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authorDavid Monahan <david.monahan@arm.com>2023-03-22 16:48:58 +0000
committerDavid Monahan <david.monahan@arm.com>2023-03-22 16:48:58 +0000
commitae050524109f1ce827962665436ef7430f2ac479 (patch)
treea087fe0c77570971dd7979f2757426c24e91afc7 /23.02/_neon_depthwise_convolution_workload_8cpp_source.xhtml
parent8d2ca734165a068478df7cffa46185680b05cd20 (diff)
downloadarmnn-ae050524109f1ce827962665436ef7430f2ac479.tar.gz
IVGCVSW-7255 Update Doxygen Documentation and publish on GitHub.
* Updating Doxygen documentation for 23.02 release. Signed-off-by: David Monahan <david.monahan@arm.com> Change-Id: I545574ff7664b4595d2fe6a91a3c35d2ad55df82
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<div class="title">NeonDepthwiseConvolutionWorkload.cpp</div> </div>
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-<a href="_neon_depthwise_convolution_workload_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 © 2017,2022 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="_neon_depthwise_convolution_workload_8hpp.xhtml">NeonDepthwiseConvolutionWorkload.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 &quot;<a class="code" href="_neon_workload_utils_8hpp.xhtml">NeonWorkloadUtils.hpp</a>&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno"> 10</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="l00011"></a><span class="lineno"> 11</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_arm_compute_tensor_utils_8hpp.xhtml">aclCommon/ArmComputeTensorUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_arm_compute_utils_8hpp.xhtml">aclCommon/ArmComputeUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_neon_layer_support_8hpp.xhtml">neon/NeonLayerSupport.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="_tensor_handle_8hpp.xhtml">armnn/backends/TensorHandle.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="_workload_utils_8hpp.xhtml">backendsCommon/WorkloadUtils.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;arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h&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="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.xhtml">armnnUtils</a>;</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;{</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="keyword">using namespace </span>armcomputetensorutils;</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"><a class="line" href="namespacearmnn.xhtml#a63d684b26fb838b22123490d780bce08"> 29</a></span>&#160;<a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.xhtml#a63d684b26fb838b22123490d780bce08">NeonDepthwiseConvolutionWorkloadValidate</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; input,</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; output,</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a>&amp; descriptor,</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; weights,</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional&lt;TensorInfo&gt;</a>&amp; biases,</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">ActivationDescriptor</a>* activationDescriptor)</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;{</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="comment">// ArmNN format for weights for depthwise is [1, H, W, C] independently of the input/output layout</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="comment">// ACL format for weights for depthwise is:</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="comment">// - [1, H, W, C] for [N, H, W, C] input/output layout (matches with ArmNN)</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="comment">// - [1, C, H, W] for [N, C, H, W] input/output layout</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="comment">// Therefore ArmNN weights have to be permuted when input/output layout is [N, C, H, W] to pass them to ACL.</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="comment">// The PermuteDepthwiseConv2dWeights backend optimization takes care of this, but it has not been performed yet,</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="comment">// so we do the permute here for the TensorInfo weights.</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> aclDepthMultiplier;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> weightsPermuted;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; std::tie(weightsPermuted, aclDepthMultiplier) = <a class="code" href="namespacearmnn.xhtml#ac4aa9e41515b354234645f115c49de32">Convert1HWOTensorInfoToAcl</a>(weights, input, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="comment">// Convert the weights into the compute library format</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weightsPermuted, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; aclWeightsInfo.set_are_values_constant(weights.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; arm_compute::TensorInfo aclBiasesInfo;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; arm_compute::TensorInfo* optionalAclBiasesInfo = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</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="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(biases.<a class="code" href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</a>());</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <span class="comment">// Same for bias as weights. We don&#39;t currently support non const.</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="keywordflow">if</span> (!biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>())</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; {</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>{arm_compute::ErrorCode::RUNTIME_ERROR,</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="stringliteral">&quot;ArmNN NeonDepthwiseConv2dWorkload does not support non constant bias.&quot;</span>};</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; }</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; aclBiasesInfo = BuildArmComputeTensorInfo(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>(), descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; aclBiasesInfo.set_are_values_constant(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; optionalAclBiasesInfo = &amp;aclBiasesInfo;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; }</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; arm_compute::PadStrideInfo aclPadStrideInfo = BuildArmComputePadStrideInfo(descriptor);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <span class="keyword">const</span> arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a>, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a>);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keyword">const</span> arm_compute::ActivationLayerInfo activationInfo = <a