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<div class="title">Pooling2dTestImpl.cpp</div>  </div>
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<a href="_pooling2d_test_impl_8cpp.xhtml">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 and Contributors. 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.xhtml">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.xhtml">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.xhtml">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.xhtml">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.xhtml">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.xhtml">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.xhtml">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="_ignore_unused_8hpp.xhtml">armnn/utility/IgnoreUnused.hpp</a>&gt;</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_numeric_cast_8hpp.xhtml">armnn/utility/NumericCast.hpp</a>&gt;</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="src_2backends_2backends_common_2_workload_info_8hpp.xhtml">backendsCommon/WorkloadInfo.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_copy_utils_8hpp.xhtml">backendsCommon/test/TensorCopyUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_workload_test_utils_8hpp.xhtml">backendsCommon/test/WorkloadTestUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_helpers_8hpp.xhtml">test/TensorHelpers.hpp</a>&gt;</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="keyword">namespace</span></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;</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.xhtml">armnnUtils</a>;</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</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="l00033"></a><span class="lineno">   33</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> SimplePooling2dTestImpl(</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor,</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    int32_t qOffset,</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    <span class="keyword">const</span> boost::multi_array&lt;T, 4&gt;&amp; input,</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    <span class="keyword">const</span> boost::multi_array&lt;T, 4&gt;&amp; outputExpected)</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;{</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>;</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml">armnnUtils::DataLayoutIndexed</a> dimensionIndices = dataLayout;</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    <span class="keyword">auto</span> heightIndex = dimensionIndices.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>();</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;    <span class="keyword">auto</span> widthIndex = dimensionIndices.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>();</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;    <span class="keyword">auto</span> channelsIndex = dimensionIndices.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>();</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight     = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(input.shape()[heightIndex]);</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth      = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(input.shape()[widthIndex]);</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels   = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(input.shape()[channelsIndex]);</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize  = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(input.shape()[0]);</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight    = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(outputExpected.shape()[heightIndex]);</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth     = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(outputExpected.shape()[widthIndex]);</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels  = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(outputExpected.shape()[channelsIndex]);</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputBatchSize = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(outputExpected.shape()[0]);</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo  = <a class="code" href="namespacearmnn_utils.xhtml#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;        inputBatchSize, inputChannels, inputHeight, inputWidth, dataLayout, ArmnnType);</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_utils.xhtml#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;        outputBatchSize, outputChannels, outputHeight, outputWidth, dataLayout, ArmnnType);</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <span class="keywordflow">if</span>(armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    {</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;        inputTensorInfo.SetQuantizationScale(qScale);</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;        inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    }</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;    <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> result(outputTensorInfo);</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">armnn::Pooling2dQueueDescriptor</a> queueDescriptor;</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a> = descriptor;</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;</div><div class="line"><a name="l00088"></a><span class="lineno">   88</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="l00089"></a><span class="lineno">   89</span>&#160;    <a class="code" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> backend = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a9f7e4296485d2812e7996089149c96d1">GetBackendId</a>();</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> reasonIfUnsupportedMaxLen = 255;</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    <span class="keywordtype">char</span> reasonIfUnsupported[reasonIfUnsupportedMaxLen+1];</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    result.supported = <a class="code" href="namespacearmnn.xhtml#aea548aa1485adbeeb3e393a13bb6bff8">armnn::IsPooling2dSupported</a>(backend, inputTensorInfo, outputTensorInfo,</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;                                                   queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>,</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;                                                   reasonIfUnsupported, reasonIfUnsupportedMaxLen);</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    <span class="keywordflow">if</span> (!result.supported)</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;        <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    }</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;    std::unique_ptr&lt;armnn::IWorkload&gt; workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a6e95afd9a55700cbf6f9e8db8089f2f2">CreatePooling2d</a>(queueDescriptor, workloadInfo);</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    inputHandle-&gt;Allocate();</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;    outputHandle-&gt;Allocate();</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;    <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &amp;input[0][0][0][0]);</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;    workload-&gt;Execute();</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;    <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;result.output[0][0][0][0], outputHandle.get());</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;    result.outputExpected = outputExpected;</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;    <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;}</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;</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">// Tests max pooling with the following parameters:</span></div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;<span class="comment">//   Pooling size: 3x3</span></div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;<span class="comment">//   Stride:       (2,4)</span></div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;<span class="comment">//   input size:   8x13</span></div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;<span class="comment">//   channels:     2</span></div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;<span class="comment">//   batch size:   2</span></div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00125"></a><span class="lineno">  125</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="l00126"></a><span class="lineno">  126</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> SimpleMaxPooling2dSize3x3Stride2x4TestCommon(</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    <span class="keywordtype">bool</span> forceNoPadding,</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;{</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 3;</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 4;</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    <span class="comment">// forceNoPadding is mainly used for compatibility with ARM Compute.</span></div><div class="line"><a name="l00140"></a><span class="lineno">  140</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="l00141"></a><span class="lineno">  141</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = forceNoPadding ? 0 : 3;</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 8;</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 13;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth =</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;        (inputWidth + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</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.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</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> outputHeight =</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;        (inputHeight + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a>) /</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;        descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>;</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 2;</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 2;</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType);</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, ArmnnType);</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160; 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       outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    }</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;    std::vector&lt;float&gt; singleChannelData({</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;        0.0f, 4.0f, 8.0f, 1.0f, 6.0f, 4.0f, 5.0f, 8.0f,</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;        1.0f, 1.0f, 6.0f, 0.0f, 3.0f, 7.0f, 4.0f, 7.0f,</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;        8.0f, 5.0f, 0.0f, 0.0f, 8.0f, 3.0f, 4.0f, 3.0f,</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;        8.0f, 2.0f, 5.0f, 4.0f, 1.0f, 9.0f, 2.0f, 0.0f,</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;        5.0f, 4.0f, 5.0f, 0.0f, 0.0f, 0.0f, 7.0f, 2.0f,</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;        1.0f, 2.0f, 6.0f, 2.0f, 7.0f, 9.0f, 5.0f, 2.0f,</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        9.0f, 7.0f, 3.0f, 1.0f, 3.0f, 4.0f, 8.0f, 3.0f,</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;        1.0f, 0.0f, 0.0f, 5.0f, 5.0f, 4.0f, 2.0f, 0.0f,</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;        6.0f, 4.0f, 3.0f, 6.0f, 9.0f, 5.0f, 5.0f, 6.0f,</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;        8.0f, 7.0f, 9.0f, 6.0f, 1.0f, 4.0f, 1.0f, 9.0f,</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;        7.0f, 1.0f, 9.0f, 2.0f, 9.0f, 9.0f, 8.0f, 1.0f,</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;        4.0f, 4.0f, 5.0f, 9.0f, 2.0f, 6.0f, 6.0f, 4.0f,</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;        3.0f, 5.0f, 4.0f, 0.0f, 1.0f, 5.0f, 9.0f, 7.0f,</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    });</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    <span class="comment">// Constructs input data.</span></div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    std::vector&lt;float&gt; inputData;</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    <span class="keyword">auto</span> negator = [](<span class="keywordtype">float</span> f) { <span class="keywordflow">return</span> -f; };</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    <span class="comment">// First image (two channels where the second channel is the negative of the first one).</span></div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160; 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   <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="l00198"></a><span class="lineno">  198</span>&#160;</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    <span class="comment">// These were calculated manually.</span></div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    <span class="keyword">auto</span> shape(GetTensorShapeAsArray&lt;4&gt;(outputTensorInfo));</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    boost::multi_array&lt;T, 4&gt; outputExpected(shape);</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;    <span class="keywordflow">if</span> (forceNoPadding)</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    {</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;        outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;            QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;                 8.0f,  8.0f,  8.0f,</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;                 9.0f,  7.0f,  9.0f,</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;                 9.0f,  9.0f,  9.0f,</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;                 0.0f,  0.0f, -3.0f,</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;                -1.0f,  0.0f,  0.0f,</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;                -1.0f, -1.0f, -1.0f,</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;                 8.0f,  8.0f,  8.0f,</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;                 9.0f,  7.0f,  9.0f,</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;                 9.0f,  9.0f,  9.0f,</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;                 0.0f,  0.0f, -3.0f,</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;                -1.0f,  0.0f,  0.0f,</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;                -1.0f, -1.0f, -1.0f</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;            },</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;            qScale, qOffset));</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;    }</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;    {</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;        outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;            QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;                0.0f, 8.0f, 8.0f, 8.0f, 8.0f, 8.0f,</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;                0.0f, 9.0f, 7.0f, 9.0f, 9.0f, 3.0f,</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;                0.0f, 8.0f, 9.0f, 9.0f, 9.0f, 9.0f,</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;                0.0f, 0.0f, 0.0f, 0.0f,-3.0f,-3.0f,</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;                0.0f,-1.0f, 0.0f, 0.0f, 0.0f,-2.0f,</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;                0.0f,-1.0f,-1.0f,-1.0f,-1.0f,-1.0f,</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;                0.0f, 8.0f, 8.0f, 8.0f, 8.0f, 8.0f,</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;                0.0f, 9.0f, 7.0f, 9.0f, 9.0f, 3.0f,</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;                0.0f, 8.0f, 9.0f, 9.0f, 9.0f, 9.0f,</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;                0.0f, 0.0f, 0.0f, 0.0f,-3.0f,-3.0f,</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;                0.0f,-1.0f, 0.0f, 0.0f, 0.0f,-2.0f,</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;                0.0f,-1.0f,-1.0f,-1.0f,-1.0f,-1.0f</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;            qScale, qOffset));</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;    }</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;    <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;}</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;</div><div class="line"><a name="l00251"></a><span class="lineno">  251</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="l00252"></a><span class="lineno">  252</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> SimpleMaxPooling2dTestCommon(</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>,</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;{</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 2;</div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo  = <a class="code" href="namespacearmnn_utils.xhtml#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(1, 2, 4, 4, dataLayout, ArmnnType);</div><div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_utils.xhtml#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(1, 2, 2, 2, dataLayout, ArmnnType);</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;    <span class="keywordflow">if</span>(armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;    {</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;        inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;        inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;    }</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;    std::vector&lt;T&gt; inputData(</div><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;             1.0f,  2.0f,  5.0f,  6.0f,</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;             3.0f,  4.0f,  7.0f,  8.0f,</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;             9.0f, 10.0f, 13.0f, 14.0f,</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;            11.0f, 12.0f, 15.0f, 16.0f,</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;            17.0f, 18.0f, 21.0f, 22.0f,</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;            19.0f, 20.0f, 23.0f, 24.0f,</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;            25.0f, 26.0f, 29.0f, 30.0f,</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;            27.0f, 28.0f, 31.0f, 32.0f,</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;        },</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;        qScale, qOffset));</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;</div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;    std::vector&lt;T&gt; outputData(</div><div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;             4.0f,  8.0f,</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;            12.0f, 16.0f,</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;</div><div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;            20.0f, 24.0f,</div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;            28.0f, 32.0f,</div><div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;        },</div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;        qScale, qOffset));</div><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;</div><div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> NCHWToNHWC = { 0, 3, 1, 2 };</div><div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;    <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</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; tmp(inputData.size());</div><div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;        <a class="code" href="namespacearmnn_utils.xhtml#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, inputData.data(), tmp.