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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 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_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;</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</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="l00015"></a><span class="lineno"> 15</span>&#160;</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_cpu_tensor_handle_8hpp.xhtml">backendsCommon/CpuTensorHandle.hpp</a>&gt;</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</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="l00018"></a><span class="lineno"> 18</span>&#160;</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="preprocessor">#include &lt;arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h&gt;</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.xhtml">armnnUtils</a>;</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;{</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="keyword">using namespace </span>armcomputetensorutils;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;</div><div class="line"><a name="l00028"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a168ebb908e1ee4bac24cb7992510de73"> 28</a></span>&#160;<a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.xhtml#a168ebb908e1ee4bac24cb7992510de73">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="l00029"></a><span class="lineno"> 29</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="l00030"></a><span class="lineno"> 30</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="l00031"></a><span class="lineno"> 31</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="l00032"></a><span class="lineno"> 32</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="l00033"></a><span class="lineno"> 33</span>&#160;{</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</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="l00035"></a><span class="lineno"> 35</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="l00036"></a><span class="lineno"> 36</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="comment">// ArmNN&#39;s weight format is [ M, I, H, W ]</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> aclDepthMultiplier = weights.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[0];</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="comment">// Convert the weight format from ArmNN&#39;s [ M, I, H, W ] (does NOT depend on the data layout) to either</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="comment">// [ 1, H, W, I * M ] (if NHWC) or [ 1, I * M, H, W ] (if NCHW), as required by the compute library</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> weightsPermuted = <a class="code" href="namespacearmnn.xhtml#a1e8288eac7e909fdb58b6113d816763a">ConvertWeightTensorInfoFromArmnnToAcl</a>(weights, descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="comment">// Convert the weights into the compute library format</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="keyword">const</span> 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="l00046"></a><span class="lineno"> 46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; arm_compute::TensorInfo aclBiasesInfo;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; arm_compute::TensorInfo *optionalAclBiasesInfo = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="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="l00051"></a><span class="lineno"> 51</span>&#160; {</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; BOOST_ASSERT(biases.<a class="code" href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</a>());</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</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="l00055"></a><span class="lineno"> 55</span>&#160; optionalAclBiasesInfo = &amp;aclBiasesInfo;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; }</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; arm_compute::PadStrideInfo aclPadStrideInfo = BuildArmComputePadStrideInfo(descriptor);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="keyword">const</span> arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</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="l00061"></a><span class="lineno"> 61</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="keywordflow">return</span> arm_compute::NEDepthwiseConvolutionLayer::validate(&amp;aclInputInfo,</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; &amp;aclWeightsInfo,</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; optionalAclBiasesInfo,</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; &amp;aclOutputInfo,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; aclPadStrideInfo,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; aclDepthMultiplier,</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; arm_compute::ActivationLayerInfo(),</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; aclDilationInfo);</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"><a class="line" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#aa6173c66256d333ee73a068206c746d6"> 72</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="l00073"></a><span class="lineno"> 73</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="l00074"></a><span class="lineno"> 74</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="l00075"></a><span class="lineno"> 75</span>&#160; : <a class="code" href="classarmnn_1_1_base_workload.xhtml">BaseWorkload</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="l00076"></a><span class="lineno"> 76</span>&#160;{</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="comment">// ArmNN&#39;s weight format is [ M, I, H, W ]</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keyword">auto</span>&amp; weightInfo = <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">m_Weight</a>-&gt;<a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>();</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="comment">// Allocate a buffer for the swizzling of the weight tensor</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; std::unique_ptr&lt;unsigned char[]&gt; permuteBuffer(<span