class="code" href="namespacearmnn.xhtml#ad701d0d29baa4266ab4d33b090aa661c">ConvertActivationDescriptorToAclActivationLayerInfo</a>(</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; activationDescriptor);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="keywordflow">return</span> arm_compute::NEDepthwiseConvolutionLayer::validate(&amp;aclInputInfo,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; &amp;aclWeightsInfo,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; optionalAclBiasesInfo,</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; &amp;aclOutputInfo,</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; aclPadStrideInfo,</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; aclDepthMultiplier,</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; activationInfo,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; aclDilationInfo);</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;</div><div class="line"><a name="l00089"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#aa6173c66256d333ee73a068206c746d6"> 89</a></span>&#160;<a class="code" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#aa6173c66256d333ee73a068206c746d6">NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload</a>(</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">DepthwiseConvolution2dQueueDescriptor</a>&amp; descriptor,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>&amp; info)</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; : <a class="code" href="classarmnn_1_1_neon_base_workload.xhtml">NeonBaseWorkload</a>&lt;<a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">DepthwiseConvolution2dQueueDescriptor</a>&gt;(descriptor, info)</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160;{</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; arm_compute::ITensor&amp; input = PolymorphicDowncast&lt;IAclTensorHandle*&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0])-&gt;GetTensor();</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; arm_compute::ITensor&amp; output = PolymorphicDowncast&lt;IAclTensorHandle*&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0])-&gt;GetTensor();</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; arm_compute::ITensor&amp; weights = PolymorphicDowncast&lt;IAclTensorHandle*&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[1])-&gt;GetTensor();</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; arm_compute::ITensor* biasesPtr = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</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; biasesPtr = &amp;PolymorphicDowncast&lt;IAclTensorHandle *&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[2])-&gt;GetTensor();</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;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; arm_compute::ITensorInfo* weightsInfo = weights.info();</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; arm_compute::ITensorInfo* inputInfo = input.info();</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <span class="keyword">auto</span> weightsShape = weightsInfo-&gt;tensor_shape();</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="keyword">auto</span> inputShape = inputInfo-&gt;tensor_shape();</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160;</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <span class="comment">// The PermuteDepthwiseConv2dWeights backend optimization has been performed,</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="comment">// converting weights to have the same data layout as input.</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthMultiplier =</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; ComputeDepthwiseConv2dDepthMultiplier(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>, weightsShape, inputShape);</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="keyword">const</span> arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a>, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a>);</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; uint32_t numInputs = <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> ? 3: 2;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">&quot;NeonDepthwiseConvolutionWorkload&quot;</span>, numInputs, 1);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a> aclDataLayout = ConvertDataLayout(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; input.info()-&gt;set_data_layout(aclDataLayout);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; weights.info()-&gt;set_data_layout(aclDataLayout);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; output.info()-&gt;set_data_layout(aclDataLayout);</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160;</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keyword">const</span> arm_compute::ActivationLayerInfo activationInfo = <a class="code" href="namespacearmnn.xhtml#abfb0841058a8190d30851f07eca3991f">ConvertAdditionalInfoToAclActivationLayerInfo</a>(descriptor);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; m_pDepthwiseConvolutionLayer = std::make_unique&lt;arm_compute::NEDepthwiseConvolutionLayer&gt;();</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <span class="keyword">static_cast&lt;</span>arm_compute::NEDepthwiseConvolutionLayer*<span class="keyword">&gt;</span>(</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; m_pDepthwiseConvolutionLayer.get())-&gt;configure(&amp;input,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; &amp;weights,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; biasesPtr,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; &amp;output,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; padStrideInfo,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; depthMultiplier,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; activationInfo,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; aclDilationInfo);</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="comment">// Add details for profiling output</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> detailsInfo;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; detailsInfo.<a class="code" href="structarmnn_1_1_workload_info.xhtml#ac97905bfa0daab357b91df1347600309">m_InputTensorInfos</a> = info.<a class="code" href="structarmnn_1_1_workload_info.xhtml#ac97905bfa0daab357b91df1347600309">m_InputTensorInfos</a>;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; detailsInfo.<a class="code" href="structarmnn_1_1_workload_info.xhtml#a67b178f8a836bc1e52b8de109760adfd">m_OutputTensorInfos</a> = info.<a class="code" href="structarmnn_1_1_workload_info.xhtml#a67b178f8a836bc1e52b8de109760adfd">m_OutputTensorInfos</a>;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; detailsInfo.<a class="code" href="structarmnn_1_1_workload_info.xhtml#afd0d41a1e6de4c1565b7f4bfd04b4abc">m_WeightsTensorInfo</a> = <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt;armnn::TensorInfo&gt;</a>(info.<a class="code" href="structarmnn_1_1_workload_info.xhtml#ac97905bfa0daab357b91df1347600309">m_InputTensorInfos</a>[1]);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; {</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; detailsInfo.<a class="code" href="structarmnn_1_1_workload_info.xhtml#a00c11ec4cda30e66fb6b6c25b3e4541b">m_BiasTensorInfo</a> = <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt;armnn::TensorInfo&gt;</a>(info.