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;        inputData = tmp;</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;        std::vector&lt;T&gt; tmp1(outputData.size());</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;        <a class="code" href="namespacearmnn_utils.xhtml#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, outputData.data(), tmp1.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;        outputData = tmp1;</div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;    }</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="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo, inputData);</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;    <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo, outputData);</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="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;}</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;</div><div class="line"><a name="l00323"></a><span class="lineno">  323</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="l00324"></a><span class="lineno">  324</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> SimpleAveragePooling2dTestCommon(</div><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>,</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;{</div><div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 2;</div><div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;</div><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160; 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   {</div><div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;        inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;        inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;    }</div><div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;</div><div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;    std::vector&lt;T&gt; inputData(</div><div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;             2.0f,  2.0f,  6.0f,  6.0f,</div><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;             4.0f,  4.0f,  8.0f,  8.0f,</div><div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;            10.0f, 12.0f, 14.0f, 16.0f,</div><div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;            10.0f, 12.0f, 16.0f, 14.0f,</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;            18.0f, 20.0f, 24.0f, 22.0f,</div><div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;            20.0f, 18.0f, 22.0f, 24.0f,</div><div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;            26.0f, 28.0f,  0.0f,  0.0f,</div><div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;            26.0f, 28.0f,  0.0f,  0.0f,</div><div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;        },</div><div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;        qScale, qOffset));</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;    std::vector&lt;T&gt; outputData(</div><div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;             3.0f,  7.0f,</div><div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;            11.0f, 15.0f,</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;            19.0f, 23.0f,</div><div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;            27.0f,  0.0f,</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;        qScale, qOffset));</div><div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;</div><div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> NCHWToNHWC = { 0, 3, 1, 2 };</div><div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;    <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div><div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;    {</div><div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;        std::vector&lt;T&gt; tmp(inputData.size());</div><div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;        <a class="code" href="namespacearmnn_utils.xhtml#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, inputData.data(), tmp.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;        inputData = tmp;</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;        std::vector&lt;T&gt; tmp1(outputData.size());</div><div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;        <a class="code" href="namespacearmnn_utils.xhtml#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, outputData.data(), tmp1.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;        outputData = tmp1;</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;</div><div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;    <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo, inputData);</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;    <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo, outputData);</div><div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;</div><div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;    <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;}</div><div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;</div><div class="line"><a name="l00395"></a><span class="lineno">  395</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="l00396"></a><span class="lineno">  396</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> LargeTensorsAveragePooling2dTestCommon(</div><div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;{</div><div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 100;</div><div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 5;</div><div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 50;</div><div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 50;</div><div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 50;</div><div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 50;</div><div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;</div><div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160; 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       inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;    }</div><div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;</div><div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;    std::vector&lt;T&gt; inputVec;</div><div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;</div><div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160; 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   std::vector&lt;T&gt; outputVec;</div><div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;</div><div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0 ; i &lt; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>().<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(); ++i)</div><div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;    {</div><div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;        outputVec.push_back(1);</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; 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   <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>,</div><div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;    int32_t qOffset = 0)</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="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div><div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 2;</div><div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;</div><div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo  = <a class="code" href="namespacearmnn_utils.xhtml#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(1, 2, 4, 4, dataLayout, ArmnnType);</div><div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_utils.xhtml#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a>(1, 2, 2, 2, dataLayout, ArmnnType);</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;    std::vector&lt;T&gt; inputData(</div><div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;            1.0f, 7.0f, 5.0f, 5.0f,</div><div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;            1.0f, 7.0f, 5.0f, 5.0f,</div><div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;            3.0f, 3.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;            3.0f, 3.0f, 1.0f, 1.0f,</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;            1.0f, 7.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;            1.0f, 7.0f, 2.0f, 0.0f,</div><div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;            0.0f, 2.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;            0.0f, 0.0f, 1.0f, 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;        qScale, qOffset));</div><div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;</div><div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;    std::vector&lt;T&gt; outputData(</div><div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;            5.0f, 5.0f,</div><div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;            3.0f, 1.0f,</div><div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;</div><div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;            5.0f, 1.0f,</div><div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;            1.0f, 1.0f,</div><div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;        },</div><div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;        qScale, qOffset));</div><div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;</div><div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> NCHWToNHWC = { 0, 3, 1, 2 };</div><div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;    <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div><div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;    {</div><div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;        std::vector&lt;T&gt; tmp(inputData.size());</div><div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;        <a class="code" href="namespacearmnn_utils.xhtml#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), NCHWToNHWC, inputData.data(), tmp.data(), <span class="keyword">sizeof</span>(T));</div><div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160; 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   <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;{</div><div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div><div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 3;</div><div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160; 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   <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;{</div><div class="line"><a name="l00554"></a><span class="lineno">  554</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="l00565"></a><span class="lineno">  565</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="l00566"></a><span class="lineno">  566</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="l00567"></a><span class="lineno">  567</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="l00568"></a><span class="lineno">  568</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="l00569"></a><span class="lineno">  569</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="l00570"></a><span class="lineno">  570</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="l00571"></a><span class="lineno">  571</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="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;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType);</div><div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;    <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;            3.0f, 3.0f, 3.0f,</div><div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;            3.0f, 3.0f, 3.0f,</div><div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;            3.0f, 3.0f, 3.0f,</div><div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;        },</div><div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;        qScale, qOffset));</div><div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;</div><div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;    <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;}</div><div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;</div><div class="line"><a name="l00588"></a><span class="lineno">  588</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="l00589"></a><span class="lineno">  589</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> L2Pooling2dSize3Stride4TestCommon(</div><div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;{</div><div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160; 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           1.0f, 2.0f, 2.0f, 0.0f, 1.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;            5.0f, 4.0f, 1.0f, 0.0f, 5.0f, 4.0f, 1.0f,</div><div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;            0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;            2.0f, 1.0f, 5.0f, 0.0f, 2.0f, 1.0f, 5.0f,</div><div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;            1.0f, 2.0f, 2.0f, 0.0f, 1.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;            5.0f, 4.0f, 1.0f, 0.0f, 5.0f, 4.0f, 1.0f,</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;        qScale, qOffset));</div><div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;</div><div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160; 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workloadFactory,</div><div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00632"></a><span class="lineno">  632</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00634"></a><span class="lineno">  634</span>&#160;{</div><div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160; 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           0.0f, 0.0f, 0.0f, 0.0f,  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160;            0.0f, 5.0f, 0.0f, 6.0f,  0.0f, 7.0f, 0.0f,</div><div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;            8.0f, 0.0f, 9.0f, 0.0f, 10.0f, 0.0f, 5.0f,</div><div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;            0.0f, 5.0f, 0.0f, 2.0f,  0.