);</div><div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>&#160;}</div><div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>&#160;</div><div class="line"><a name="l01605"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a26dc25f8fe0401dd5b9c1c733ed14f3d"> 1605</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a26dc25f8fe0401dd5b9c1c733ed14f3d">SimpleL2Pooling2dTest</a>(</div><div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>&#160;{</div><div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>&#160; <span class="keywordflow">return</span> SimpleL2Pooling2dTestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>&#160;}</div><div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>&#160;</div><div class="line"><a name="l01613"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#aafecf98426773306be1715559ea4019e"> 1613</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#aafecf98426773306be1715559ea4019e">SimpleL2Pooling2dUint8Test</a>(</div><div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01615"></a><span class="lineno"> 1615</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>&#160;{</div><div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>&#160; <span class="keywordflow">return</span> SimpleL2Pooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l01619"></a><span class="lineno"> 1619</span>&#160;}</div><div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>&#160;</div><div class="line"><a name="l01621"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a9ed42b523afa1b8017f75478bf90d28b"> 1621</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a9ed42b523afa1b8017f75478bf90d28b">SimpleL2Pooling2dInt16Test</a>(</div><div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>&#160;{</div><div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>&#160; <span class="keywordflow">return</span> SimpleL2Pooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>&#160;}</div><div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>&#160;</div><div class="line"><a name="l01629"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a8d68b7bc57ed5234008b9cc8f67f13ae"> 1629</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a8d68b7bc57ed5234008b9cc8f67f13ae">L2Pooling2dSize3Stride1Test</a>(</div><div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>&#160;{</div><div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize3Stride1TestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>&#160;}</div><div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>&#160;</div><div class="line"><a name="l01636"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#adfc1ba9f35e1c8657ba32d3d6d56a76e"> 1636</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#adfc1ba9f35e1c8657ba32d3d6d56a76e">L2Pooling2dSize3Stride1Uint8Test</a>(</div><div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>&#160;{</div><div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize3Stride1TestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01641"></a><span class="lineno"> 1641</span>&#160;}</div><div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>&#160;</div><div class="line"><a name="l01643"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a35c905df849b9042cf2b1d64b673018e"> 1643</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a35c905df849b9042cf2b1d64b673018e">L2Pooling2dSize3Stride1Int16Test</a>(</div><div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>&#160;{</div><div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize3Stride1TestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>&#160;}</div><div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>&#160;</div><div class="line"><a name="l01650"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#ae82ddbd442401119c0d873cc08384ba4"> 1650</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#ae82ddbd442401119c0d873cc08384ba4">L2Pooling2dSize3Stride3Test</a>(</div><div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>&#160;{</div><div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize3Stride3TestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01655"></a><span class="lineno"> 1655</span>&#160;}</div><div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>&#160;</div><div class="line"><a name="l01657"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a8c53d690773392aeeaa0eeae95fd16e2"> 1657</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a8c53d690773392aeeaa0eeae95fd16e2">L2Pooling2dSize3Stride3Uint8Test</a>(</div><div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>&#160;{</div><div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize3Stride3TestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>&#160;}</div><div class="line"><a name="l01663"></a><span class="lineno"> 1663</span>&#160;</div><div class="line"><a name="l01664"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a89809041249c49e29272cabb382e6898"> 1664</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a89809041249c49e29272cabb382e6898">L2Pooling2dSize3Stride3Int16Test</a>(</div><div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>&#160;{</div><div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize3Stride3TestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>&#160;}</div><div class="line"><a name="l01670"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#aa9dce9d99b3c10eedf8abfd853478e0a"> 1670</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#aa9dce9d99b3c10eedf8abfd853478e0a">L2Pooling2dSize3Stride4Test</a>(</div><div class="line"><a name="l01671"></a><span class="lineno"> 1671</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01672"></a><span class="lineno"> 1672</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01673"></a><span class="lineno"> 1673</span>&#160;{</div><div class="line"><a name="l01674"></a><span class="lineno"> 1674</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize3Stride4TestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01675"></a><span class="lineno"> 1675</span>&#160;}</div><div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>&#160;</div><div class="line"><a name="l01677"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#af936b77fe82b71e5cbd58cad48b1bfc2"> 1677</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#af936b77fe82b71e5cbd58cad48b1bfc2">L2Pooling2dSize3Stride4Uint8Test</a>(</div><div class="line"><a name="l01678"></a><span class="lineno"> 1678</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01680"></a><span class="lineno"> 1680</span>&#160;{</div><div class="line"><a name="l01681"></a><span class="lineno"> 1681</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize3Stride4TestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01682"></a><span