<a class="code" href="structarmnn_1_1_workload_info.xhtml#ac97905bfa0daab357b91df1347600309">m_InputTensorInfos</a>[2]);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; }</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="comment">// Report Profiling Details</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <a class="code" href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>(<span class="stringliteral">&quot;NeonDepthwiseConvolution2dWorkload_Construct&quot;</span>,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; detailsInfo,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">GetGuid</a>());</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160;</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(m_pDepthwiseConvolutionLayer);</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; m_pDepthwiseConvolutionLayer-&gt;prepare();</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;</div><div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#ae071e8822437c78baea75c3aef3a263a"> 161</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">NeonDepthwiseConvolutionWorkload::Execute</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; <a class="code" href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>(<span class="stringliteral">&quot;NeonDepthwiseConvolutionWorkload_Execute&quot;</span>, <a class="code" href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">GetGuid</a>());</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(m_pDepthwiseConvolutionLayer);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; m_pDepthwiseConvolutionLayer-&gt;run();</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;} <span class="comment">//namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a945263e85c27f3216a8323cfc16d8919"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">armnn::TensorInfo::IsConstant</a></div><div class="ttdeci">bool IsConstant() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00509">Tensor.cpp:509</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_depthwise_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00676">Descriptors.hpp:676</a></div></div>
-<div class="ttc" id="_neon_layer_support_8hpp_xhtml"><div class="ttname"><a href="_neon_layer_support_8hpp.xhtml">NeonLayerSupport.hpp</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#l00062">Types.hpp:62</a></div></div>
-<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00270">Optional.hpp:270</a></div></div>
-<div class="ttc" id="_arm_compute_utils_8hpp_xhtml"><div class="ttname"><a href="_arm_compute_utils_8hpp.xhtml">ArmComputeUtils.hpp</a></div></div>
-<div class="ttc" id="_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_tensor_handle_8hpp.xhtml">TensorHandle.hpp</a></div></div>
-<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::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#l00678">Descriptors.hpp:678</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="namespacearmnn_xhtml_a63d684b26fb838b22123490d780bce08"><div class="ttname"><a href="namespacearmnn.xhtml#a63d684b26fb838b22123490d780bce08">armnn::NeonDepthwiseConvolutionWorkloadValidate</a></div><div class="ttdeci">arm_compute::Status NeonDepthwiseConvolutionWorkloadValidate(const TensorInfo &amp;input, const TensorInfo &amp;output, const DepthwiseConvolution2dDescriptor &amp;descriptor, const TensorInfo &amp;weights, const Optional&lt; TensorInfo &gt; &amp;biases, const ActivationDescriptor *activationDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_depthwise_convolution_workload_8cpp_source.xhtml#l00029">NeonDepthwiseConvolutionWorkload.cpp:29</a></div></div>
-<div class="ttc" id="namespacearmnn_xhtml_abfb0841058a8190d30851f07eca3991f"><div class="ttname"><a href="namespacearmnn.xhtml#abfb0841058a8190d30851f07eca3991f">armnn::ConvertAdditionalInfoToAclActivationLayerInfo</a></div><div class="ttdeci">arm_compute::ActivationLayerInfo ConvertAdditionalInfoToAclActivationLayerInfo(const QueueDescriptor &amp;queueDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.xhtml#l00103">ArmComputeUtils.hpp:103</a></div></div>
-<div class="ttc" id="classarmnn_1_1_base_workload_xhtml_aaff95a48875d8fb4a616352906660ca9"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">armnn::BaseWorkload&lt; DepthwiseConvolution2dQueueDescriptor &gt;::GetGuid</a></div><div class="ttdeci">arm::pipe::ProfilingGuid GetGuid() const final</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00061">Workload.hpp:61</a></div></div>
-<div class="ttc" id="_arm_compute_tensor_utils_8hpp_xhtml"><div class="ttname"><a href="_arm_compute_tensor_utils_8hpp.xhtml">ArmComputeTensorUtils.hpp</a></div></div>
-<div class="ttc" id="_neon_depthwise_convolution_workload_8hpp_xhtml"><div class="ttname"><a href="_neon_depthwise_convolution_workload_8hpp.xhtml">NeonDepthwiseConvolutionWorkload.hpp</a></div></div>
-<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a765d2cee4ccce5b9467e0c2b6d25b84a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">armnn::QueueDescriptor::ValidateInputsOutputs</a></div><div class="ttdeci">void ValidateInputsOutputs(const std::string &amp;descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8cpp_source.xhtml#l00475">WorkloadData.cpp:475</a></div></div>
-<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.dox:6</a></div></div>
-<div class="ttc" id="classarmnn_1_1_optional_reference_switch_xhtml_a77c7d528ac063d870b8c8426ec81c1c3"><div class="ttname"><a href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">armnn::OptionalReferenceSwitch&lt; std::is_reference&lt; T &gt;::value, T &gt;::value</a></div><div class="ttdeci">const T &amp; value() const</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00146">Optional.hpp:146</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#l00066">WorkloadData.hpp:66</a></div></div>
-<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::DepthwiseConvolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation factor value for height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00674">Descriptors.hpp:674</a></div></div>
-<div class="ttc" id="classarmnn_1_1_neon_base_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_base_workload.xhtml">armnn::NeonBaseWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_base_workload_8hpp_source.xhtml#l00013">NeonBaseWorkload.hpp:13</a></div></div>
-<div class="ttc" id="structarmnn_1_1_workload_info_xhtml_ac97905bfa0daab357b91df1347600309"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml#ac97905bfa0daab357b91df1347600309">armnn::WorkloadInfo::m_InputTensorInfos</a></div><div class="ttdeci">std::vector&lt; TensorInfo &gt; m_InputTensorInfos</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00018">WorkloadInfo.hpp:18</a></div></div>
-<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::DepthwiseConvolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation factor value for width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00672">Descriptors.hpp:672</a></div></div>