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160;            0.0f, 0.0f, 0.0f, 0.0f,  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;            0.0f, 0.0f, 0.0f, 0.0f,  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;        },</div><div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;        qScale, qOffset));</div><div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160;</div><div class="line"><a name="l00654"></a><span class="lineno">  654</span>&#160; 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memoryManager,</div><div class="line"><a name="l00669"></a><span class="lineno">  669</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160;{</div><div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div><div class="line"><a name="l00675"></a><span class="lineno">  675</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="l00687"></a><span class="lineno">  687</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="l00688"></a><span class="lineno">  688</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="l00689"></a><span class="lineno">  689</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="l00690"></a><span class="lineno">  690</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="l00691"></a><span class="lineno">  691</span>&#160;        },</div><div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;        qScale, qOffset));</div><div class="line"><a name="l00693"></a><span class="lineno">  693</span>&#160;</div><div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160; 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       workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160;}</div><div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;</div><div class="line"><a name="l00705"></a><span class="lineno">  705</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="l00706"></a><span class="lineno">  706</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> AsymmetricNonSquarePooling2dTestCommon(</div><div class="line"><a name="l00707"></a><span class="lineno">  707</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160; 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   <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00750"></a><span class="lineno">  750</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; refWorkloadFactory,</div><div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; refTensorHandleFactory,</div><div class="line"><a name="l00754"></a><span class="lineno">  754</span>&#160;    <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a> poolingType,</div><div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00757"></a><span class="lineno">  757</span>&#160;{</div><div class="line"><a name="l00758"></a><span class="lineno">  758</span>&#160;    <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00759"></a><span class="lineno">  759</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="l00760"></a><span class="lineno">  760</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="l00761"></a><span class="lineno">  761</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="l00762"></a><span class="lineno">  762</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="l00763"></a><span class="lineno">  763</span>&#160;</div><div class="line"><a name="l00764"></a><span class="lineno">  764</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> poolSize = 3;</div><div class="line"><a name="l00765"></a><span class="lineno">  765</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> strideX = 2;</div><div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> strideY = 4;</div><div class="line"><a name="l00767"></a><span class="lineno">  767</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> padX = 0;</div><div class="line"><a name="l00768"></a><span class="lineno">  768</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> padY = 0;</div><div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160;</div><div class="line"><a name="l00770"></a><span class="lineno">  770</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = (inputWidth + 2 * padX + strideX - poolSize) / strideX;</div><div class="line"><a name="l00771"></a><span class="lineno">  771</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = (inputHeight + 2 * padY + strideY - poolSize) / strideY;</div><div class="line"><a name="l00772"></a><span class="lineno">  772</span>&#160;</div><div class="line"><a name="l00773"></a><span class="lineno">  773</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00774"></a><span class="lineno">  774</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</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;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { batchSize, channelCount, inputHeight, inputWidth };</div><div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { batchSize, channelCount, outputHeight, outputWidth };</div><div class="line"><a name="l00778"></a><span class="lineno">  778</span>&#160;</div><div class="line"><a name="l00779"></a><span class="lineno">  779</span>&#160;    inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, inputShape, ArmnnType);</div><div class="line"><a name="l00780"></a><span class="lineno">  780</span>&#160;    outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, outputShape, ArmnnType);</div><div class="line"><a name="l00781"></a><span class="lineno">  781</span>&#160;</div><div class="line"><a name="l00782"></a><span class="lineno">  782</span>&#160;    <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00783"></a><span class="lineno">  783</span>&#160;    <span class="keywordflow">if</span>(armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00784"></a><span class="lineno">  784</span>&#160;    {</div><div class="line"><a name="l00785"></a><span class="lineno">  785</span>&#160;        inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;        inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00787"></a><span class="lineno">  787</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00788"></a><span class="lineno">  788</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00789"></a><span class="lineno">  789</span>&#160;    }</div><div class="line"><a name="l00790"></a><span class="lineno">  790</span>&#160;</div><div class="line"><a name="l00791"></a><span class="lineno">  791</span>&#160;    boost::multi_array&lt;T, 4&gt; input = MakeRandomTensor&lt;T, 4&gt;(inputTensorInfo, 81715);</div><div class="line"><a name="l00792"></a><span class="lineno">  792</span>&#160;</div><div class="line"><a name="l00793"></a><span class="lineno">  793</span>&#160;    <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> comparisonResult(outputTensorInfo);</div><div class="line"><a name="l00794"></a><span class="lineno">  794</span>&#160;</div><div class="line"><a name="l00795"></a><span class="lineno">  795</span>&#160;    std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00796"></a><span class="lineno">  796</span>&#160;    std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</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;    <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">armnn::Pooling2dQueueDescriptor</a> data;</div><div class="line"><a name="l00799"></a><span class="lineno">  799</span>&#160;    <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00800"></a><span class="lineno">  800</span>&#160;    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00801"></a><span class="lineno">  801</span>&#160;    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00802"></a><span class="lineno">  802</span>&#160;    data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = poolingType;</div><div class="line"><a name="l00803"></a><span class="lineno">  803</span>&#160;    data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = poolSize;</div><div class="line"><a name="l00804"></a><span class="lineno">  804</span>&#160;    data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = poolSize;</div><div class="line"><a name="l00805"></a><span class="lineno">  805</span>&#160;    data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = strideX;</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.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = strideY;</div><div class="line"><a name="l00807"></a><span class="lineno">  807</span>&#160;    data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = padX;</div><div class="line"><a name="l00808"></a><span class="lineno">  808</span>&#160;    data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = padX;</div><div class="line"><a name="l00809"></a><span class="lineno">  809</span>&#160;    data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = padY;</div><div class="line"><a name="l00810"></a><span class="lineno">  810</span>&#160;    data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = padY;</div><div class="line"><a name="l00811"></a><span class="lineno">  811</span>&#160;    data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</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;    std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandleRef = refTensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00814"></a><span class="lineno">  814</span>&#160;    std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandleRef = refTensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00815"></a><span class="lineno">  815</span>&#160;</div><div class="line"><a name="l00816"></a><span class="lineno">  816</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="l00817"></a><span class="lineno">  817</span>&#160;    <a class="code" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> backend = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a9f7e4296485d2812e7996089149c96d1">GetBackendId</a>();</div><div class="line"><a name="l00818"></a><span class="lineno">  818</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> reasonIfUnsupportedMaxLen = 255;</div><div class="line"><a name="l00819"></a><span class="lineno">  819</span>&#160; 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   outputHandle-&gt;Allocate();</div><div class="line"><a name="l00840"></a><span class="lineno">  840</span>&#160;</div><div class="line"><a name="l00841"></a><span class="lineno">  841</span>&#160;    <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &amp;input[0][0][0][0]);</div><div class="line"><a name="l00842"></a><span class="lineno">  842</span>&#160;    <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandleRef.get(), &amp;input[0][0][0][0]);</div><div class="line"><a name="l00843"></a><span class="lineno">  843</span>&#160;</div><div class="line"><a name="l00844"></a><span class="lineno">  844</span>&#160;    workload-&gt;Execute();</div><div class="line"><a name="l00845"></a><span class="lineno">  845</span>&#160;    workloadRef-&gt;Execute();</div><div class="line"><a name="l00846"></a><span class="lineno">  846</span>&#160;</div><div class="line"><a name="l00847"></a><span class="lineno">  847</span>&#160;    <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;comparisonResult.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00848"></a><span class="lineno">  848</span>&#160;    <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;comparisonResult.outputExpected[0][0][0][0], outputHandleRef.get());</div><div class="line"><a name="l00849"></a><span class="lineno">  849</span>&#160;</div><div class="line"><a name="l00850"></a><span class="lineno">  850</span>&#160;    <span class="keywordflow">return</span> comparisonResult;</div><div class="line"><a name="l00851"></a><span class="lineno">  851</span>&#160;}</div><div class="line"><a name="l00852"></a><span class="lineno">  852</span>&#160;</div><div class="line"><a name="l00853"></a><span class="lineno">  853</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00854"></a><span class="lineno">  854</span>&#160;<span class="comment">// Tests max pooling with the following parameters:</span></div><div class="line"><a name="l00855"></a><span class="lineno">  855</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00856"></a><span class="lineno">  856</span>&#160;<span class="comment">//   Pooling size: 2x2</span></div><div class="line"><a name="l00857"></a><span class="lineno">  857</span>&#160;<span class="comment">//   Stride:       (2,2)</span></div><div class="line"><a name="l00858"></a><span class="lineno">  858</span>&#160;<span class="comment">//   input size:   4x4</span></div><div class="line"><a name="l00859"></a><span class="lineno">  859</span>&#160;<span class="comment">//   channels:     1</span></div><div class="line"><a name="l00860"></a><span class="lineno">  860</span>&#160;<span class="comment">//   batch size:   1</span></div><div class="line"><a name="l00861"></a><span class="lineno">  861</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00862"></a><span class="lineno">  862</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="l00863"></a><span class="lineno">  863</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> SimpleMaxPooling2dSize2x2Stride2x2TestCommon(</div><div class="line"><a name="l00864"></a><span class="lineno">  864</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00865"></a><span class="lineno">  865</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00866"></a><span class="lineno">  866</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00867"></a><span class="lineno">  867</span>&#160;    <span class="keywordtype">bool</span> forceNoPadding,</div><div class="line"><a name="l00868"></a><span class="lineno">  868</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00869"></a><span class="lineno">  869</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l00870"></a><span class="lineno">  870</span>&#160;{</div><div class="line"><a name="l00871"></a><span class="lineno">  871</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00872"></a><span class="lineno">  872</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l00873"></a><span class="lineno">  873</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 2;</div><div class="line"><a name="l00874"></a><span class="lineno">  874</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00875"></a><span class="lineno">  875</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00876"></a><span class="lineno">  876</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = forceNoPadding ? 0 : 3;</div><div class="line"><a name="l00877"></a><span class="lineno">  877</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l00878"></a><span class="lineno">  878</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div><div class="line"><a name="l00879"></a><span class="lineno">  879</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00880"></a><span class="lineno">  880</span>&#160;</div><div class="line"><a name="l00881"></a><span class="lineno">  881</span>&#160;</div><div class="line"><a name="l00882"></a><span class="lineno">  882</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 4;</div><div class="line"><a name="l00883"></a><span class="lineno">  883</span>&#160;</div><div class="line"><a name="l00884"></a><span class="lineno">  884</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 4;</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth =</div><div class="line"><a name="l00887"></a><span class="lineno">  887</span>&#160;        (inputWidth + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a>) /</div><div class="line"><a name="l00888"></a><span class="lineno">  888</span>&#160;        descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>;</div><div class="line"><a name="l00889"></a><span class="lineno">  889</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight =</div><div class="line"><a name="l00890"></a><span class="lineno">  890</span>&#160;        (inputHeight + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a>) /</div><div class="line"><a name="l00891"></a><span class="lineno">  891</span>&#160;        descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>;</div><div class="line"><a name="l00892"></a><span class="lineno">  892</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 1;</div><div class="line"><a name="l00893"></a><span class="lineno">  893</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 1;</div><div class="line"><a name="l00894"></a><span class="lineno">  894</span>&#160;</div><div class="line"><a name="l00895"></a><span class="lineno">  895</span>&#160;    std::vector&lt;float&gt; inputData = {</div><div class="line"><a name="l00896"></a><span class="lineno">  896</span>&#160;        510.0f, 222.0f, 780.0f, 654.0f,</div><div class="line"><a name="l00897"></a><span class="lineno">  897</span>&#160;        141.0f, 276.0f,  15.0f, 546.0f,</div><div class="line"><a name="l00898"></a><span class="lineno">  898</span>&#160;        303.0f, 618.0f, 582.0f, 339.0f,</div><div class="line"><a name="l00899"></a><span class="lineno">  899</span>&#160;        438.0f, 564.0f, 573.0f, 402.0f</div><div class="line"><a name="l00900"></a><span class="lineno">  900</span>&#160;    };</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">// 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="l00903"></a><span class="lineno">  903</span>&#160;    std::vector&lt;float&gt; expectedOutputDataWithPadding = {</div><div class="line"><a name="l00904"></a><span class="lineno">  904</span>&#160;        0.0f, 510.0f, 780.0f, 654.0f, 0.0f,</div><div class="line"><a name="l00905"></a><span class="lineno">  905</span>&#160;        0.0f, 438.0f, 618.0f, 402.0f, 0.0f</div><div class="line"><a name="l00906"></a><span class="lineno">  906</span>&#160;    };</div><div class="line"><a name="l00907"></a><span class="lineno">  907</span>&#160;</div><div class="line"><a name="l00908"></a><span class="lineno">  908</span>&#160;    std::vector&lt;float&gt; expectedOutputDataNoPadding = {</div><div class="line"><a name="l00909"></a><span class="lineno">  909</span>&#160;        510.0f, 780.0f,</div><div class="line"><a name="l00910"></a><span class="lineno">  910</span>&#160;        618.0f, 582.0f</div><div class="line"><a name="l00911"></a><span class="lineno">  911</span>&#160;    };</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;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType);</div><div class="line"><a name="l00914"></a><span class="lineno">  914</span>&#160;</div><div class="line"><a name="l00915"></a><span class="lineno">  915</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="l00916"></a><span class="lineno">  916</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, ArmnnType);</div><div class="line"><a name="l00917"></a><span class="lineno">  917</span>&#160;</div><div class="line"><a name="l00918"></a><span class="lineno">  918</span>&#160;    <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00919"></a><span class="lineno">  919</span>&#160;    <span class="keywordflow">if</span>(armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00920"></a><span class="lineno">  920</span>&#160;    {</div><div class="line"><a name="l00921"></a><span class="lineno">  921</span>&#160;        inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00922"></a><span class="lineno">  922</span>&#160;        inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00923"></a><span class="lineno">  923</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00924"></a><span class="lineno">  924</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00925"></a><span class="lineno">  925</span>&#160;    }</div><div class="line"><a name="l00926"></a><span class="lineno">  926</span>&#160;</div><div class="line"><a name="l00927"></a><span class="lineno">  927</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="l00928"></a><span class="lineno">  928</span>&#160;</div><div class="line"><a name="l00929"></a><span class="lineno">  929</span>&#160;    <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l00930"></a><span class="lineno">  930</span>&#160;        forceNoPadding ? QuantizedVector&lt;T&gt;(expectedOutputDataNoPadding, qScale, qOffset) :</div><div class="line"><a name="l00931"></a><span class="lineno">  931</span>&#160;                         QuantizedVector&lt;T&gt;(expectedOutputDataWithPadding, qScale, qOffset));</div><div class="line"><a name="l00932"></a><span class="lineno">  932</span>&#160;</div><div class="line"><a name="l00933"></a><span class="lineno">  933</span>&#160;    <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l00934"></a><span class="lineno">  934</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l00935"></a><span class="lineno">  935</span>&#160;}</div><div class="line"><a name="l00936"></a><span class="lineno">  936</span>&#160;</div><div class="line"><a name="l00937"></a><span class="lineno">  937</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00938"></a><span class="lineno">  938</span>&#160;<span class="comment">// Tests max pooling with the following parameters:</span></div><div class="line"><a name="l00939"></a><span class="lineno">  939</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00940"></a><span class="lineno">  940</span>&#160;<span class="comment">//   Pooling size: 3x2</span></div><div class="line"><a name="l00941"></a><span class="lineno">  941</span>&#160;<span class="comment">//   Stride:       (2,2)</span></div><div class="line"><a name="l00942"></a><span class="lineno">  942</span>&#160;<span class="comment">//   input size:   3x2</span></div><div class="line"><a name="l00943"></a><span class="lineno">  943</span>&#160;<span class="comment">//   channels:     1</span></div><div class="line"><a name="l00944"></a><span class="lineno">  944</span>&#160;<span class="comment">//   batch size:   1</span></div><div class="line"><a name="l00945"></a><span class="lineno">  945</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00946"></a><span class="lineno">  946</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="l00947"></a><span class="lineno">  947</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> IgnorePaddingAveragePooling2dSize3x2Stride2x2TestCommon(</div><div class="line"><a name="l00948"></a><span class="lineno">  948</span>&#160;        <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l00949"></a><span class="lineno">  949</span>&#160;        <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l00950"></a><span class="lineno">  950</span>&#160;        <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l00951"></a><span class="lineno">  951</span>&#160;        <span class="keywordtype">bool</span> forceNoPadding,</div><div class="line"><a name="l00952"></a><span class="lineno">  952</span>&#160;        <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00953"></a><span class="lineno">  953</span>&#160; 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   descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00960"></a><span class="lineno">  960</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00961"></a><span class="lineno">  961</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = (forceNoPadding) ? 0 : 1;</div><div class="line"><a name="l00962"></a><span class="lineno">  962</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>;</div><div class="line"><a name="l00963"></a><span class="lineno">  963</span>&#160; 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       descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>;</div><div class="line"><a name="l00973"></a><span class="lineno">  973</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight =</div><div class="line"><a name="l00974"></a><span class="lineno">  974</span>&#160;        (inputHeight + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> + descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> - descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a>) /</div><div class="line"><a name="l00975"></a><span class="lineno">  975</span>&#160;        descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>;</div><div class="line"><a name="l00976"></a><span class="lineno">  976</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 1;</div><div class="line"><a name="l00977"></a><span class="lineno">  977</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 1;</div><div class="line"><a name="l00978"></a><span class="lineno">  978</span>&#160;</div><div class="line"><a name="l00979"></a><span class="lineno">  979</span>&#160;    std::vector&lt;float&gt; inputData = {</div><div class="line"><a name="l00980"></a><span class="lineno">  980</span>&#160;        3.0f, 6.0f, 9.0f,</div><div class="line"><a name="l00981"></a><span class="lineno">  981</span>&#160;        12.0f, 15.0f, 18.0f,</div><div class="line"><a name="l00982"></a><span class="lineno">  982</span>&#160; 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       inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l01300"></a><span class="lineno"> 1300</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>&#160;    }</div><div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>&#160;</div><div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>&#160;    <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>&#160;            2.0f,  4.0f, 8.0f, 16.0f,</div><div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>&#160;            4.0f,  2.0f, 2.0f, 4.0f,</div><div class="line"><a name="l01308"></a><span class="lineno"> 1308</span>&#160;            8.0f,  2.0f, 4.0f, 2.0f,</div><div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>&#160;            16.0f, 2.0f, 2.0f, 8.0f,</div><div class="line"><a name="l01310"></a><span class="lineno"> 1310</span>&#160;        },</div><div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>&#160;        qScale, qOffset));</div><div class="line"><a name="l01312"></a><span class="lineno"> 1312</span>&#160;</div><div class="line"><a name="l01313"></a><span class="lineno"> 1313</span>&#160;    <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l01314"></a><span class="lineno"> 1314</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l01315"></a><span class="lineno"> 1315</span>&#160;               1.0f,     4.4721f,   8.0f,</div><div class="line"><a name="l01316"></a><span class="lineno"> 1316</span>&#160;            4.4721f,     2.6457f,   2.236f,</div><div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>&#160;               8.0f,     1.4142f,   4.0f,</div><div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>&#160;        },</div><div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>&#160;        qScale, qOffset));</div><div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>&#160;</div><div class="line"><a name="l01321"></a><span class="lineno"> 1321</span>&#160;    <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>&#160;}</div><div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>&#160;</div><div class="line"><a name="l01325"></a><span class="lineno"> 1325</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="l01326"></a><span class="lineno"> 1326</span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> IgnorePaddingL2Pooling2dSize3TestCommon(</div><div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01328"></a><span class="lineno"> 1328</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>&#160;    <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>&#160;    int32_t qOffset = 0)</div><div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>&#160;{</div><div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a>;</div><div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 3;</div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>&#160; 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       inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>&#160;        outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>&#160;    }</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"> 1355</span>&#160;    <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l01356"></a><span class="lineno"> 1356</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>&#160;            1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>&#160;            1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>&#160;            1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>&#160;            1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>&#160;        },</div><div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>&#160;        qScale, qOffset));</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"> 1364</span>&#160;    <span class="keyword">auto</span> outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>&#160;        QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l01366"></a><span class="lineno"> 1366</span>&#160;            1.0540f, 1.7638f, 2.5385f, 2.3570f,</div><div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>&#160;            1.2909f, 2.1602f, 3.1091f, 2.8867f,</div><div class="line"><a name="l01368"></a><span class="lineno"> 1368</span>&#160;            1.2909f, 2.1602f, 3.1091f, 2.8867f,</div><div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>&#160;            1.0540f, 1.7638f, 2.5385f, 2.3570f,</div><div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>&#160;        },</div><div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>&#160;        qScale, qOffset));</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"> 1373</span>&#160;    <span class="keywordflow">return</span> SimplePooling2dTestImpl&lt;ArmnnType&gt;(</div><div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, input, outputExpected);</div><div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>&#160;}</div><div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>&#160;</div><div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>&#160;} <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>&#160;</div><div class="line"><a name="l01379"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#ad18df1220453e97c0686a129b2d2d79b"> 1379</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#ad18df1220453e97c0686a129b2d2d79b">SimpleMaxPooling2dSize2x2Stride2x2Test</a>(</div><div class="line"><a name="l01380"></a><span class="lineno"> 1380</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>&#160;    <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>&#160;{</div><div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>&#160;    <span class="keywordflow">return</span> SimpleMaxPooling2dSize2x2Stride2x2TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, forceNoPadding);</div><div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>&#160;}</div><div class="line"><a name="l01388"></a><span class="lineno"> 1388</span>&#160;</div><div class="line"><a name="l01389"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#af1f2a5c336e021b1c1a2cfd9c66644b2"> 1389</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#af1f2a5c336e021b1c1a2cfd9c66644b2">SimpleMaxPooling2dSize2x2Stride2x2Uint8Test</a>(</div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>&#160;    <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>&#160;{</div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>&#160;    <span class="keywordflow">return</span> SimpleMaxPooling2dSize2x2Stride2x2TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, forceNoPadding, 3.0f, -5);</div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>&#160;}</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"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#afdded119a95bdac07fd8d086b1cc9b5f"> 1399</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#afdded119a95bdac07fd8d086b1cc9b5f">SimpleMaxPooling2dSize2x2Stride2x2Int16Test</a>(</div><div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</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_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</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> SimpleMaxPooling2dSize2x2Stride2x2TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, 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.xhtml#a15d723fdf9c3c80f6b5deb2e66240622"> 1409</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a15d723fdf9c3c80f6b5deb2e66240622">SimpleMaxPooling2dSize3x3Stride2x4Test</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.xhtml">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.xhtml#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="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>&#160;    <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>&#160;{</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>&#160;    <span class="keywordflow">return</span> SimpleMaxPooling2dSize3x3Stride2x4TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, forceNoPadding);</div><div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>&#160;}</div><div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>&#160;</div><div class="line"><a name="l01419"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a38e23959bb4200e6e019aa490f151e62"> 1419</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a38e23959bb4200e6e019aa490f151e62">SimpleMaxPooling2dSize3x3Stride2x4Uint8Test</a>(</div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>&#160;    <span class="keywordtype">bool</span> forceNoPadding)</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"> 1425</span>&#160;    <span class="keywordflow">return</span> SimpleMaxPooling2dSize3x3Stride2x4TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, forceNoPadding, 0.1f, 128);</div><div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>&#160;}</div><div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>&#160;</div><div class="line"><a name="l01429"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a2fbb1973ecc2c9f0943922e9a122af63"> 1429</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a2fbb1973ecc2c9f0943922e9a122af63">SimpleMaxPooling2dSize3x3Stride2x4Int16Test</a>(</div><div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>&#160;    <span class="keywordtype">bool</span> forceNoPadding)</div><div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>&#160;{</div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>&#160;    <span class="keywordflow">return</span> SimpleMaxPooling2dSize3x3Stride2x4TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, forceNoPadding);</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.xhtml#aa3e57d4e48a91435d73487dabacc091b"> 1439</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#aa3e57d4e48a91435d73487dabacc091b">SimpleMaxPooling2dTest</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.xhtml">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.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>&#160;{</div><div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>&#160;    <span class="keywordflow">return</span> SimpleMaxPooling2dTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, dataLayout);</div><div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>&#160;}</div><div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>&#160;</div><div class="line"><a name="l01449"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a6c607ea3a6688789e82b78298903e5d2"> 1449</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a6c607ea3a6688789e82b78298903e5d2">SimpleMaxPooling2dUint8Test</a>(</div><div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; 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           workloadFactory, memoryManager, tensorHandleFactory, dataLayout);</div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>&#160;}</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"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#ab7a75e53f39941cb732a35a8b2dd6c60"> 1459</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#ab7a75e53f39941cb732a35a8b2dd6c60">SimpleMaxPooling2dInt16Test</a>(</div><div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>&#160;{</div><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>&#160;    <span class="keywordflow">return</span> SimpleMaxPooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, dataLayout);</div><div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>&#160;}</div><div class="line"><a name="l01468"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a8f8edbf4d70c91dcfefeb6bcfc48dfb4"> 1468</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a8f8edbf4d70c91dcfefeb6bcfc48dfb4">IgnorePaddingSimpleMaxPooling2dTest</a>(</div><div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01470"></a><span class="lineno"> 1470</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>&#160;{</div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleMaxPooling2dTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>&#160;}</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"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#af2f5d449f05421b21cb686d6b341e75a"> 1477</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#af2f5d449f05421b21cb686d6b341e75a">IgnorePaddingSimpleMaxPooling2dUint8Test</a>(</div><div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</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_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>&#160;{</div><div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleMaxPooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, 1.0f, -5);</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.xhtml#a98ea0eccf818625f0d4c6ea5dbc6f452"> 1486</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a98ea0eccf818625f0d4c6ea5dbc6f452">IgnorePaddingSimpleMaxPooling2dInt16Test</a>(</div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01488"></a><span class="lineno"> 1488</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01489"></a><span class="lineno"> 1489</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>&#160;{</div><div class="line"><a name="l01491"></a><span class="lineno"> 1491</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleMaxPooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>&#160; 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memoryManager,</div><div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>&#160;{</div><div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingMaxPooling2dSize3TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>&#160;}</div><div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>&#160;</div><div class="line"><a name="l01504"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a3b8c319c895ac738290d754f913471cd"> 1504</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a3b8c319c895ac738290d754f913471cd">IgnorePaddingMaxPooling2dSize3Uint8Test</a>(</div><div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">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.