class="lineno"> 1682</span>&#160;}</div><div class="line"><a name="l01683"></a><span class="lineno"> 1683</span>&#160;</div><div class="line"><a name="l01684"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#afbe0dfcc631615f3de96b415788e5630"> 1684</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#afbe0dfcc631615f3de96b415788e5630">L2Pooling2dSize3Stride4Int16Test</a>(</div><div class="line"><a name="l01685"></a><span class="lineno"> 1685</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01686"></a><span class="lineno"> 1686</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01687"></a><span class="lineno"> 1687</span>&#160;{</div><div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize3Stride4TestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01689"></a><span class="lineno"> 1689</span>&#160;}</div><div class="line"><a name="l01690"></a><span class="lineno"> 1690</span>&#160;</div><div class="line"><a name="l01691"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#ae4591d1175ba7115661b8eb80745cb64"> 1691</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#ae4591d1175ba7115661b8eb80745cb64">L2Pooling2dSize7Test</a>(</div><div class="line"><a name="l01692"></a><span class="lineno"> 1692</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01693"></a><span class="lineno"> 1693</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01694"></a><span class="lineno"> 1694</span>&#160;{</div><div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize7TestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01696"></a><span class="lineno"> 1696</span>&#160;}</div><div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>&#160;</div><div class="line"><a name="l01698"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a7a85e2ce7c2117c9e2ab829be378deb0"> 1698</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a7a85e2ce7c2117c9e2ab829be378deb0">L2Pooling2dSize7Uint8Test</a>(</div><div class="line"><a name="l01699"></a><span class="lineno"> 1699</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01701"></a><span class="lineno"> 1701</span>&#160;{</div><div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize7TestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01703"></a><span class="lineno"> 1703</span>&#160;}</div><div class="line"><a name="l01704"></a><span class="lineno"> 1704</span>&#160;</div><div class="line"><a name="l01705"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a819c382960e69594f22f5e11a9fbf5bb"> 1705</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a819c382960e69594f22f5e11a9fbf5bb">L2Pooling2dSize7Int16Test</a>(</div><div class="line"><a name="l01706"></a><span class="lineno"> 1706</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01707"></a><span class="lineno"> 1707</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01708"></a><span class="lineno"> 1708</span>&#160;{</div><div class="line"><a name="l01709"></a><span class="lineno"> 1709</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize7TestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>&#160;}</div><div class="line"><a name="l01711"></a><span class="lineno"> 1711</span>&#160;</div><div class="line"><a name="l01712"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#ae6eec78e8c9af37214d683eb97085ffb"> 1712</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#ae6eec78e8c9af37214d683eb97085ffb">L2Pooling2dSize9Test</a>(</div><div class="line"><a name="l01713"></a><span class="lineno"> 1713</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01714"></a><span class="lineno"> 1714</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01715"></a><span class="lineno"> 1715</span>&#160;{</div><div class="line"><a name="l01716"></a><span class="lineno"> 1716</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize9TestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01717"></a><span class="lineno"> 1717</span>&#160;}</div><div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>&#160;</div><div class="line"><a name="l01719"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a416503aafd0e95894ff1d40bf4b9750e"> 1719</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a416503aafd0e95894ff1d40bf4b9750e">L2Pooling2dSize9Uint8Test</a>(</div><div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>&#160;{</div><div class="line"><a name="l01723"></a><span class="lineno"> 1723</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize9TestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01724"></a><span class="lineno"> 1724</span>&#160;}</div><div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>&#160;</div><div class="line"><a name="l01726"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a23dfab8d454bf41fccb664a0cfce3db2"> 1726</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a23dfab8d454bf41fccb664a0cfce3db2">L2Pooling2dSize9Int16Test</a>(</div><div class="line"><a name="l01727"></a><span class="lineno"> 1727</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01728"></a><span class="lineno"> 1728</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>&#160;{</div><div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>&#160; <span class="keywordflow">return</span> L2Pooling2dSize9TestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01731"></a><span class="lineno"> 1731</span>&#160;}</div><div class="line"><a name="l01732"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#aa89af1e396c0f689aa6078f6a3f45825"> 1732</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#aa89af1e396c0f689aa6078f6a3f45825">IgnorePaddingSimpleL2Pooling2dTest</a>(</div><div class="line"><a name="l01733"></a><span class="lineno"> 1733</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01734"></a><span class="lineno"> 1734</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01735"></a><span class="lineno"> 1735</span>&#160;{</div><div class="line"><a name="l01736"></a><span class="lineno"> 1736</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleL2Pooling2dTestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01737"></a><span class="lineno"> 1737</span>&#160;}</div><div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>&#160;</div><div class="line"><a name="l01739"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#aab64d2d563a7dbca5e5f47d95774ac52"> 1739</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#aab64d2d563a7dbca5e5f47d95774ac52">IgnorePaddingSimpleL2Pooling2dUint8Test</a>(</div><div class="line"><a name="l01740"></a><span class="lineno"> 1740</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01742"></a><span class="lineno"> 1742</span>&#160;{</div><div class="line"><a name="l01743"></a><span class="lineno"> 