-<div class="ttc" id="classarmnn_1_1_base_workload_xhtml_afb8d2c8817c75de9d01a4c0e0d5c160b"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">armnn::BaseWorkload&lt; DepthwiseConvolution2dQueueDescriptor &gt;::m_Data</a></div><div class="ttdeci">DepthwiseConvolution2dQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00083">Workload.hpp:83</a></div></div>
-<div class="ttc" id="classarmnn_1_1_optional_base_xhtml_a86b749ce2c4bc627fa8a1fcfaf0e314f"><div class="ttname"><a href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">armnn::OptionalBase::has_value</a></div><div class="ttdeci">bool has_value() const noexcept</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00053">Optional.hpp:53</a></div></div>
-<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70b"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a></div><div class="ttdeci">Status</div><div class="ttdoc">enumeration </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00042">Types.hpp:42</a></div></div>
-<div class="ttc" id="_neon_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml">NeonWorkloadUtils.hpp</a></div></div>
-<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div>
-<div class="ttc" id="namespacearmnn_xhtml_ac4aa9e41515b354234645f115c49de32"><div class="ttname"><a href="namespacearmnn.xhtml#ac4aa9e41515b354234645f115c49de32">armnn::Convert1HWOTensorInfoToAcl</a></div><div class="ttdeci">std::tuple&lt; TensorInfo, unsigned int &gt; Convert1HWOTensorInfoToAcl(const TensorInfo &amp;weightInfo, const TensorInfo &amp;inputInfo, const DataLayout dataLayout)</div><div class="ttdoc">Weights for depthwise have a datalayout of [1,H,W,O] = [1,H,W,I*M] This function coverts a TensorInfo...</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00170">WorkloadUtils.cpp:170</a></div></div>
-<div class="ttc" id="structarmnn_1_1_workload_info_xhtml_a67b178f8a836bc1e52b8de109760adfd"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml#a67b178f8a836bc1e52b8de109760adfd">armnn::WorkloadInfo::m_OutputTensorInfos</a></div><div class="ttdeci">std::vector&lt; TensorInfo &gt; m_OutputTensorInfos</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00019">WorkloadInfo.hpp:19</a></div></div>
-<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00036">Descriptors.hpp:36</a></div></div>
-<div class="ttc" id="classarmnn_1_1_neon_depthwise_convolution_workload_xhtml_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">armnn::NeonDepthwiseConvolutionWorkload::Execute</a></div><div class="ttdeci">virtual void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_neon_depthwise_convolution_workload_8cpp_source.xhtml#l00161">NeonDepthwiseConvolutionWorkload.cpp:161</a></div></div>
-<div class="ttc" id="structarmnn_1_1_workload_info_xhtml_a00c11ec4cda30e66fb6b6c25b3e4541b"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml#a00c11ec4cda30e66fb6b6c25b3e4541b">armnn::WorkloadInfo::m_BiasTensorInfo</a></div><div class="ttdeci">Optional&lt; TensorInfo &gt; m_BiasTensorInfo</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00021">WorkloadInfo.hpp:21</a></div></div>
-<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00027">WorkloadData.hpp:27</a></div></div>
-<div class="ttc" id="_profiling_8hpp_xhtml_a786492a3881a4c760ab1eec2149f4aba"><div class="ttname"><a href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a></div><div class="ttdeci">#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00227">Profiling.hpp:227</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="_compatible_types_8hpp_source.xhtml#l00010">CompatibleTypes.hpp:10</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 TensorInfos of 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="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00026">WorkloadData.hpp:26</a></div></div>
-<div class="ttc" id="classarmnn_1_1_neon_depthwise_convolution_workload_xhtml_aa6173c66256d333ee73a068206c746d6"><div class="ttname"><a href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#aa6173c66256d333ee73a068206c746d6">armnn::NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload</a></div><div class="ttdeci">NeonDepthwiseConvolutionWorkload(const DepthwiseConvolution2dQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_depthwise_convolution_workload_8cpp_source.xhtml#l00089">NeonDepthwiseConvolutionWorkload.cpp:89</a></div></div>
-<div class="ttc" id="_neon_workload_utils_8hpp_xhtml_a9165e41bcaf1b90f9ff91ef681e88c4f"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00024">NeonWorkloadUtils.hpp:24</a></div></div>
-<div class="ttc" id="structarmnn_1_1_workload_info_xhtml_afd0d41a1e6de4c1565b7f4bfd04b4abc"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml#afd0d41a1e6de4c1565b7f4bfd04b4abc">armnn::WorkloadInfo::m_WeightsTensorInfo</a></div><div class="ttdeci">Optional&lt; TensorInfo &gt; m_WeightsTensorInfo</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00020">WorkloadInfo.hpp:20</a></div></div>
-<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00627">Descriptors.hpp:627</a></div></div>
-<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">armnn::DepthwiseConvolution2dQueueDescriptor</a></div><div class="ttdoc">Depthwise Convolution 2D layer workload data. </div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00229">WorkloadData.hpp:229</a></div></div>
-<div class="ttc" id="_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_utils_8hpp.xhtml">WorkloadUtils.hpp</a></div></div>
-<div class="ttc" id="namespacearmnn_xhtml_ad701d0d29baa4266ab4d33b090aa661c"><div class="ttname"><a href="namespacearmnn.xhtml#ad701d0d29baa4266ab4d33b090aa661c">armnn::ConvertActivationDescriptorToAclActivationLayerInfo</a></div><div class="ttdeci">arm_compute::ActivationLayerInfo ConvertActivationDescriptorToAclActivationLayerInfo(const ActivationDescriptor &amp;actDesc)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.xhtml#l00085">ArmComputeUtils.hpp:85</a></div></div>
+<a href="_neon_depthwise_convolution_workload_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 © 2017,2022 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="_neon_depthwise_convolution_workload_8hpp.xhtml">NeonDepthwiseConvolutionWorkload.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 &quot;<a class="code" href="_neon_workload_utils_8hpp.xhtml">NeonWorkloadUtils.hpp</a>&quot;</span></div>
+<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160; </div>
+<div class="line"><a name="l00010"></a><span class="lineno"> 10</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="l00011"></a><span class="lineno"> 11</span>&#160; </div>
+<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_arm_compute_tensor_utils_8hpp.xhtml">aclCommon/ArmComputeTensorUtils.hpp</a>&gt;</span></div>
+<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_arm_compute_utils_8hpp.xhtml">aclCommon/ArmComputeUtils.hpp</a>&gt;</span></div>
+<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160; </div>
+<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_neon_layer_support_8hpp.xhtml">neon/NeonLayerSupport.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="_tensor_handle_8hpp.xhtml">armnn/backends/TensorHandle.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="_workload_utils_8hpp.xhtml">backendsCommon/WorkloadUtils.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;arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h&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="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.xhtml">armnnUtils</a>;</div>