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</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> IgnorePaddingMaxPooling2dSize3TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, 1.0f, -5);</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.xhtml#abd30e75a9348c916154fe64dce659933"> 1513</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#abd30e75a9348c916154fe64dce659933">IgnorePaddingMaxPooling2dSize3Int16Test</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.xhtml">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.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>&#160;{</div><div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingMaxPooling2dSize3TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01520"></a><span class="lineno"> 1520</span>&#160;}</div><div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>&#160;</div><div class="line"><a name="l01522"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#ace5d07b4866c0c0a7d6c20a1608c3213"> 1522</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#ace5d07b4866c0c0a7d6c20a1608c3213">SimpleAveragePooling2dTest</a>(</div><div class="line"><a name="l01523"></a><span class="lineno"> 1523</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>&#160;{</div><div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>&#160;    <span class="keywordflow">return</span> SimpleAveragePooling2dTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, dataLayout);</div><div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>&#160;}</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"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a92b460c3ad7d8ad1e3cc91fca779423f"> 1532</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a92b460c3ad7d8ad1e3cc91fca779423f">SimpleAveragePooling2dUint8Test</a>(</div><div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; 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       workloadFactory, memoryManager, tensorHandleFactory, dataLayout, 0.5, -1);</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.xhtml#aeb0f50adb2d9d42bfc469b3c961b344c"> 1542</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#aeb0f50adb2d9d42bfc469b3c961b344c">SimpleAveragePooling2dInt16Test</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.xhtml">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.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>&#160;{</div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>&#160;    <span class="keywordflow">return</span> SimpleAveragePooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, dataLayout);</div><div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>&#160;}</div><div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>&#160;</div><div class="line"><a name="l01552"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a45b7b4ee1096c02cb56cc68907171533"> 1552</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a45b7b4ee1096c02cb56cc68907171533">IgnorePaddingAveragePooling2dSize3x2Stride2x2Test</a>(</div><div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>&#160;    <span class="keywordtype">bool</span> forceNoPadding)</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"> 1558</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingAveragePooling2dSize3x2Stride2x2TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, forceNoPadding);</div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>&#160;}</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"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a2a0bad554a0733d7af21b9d0eca627d7"> 1562</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a2a0bad554a0733d7af21b9d0eca627d7">LargeTensorsAveragePooling2dTest</a>(</div><div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>&#160;{</div><div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>&#160;    <span class="keywordflow">return</span> LargeTensorsAveragePooling2dTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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;</div><div class="line"><a name="l01571"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a1cfcbf24e161da40af56add364386513"> 1571</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a1cfcbf24e161da40af56add364386513">LargeTensorsAveragePooling2dUint8Test</a>(</div><div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>&#160;{</div><div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>&#160;    <span class="keywordflow">return</span> LargeTensorsAveragePooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>&#160;        workloadFactory, memoryManager, tensorHandleFactory, 0.5, -1);</div><div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>&#160;}</div><div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>&#160;</div><div class="line"><a name="l01580"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#ab693227602a70e077d310acf71c0c08d"> 1580</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#ab693227602a70e077d310acf71c0c08d">LargeTensorsAveragePooling2dInt16Test</a>(</div><div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>&#160;{</div><div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>&#160;    <span class="keywordflow">return</span> LargeTensorsAveragePooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a0fa96bdee9e4e1b84b1ead192e4d37d3"> 1588</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a0fa96bdee9e4e1b84b1ead192e4d37d3">IgnorePaddingSimpleAveragePooling2dTest</a>(</div><div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>&#160; 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           workloadFactory, memoryManager, tensorHandleFactory);</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.xhtml#a6e05c1f0877310caac35214456502cd5"> 1597</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a6e05c1f0877310caac35214456502cd5">IgnorePaddingSimpleAveragePooling2dUint8Test</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.xhtml">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.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>&#160;{</div><div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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"> 1605</span>&#160;</div><div class="line"><a name="l01606"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#af6da475d5a9c9349cb7213e610acf89e"> 1606</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#af6da475d5a9c9349cb7213e610acf89e">IgnorePaddingSimpleAveragePooling2dInt16Test</a>(</div><div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>&#160;{</div><div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01613"></a><span class="lineno"> 1613</span>&#160;}</div><div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>&#160;</div><div class="line"><a name="l01615"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a8ea02afa5072ae475b4fa19e9674796d"> 1615</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a8ea02afa5072ae475b4fa19e9674796d">IgnorePaddingSimpleAveragePooling2dNoPaddingTest</a>(</div><div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</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;    <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>&#160;}</div><div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>&#160;</div><div class="line"><a name="l01624"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#ad89767b400c345ca8f2b35c5b57e4d45"> 1624</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#ad89767b400c345ca8f2b35c5b57e4d45">IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test</a>(</div><div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</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"> 1629</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>&#160;}</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"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a30dbe98e901d2315c7dc8d92789a3270"> 1633</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a30dbe98e901d2315c7dc8d92789a3270">IgnorePaddingSimpleAveragePooling2dNoPaddingInt16Test</a>(</div><div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01636"></a><span class="lineno"> 1636</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>&#160;{</div><div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>&#160;}</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"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a61f14785fbec16c8820b55fd895fc763"> 1642</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a61f14785fbec16c8820b55fd895fc763">IgnorePaddingAveragePooling2dSize3Test</a>(</div><div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</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_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</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> IgnorePaddingAveragePooling2dSize3TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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"> 1650</span>&#160;</div><div class="line"><a name="l01651"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a6c6b75b8666fab92de438be79ca9ed64"> 1651</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a6c6b75b8666fab92de438be79ca9ed64">IgnorePaddingAveragePooling2dSize3Uint8Test</a>(</div><div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</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;    <span class="keywordflow">return</span> IgnorePaddingAveragePooling2dSize3TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01657"></a><span class="lineno"> 1657</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>&#160;}</div><div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>&#160;</div><div class="line"><a name="l01660"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a8a3cfd8f41f6fae3ff94fcb0f7926693"> 1660</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a8a3cfd8f41f6fae3ff94fcb0f7926693">IgnorePaddingAveragePooling2dSize3Int16Test</a>(</div><div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01663"></a><span class="lineno"> 1663</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>&#160;{</div><div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingAveragePooling2dSize3TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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;</div><div class="line"><a name="l01669"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#aa4bc368a4e78d01a9b7daaad2a2dbd51"> 1669</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#aa4bc368a4e78d01a9b7daaad2a2dbd51">SimpleL2Pooling2dTest</a>(</div><div class="line"><a name="l01670"></a><span class="lineno"> 1670</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01671"></a><span class="lineno"> 1671</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</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_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01673"></a><span class="lineno"> 1673</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01674"></a><span class="lineno"> 1674</span>&#160;{</div><div class="line"><a name="l01675"></a><span class="lineno"> 1675</span>&#160;    <span class="keywordflow">return</span> SimpleL2Pooling2dTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, dataLayout);</div><div class="line"><a name="l01677"></a><span class="lineno"> 1677</span>&#160;}</div><div class="line"><a name="l01678"></a><span class="lineno"> 1678</span>&#160;</div><div class="line"><a name="l01679"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a3e863f692b93f2f36ae0787a0421c952"> 1679</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a3e863f692b93f2f36ae0787a0421c952">SimpleL2Pooling2dUint8Test</a>(</div><div class="line"><a name="l01680"></a><span class="lineno"> 1680</span>&#160; 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   <span class="keywordflow">return</span> SimpleL2Pooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01686"></a><span class="lineno"> 1686</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, dataLayout);</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;</div><div class="line"><a name="l01689"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a8294d39b64461dc8cc264e2090428d8f"> 1689</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a8294d39b64461dc8cc264e2090428d8f">SimpleL2Pooling2dInt16Test</a>(</div><div class="line"><a name="l01690"></a><span class="lineno"> 1690</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01691"></a><span class="lineno"> 1691</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01692"></a><span class="lineno"> 1692</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01693"></a><span class="lineno"> 1693</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</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> SimpleL2Pooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01696"></a><span class="lineno"> 1696</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory, dataLayout);</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"> 1698</span>&#160;</div><div class="line"><a name="l01699"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a716ac8b594c1f6b9fa2bbde4597756d5"> 1699</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a716ac8b594c1f6b9fa2bbde4597756d5">L2Pooling2dSize3Stride1Test</a>(</div><div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01701"></a><span class="lineno"> 1701</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</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;    <span class="keywordflow">return</span> L2Pooling2dSize3Stride1TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01705"></a><span class="lineno"> 1705</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01706"></a><span class="lineno"> 1706</span>&#160;}</div><div class="line"><a name="l01707"></a><span class="lineno"> 1707</span>&#160;</div><div class="line"><a name="l01708"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a0bbcbeb6102a5354028a18056e323b26"> 1708</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a0bbcbeb6102a5354028a18056e323b26">L2Pooling2dSize3Stride1Uint8Test</a>(</div><div class="line"><a name="l01709"></a><span class="lineno"> 1709</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01711"></a><span class="lineno"> 1711</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01712"></a><span class="lineno"> 1712</span>&#160;{</div><div class="line"><a name="l01713"></a><span class="lineno"> 1713</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize3Stride1TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01714"></a><span class="lineno"> 1714</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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;</div><div class="line"><a name="l01717"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#aba20cbea840a4a32df631ba77ab67087"> 1717</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#aba20cbea840a4a32df631ba77ab67087">L2Pooling2dSize3Stride1Int16Test</a>(</div><div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01719"></a><span class="lineno"> 1719</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>&#160;{</div><div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize3Stride1TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01723"></a><span class="lineno"> 1723</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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.xhtml#a01ba3efd925240328de48bc75a8cc076"> 1726</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a01ba3efd925240328de48bc75a8cc076">L2Pooling2dSize3Stride3Test</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.xhtml">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.