1743</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleL2Pooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01744"></a><span class="lineno"> 1744</span>&#160;}</div><div class="line"><a name="l01745"></a><span class="lineno"> 1745</span>&#160;</div><div class="line"><a name="l01746"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a9b1409ed5591fd540c6102628897ebf6"> 1746</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a9b1409ed5591fd540c6102628897ebf6">IgnorePaddingSimpleL2Pooling2dInt16Test</a>(</div><div class="line"><a name="l01747"></a><span class="lineno"> 1747</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01748"></a><span class="lineno"> 1748</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01749"></a><span class="lineno"> 1749</span>&#160;{</div><div class="line"><a name="l01750"></a><span class="lineno"> 1750</span>&#160; <span class="keywordflow">return</span> IgnorePaddingSimpleL2Pooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01751"></a><span class="lineno"> 1751</span>&#160;}</div><div class="line"><a name="l01752"></a><span class="lineno"> 1752</span>&#160;</div><div class="line"><a name="l01753"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#ac5c1d6307ea085e55299611717f17756"> 1753</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#ac5c1d6307ea085e55299611717f17756">IgnorePaddingL2Pooling2dSize3Test</a>(</div><div class="line"><a name="l01754"></a><span class="lineno"> 1754</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01755"></a><span class="lineno"> 1755</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01756"></a><span class="lineno"> 1756</span>&#160;{</div><div class="line"><a name="l01757"></a><span class="lineno"> 1757</span>&#160; <span class="keywordflow">return</span> IgnorePaddingL2Pooling2dSize3TestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01758"></a><span class="lineno"> 1758</span>&#160;}</div><div class="line"><a name="l01759"></a><span class="lineno"> 1759</span>&#160;</div><div class="line"><a name="l01760"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a671584b349d7c94cd7c108c8507ba149"> 1760</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a671584b349d7c94cd7c108c8507ba149">IgnorePaddingL2Pooling2dSize3Uint8Test</a>(</div><div class="line"><a name="l01761"></a><span class="lineno"> 1761</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01762"></a><span class="lineno"> 1762</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01763"></a><span class="lineno"> 1763</span>&#160;{</div><div class="line"><a name="l01764"></a><span class="lineno"> 1764</span>&#160; <span class="keywordflow">return</span> IgnorePaddingL2Pooling2dSize3TestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01765"></a><span class="lineno"> 1765</span>&#160;}</div><div class="line"><a name="l01766"></a><span class="lineno"> 1766</span>&#160;</div><div class="line"><a name="l01767"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#ab721b365fc476b3917abe60c802823b7"> 1767</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#ab721b365fc476b3917abe60c802823b7">IgnorePaddingL2Pooling2dSize3Int16Test</a>(</div><div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01770"></a><span class="lineno"> 1770</span>&#160;{</div><div class="line"><a name="l01771"></a><span class="lineno"> 1771</span>&#160; <span class="keywordflow">return</span> IgnorePaddingL2Pooling2dSize3TestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01772"></a><span class="lineno"> 1772</span>&#160;}</div><div class="line"><a name="l01773"></a><span class="lineno"> 1773</span>&#160;</div><div class="line"><a name="l01774"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a2b1ede7e8d8e5dad79d99030f57b8745"> 1774</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a2b1ede7e8d8e5dad79d99030f57b8745">AsymmetricNonSquarePooling2dTest</a>(</div><div class="line"><a name="l01775"></a><span class="lineno"> 1775</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01776"></a><span class="lineno"> 1776</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01777"></a><span class="lineno"> 1777</span>&#160;{</div><div class="line"><a name="l01778"></a><span class="lineno"> 1778</span>&#160; <span class="keywordflow">return</span> AsymmetricNonSquarePooling2dTestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01779"></a><span class="lineno"> 1779</span>&#160;}</div><div class="line"><a name="l01780"></a><span class="lineno"> 1780</span>&#160;</div><div class="line"><a name="l01781"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a1a1e6dc70b7f1ca0c99fd6f0b48b4d48"> 1781</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a1a1e6dc70b7f1ca0c99fd6f0b48b4d48">AsymmetricNonSquarePooling2dUint8Test</a>(</div><div class="line"><a name="l01782"></a><span class="lineno"> 1782</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01783"></a><span class="lineno"> 1783</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01784"></a><span class="lineno"> 1784</span>&#160;{</div><div class="line"><a name="l01785"></a><span class="lineno"> 1785</span>&#160; <span class="keywordflow">return</span> AsymmetricNonSquarePooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01786"></a><span class="lineno"> 1786</span>&#160;}</div><div class="line"><a name="l01787"></a><span class="lineno"> 1787</span>&#160;</div><div class="line"><a name="l01788"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a866c67e5db471212f6ff29411aac0e8f"> 1788</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a866c67e5db471212f6ff29411aac0e8f">AsymmetricNonSquarePooling2dInt16Test</a>(</div><div class="line"><a name="l01789"></a><span class="lineno"> 1789</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01790"></a><span class="lineno"> 1790</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager)</div><div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>&#160;{</div><div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>&#160; <span class="keywordflow">return</span> AsymmetricNonSquarePooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(workloadFactory, memoryManager);</div><div class="line"><a name="l01793"></a><span class="lineno"> 1793</span>&#160;}</div><div class="line"><a name="l01794"></a><span class="lineno"> 1794</span>&#160;</div><div class="line"><a name="l01795"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a694dbeb3a87d65cd3cb854b5ced22a5b"> 1795</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a694dbeb3a87d65cd3cb854b5ced22a5b">ComparePooling2dTest</a>(</div><div class="line"><a name="l01796"></a><span class="lineno"> 1796</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01797"></a><span class="lineno"> 1797</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01798"></a><span