+<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; </div>
+<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div>
+<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;{</div>
+<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; </div>
+<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="keyword">using namespace </span>armcomputetensorutils;</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"><a class="line" href="namespacearmnn.xhtml#a63d684b26fb838b22123490d780bce08"> 29</a></span>&#160;<a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.xhtml#a63d684b26fb838b22123490d780bce08">NeonDepthwiseConvolutionWorkloadValidate</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; input,</div>
+<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; output,</div>
+<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a>&amp; descriptor,</div>
+<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; weights,</div>
+<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional&lt;TensorInfo&gt;</a>&amp; biases,</div>
+<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">ActivationDescriptor</a>* activationDescriptor)</div>
+<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;{</div>
+<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
+<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
+<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; </div>
+<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="comment">// ArmNN format for weights for depthwise is [1, H, W, C] independently of the input/output layout</span></div>
+<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="comment">//</span></div>
+<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="comment">// ACL format for weights for depthwise is:</span></div>
+<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="comment">// - [1, H, W, C] for [N, H, W, C] input/output layout (matches with ArmNN)</span></div>
+<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="comment">// - [1, C, H, W] for [N, C, H, W] input/output layout</span></div>
+<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="comment">//</span></div>
+<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="comment">// Therefore ArmNN weights have to be permuted when input/output layout is [N, C, H, W] to pass them to ACL.</span></div>
+<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="comment">// The PermuteDepthwiseConv2dWeights backend optimization takes care of this, but it has not been performed yet,</span></div>
+<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="comment">// so we do the permute here for the TensorInfo weights.</span></div>
+<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> aclDepthMultiplier;</div>
+<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> weightsPermuted;</div>
+<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; std::tie(weightsPermuted, aclDepthMultiplier) = <a class="code" href="namespacearmnn.xhtml#ac4aa9e41515b354234645f115c49de32">Convert1HWOTensorInfoToAcl</a>(weights, input, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
+<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; </div>
+<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="comment">// Convert the weights into the compute library format</span></div>
+<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weightsPermuted, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
+<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; aclWeightsInfo.set_are_values_constant(weights.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</div>
+<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; </div>
+<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; arm_compute::TensorInfo aclBiasesInfo;</div>
+<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; arm_compute::TensorInfo* optionalAclBiasesInfo = <span class="keyword">nullptr</span>;</div>
+<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</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="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(biases.<a class="code" href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</a>());</div>
+<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <span class="comment">// Same for bias as weights. We don&#39;t currently support non const.</span></div>
+<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="keywordflow">if</span> (!biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>())</div>
+<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; {</div>
+<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>{arm_compute::ErrorCode::RUNTIME_ERROR,</div>
+<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="stringliteral">&quot;ArmNN NeonDepthwiseConv2dWorkload does not support non constant bias.&quot;</span>};</div>
+<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; }</div>
+<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; aclBiasesInfo = BuildArmComputeTensorInfo(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>(), descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
+<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; aclBiasesInfo.set_are_values_constant(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</div>
+<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; optionalAclBiasesInfo = &amp;aclBiasesInfo;</div>
+<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; }</div>
+<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; </div>
+<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; arm_compute::PadStrideInfo aclPadStrideInfo = BuildArmComputePadStrideInfo(descriptor);</div>
+<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <span class="keyword">const</span> arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(</div>
+<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a>, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a>);</div>
+<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; </div>
+<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keyword">const</span> arm_compute::ActivationLayerInfo activationInfo = <a class="code" href="namespacearmnn.xhtml#ad701d0d29baa4266ab4d33b090aa661c">ConvertActivationDescriptorToAclActivationLayerInfo</a>(</div>
+<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; activationDescriptor);</div>
+<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; </div>
+<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="keywordflow">return</span> arm_compute::NEDepthwiseConvolutionLayer::validate(&amp;aclInputInfo,</div>
+<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; &amp;aclWeightsInfo,</div>
+<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; optionalAclBiasesInfo,</div>
+<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; &amp;aclOutputInfo,</div>
+<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; aclPadStrideInfo,</div>