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>&#160;{</div><div class="line"><a name="l01731"></a><span class="lineno"> 1731</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize3Stride3TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01732"></a><span class="lineno"> 1732</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01733"></a><span class="lineno"> 1733</span>&#160;}</div><div class="line"><a name="l01734"></a><span class="lineno"> 1734</span>&#160;</div><div class="line"><a name="l01735"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#ac882f58604273a64c05f572aa1dabbed"> 1735</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#ac882f58604273a64c05f572aa1dabbed">L2Pooling2dSize3Stride3Uint8Test</a>(</div><div class="line"><a name="l01736"></a><span class="lineno"> 1736</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01737"></a><span class="lineno"> 1737</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01739"></a><span class="lineno"> 1739</span>&#160;{</div><div class="line"><a name="l01740"></a><span class="lineno"> 1740</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize3Stride3TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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;</div><div class="line"><a name="l01744"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#adce92334083f7abae7b3489dd73a6bad"> 1744</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#adce92334083f7abae7b3489dd73a6bad">L2Pooling2dSize3Stride3Int16Test</a>(</div><div class="line"><a name="l01745"></a><span class="lineno"> 1745</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01746"></a><span class="lineno"> 1746</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01747"></a><span class="lineno"> 1747</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01748"></a><span class="lineno"> 1748</span>&#160;{</div><div class="line"><a name="l01749"></a><span class="lineno"> 1749</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize3Stride3TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01750"></a><span class="lineno"> 1750</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a87075aa041ea71db03f8715c876d935f"> 1752</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a87075aa041ea71db03f8715c876d935f">L2Pooling2dSize3Stride4Test</a>(</div><div class="line"><a name="l01753"></a><span class="lineno"> 1753</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01754"></a><span class="lineno"> 1754</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</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_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</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> L2Pooling2dSize3Stride4TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01758"></a><span class="lineno"> 1758</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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"> 1760</span>&#160;</div><div class="line"><a name="l01761"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a8a532ef3dc9c0f9bab278408613c2d3c"> 1761</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a8a532ef3dc9c0f9bab278408613c2d3c">L2Pooling2dSize3Stride4Uint8Test</a>(</div><div class="line"><a name="l01762"></a><span class="lineno"> 1762</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01763"></a><span class="lineno"> 1763</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01764"></a><span class="lineno"> 1764</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</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;    <span class="keywordflow">return</span> L2Pooling2dSize3Stride4TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>&#160;}</div><div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>&#160;</div><div class="line"><a name="l01770"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a107fb3feb7d58601694580e70f517321"> 1770</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a107fb3feb7d58601694580e70f517321">L2Pooling2dSize3Stride4Int16Test</a>(</div><div class="line"><a name="l01771"></a><span class="lineno"> 1771</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01772"></a><span class="lineno"> 1772</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01773"></a><span class="lineno"> 1773</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01774"></a><span class="lineno"> 1774</span>&#160;{</div><div class="line"><a name="l01775"></a><span class="lineno"> 1775</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize3Stride4TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01776"></a><span class="lineno"> 1776</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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;</div><div class="line"><a name="l01779"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#aede50105e28116d2f3dee8e560ae386a"> 1779</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#aede50105e28116d2f3dee8e560ae386a">L2Pooling2dSize7Test</a>(</div><div class="line"><a name="l01780"></a><span class="lineno"> 1780</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01781"></a><span class="lineno"> 1781</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01782"></a><span class="lineno"> 1782</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01783"></a><span class="lineno"> 1783</span>&#160;{</div><div class="line"><a name="l01784"></a><span class="lineno"> 1784</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize7TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01785"></a><span class="lineno"> 1785</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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.xhtml#a4d1af0ebb95be7492f9fe9fd0cb500e3"> 1788</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a4d1af0ebb95be7492f9fe9fd0cb500e3">L2Pooling2dSize7Uint8Test</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.xhtml">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.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>&#160;{</div><div class="line"><a name="l01793"></a><span class="lineno"> 1793</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize7TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01794"></a><span class="lineno"> 1794</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01795"></a><span class="lineno"> 1795</span>&#160;}</div><div class="line"><a name="l01796"></a><span class="lineno"> 1796</span>&#160;</div><div class="line"><a name="l01797"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a53cdda233480f3323bdf6daf50d52dc9"> 1797</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a53cdda233480f3323bdf6daf50d52dc9">L2Pooling2dSize7Int16Test</a>(</div><div class="line"><a name="l01798"></a><span class="lineno"> 1798</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01799"></a><span class="lineno"> 1799</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01800"></a><span class="lineno"> 1800</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01801"></a><span class="lineno"> 1801</span>&#160;{</div><div class="line"><a name="l01802"></a><span class="lineno"> 1802</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize7TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01803"></a><span class="lineno"> 1803</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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"> 1805</span>&#160;</div><div class="line"><a name="l01806"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a50af9d3062e9a65532009182882a9346"> 1806</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a50af9d3062e9a65532009182882a9346">L2Pooling2dSize9Test</a>(</div><div class="line"><a name="l01807"></a><span class="lineno"> 1807</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01808"></a><span class="lineno"> 1808</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01809"></a><span class="lineno"> 1809</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</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> L2Pooling2dSize9TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01812"></a><span class="lineno"> 1812</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</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.xhtml#a04e67f517f6c414c2da165045e36c148"> 1815</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a04e67f517f6c414c2da165045e36c148">L2Pooling2dSize9Uint8Test</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.xhtml">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.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01818"></a><span class="lineno"> 1818</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01819"></a><span class="lineno"> 1819</span>&#160;{</div><div class="line"><a name="l01820"></a><span class="lineno"> 1820</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize9TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01821"></a><span class="lineno"> 1821</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01822"></a><span class="lineno"> 1822</span>&#160;}</div><div class="line"><a name="l01823"></a><span class="lineno"> 1823</span>&#160;</div><div class="line"><a name="l01824"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a61ff39d536c46c9b5eab282d786aa376"> 1824</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a61ff39d536c46c9b5eab282d786aa376">L2Pooling2dSize9Int16Test</a>(</div><div class="line"><a name="l01825"></a><span class="lineno"> 1825</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01826"></a><span class="lineno"> 1826</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01827"></a><span class="lineno"> 1827</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01828"></a><span class="lineno"> 1828</span>&#160;{</div><div class="line"><a name="l01829"></a><span class="lineno"> 1829</span>&#160;    <span class="keywordflow">return</span> L2Pooling2dSize9TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01830"></a><span class="lineno"> 1830</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01831"></a><span class="lineno"> 1831</span>&#160;}</div><div class="line"><a name="l01832"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#af505ddff09864af91b9c88be14ae9d40"> 1832</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#af505ddff09864af91b9c88be14ae9d40">IgnorePaddingSimpleL2Pooling2dTest</a>(</div><div class="line"><a name="l01833"></a><span class="lineno"> 1833</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01834"></a><span class="lineno"> 1834</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01835"></a><span class="lineno"> 1835</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01836"></a><span class="lineno"> 1836</span>&#160;{</div><div class="line"><a name="l01837"></a><span class="lineno"> 1837</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleL2Pooling2dTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01838"></a><span class="lineno"> 1838</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01839"></a><span class="lineno"> 1839</span>&#160;}</div><div class="line"><a name="l01840"></a><span class="lineno"> 1840</span>&#160;</div><div class="line"><a name="l01841"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#afbb3d6e16938473c96b1751b3f914e79"> 1841</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#afbb3d6e16938473c96b1751b3f914e79">IgnorePaddingSimpleL2Pooling2dUint8Test</a>(</div><div class="line"><a name="l01842"></a><span class="lineno"> 1842</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01843"></a><span class="lineno"> 1843</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01844"></a><span class="lineno"> 1844</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01845"></a><span class="lineno"> 1845</span>&#160;{</div><div class="line"><a name="l01846"></a><span class="lineno"> 1846</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleL2Pooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01847"></a><span class="lineno"> 1847</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01848"></a><span class="lineno"> 1848</span>&#160;}</div><div class="line"><a name="l01849"></a><span class="lineno"> 1849</span>&#160;</div><div class="line"><a name="l01850"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#ae479ee8c436c237bad1db32016904793"> 1850</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#ae479ee8c436c237bad1db32016904793">IgnorePaddingSimpleL2Pooling2dInt16Test</a>(</div><div class="line"><a name="l01851"></a><span class="lineno"> 1851</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01852"></a><span class="lineno"> 1852</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01853"></a><span class="lineno"> 1853</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01854"></a><span class="lineno"> 1854</span>&#160;{</div><div class="line"><a name="l01855"></a><span class="lineno"> 1855</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingSimpleL2Pooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01856"></a><span class="lineno"> 1856</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01857"></a><span class="lineno"> 1857</span>&#160;}</div><div class="line"><a name="l01858"></a><span class="lineno"> 1858</span>&#160;</div><div class="line"><a name="l01859"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a854b1d1211061a45f14cbab50e6f81fd"> 1859</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a854b1d1211061a45f14cbab50e6f81fd">IgnorePaddingL2Pooling2dSize3Test</a>(</div><div class="line"><a name="l01860"></a><span class="lineno"> 1860</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01861"></a><span class="lineno"> 1861</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01862"></a><span class="lineno"> 1862</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01863"></a><span class="lineno"> 1863</span>&#160;{</div><div class="line"><a name="l01864"></a><span class="lineno"> 1864</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingL2Pooling2dSize3TestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01865"></a><span class="lineno"> 1865</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01866"></a><span class="lineno"> 1866</span>&#160;}</div><div class="line"><a name="l01867"></a><span class="lineno"> 1867</span>&#160;</div><div class="line"><a name="l01868"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a6c06ab6f3153c690d39f9a88120c2645"> 1868</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a6c06ab6f3153c690d39f9a88120c2645">IgnorePaddingL2Pooling2dSize3Uint8Test</a>(</div><div class="line"><a name="l01869"></a><span class="lineno"> 1869</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01870"></a><span class="lineno"> 1870</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01871"></a><span class="lineno"> 1871</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01872"></a><span class="lineno"> 1872</span>&#160;{</div><div class="line"><a name="l01873"></a><span class="lineno"> 1873</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingL2Pooling2dSize3TestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01874"></a><span class="lineno"> 1874</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01875"></a><span class="lineno"> 1875</span>&#160;}</div><div class="line"><a name="l01876"></a><span class="lineno"> 1876</span>&#160;</div><div class="line"><a name="l01877"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a27406e3855c4c293dc50ac131eef292c"> 1877</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a27406e3855c4c293dc50ac131eef292c">IgnorePaddingL2Pooling2dSize3Int16Test</a>(</div><div class="line"><a name="l01878"></a><span class="lineno"> 1878</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01879"></a><span class="lineno"> 1879</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01880"></a><span class="lineno"> 1880</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01881"></a><span class="lineno"> 1881</span>&#160;{</div><div class="line"><a name="l01882"></a><span class="lineno"> 1882</span>&#160;    <span class="keywordflow">return</span> IgnorePaddingL2Pooling2dSize3TestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01883"></a><span class="lineno"> 1883</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01884"></a><span class="lineno"> 1884</span>&#160;}</div><div class="line"><a name="l01885"></a><span class="lineno"> 1885</span>&#160;</div><div class="line"><a name="l01886"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a5f7af512644b76af39b8ca0601c1e4f6"> 1886</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a5f7af512644b76af39b8ca0601c1e4f6">AsymmetricNonSquarePooling2dTest</a>(</div><div class="line"><a name="l01887"></a><span class="lineno"> 1887</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01888"></a><span class="lineno"> 1888</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01889"></a><span class="lineno"> 1889</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01890"></a><span class="lineno"> 1890</span>&#160;{</div><div class="line"><a name="l01891"></a><span class="lineno"> 1891</span>&#160;    <span class="keywordflow">return</span> AsymmetricNonSquarePooling2dTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01892"></a><span class="lineno"> 1892</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01893"></a><span class="lineno"> 1893</span>&#160;}</div><div class="line"><a name="l01894"></a><span class="lineno"> 1894</span>&#160;</div><div class="line"><a name="l01895"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a7db36aeba6b21f71a358e7045c8170f6"> 1895</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a7db36aeba6b21f71a358e7045c8170f6">AsymmetricNonSquarePooling2dUint8Test</a>(</div><div class="line"><a name="l01896"></a><span class="lineno"> 1896</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01897"></a><span class="lineno"> 1897</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01898"></a><span class="lineno"> 1898</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01899"></a><span class="lineno"> 1899</span>&#160;{</div><div class="line"><a name="l01900"></a><span class="lineno"> 1900</span>&#160;    <span class="keywordflow">return</span> AsymmetricNonSquarePooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01901"></a><span class="lineno"> 1901</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01902"></a><span class="lineno"> 1902</span>&#160;}</div><div class="line"><a name="l01903"></a><span class="lineno"> 1903</span>&#160;</div><div class="line"><a name="l01904"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a4c4f3be262de9165bd65893e2c8b4046"> 1904</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a4c4f3be262de9165bd65893e2c8b4046">AsymmetricNonSquarePooling2dInt16Test</a>(</div><div class="line"><a name="l01905"></a><span class="lineno"> 1905</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01906"></a><span class="lineno"> 1906</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01907"></a><span class="lineno"> 1907</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory)</div><div class="line"><a name="l01908"></a><span class="lineno"> 1908</span>&#160;{</div><div class="line"><a name="l01909"></a><span class="lineno"> 1909</span>&#160;    <span class="keywordflow">return</span> AsymmetricNonSquarePooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01910"></a><span class="lineno"> 1910</span>&#160;            workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l01911"></a><span class="lineno"> 1911</span>&#160;}</div><div class="line"><a name="l01912"></a><span class="lineno"> 1912</span>&#160;</div><div class="line"><a name="l01913"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#ac2d7d039990aea21189c39d5c721b488"> 1913</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;float, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#ac2d7d039990aea21189c39d5c721b488">ComparePooling2dTest</a>(</div><div class="line"><a name="l01914"></a><span class="lineno"> 