class="lineno"> 1798</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; refWorkloadFactory,</div><div class="line"><a name="l01799"></a><span class="lineno"> 1799</span>&#160; <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a> poolingType)</div><div class="line"><a name="l01800"></a><span class="lineno"> 1800</span>&#160;{</div><div class="line"><a name="l01801"></a><span class="lineno"> 1801</span>&#160; <span class="keywordflow">return</span> ComparePooling2dTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01802"></a><span class="lineno"> 1802</span>&#160; workloadFactory, memoryManager, refWorkloadFactory, poolingType);</div><div class="line"><a name="l01803"></a><span class="lineno"> 1803</span>&#160;}</div><div class="line"><a name="l01804"></a><span class="lineno"> 1804</span>&#160;</div><div class="line"><a name="l01805"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#a7e5faed333caf71f1a19839308368046"> 1805</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#a7e5faed333caf71f1a19839308368046">ComparePooling2dUint8Test</a>(</div><div class="line"><a name="l01806"></a><span class="lineno"> 1806</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01807"></a><span class="lineno"> 1807</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01808"></a><span class="lineno"> 1808</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; refWorkloadFactory,</div><div class="line"><a name="l01809"></a><span class="lineno"> 1809</span>&#160; <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a> poolingType)</div><div class="line"><a name="l01810"></a><span class="lineno"> 1810</span>&#160;{</div><div class="line"><a name="l01811"></a><span class="lineno"> 1811</span>&#160; <span class="keywordflow">return</span> ComparePooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01812"></a><span class="lineno"> 1812</span>&#160; workloadFactory, memoryManager, refWorkloadFactory, poolingType, 0.1f, 128);</div><div class="line"><a name="l01813"></a><span class="lineno"> 1813</span>&#160;}</div><div class="line"><a name="l01814"></a><span class="lineno"> 1814</span>&#160;</div><div class="line"><a name="l01815"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.html#ad67e6517d14f15abee1d159e89deb5fd"> 1815</a></span>&#160;<a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.html#ad67e6517d14f15abee1d159e89deb5fd">ComparePooling2dInt16Test</a>(</div><div class="line"><a name="l01816"></a><span class="lineno"> 1816</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01817"></a><span class="lineno"> 1817</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01818"></a><span class="lineno"> 1818</span>&#160; <a class="code" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a>&amp; refWorkloadFactory,</div><div class="line"><a name="l01819"></a><span class="lineno"> 1819</span>&#160; <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a> poolingType)</div><div class="line"><a name="l01820"></a><span class="lineno"> 1820</span>&#160;{</div><div class="line"><a name="l01821"></a><span class="lineno"> 1821</span>&#160; <span class="keywordflow">return</span> ComparePooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01822"></a><span class="lineno"> 1822</span>&#160; workloadFactory, memoryManager, refWorkloadFactory, poolingType);</div><div class="line"><a name="l01823"></a><span class="lineno"> 1823</span>&#160;}</div><div class="ttc" id="src_2backends_2backends_common_2_workload_info_8hpp_html"><div class="ttname"><a href="src_2backends_2backends_common_2_workload_info_8hpp.html">WorkloadInfo.hpp</a></div></div>
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<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a694dbeb3a87d65cd3cb854b5ced22a5b"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a694dbeb3a87d65cd3cb854b5ced22a5b">ComparePooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; ComparePooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, armnn::IWorkloadFactory &amp;refWorkloadFactory, armnn::PoolingAlgorithm poolingType)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01795">Pooling2dTestImpl.cpp:1795</a></div></div>
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<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a7e5faed333caf71f1a19839308368046"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a7e5faed333caf71f1a19839308368046">ComparePooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; ComparePooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, armnn::IWorkloadFactory &amp;refWorkloadFactory, armnn::PoolingAlgorithm poolingType)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01805">Pooling2dTestImpl.cpp:1805</a></div></div>
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<div class="ttc" id="namespacearmnn_utils_html_af3c74017185773dd61d8ca6662d65d43"><div class="ttname"><a href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a></div><div class="ttdeci">void Permute(const armnn::TensorShape &amp;dstShape, const armnn::PermutationVector &amp;mappings, const void *src, void *dst, size_t dataTypeSize)</div><div class="ttdef"><b>Definition:</b> <a href="_permute_8cpp_source.html#l00121">Permute.cpp:121</a></div></div>
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<div class="ttc" id="classarmnn_1_1_permutation_vector_html"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00170">Types.hpp:170</a></div></div>
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<div class="ttc" id="_permute_8hpp_html"><div class="ttname"><a href="_permute_8hpp.html">Permute.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_aa9dce9d99b3c10eedf8abfd853478e0a"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#aa9dce9d99b3c10eedf8abfd853478e0a">L2Pooling2dSize3Stride4Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize3Stride4Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01670">Pooling2dTestImpl.cpp:1670</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_afb670e621e8c15f457eb0b178ff70f93"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#afb670e621e8c15f457eb0b178ff70f93">LargeTensorsAveragePooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; LargeTensorsAveragePooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01528">Pooling2dTestImpl.cpp:1528</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_ad5690176a9dd35986a5e895f1378efc0"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#ad5690176a9dd35986a5e895f1378efc0">IgnorePaddingAveragePooling2dSize3Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingAveragePooling2dSize3Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01589">Pooling2dTestImpl.cpp:1589</a></div></div>