+<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; aclDepthMultiplier,</div>
+<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; activationInfo,</div>
+<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; aclDilationInfo);</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; </div>
+<div class="line"><a name="l00089"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#aa6173c66256d333ee73a068206c746d6"> 89</a></span>&#160;<a class="code" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#aa6173c66256d333ee73a068206c746d6">NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload</a>(</div>
+<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">DepthwiseConvolution2dQueueDescriptor</a>&amp; descriptor,</div>
+<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>&amp; info)</div>
+<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; : <a class="code" href="classarmnn_1_1_neon_base_workload.xhtml">NeonBaseWorkload</a>&lt;<a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">DepthwiseConvolution2dQueueDescriptor</a>&gt;(descriptor, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div>
+<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160;{</div>
+<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; arm_compute::ITensor&amp; input = PolymorphicDowncast&lt;IAclTensorHandle*&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0])-&gt;GetTensor();</div>
+<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; arm_compute::ITensor&amp; output = PolymorphicDowncast&lt;IAclTensorHandle*&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0])-&gt;GetTensor();</div>
+<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; arm_compute::ITensor&amp; weights = PolymorphicDowncast&lt;IAclTensorHandle*&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[1])-&gt;GetTensor();</div>
+<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; arm_compute::ITensor* biasesPtr = <span class="keyword">nullptr</span>;</div>
+<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</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; biasesPtr = &amp;PolymorphicDowncast&lt;IAclTensorHandle *&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[2])-&gt;GetTensor();</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; </div>
+<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; arm_compute::ITensorInfo* weightsInfo = weights.info();</div>
+<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; arm_compute::ITensorInfo* inputInfo = input.info();</div>
+<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <span class="keyword">auto</span> weightsShape = weightsInfo-&gt;tensor_shape();</div>
+<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="keyword">auto</span> inputShape = inputInfo-&gt;tensor_shape();</div>
+<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; </div>
+<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <span class="comment">// The PermuteDepthwiseConv2dWeights backend optimization has been performed,</span></div>
+<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="comment">// converting weights to have the same data layout as input.</span></div>
+<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthMultiplier =</div>
+<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; ComputeDepthwiseConv2dDepthMultiplier(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>, weightsShape, inputShape);</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="keyword">const</span> arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(</div>
+<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a>, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a>);</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; uint32_t numInputs = <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> ? 3: 2;</div>
+<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">&quot;NeonDepthwiseConvolutionWorkload&quot;</span>, numInputs, 1);</div>
+<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; </div>
+<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a> aclDataLayout = ConvertDataLayout(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
+<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; input.info()-&gt;set_data_layout(aclDataLayout);</div>
+<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; weights.info()-&gt;set_data_layout(aclDataLayout);</div>
+<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; output.info()-&gt;set_data_layout(aclDataLayout);</div>
+<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; </div>
+<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>);</div>
+<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; </div>
+<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keyword">const</span> arm_compute::ActivationLayerInfo activationInfo = <a class="code" href="namespacearmnn.xhtml#abfb0841058a8190d30851f07eca3991f">ConvertAdditionalInfoToAclActivationLayerInfo</a>(descriptor);</div>
+<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; </div>
+<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; m_pDepthwiseConvolutionLayer = std::make_unique&lt;arm_compute::NEDepthwiseConvolutionLayer&gt;();</div>
+<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <span class="keyword">static_cast&lt;</span>arm_compute::NEDepthwiseConvolutionLayer*<span class="keyword">&gt;</span>(</div>
+<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; m_pDepthwiseConvolutionLayer.get())-&gt;configure(&amp;input,</div>
+<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; &amp;weights,</div>
+<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; biasesPtr,</div>
+<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; &amp;output,</div>
+<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; padStrideInfo,</div>
+<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; depthMultiplier,</div>
+<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; activationInfo,</div>
+<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; aclDilationInfo);</div>
+<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; </div>
+<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="comment">// Add details for profiling output</span></div>
+<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> detailsInfo;</div>
+<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; </div>
+<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; detailsInfo.<a class="code" href="structarmnn_1_1_workload_info.xhtml#ac97905bfa0daab357b91df1347600309">m_InputTensorInfos</a> = <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos;</div>
+<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; detailsInfo.<a class="code" href="structarmnn_1_1_workload_info.xhtml#a67b178f8a836bc1e52b8de109760adfd">m_OutputTensorInfos</a> = <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_OutputTensorInfos;</div>
+<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; detailsInfo.<a class="code" href="structarmnn_1_1_workload_info.xhtml#afd0d41a1e6de4c1565b7f4bfd04b4abc">m_WeightsTensorInfo</a> = <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt;armnn::TensorInfo&gt;</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[1]);</div>