class="keyword">new</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>[<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">m_Weight</a>-&gt;<a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>()]);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="comment">// Convert the weight format from ArmNN&#39;s [ M, I, H, W ] (does NOT depend on the data layout) to either</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="comment">// [ 1, H, W, I * M ] (if NHWC) or [ 1, I * M, H, W ] (if NCHW), as required by the compute library</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> weightPermuted = <a class="code" href="namespacearmnn.xhtml#a51e8b95a429e11678ffa8b9fdc88351b">ConvertWeightTensorFromArmnnToAcl</a>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">m_Weight</a>,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">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="l00087"></a><span class="lineno"> 87</span>&#160; permuteBuffer.get());</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"> 89</span>&#160; <span class="comment">// Convert the weights into the compute library format</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; m_KernelTensor = std::make_unique&lt;arm_compute::Tensor&gt;();</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; BuildArmComputeTensor(*m_KernelTensor, weightPermuted.GetInfo(), <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">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="l00092"></a><span class="lineno"> 92</span>&#160;</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">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="l00094"></a><span class="lineno"> 94</span>&#160; {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; m_BiasTensor = std::make_unique&lt;arm_compute::Tensor&gt;();</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; BuildArmComputeTensor(*m_BiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">m_Bias</a>-&gt;<a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>(), <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">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="l00097"></a><span class="lineno"> 97</span>&#160; }</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keyword">const</span> arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">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#a0a487c549c63319505095b855ea3c195">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="l00101"></a><span class="lineno"> 101</span>&#160;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">&quot;NeonDepthwiseConvolutionWorkload&quot;</span>, 1, 1);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* inputTensorHandle = <span class="keyword">static_cast&lt;</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>*<span class="keyword">&gt;</span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0]);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* outputTensorHandle = <span class="keyword">static_cast&lt;</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>*<span class="keyword">&gt;</span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; arm_compute::ITensor&amp; input = inputTensorHandle-&gt;<a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a326e78519af5570a5921c6aa39968a20">GetTensor</a>();</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; arm_compute::ITensor&amp; output = outputTensorHandle-&gt;<a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a326e78519af5570a5921c6aa39968a20">GetTensor</a>();</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</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#a0a487c549c63319505095b855ea3c195">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="l00111"></a><span class="lineno"> 111</span>&#160; input.info()-&gt;set_data_layout(aclDataLayout);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; output.info()-&gt;set_data_layout(aclDataLayout);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <span class="comment">// Get the depth multiplier</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthMultiplier = weightInfo.GetShape()[0];</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">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="l00118"></a><span class="lineno"> 118</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; m_pDepthwiseConvolutionLayer = std::make_unique&lt;arm_compute::NEDepthwiseConvolutionLayer&gt;();</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keyword">static_cast&lt;</span>arm_compute::NEDepthwiseConvolutionLayer*<span class="keyword">&gt;</span>(</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; m_pDepthwiseConvolutionLayer.get())-&gt;configure(&amp;input,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; m_KernelTensor.get(),</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; m_BiasTensor.get(),</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; &amp;output,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; padStrideInfo,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; depthMultiplier,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; arm_compute::ActivationLayerInfo(),</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; aclDilationInfo);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; BOOST_ASSERT(m_pDepthwiseConvolutionLayer);</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">ScopedCpuTensorHandle</a> weightsPermutedHandle(weightPermuted);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad9aa8d49d42ada3f757290033af39857">InitializeArmComputeTensorData</a>(*m_KernelTensor, &amp;weightsPermutedHandle);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160;</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">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="l00136"></a><span class="lineno"> 136</span>&#160; {</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad9aa8d49d42ada3f757290033af39857">InitializeArmComputeTensorData</a>(*m_BiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">m_Bias</a>);</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;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; m_pDepthwiseConvolutionLayer-&gt;prepare();</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; FreeUnusedTensors();</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160;}</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml#ae071e8822437c78baea75c3aef3a263a"> 