<div class="ttc" id="namespacearmnn_utils_html_acee63cd08da47910fc166a1990988fa8"><div class="ttname"><a href="namespacearmnn_utils.html#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a></div><div class="ttdeci">armnn::TensorInfo GetTensorInfo(unsigned int numberOfBatches, unsigned int numberOfChannels, unsigned int height, unsigned int width, const armnn::DataLayout dataLayout, const armnn::DataType dataType)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00038">TensorUtils.cpp:38</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">armnn::Pooling2dDescriptor::m_PoolHeight</a></div><div class="ttdeci">uint32_t m_PoolHeight</div><div class="ttdoc">Pooling height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00359">Descriptors.hpp:359</a></div></div>
<div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
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<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr&lt; ITensorHandle &gt; CreateTensorHandle(const TensorInfo &amp;tensorInfo, const bool IsMemoryManaged=true) const =0</div></div>
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<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a01264032fbe8272556bf1142b7cd74b1"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a01264032fbe8272556bf1142b7cd74b1">IgnorePaddingAveragePooling2dSize3Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingAveragePooling2dSize3Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01582">Pooling2dTestImpl.cpp:1582</a></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="_pooling2d_test_impl_8cpp_html_a5ff218665f1e7dc5b90c395027573e8c"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a5ff218665f1e7dc5b90c395027573e8c">SimpleMaxPooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; SimpleMaxPooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01425">Pooling2dTestImpl.cpp:1425</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::Pooling2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00351">Descriptors.hpp:351</a></div></div>
<div class="ttc" id="_tensor_utils_8hpp_html"><div class="ttname"><a href="_tensor_utils_8hpp.html">TensorUtils.hpp</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="_pooling2d_test_impl_8cpp_html_a7a85e2ce7c2117c9e2ab829be378deb0"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a7a85e2ce7c2117c9e2ab829be378deb0">L2Pooling2dSize7Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize7Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01698">Pooling2dTestImpl.cpp:1698</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_af936b77fe82b71e5cbd58cad48b1bfc2"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#af936b77fe82b71e5cbd58cad48b1bfc2">L2Pooling2dSize3Stride4Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize3Stride4Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01677">Pooling2dTestImpl.cpp:1677</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&lt; IMemoryManager &gt; 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="_pooling2d_test_impl_8cpp_html_af0a9b7e26de79a55506a3cd3d36a83a7"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#af0a9b7e26de79a55506a3cd3d36a83a7">IgnorePaddingSimpleMaxPooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingSimpleMaxPooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01447">Pooling2dTestImpl.cpp:1447</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a50dff405960b48e03ee0d296f72743df"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a50dff405960b48e03ee0d296f72743df">SimpleMaxPooling2dSize2x2Stride2x2Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; SimpleMaxPooling2dSize2x2Stride2x2Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01373">Pooling2dTestImpl.cpp:1373</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a9f7e4296485d2812e7996089149c96d1"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a9f7e4296485d2812e7996089149c96d1">armnn::IWorkloadFactory::GetBackendId</a></div><div class="ttdeci">virtual const BackendId &amp; GetBackendId() const =0</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="_pooling2d_test_impl_8cpp_html_ac5c1d6307ea085e55299611717f17756"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#ac5c1d6307ea085e55299611717f17756">IgnorePaddingL2Pooling2dSize3Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingL2Pooling2dSize3Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01753">Pooling2dTestImpl.cpp:1753</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a2008735411bf96a7febef693c41a4ff5"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a2008735411bf96a7febef693c41a4ff5">IgnorePaddingSimpleMaxPooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingSimpleMaxPooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01432">Pooling2dTestImpl.cpp:1432</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_ad67e6517d14f15abee1d159e89deb5fd"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#ad67e6517d14f15abee1d159e89deb5fd">ComparePooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; ComparePooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, armnn::IWorkloadFactory &amp;refWorkloadFactory, armnn::PoolingAlgorithm poolingType)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01815">Pooling2dTestImpl.cpp:1815</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a1b114f8624e335814f7a17856669ada2"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a1b114f8624e335814f7a17856669ada2">SimpleAveragePooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; SimpleAveragePooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01486">Pooling2dTestImpl.cpp:1486</a></div></div>
<div class="ttc" id="_resolve_type_8hpp_html"><div class="ttname"><a href="_resolve_type_8hpp.html">ResolveType.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a08f2f1d9a1f69a5799294a881dbb24b4"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a08f2f1d9a1f69a5799294a881dbb24b4">IgnorePaddingMaxPooling2dSize3Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingMaxPooling2dSize3Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01455">Pooling2dTestImpl.cpp:1455</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a7f7147713ac3346b30c1071bf14fb374"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a7f7147713ac3346b30c1071bf14fb374">IgnorePaddingMaxPooling2dSize3Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingMaxPooling2dSize3Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01462">Pooling2dTestImpl.cpp:1462</a></div></div>