+<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div>
+<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; {</div>
+<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; detailsInfo.<a class="code" href="structarmnn_1_1_workload_info.xhtml#a00c11ec4cda30e66fb6b6c25b3e4541b">m_BiasTensorInfo</a> = <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt;armnn::TensorInfo&gt;</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[2]);</div>
+<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; }</div>
+<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; </div>
+<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="comment">// Report Profiling Details</span></div>
+<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <a class="code" href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>(<span class="stringliteral">&quot;NeonDepthwiseConvolution2dWorkload_Construct&quot;</span>,</div>
+<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>,</div>
+<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; detailsInfo,</div>
+<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">GetGuid</a>());</div>
+<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; </div>
+<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(m_pDepthwiseConvolutionLayer);</div>
+<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; </div>
+<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; m_pDepthwiseConvolutionLayer-&gt;prepare();</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; </div>
+<div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#ae071e8822437c78baea75c3aef3a263a"> 161</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">NeonDepthwiseConvolutionWorkload::Execute</a>()<span class="keyword"> const</span></div>
+<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160;<span class="keyword"></span>{</div>
+<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; <a class="code" href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>(<span class="stringliteral">&quot;NeonDepthwiseConvolutionWorkload_Execute&quot;</span>, <a class="code" href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">GetGuid</a>());</div>
+<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(m_pDepthwiseConvolutionLayer);</div>
+<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; </div>
+<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; m_pDepthwiseConvolutionLayer-&gt;run();</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;} <span class="comment">//namespace armnn</span></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
+<div class="ttc" id="astructarmnn_1_1_workload_info_xhtml_a00c11ec4cda30e66fb6b6c25b3e4541b"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml#a00c11ec4cda30e66fb6b6c25b3e4541b">armnn::WorkloadInfo::m_BiasTensorInfo</a></div><div class="ttdeci">Optional&lt; TensorInfo &gt; m_BiasTensorInfo</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00021">WorkloadInfo.hpp:21</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_base_workload_xhtml_aaff95a48875d8fb4a616352906660ca9"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">armnn::BaseWorkload&lt; DepthwiseConvolution2dQueueDescriptor &gt;::GetGuid</a></div><div class="ttdeci">arm::pipe::ProfilingGuid GetGuid() const final</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00061">Workload.hpp:61</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a765d2cee4ccce5b9467e0c2b6d25b84a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">armnn::QueueDescriptor::ValidateInputsOutputs</a></div><div class="ttdeci">void ValidateInputsOutputs(const std::string &amp;descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8cpp_source.xhtml#l00475">WorkloadData.cpp:475</a></div></div>
+<div class="ttc" id="anamespacearmnn_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#l00062">Types.hpp:62</a></div></div>
+<div class="ttc" id="a_data_layout_indexed_8hpp_xhtml"><div class="ttname"><a href="_data_layout_indexed_8hpp.xhtml">DataLayoutIndexed.hpp</a></div></div>
+<div class="ttc" id="anamespacearmnn_xhtml_ad701d0d29baa4266ab4d33b090aa661c"><div class="ttname"><a href="namespacearmnn.xhtml#ad701d0d29baa4266ab4d33b090aa661c">armnn::ConvertActivationDescriptorToAclActivationLayerInfo</a></div><div class="ttdeci">arm_compute::ActivationLayerInfo ConvertActivationDescriptorToAclActivationLayerInfo(const ActivationDescriptor &amp;actDesc)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.xhtml#l00085">ArmComputeUtils.hpp:85</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_activation_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00036">Descriptors.hpp:36</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">armnn::DepthwiseConvolution2dQueueDescriptor</a></div><div class="ttdoc">Depthwise Convolution 2D layer workload data.</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00229">WorkloadData.hpp:229</a></div></div>
+<div class="ttc" id="a_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_tensor_handle_8hpp.xhtml">TensorHandle.hpp</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00676">Descriptors.hpp:676</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_base_workload_xhtml_afb8d2c8817c75de9d01a4c0e0d5c160b"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">armnn::BaseWorkload&lt; DepthwiseConvolution2dQueueDescriptor &gt;::m_Data</a></div><div class="ttdeci">DepthwiseConvolution2dQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00083">Workload.hpp:83</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_neon_depthwise_convolution_workload_xhtml_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">armnn::NeonDepthwiseConvolutionWorkload::Execute</a></div><div class="ttdeci">virtual void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_neon_depthwise_convolution_workload_8cpp_source.xhtml#l00161">NeonDepthwiseConvolutionWorkload.cpp:161</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_workload_info_xhtml_afd0d41a1e6de4c1565b7f4bfd04b4abc"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml#afd0d41a1e6de4c1565b7f4bfd04b4abc">armnn::WorkloadInfo::m_WeightsTensorInfo</a></div><div class="ttdeci">Optional&lt; TensorInfo &gt; m_WeightsTensorInfo</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00020">WorkloadInfo.hpp:20</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::DepthwiseConvolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation factor value for width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00672">Descriptors.hpp:672</a></div></div>
+<div class="ttc" id="a_neon_layer_support_8hpp_xhtml"><div class="ttname"><a href="_neon_layer_support_8hpp.xhtml">NeonLayerSupport.hpp</a></div></div>
+<div class="ttc" id="anamespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors.</div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.dox:6</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_optional_reference_switch_xhtml_a77c7d528ac063d870b8c8426ec81c1c3"><div class="ttname"><a href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">armnn::OptionalReferenceSwitch&lt; std::is_reference&lt; T &gt;::value, T &gt;::value</a></div><div class="ttdeci">const T &amp; value() const</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00146">Optional.hpp:146</a></div></div>