1914</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01915"></a><span class="lineno"> 1915</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01916"></a><span class="lineno"> 1916</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; refWorkloadFactory,</div><div class="line"><a name="l01917"></a><span class="lineno"> 1917</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01918"></a><span class="lineno"> 1918</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; refTensorHandleFactory,</div><div class="line"><a name="l01919"></a><span class="lineno"> 1919</span>&#160;    <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a>  poolingType)</div><div class="line"><a name="l01920"></a><span class="lineno"> 1920</span>&#160;{</div><div class="line"><a name="l01921"></a><span class="lineno"> 1921</span>&#160;    <span class="keywordflow">return</span> ComparePooling2dTestCommon&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l01922"></a><span class="lineno"> 1922</span>&#160;        workloadFactory, memoryManager,  refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, poolingType);</div><div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>&#160;}</div><div class="line"><a name="l01924"></a><span class="lineno"> 1924</span>&#160;</div><div class="line"><a name="l01925"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a60a9b8d416252310b0fe082cdd8ef95f"> 1925</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;uint8_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a60a9b8d416252310b0fe082cdd8ef95f">ComparePooling2dUint8Test</a>(</div><div class="line"><a name="l01926"></a><span class="lineno"> 1926</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01927"></a><span class="lineno"> 1927</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01928"></a><span class="lineno"> 1928</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; refWorkloadFactory,</div><div class="line"><a name="l01929"></a><span class="lineno"> 1929</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01930"></a><span class="lineno"> 1930</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; refTensorHandleFactory,</div><div class="line"><a name="l01931"></a><span class="lineno"> 1931</span>&#160;    <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a>  poolingType)</div><div class="line"><a name="l01932"></a><span class="lineno"> 1932</span>&#160;{</div><div class="line"><a name="l01933"></a><span class="lineno"> 1933</span>&#160;    <span class="keywordflow">return</span> ComparePooling2dTestCommon&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l01934"></a><span class="lineno"> 1934</span>&#160;        workloadFactory, memoryManager,  refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory,</div><div class="line"><a name="l01935"></a><span class="lineno"> 1935</span>&#160;        poolingType, 0.1f, 128);</div><div class="line"><a name="l01936"></a><span class="lineno"> 1936</span>&#160;}</div><div class="line"><a name="l01937"></a><span class="lineno"> 1937</span>&#160;</div><div class="line"><a name="l01938"></a><span class="lineno"><a class="line" href="_pooling2d_test_impl_8hpp.xhtml#a6f431ecff87308a54cc3dde327b368ff"> 1938</a></span>&#160;<a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;int16_t, 4&gt;</a> <a class="code" href="_pooling2d_test_impl_8cpp.xhtml#a6f431ecff87308a54cc3dde327b368ff">ComparePooling2dInt16Test</a>(</div><div class="line"><a name="l01939"></a><span class="lineno"> 1939</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; workloadFactory,</div><div class="line"><a name="l01940"></a><span class="lineno"> 1940</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>&amp; memoryManager,</div><div class="line"><a name="l01941"></a><span class="lineno"> 1941</span>&#160;    <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; refWorkloadFactory,</div><div class="line"><a name="l01942"></a><span class="lineno"> 1942</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; tensorHandleFactory,</div><div class="line"><a name="l01943"></a><span class="lineno"> 1943</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>&amp; refTensorHandleFactory,</div><div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>&#160;    <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a>  poolingType)</div><div class="line"><a name="l01945"></a><span class="lineno"> 1945</span>&#160;{</div><div class="line"><a name="l01946"></a><span class="lineno"> 1946</span>&#160;    <span class="keywordflow">return</span> ComparePooling2dTestCommon&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l01947"></a><span class="lineno"> 1947</span>&#160;        workloadFactory, memoryManager,  refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, poolingType);</div><div class="line"><a name="l01948"></a><span class="lineno"> 1948</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorShape::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdoc">Function that calculates the tensor elements by multiplying all dimension size which are Specified...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00181">Tensor.cpp:181</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a0bbcbeb6102a5354028a18056e323b26"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a0bbcbeb6102a5354028a18056e323b26">L2Pooling2dSize3Stride1Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize3Stride1Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01708">Pooling2dTestImpl.cpp:1708</a></div></div>
<div class="ttc" id="_ignore_unused_8hpp_xhtml"><div class="ttname"><a href="_ignore_unused_8hpp.xhtml">IgnoreUnused.hpp</a></div></div>
<div class="ttc" id="_tensor_copy_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_copy_utils_8hpp.xhtml">TensorCopyUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a9f7e4296485d2812e7996089149c96d1"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a9f7e4296485d2812e7996089149c96d1">armnn::IWorkloadFactory::GetBackendId</a></div><div class="ttdeci">virtual const BackendId &amp; GetBackendId() const =0</div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a8294d39b64461dc8cc264e2090428d8f"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a8294d39b64461dc8cc264e2090428d8f">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::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01689">Pooling2dTestImpl.cpp:1689</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_af1f2a5c336e021b1c1a2cfd9c66644b2"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#af1f2a5c336e021b1c1a2cfd9c66644b2">SimpleMaxPooling2dSize2x2Stride2x2Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; SimpleMaxPooling2dSize2x2Stride2x2Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01389">Pooling2dTestImpl.cpp:1389</a></div></div>
<div class="ttc" id="_data_layout_indexed_8hpp_xhtml"><div class="ttname"><a href="_data_layout_indexed_8hpp.xhtml">DataLayoutIndexed.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00371">Descriptors.hpp:371</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00050">Types.hpp:50</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml_a414e6f95548e6f7a01d5028b55ad3941"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml#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.xhtml#l00025">DataLayoutIndexed.hpp:25</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a8a3cfd8f41f6fae3ff94fcb0f7926693"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a8a3cfd8f41f6fae3ff94fcb0f7926693">IgnorePaddingAveragePooling2dSize3Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingAveragePooling2dSize3Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01660">Pooling2dTestImpl.cpp:1660</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aea548aa1485adbeeb3e393a13bb6bff8"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00542">LayerSupport.cpp:542</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a61f14785fbec16c8820b55fd895fc763"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a61f14785fbec16c8820b55fd895fc763">IgnorePaddingAveragePooling2dSize3Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingAveragePooling2dSize3Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01642">Pooling2dTestImpl.cpp:1642</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#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.xhtml#l00187">Tensor.hpp:187</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb"><div class="ttname"><a href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">armnn::OutputShapeRounding::Ceiling</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00365">Descriptors.hpp:365</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3"><div class="ttname"><a href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_ab693227602a70e077d310acf71c0c08d"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#ab693227602a70e077d310acf71c0c08d">LargeTensorsAveragePooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; LargeTensorsAveragePooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01580">Pooling2dTestImpl.cpp:1580</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_ab7a75e53f39941cb732a35a8b2dd6c60"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#ab7a75e53f39941cb732a35a8b2dd6c60">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::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01459">Pooling2dTestImpl.cpp:1459</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a98ea0eccf818625f0d4c6ea5dbc6f452"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a98ea0eccf818625f0d4c6ea5dbc6f452">IgnorePaddingSimpleMaxPooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingSimpleMaxPooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01486">Pooling2dTestImpl.cpp:1486</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="_quantize_helper_8hpp_xhtml"><div class="ttname"><a href="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.xhtml#l00022">WorkloadFactory.hpp:22</a></div></div>
<div class="ttc" id="_workload_test_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_test_utils_8hpp.xhtml">WorkloadTestUtils.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a6c607ea3a6688789e82b78298903e5d2"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a6c607ea3a6688789e82b78298903e5d2">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::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01449">Pooling2dTestImpl.cpp:1449</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_af505ddff09864af91b9c88be14ae9d40"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#af505ddff09864af91b9c88be14ae9d40">IgnorePaddingSimpleL2Pooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingSimpleL2Pooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01832">Pooling2dTestImpl.cpp:1832</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00373">Descriptors.hpp:373</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a6c06ab6f3153c690d39f9a88120c2645"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a6c06ab6f3153c690d39f9a88120c2645">IgnorePaddingL2Pooling2dSize3Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingL2Pooling2dSize3Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01868">Pooling2dTestImpl.cpp:1868</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6"><div class="ttname"><a href="namespacearmnn.xhtml#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="structarmnn_1_1_pooling2d_descriptor_xhtml_a8c29d6ea9b4186d69aad5961c910939c"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00383">Descriptors.hpp:383</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a854b1d1211061a45f14cbab50e6f81fd"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a854b1d1211061a45f14cbab50e6f81fd">IgnorePaddingL2Pooling2dSize3Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingL2Pooling2dSize3Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01859">Pooling2dTestImpl.cpp:1859</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_ad18df1220453e97c0686a129b2d2d79b"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#ad18df1220453e97c0686a129b2d2d79b">SimpleMaxPooling2dSize2x2Stride2x2Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleMaxPooling2dSize2x2Stride2x2Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01379">Pooling2dTestImpl.cpp:1379</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::Pooling2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00369">Descriptors.hpp:369</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a2fbb1973ecc2c9f0943922e9a122af63"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a2fbb1973ecc2c9f0943922e9a122af63">SimpleMaxPooling2dSize3x3Stride2x4Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; SimpleMaxPooling2dSize3x3Stride2x4Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01429">Pooling2dTestImpl.cpp:1429</a></div></div>
<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_ad89767b400c345ca8f2b35c5b57e4d45"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#ad89767b400c345ca8f2b35c5b57e4d45">IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01624">Pooling2dTestImpl.cpp:1624</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_aa3e57d4e48a91435d73487dabacc091b"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#aa3e57d4e48a91435d73487dabacc091b">SimpleMaxPooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleMaxPooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01439">Pooling2dTestImpl.cpp:1439</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &amp;&amp;...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a></div><div class="ttdeci">PoolingAlgorithm</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00104">Types.hpp:104</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a50af9d3062e9a65532009182882a9346"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a50af9d3062e9a65532009182882a9346">L2Pooling2dSize9Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize9Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01806">Pooling2dTestImpl.cpp:1806</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00057">WorkloadData.hpp:57</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a6f431ecff87308a54cc3dde327b368ff"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a6f431ecff87308a54cc3dde327b368ff">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, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::ITensorHandleFactory &amp;refTensorHandleFactory, armnn::PoolingAlgorithm poolingType)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01938">Pooling2dTestImpl.cpp:1938</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00377">Descriptors.hpp:377</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a107fb3feb7d58601694580e70f517321"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a107fb3feb7d58601694580e70f517321">L2Pooling2dSize3Stride4Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize3Stride4Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01770">Pooling2dTestImpl.cpp:1770</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a4c4f3be262de9165bd65893e2c8b4046"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a4c4f3be262de9165bd65893e2c8b4046">AsymmetricNonSquarePooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; AsymmetricNonSquarePooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01904">Pooling2dTestImpl.cpp:1904</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml_a61c00316c443adc233c24e85c6c5b740"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a61c00316c443adc233c24e85c6c5b740">armnnUtils::DataLayoutIndexed::GetHeightIndex</a></div><div class="ttdeci">unsigned int GetHeightIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00024">DataLayoutIndexed.hpp:24</a></div></div>
<div class="ttc" id="_numeric_cast_8hpp_xhtml"><div class="ttname"><a href="_numeric_cast_8hpp.xhtml">NumericCast.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a716ac8b594c1f6b9fa2bbde4597756d5"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a716ac8b594c1f6b9fa2bbde4597756d5">L2Pooling2dSize3Stride1Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize3Stride1Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01699">Pooling2dTestImpl.cpp:1699</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a3e863f692b93f2f36ae0787a0421c952"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a3e863f692b93f2f36ae0787a0421c952">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::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01679">Pooling2dTestImpl.cpp:1679</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a60a9b8d416252310b0fe082cdd8ef95f"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a60a9b8d416252310b0fe082cdd8ef95f">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, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::ITensorHandleFactory &amp;refTensorHandleFactory, armnn::PoolingAlgorithm poolingType)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01925">Pooling2dTestImpl.cpp:1925</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00375">Descriptors.hpp:375</a></div></div>
<div class="ttc" id="namespacearmnn_utils_xhtml_af3c74017185773dd61d8ca6662d65d43"><div class="ttname"><a href="namespacearmnn_utils.xhtml#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.xhtml#l00131">Permute.cpp:131</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_aa4bc368a4e78d01a9b7daaad2a2dbd51"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#aa4bc368a4e78d01a9b7daaad2a2dbd51">SimpleL2Pooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleL2Pooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01669">Pooling2dTestImpl.cpp:1669</a></div></div>
<div class="ttc" id="_tensor_helpers_8hpp_xhtml"><div class="ttname"><a href="_tensor_helpers_8hpp.xhtml">TensorHelpers.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_adce92334083f7abae7b3489dd73a6bad"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#adce92334083f7abae7b3489dd73a6bad">L2Pooling2dSize3Stride3Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize3Stride3Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01744">Pooling2dTestImpl.cpp:1744</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a01ba3efd925240328de48bc75a8cc076"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a01ba3efd925240328de48bc75a8cc076">L2Pooling2dSize3Stride3Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize3Stride3Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01726">Pooling2dTestImpl.cpp:1726</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a8a532ef3dc9c0f9bab278408613c2d3c"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a8a532ef3dc9c0f9bab278408613c2d3c">L2Pooling2dSize3Stride4Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize3Stride4Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01761">Pooling2dTestImpl.cpp:1761</a></div></div>