<div class="ttc" id="classarmnn_1_1_backend_id_html"><div class="ttname"><a href="classarmnn_1_1_backend_id.html">armnn::BackendId</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.html#l00075">BackendId.hpp:75</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a414e6f95548e6f7a01d5028b55ad3941"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">armnnUtils::DataLayoutIndexed::GetWidthIndex</a></div><div class="ttdeci">unsigned int GetWidthIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00025">DataLayoutIndexed.hpp:25</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">armnn::Pooling2dDescriptor::m_PoolWidth</a></div><div class="ttdeci">uint32_t m_PoolWidth</div><div class="ttdoc">Pooling width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00357">Descriptors.hpp:357</a></div></div>
<div class="ttc" id="namespacearmnn_html_a961bbfe1db71a848eff5a1f0ab775718"><div class="ttname"><a href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a></div><div class="ttdeci">PoolingAlgorithm</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00093">Types.hpp:93</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_ab721b365fc476b3917abe60c802823b7"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#ab721b365fc476b3917abe60c802823b7">IgnorePaddingL2Pooling2dSize3Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingL2Pooling2dSize3Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01767">Pooling2dTestImpl.cpp:1767</a></div></div>
<div class="ttc" id="namespacearmnn_html_a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a"><div class="ttname"><a href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a></div><div class="ttdoc">The padding fields count, but are ignored. </div></div>
<div class="ttc" id="namespacearmnn_utils_html"><div class="ttname"><a href="namespacearmnn_utils.html">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00013">DataLayoutIndexed.hpp:13</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_acf9c19888a6f2139b355052d542920bb"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#acf9c19888a6f2139b355052d542920bb">IgnorePaddingMaxPooling2dSize3Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingMaxPooling2dSize3Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01470">Pooling2dTestImpl.cpp:1470</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_aab64d2d563a7dbca5e5f47d95774ac52"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#aab64d2d563a7dbca5e5f47d95774ac52">IgnorePaddingSimpleL2Pooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingSimpleL2Pooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01739">Pooling2dTestImpl.cpp:1739</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_adb17ca1fb168506bdd494149525c4dea"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#adb17ca1fb168506bdd494149525c4dea">IgnorePaddingAveragePooling2dSize3x2Stride2x2Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingAveragePooling2dSize3x2Stride2x2Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01504">Pooling2dTestImpl.cpp:1504</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a12f407a57b0a6ae541ad67275e398788"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a12f407a57b0a6ae541ad67275e398788">SimpleAveragePooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleAveragePooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01478">Pooling2dTestImpl.cpp:1478</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a7c0c120c3d2c63941fd2dec93b7d9564"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a7c0c120c3d2c63941fd2dec93b7d9564">IgnorePaddingSimpleAveragePooling2dNoPaddingInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingSimpleAveragePooling2dNoPaddingInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01574">Pooling2dTestImpl.cpp:1574</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a3929c1959366adb6236ad41acee93b19"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a3929c1959366adb6236ad41acee93b19">LargeTensorsAveragePooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; LargeTensorsAveragePooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01513">Pooling2dTestImpl.cpp:1513</a></div></div>
<div class="ttc" id="namespacearmnn_html_a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6"><div class="ttname"><a href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a></div><div class="ttdoc">The padding fields don&amp;#39;t count and are ignored. </div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a2f7ec646738a0e279cfbb77afb3e41bd"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a2f7ec646738a0e279cfbb77afb3e41bd">SimpleMaxPooling2dSize3x3Stride2x4Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleMaxPooling2dSize3x3Stride2x4Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01382">Pooling2dTestImpl.cpp:1382</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a6f4185540ddce123892c799e516ee50d"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a6f4185540ddce123892c799e516ee50d">SimpleMaxPooling2dSize2x2Stride2x2Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; SimpleMaxPooling2dSize2x2Stride2x2Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01364">Pooling2dTestImpl.cpp:1364</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a807ea3c4451f81f5b91b7db53eb0a138"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a807ea3c4451f81f5b91b7db53eb0a138">SimpleMaxPooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; SimpleMaxPooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01417">Pooling2dTestImpl.cpp:1417</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00259">Tensor.cpp:259</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Pooling2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00349">Descriptors.hpp:349</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_html_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorShape::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00106">Tensor.cpp:106</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a9b1409ed5591fd540c6102628897ebf6"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a9b1409ed5591fd540c6102628897ebf6">IgnorePaddingSimpleL2Pooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingSimpleL2Pooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01746">Pooling2dTestImpl.cpp:1746</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a9ed42b523afa1b8017f75478bf90d28b"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a9ed42b523afa1b8017f75478bf90d28b">SimpleL2Pooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; SimpleL2Pooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01621">Pooling2dTestImpl.cpp:1621</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a866c67e5db471212f6ff29411aac0e8f"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a866c67e5db471212f6ff29411aac0e8f">AsymmetricNonSquarePooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; AsymmetricNonSquarePooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01788">Pooling2dTestImpl.cpp:1788</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="classarmnn_1_1_i_workload_factory_html_a6e95afd9a55700cbf6f9e8db8089f2f2"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a6e95afd9a55700cbf6f9e8db8089f2f2">armnn::IWorkloadFactory::CreatePooling2d</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreatePooling2d(const