+<div class="ttc" id="anamespacearmnn_utils_xhtml"><div class="ttname"><a href="namespacearmnn_utils.xhtml">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_compatible_types_8hpp_source.xhtml#l00010">CompatibleTypes.hpp:10</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_neon_depthwise_convolution_workload_xhtml_aa6173c66256d333ee73a068206c746d6"><div class="ttname"><a href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#aa6173c66256d333ee73a068206c746d6">armnn::NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload</a></div><div class="ttdeci">NeonDepthwiseConvolutionWorkload(const DepthwiseConvolution2dQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_depthwise_convolution_workload_8cpp_source.xhtml#l00089">NeonDepthwiseConvolutionWorkload.cpp:89</a></div></div>
+<div class="ttc" id="a_neon_workload_utils_8hpp_xhtml_a9165e41bcaf1b90f9ff91ef681e88c4f"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00024">NeonWorkloadUtils.hpp:24</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::DepthwiseConvolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation factor value for height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00674">Descriptors.hpp:674</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_workload_info_xhtml_a67b178f8a836bc1e52b8de109760adfd"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml#a67b178f8a836bc1e52b8de109760adfd">armnn::WorkloadInfo::m_OutputTensorInfos</a></div><div class="ttdeci">std::vector&lt; TensorInfo &gt; m_OutputTensorInfos</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00019">WorkloadInfo.hpp:19</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::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#l00678">Descriptors.hpp:678</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a945263e85c27f3216a8323cfc16d8919"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">armnn::TensorInfo::IsConstant</a></div><div class="ttdeci">bool IsConstant() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00509">Tensor.cpp:509</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00627">Descriptors.hpp:627</a></div></div>
+<div class="ttc" id="a_arm_compute_tensor_utils_8hpp_xhtml"><div class="ttname"><a href="_arm_compute_tensor_utils_8hpp.xhtml">ArmComputeTensorUtils.hpp</a></div></div>
+<div class="ttc" id="anamespacearmnn_xhtml_ac4aa9e41515b354234645f115c49de32"><div class="ttname"><a href="namespacearmnn.xhtml#ac4aa9e41515b354234645f115c49de32">armnn::Convert1HWOTensorInfoToAcl</a></div><div class="ttdeci">std::tuple&lt; TensorInfo, unsigned int &gt; Convert1HWOTensorInfoToAcl(const TensorInfo &amp;weightInfo, const TensorInfo &amp;inputInfo, const DataLayout dataLayout)</div><div class="ttdoc">Weights for depthwise have a datalayout of [1,H,W,O] = [1,H,W,I*M] This function coverts a TensorInfo...</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00170">WorkloadUtils.cpp:170</a></div></div>
+<div class="ttc" id="a_arm_compute_utils_8hpp_xhtml"><div class="ttname"><a href="_arm_compute_utils_8hpp.xhtml">ArmComputeUtils.hpp</a></div></div>
+<div class="ttc" id="aclassarmnn_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="a_neon_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml">NeonWorkloadUtils.hpp</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_optional_base_xhtml_a86b749ce2c4bc627fa8a1fcfaf0e314f"><div class="ttname"><a href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">armnn::OptionalBase::has_value</a></div><div class="ttdeci">bool has_value() const noexcept</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00053">Optional.hpp:53</a></div></div>
+<div class="ttc" id="anamespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70b"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a></div><div class="ttdeci">Status</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00042">Types.hpp:42</a></div></div>
+<div class="ttc" id="anamespacearmnn_xhtml_abfb0841058a8190d30851f07eca3991f"><div class="ttname"><a href="namespacearmnn.xhtml#abfb0841058a8190d30851f07eca3991f">armnn::ConvertAdditionalInfoToAclActivationLayerInfo</a></div><div class="ttdeci">arm_compute::ActivationLayerInfo ConvertAdditionalInfoToAclActivationLayerInfo(const QueueDescriptor &amp;queueDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.xhtml#l00103">ArmComputeUtils.hpp:103</a></div></div>
+<div class="ttc" id="astructarmnn_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 TensorInfos of 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="a_neon_depthwise_convolution_workload_8hpp_xhtml"><div class="ttname"><a href="_neon_depthwise_convolution_workload_8hpp.xhtml">NeonDepthwiseConvolutionWorkload.hpp</a></div></div>
+<div class="ttc" id="astructarmnn_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#l00066">WorkloadData.hpp:66</a></div></div>
+<div class="ttc" id="a_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div>
+<div class="ttc" id="a_profiling_8hpp_xhtml_a786492a3881a4c760ab1eec2149f4aba"><div class="ttname"><a href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a></div><div class="ttdeci">#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00227">Profiling.hpp:227</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00270">Optional.hpp:270</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00027">WorkloadData.hpp:27</a></div></div>
+<div class="ttc" id="a_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_utils_8hpp.xhtml">WorkloadUtils.hpp</a></div></div>
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+<div class="ttc" id="anamespacearmnn_xhtml_a63d684b26fb838b22123490d780bce08"><div class="ttname"><a href="namespacearmnn.xhtml#a63d684b26fb838b22123490d780bce08">armnn::NeonDepthwiseConvolutionWorkloadValidate</a></div><div class="ttdeci">arm_compute::Status NeonDepthwiseConvolutionWorkloadValidate(const TensorInfo &amp;input, const TensorInfo &amp;output, const DepthwiseConvolution2dDescriptor &amp;descriptor, const TensorInfo &amp;weights, const Optional&lt; TensorInfo &gt; &amp;biases, const ActivationDescriptor *activationDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_depthwise_convolution_workload_8cpp_source.xhtml#l00029">NeonDepthwiseConvolutionWorkload.cpp:29</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_workload_info_xhtml_ac97905bfa0daab357b91df1347600309"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml#ac97905bfa0daab357b91df1347600309">armnn::WorkloadInfo::m_InputTensorInfos</a></div><div class="ttdeci">std::vector&lt; TensorInfo &gt; m_InputTensorInfos</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00018">WorkloadInfo.hpp:18</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00026">WorkloadData.hpp:26</a></div></div>
+<div class="ttc" id="anamespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div><div class="ttdeci">@ info</div></div>
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