<div class="ttc" id="_permute_8hpp_xhtml"><div class="ttname"><a href="_permute_8hpp.xhtml">Permute.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a45b7b4ee1096c02cb56cc68907171533"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a45b7b4ee1096c02cb56cc68907171533">IgnorePaddingAveragePooling2dSize3x2Stride2x2Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingAveragePooling2dSize3x2Stride2x2Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01552">Pooling2dTestImpl.cpp:1552</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a2a0bad554a0733d7af21b9d0eca627d7"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a2a0bad554a0733d7af21b9d0eca627d7">LargeTensorsAveragePooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; LargeTensorsAveragePooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01562">Pooling2dTestImpl.cpp:1562</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a92b460c3ad7d8ad1e3cc91fca779423f"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a92b460c3ad7d8ad1e3cc91fca779423f">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::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01532">Pooling2dTestImpl.cpp:1532</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00367">Descriptors.hpp:367</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_ace5d07b4866c0c0a7d6c20a1608c3213"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#ace5d07b4866c0c0a7d6c20a1608c3213">SimpleAveragePooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleAveragePooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01522">Pooling2dTestImpl.cpp:1522</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_backend_internal_xhtml_a693b40e6b94e958836aeb0410ca186bd"><div class="ttname"><a href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a></div><div class="ttdeci">std::shared_ptr&lt; IMemoryManager &gt; IMemoryManagerSharedPtr</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.xhtml#l00092">IBackendInternal.hpp:92</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml">armnnUtils::DataLayoutIndexed</a></div><div class="ttdoc">Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00017">DataLayoutIndexed.hpp:17</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a6e05c1f0877310caac35214456502cd5"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a6e05c1f0877310caac35214456502cd5">IgnorePaddingSimpleAveragePooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingSimpleAveragePooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01597">Pooling2dTestImpl.cpp:1597</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_aede50105e28116d2f3dee8e560ae386a"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#aede50105e28116d2f3dee8e560ae386a">L2Pooling2dSize7Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize7Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01779">Pooling2dTestImpl.cpp:1779</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a04e67f517f6c414c2da165045e36c148"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a04e67f517f6c414c2da165045e36c148">L2Pooling2dSize9Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize9Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01815">Pooling2dTestImpl.cpp:1815</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#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.xhtml#l00464">Tensor.cpp:464</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a6c6b75b8666fab92de438be79ca9ed64"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a6c6b75b8666fab92de438be79ca9ed64">IgnorePaddingAveragePooling2dSize3Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingAveragePooling2dSize3Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01651">Pooling2dTestImpl.cpp:1651</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a87075aa041ea71db03f8715c876d935f"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a87075aa041ea71db03f8715c876d935f">L2Pooling2dSize3Stride4Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; L2Pooling2dSize3Stride4Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01752">Pooling2dTestImpl.cpp:1752</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_ac2d7d039990aea21189c39d5c721b488"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#ac2d7d039990aea21189c39d5c721b488">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, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::ITensorHandleFactory &amp;refTensorHandleFactory, armnn::PoolingAlgorithm poolingType)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01913">Pooling2dTestImpl.cpp:1913</a></div></div>
<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a53cdda233480f3323bdf6daf50d52dc9"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a53cdda233480f3323bdf6daf50d52dc9">L2Pooling2dSize7Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize7Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01797">Pooling2dTestImpl.cpp:1797</a></div></div>
<div class="ttc" id="classarmnn_1_1_permutation_vector_xhtml"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00212">Types.hpp:212</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a15d723fdf9c3c80f6b5deb2e66240622"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a15d723fdf9c3c80f6b5deb2e66240622">SimpleMaxPooling2dSize3x3Stride2x4Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; SimpleMaxPooling2dSize3x3Stride2x4Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01409">Pooling2dTestImpl.cpp:1409</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00385">Descriptors.hpp:385</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a6e95afd9a55700cbf6f9e8db8089f2f2"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#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.xhtml#l01567">WorkloadFactory.cpp:1567</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a7db36aeba6b21f71a358e7045c8170f6"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a7db36aeba6b21f71a358e7045c8170f6">AsymmetricNonSquarePooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; AsymmetricNonSquarePooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01895">Pooling2dTestImpl.cpp:1895</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a5f7af512644b76af39b8ca0601c1e4f6"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a5f7af512644b76af39b8ca0601c1e4f6">AsymmetricNonSquarePooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; AsymmetricNonSquarePooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01886">Pooling2dTestImpl.cpp:1886</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_af6da475d5a9c9349cb7213e610acf89e"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#af6da475d5a9c9349cb7213e610acf89e">IgnorePaddingSimpleAveragePooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingSimpleAveragePooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01606">Pooling2dTestImpl.cpp:1606</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_af2f5d449f05421b21cb686d6b341e75a"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#af2f5d449f05421b21cb686d6b341e75a">IgnorePaddingSimpleMaxPooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingSimpleMaxPooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01477">Pooling2dTestImpl.cpp:1477</a></div></div>
<div class="ttc" id="_layer_support_8hpp_xhtml"><div class="ttname"><a href="_layer_support_8hpp.xhtml">LayerSupport.hpp</a></div></div>
<div class="ttc" id="_tensor_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_utils_8hpp.xhtml">TensorUtils.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00363">Descriptors.hpp:363</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a30dbe98e901d2315c7dc8d92789a3270"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a30dbe98e901d2315c7dc8d92789a3270">IgnorePaddingSimpleAveragePooling2dNoPaddingInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingSimpleAveragePooling2dNoPaddingInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01633">Pooling2dTestImpl.cpp:1633</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a"><div class="ttname"><a href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a></div><div class="ttdoc">The padding fields count, but are ignored. </div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a3b8c319c895ac738290d754f913471cd"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a3b8c319c895ac738290d754f913471cd">IgnorePaddingMaxPooling2dSize3Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingMaxPooling2dSize3Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01504">Pooling2dTestImpl.cpp:1504</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_ade050660fe0a2557ba60130c40f40017"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#ade050660fe0a2557ba60130c40f40017">IgnorePaddingMaxPooling2dSize3Test</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingMaxPooling2dSize3Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01495">Pooling2dTestImpl.cpp:1495</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00041">ITensorHandleFactory.hpp:41</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_affb5b68b3eba3ed45a06c7cde7781962"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00381">Descriptors.hpp:381</a></div></div>
<div class="ttc" id="src_2backends_2backends_common_2_workload_info_8hpp_xhtml"><div class="ttname"><a href="src_2backends_2backends_common_2_workload_info_8hpp.xhtml">WorkloadInfo.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a61ff39d536c46c9b5eab282d786aa376"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a61ff39d536c46c9b5eab282d786aa376">L2Pooling2dSize9Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize9Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01824">Pooling2dTestImpl.cpp:1824</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a375ca3cff9f1b005d1412dc5f3cf5b6e"><div class="ttname"><a href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t&lt; std::is_unsigned&lt; Source &gt;::value &amp;&amp;std::is_unsigned&lt; Dest &gt;::value, Dest &gt; numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00035">NumericCast.hpp:35</a></div></div>
<div class="ttc" id="namespacearmnn_utils_xhtml"><div class="ttname"><a href="namespacearmnn_utils.xhtml">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00013">DataLayoutIndexed.hpp:13</a></div></div>
<div class="ttc" id="namespacearmnn_utils_xhtml_acee63cd08da47910fc166a1990988fa8"><div class="ttname"><a href="namespacearmnn_utils.xhtml#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.xhtml#l00038">TensorUtils.cpp:38</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a1cfcbf24e161da40af56add364386513"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a1cfcbf24e161da40af56add364386513">LargeTensorsAveragePooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; LargeTensorsAveragePooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01571">Pooling2dTestImpl.cpp:1571</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a></div></div>
<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div>
<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00030">LayerTestResult.hpp:30</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8hpp_xhtml"><div class="ttname"><a href="_pooling2d_test_impl_8hpp.xhtml">Pooling2dTestImpl.hpp</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_ac882f58604273a64c05f572aa1dabbed"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#ac882f58604273a64c05f572aa1dabbed">L2Pooling2dSize3Stride3Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize3Stride3Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01735">Pooling2dTestImpl.cpp:1735</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#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.xhtml#l00480">Tensor.cpp:480</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_afbb3d6e16938473c96b1751b3f914e79"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#afbb3d6e16938473c96b1751b3f914e79">IgnorePaddingSimpleL2Pooling2dUint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; IgnorePaddingSimpleL2Pooling2dUint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01841">Pooling2dTestImpl.cpp:1841</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_aeb0f50adb2d9d42bfc469b3c961b344c"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#aeb0f50adb2d9d42bfc469b3c961b344c">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::ITensorHandleFactory &amp;tensorHandleFactory, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01542">Pooling2dTestImpl.cpp:1542</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a0fa96bdee9e4e1b84b1ead192e4d37d3"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a0fa96bdee9e4e1b84b1ead192e4d37d3">IgnorePaddingSimpleAveragePooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingSimpleAveragePooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01588">Pooling2dTestImpl.cpp:1588</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_abd30e75a9348c916154fe64dce659933"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#abd30e75a9348c916154fe64dce659933">IgnorePaddingMaxPooling2dSize3Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingMaxPooling2dSize3Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01513">Pooling2dTestImpl.cpp:1513</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a8ea02afa5072ae475b4fa19e9674796d"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a8ea02afa5072ae475b4fa19e9674796d">IgnorePaddingSimpleAveragePooling2dNoPaddingTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingSimpleAveragePooling2dNoPaddingTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01615">Pooling2dTestImpl.cpp:1615</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">armnn::Pooling2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00186">WorkloadData.hpp:186</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00329">Descriptors.hpp:329</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a8f8edbf4d70c91dcfefeb6bcfc48dfb4"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a8f8edbf4d70c91dcfefeb6bcfc48dfb4">IgnorePaddingSimpleMaxPooling2dTest</a></div><div class="ttdeci">LayerTestResult&lt; float, 4 &gt; IgnorePaddingSimpleMaxPooling2dTest(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01468">Pooling2dTestImpl.cpp:1468</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_aba20cbea840a4a32df631ba77ab67087"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#aba20cbea840a4a32df631ba77ab67087">L2Pooling2dSize3Stride1Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; L2Pooling2dSize3Stride1Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01717">Pooling2dTestImpl.cpp:1717</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a27406e3855c4c293dc50ac131eef292c"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a27406e3855c4c293dc50ac131eef292c">IgnorePaddingL2Pooling2dSize3Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingL2Pooling2dSize3Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01877">Pooling2dTestImpl.cpp:1877</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a38e23959bb4200e6e019aa490f151e62"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a38e23959bb4200e6e019aa490f151e62">SimpleMaxPooling2dSize3x3Stride2x4Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; SimpleMaxPooling2dSize3x3Stride2x4Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01419">Pooling2dTestImpl.cpp:1419</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_ae479ee8c436c237bad1db32016904793"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#ae479ee8c436c237bad1db32016904793">IgnorePaddingSimpleL2Pooling2dInt16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; IgnorePaddingSimpleL2Pooling2dInt16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01850">Pooling2dTestImpl.cpp:1850</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_afdded119a95bdac07fd8d086b1cc9b5f"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#afdded119a95bdac07fd8d086b1cc9b5f">SimpleMaxPooling2dSize2x2Stride2x2Int16Test</a></div><div class="ttdeci">LayerTestResult&lt; int16_t, 4 &gt; SimpleMaxPooling2dSize2x2Stride2x2Int16Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory, bool forceNoPadding)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01399">Pooling2dTestImpl.cpp:1399</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml_a861b2621ee46e4b63379988b360b8cd9"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml#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.xhtml#l00023">DataLayoutIndexed.hpp:23</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr&lt; ITensorHandle &gt; CreateTensorHandle(const TensorInfo &amp;tensorInfo) const =0</div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00379">Descriptors.hpp:379</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
<div class="ttc" id="_pooling2d_test_impl_8cpp_xhtml_a4d1af0ebb95be7492f9fe9fd0cb500e3"><div class="ttname"><a href="_pooling2d_test_impl_8cpp.xhtml#a4d1af0ebb95be7492f9fe9fd0cb500e3">L2Pooling2dSize7Uint8Test</a></div><div class="ttdeci">LayerTestResult&lt; uint8_t, 4 &gt; L2Pooling2dSize7Uint8Test(armnn::IWorkloadFactory &amp;workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &amp;memoryManager, const armnn::ITensorHandleFactory &amp;tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_test_impl_8cpp_source.xhtml#l01788">Pooling2dTestImpl.cpp:1788</a></div></div>
<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div>
<div class="ttc" id="classarmnn_1_1_backend_id_xhtml"><div class="ttname"><a href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.xhtml#l00075">BackendId.hpp:75</a></div></div>
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