Pooling2dQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01323">WorkloadFactory.cpp:1323</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a0040a2bec5090be39bc6c4382fb7b6ee"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a0040a2bec5090be39bc6c4382fb7b6ee">SimpleAveragePooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; SimpleAveragePooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01495">Pooling2dTestImpl.cpp:1495</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a8c29d6ea9b4186d69aad5961c910939c"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">armnn::Pooling2dDescriptor::m_PaddingMethod</a></div><div class="ttdeci">PaddingMethod m_PaddingMethod</div><div class="ttdoc">The padding method to be used. (Exclude, IgnoreValue). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00367">Descriptors.hpp:367</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a861b2621ee46e4b63379988b360b8cd9"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">armnnUtils::DataLayoutIndexed::GetChannelsIndex</a></div><div class="ttdeci">unsigned int GetChannelsIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00023">DataLayoutIndexed.hpp:23</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="_data_layout_indexed_8hpp_html"><div class="ttname"><a href="_data_layout_indexed_8hpp.html">DataLayoutIndexed.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a3a693fe529564ec9bdf6b66965b0083e"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a3a693fe529564ec9bdf6b66965b0083e">IgnorePaddingAveragePooling2dSize3Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingAveragePooling2dSize3Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01597">Pooling2dTestImpl.cpp:1597</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_affb5b68b3eba3ed45a06c7cde7781962"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#affb5b68b3eba3ed45a06c7cde7781962">armnn::Pooling2dDescriptor::m_OutputShapeRounding</a></div><div class="ttdeci">OutputShapeRounding m_OutputShapeRounding</div><div class="ttdoc">The rounding method for the output shape. (Floor, Ceiling). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00365">Descriptors.hpp:365</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_ae6eec78e8c9af37214d683eb97085ffb"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#ae6eec78e8c9af37214d683eb97085ffb">L2Pooling2dSize9Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize9Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01712">Pooling2dTestImpl.cpp:1712</a></div></div>
<div class="ttc" id="namespacearmnn_html_a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76"><div class="ttname"><a href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a></div></div>
<div class="ttc" id="_layer_support_8hpp_html"><div class="ttname"><a href="_layer_support_8hpp.html">LayerSupport.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Pooling2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00363">Descriptors.hpp:363</a></div></div>
<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00048">Types.hpp:48</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">armnn::Pooling2dDescriptor::m_PoolType</a></div><div class="ttdeci">PoolingAlgorithm m_PoolType</div><div class="ttdoc">The pooling algorithm to use (Max. Average, L2). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00347">Descriptors.hpp:347</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a8c53d690773392aeeaa0eeae95fd16e2"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a8c53d690773392aeeaa0eeae95fd16e2">L2Pooling2dSize3Stride3Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize3Stride3Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01657">Pooling2dTestImpl.cpp:1657</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a13ccef523e801fb5fdc2868fae871a26"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a13ccef523e801fb5fdc2868fae871a26">IgnorePaddingSimpleAveragePooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingSimpleAveragePooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01550">Pooling2dTestImpl.cpp:1550</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a8d68b7bc57ed5234008b9cc8f67f13ae"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a8d68b7bc57ed5234008b9cc8f67f13ae">L2Pooling2dSize3Stride1Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize3Stride1Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01629">Pooling2dTestImpl.cpp:1629</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_aafecf98426773306be1715559ea4019e"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#aafecf98426773306be1715559ea4019e">SimpleL2Pooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; SimpleL2Pooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01613">Pooling2dTestImpl.cpp:1613</a></div></div>
<div class="ttc" id="namespacearmnn_html_aea548aa1485adbeeb3e393a13bb6bff8"><div class="ttname"><a href="namespacearmnn.html#aea548aa1485adbeeb3e393a13bb6bff8">armnn::IsPooling2dSupported</a></div><div class="ttdeci">bool IsPooling2dSupported(const BackendId &amp;backend, const TensorInfo &amp;input, const TensorInfo &amp;output, const Pooling2dDescriptor &amp;descriptor, char *reasonIfUnsupported=nullptr, size_t reasonIfUnsupportedMaxLength=1024)</div><div class="ttdoc">Deprecated in favor of IBackend and ILayerSupport interfaces. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_support_8cpp_source.html#l00511">LayerSupport.cpp:511</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_abdb3d542a8c5a5e6a42cb91e3ebce21f"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#abdb3d542a8c5a5e6a42cb91e3ebce21f">IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01566">Pooling2dTestImpl.cpp:1566</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a26dc25f8fe0401dd5b9c1c733ed14f3d"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a26dc25f8fe0401dd5b9c1c733ed14f3d">SimpleL2Pooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleL2Pooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01605">Pooling2dTestImpl.cpp:1605</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a23dfab8d454bf41fccb664a0cfce3db2"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a23dfab8d454bf41fccb664a0cfce3db2">L2Pooling2dSize9Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize9Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01726">Pooling2dTestImpl.cpp:1726</a></div></div>
<div class="ttc" id="namespacearmnn_html_adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3"><div class="ttname"><a href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00313">Descriptors.hpp:313</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_afdc8b9898475e00425b125447eb0bf3e"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#afdc8b9898475e00425b125447eb0bf3e">IgnorePaddingSimpleAveragePooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingSimpleAveragePooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01542">Pooling2dTestImpl.cpp:1542</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a35c905df849b9042cf2b1d64b673018e"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a35c905df849b9042cf2b1d64b673018e">L2Pooling2dSize3Stride1Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize3Stride1Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01643">Pooling2dTestImpl.cpp:1643</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Pooling2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00369">Descriptors.hpp:369</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_adfc1ba9f35e1c8657ba32d3d6d56a76e"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#adfc1ba9f35e1c8657ba32d3d6d56a76e">L2Pooling2dSize3Stride1Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize3Stride1Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01636">Pooling2dTestImpl.cpp:1636</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a416503aafd0e95894ff1d40bf4b9750e"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a416503aafd0e95894ff1d40bf4b9750e">L2Pooling2dSize9Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize9Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01719">Pooling2dTestImpl.cpp:1719</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00275">Tensor.cpp:275</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_ae398f1e979dd0ad467a8f5182b9101ee"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#ae398f1e979dd0ad467a8f5182b9101ee">SimpleMaxPooling2dSize3x3Stride2x4Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; SimpleMaxPooling2dSize3x3Stride2x4Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01400">Pooling2dTestImpl.cpp:1400</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00017">DataLayoutIndexed.hpp:17</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a89809041249c49e29272cabb382e6898"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a89809041249c49e29272cabb382e6898">L2Pooling2dSize3Stride3Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize3Stride3Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01664">Pooling2dTestImpl.cpp:1664</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_pooling2d_queue_descriptor.html">armnn::Pooling2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00162">WorkloadData.hpp:162</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_aacd91233b18641d11b190969bcd93057"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#aacd91233b18641d11b190969bcd93057">SimpleMaxPooling2dSize3x3Stride2x4Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; SimpleMaxPooling2dSize3x3Stride2x4Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01391">Pooling2dTestImpl.cpp:1391</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a6b0562007adce4063f111fa1e90e4344"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a6b0562007adce4063f111fa1e90e4344">LargeTensorsAveragePooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; LargeTensorsAveragePooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01520">Pooling2dTestImpl.cpp:1520</a></div></div>
<div class="ttc" id="namespacearmnn_html_a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021"><div class="ttname"><a href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::Pooling2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00355">Descriptors.hpp:355</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a0f8bd9f2e91b9b2aad21e2728bb655e3"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a0f8bd9f2e91b9b2aad21e2728bb655e3">SimpleMaxPooling2dSize2x2Stride2x2Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleMaxPooling2dSize2x2Stride2x2Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01355">Pooling2dTestImpl.cpp:1355</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape &amp; GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00088">Tensor.hpp:88</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_afbe0dfcc631615f3de96b415788e5630"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#afbe0dfcc631615f3de96b415788e5630">L2Pooling2dSize3Stride4Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize3Stride4Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01684">Pooling2dTestImpl.cpp:1684</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="_pooling2d_test_impl_8cpp_html_a819c382960e69594f22f5e11a9fbf5bb"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a819c382960e69594f22f5e11a9fbf5bb">L2Pooling2dSize7Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize7Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01705">Pooling2dTestImpl.cpp:1705</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Pooling2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00361">Descriptors.hpp:361</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a2b1ede7e8d8e5dad79d99030f57b8745"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a2b1ede7e8d8e5dad79d99030f57b8745">AsymmetricNonSquarePooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; AsymmetricNonSquarePooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01774">Pooling2dTestImpl.cpp:1774</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>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_a2783cdc0a074cbdfbf2f91e116c92c97"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#a2783cdc0a074cbdfbf2f91e116c92c97">SimpleMaxPooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleMaxPooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01409">Pooling2dTestImpl.cpp:1409</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_ae82ddbd442401119c0d873cc08384ba4"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#ae82ddbd442401119c0d873cc08384ba4">L2Pooling2dSize3Stride3Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize3Stride3Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01650">Pooling2dTestImpl.cpp:1650</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_html_ae4591d1175ba7115661b8eb80745cb64"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.html#ae4591d1175ba7115661b8eb80745cb64">L2Pooling2dSize7Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize7Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.html#l01691">Pooling2dTestImpl.cpp:1691</a></div></div>
<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
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