144</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="l00145"></a><span class="lineno"> 145</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <a class="code" href="_neon_workload_utils_8hpp.xhtml#a8bf91fd5e5875631bcf6abbcd97fe2f4">ARMNN_SCOPED_PROFILING_EVENT_NEON</a>(<span class="stringliteral">&quot;NeonDepthwiseConvolutionWorkload_Execute&quot;</span>);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; BOOST_ASSERT(m_pDepthwiseConvolutionLayer);</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; m_pDepthwiseConvolutionLayer-&gt;run();</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160;}</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160;</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160;<span class="keywordtype">void</span> NeonDepthwiseConvolutionWorkload::FreeUnusedTensors()</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160;{</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; FreeTensorIfUnused(m_KernelTensor);</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; FreeTensorIfUnused(m_BiasTensor);</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160;}</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160;} <span class="comment">//namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_i_acl_tensor_handle_xhtml_a326e78519af5570a5921c6aa39968a20"><div class="ttname"><a href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a326e78519af5570a5921c6aa39968a20">armnn::IAclTensorHandle::GetTensor</a></div><div class="ttdeci">virtual arm_compute::ITensor &amp; GetTensor()=0</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#l00490">Descriptors.hpp:490</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#l00049">Types.hpp:49</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape &amp; GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00088">Tensor.hpp:88</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a51e8b95a429e11678ffa8b9fdc88351b"><div class="ttname"><a href="namespacearmnn.xhtml#a51e8b95a429e11678ffa8b9fdc88351b">armnn::ConvertWeightTensorFromArmnnToAcl</a></div><div class="ttdeci">armnn::ConstTensor ConvertWeightTensorFromArmnnToAcl(const ConstCpuTensorHandle *weightTensor, DataLayout dataLayout, void *permuteBuffer)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00132">WorkloadUtils.cpp:132</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="namespacearmnn_xhtml_a1e8288eac7e909fdb58b6113d816763a"><div class="ttname"><a href="namespacearmnn.xhtml#a1e8288eac7e909fdb58b6113d816763a">armnn::ConvertWeightTensorInfoFromArmnnToAcl</a></div><div class="ttdeci">TensorInfo ConvertWeightTensorInfoFromArmnnToAcl(const TensorInfo &amp;weightInfo, DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00109">WorkloadUtils.cpp:109</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#l00492">Descriptors.hpp:492</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml_ab3437cee6b0687812104fc1b37cbe8b3"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">armnn::DepthwiseConvolution2dQueueDescriptor::m_Bias</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Bias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00192">WorkloadData.hpp:192</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_workload_xhtml_a0a487c549c63319505095b855ea3c195"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">armnn::BaseWorkload&lt; DepthwiseConvolution2dQueueDescriptor &gt;::m_Data</a></div><div class="ttdeci">const DepthwiseConvolution2dQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00046">Workload.hpp:46</a></div></div>
<div class="ttc" id="_neon_workload_utils_8hpp_xhtml_a8bf91fd5e5875631bcf6abbcd97fe2f4"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml#a8bf91fd5e5875631bcf6abbcd97fe2f4">ARMNN_SCOPED_PROFILING_EVENT_NEON</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON(name)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00017">NeonWorkloadUtils.hpp:17</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_abcbdfb544ece4c31d0b37715ad0f3be0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">armnn::TensorInfo::GetNumBytes</a></div><div class="ttdeci">unsigned int GetNumBytes() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00213">Tensor.cpp:213</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#l00461">WorkloadData.cpp:461</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_acl_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_tensor_handle_8hpp_source.xhtml#l00016">ArmComputeTensorHandle.hpp:16</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#l00049">WorkloadData.hpp:49</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#l00488">Descriptors.hpp:488</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml_a3369b66d9316a773a41711e3f590c041"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">armnn::DepthwiseConvolution2dQueueDescriptor::m_Weight</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Weight</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00191">WorkloadData.hpp:191</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml">armnn::BaseWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00028">Workload.hpp:28</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#l00486">Descriptors.hpp:486</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="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00199">Tensor.hpp:199</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#l00026">Types.hpp:26</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="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#l00144">NeonDepthwiseConvolutionWorkload.cpp:144</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad9aa8d49d42ada3f757290033af39857"><div class="ttname"><a href="namespacearmnn.xhtml#ad9aa8d49d42ada3f757290033af39857">armnn::InitializeArmComputeTensorData</a></div><div class="ttdeci">void InitializeArmComputeTensorData(arm_compute::Tensor &amp;tensor, const ConstCpuTensorHandle *handle)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00035">NeonWorkloadUtils.hpp:35</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a168ebb908e1ee4bac24cb7992510de73"><div class="ttname"><a href="namespacearmnn.xhtml#a168ebb908e1ee4bac24cb7992510de73">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)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_depthwise_convolution_workload_8cpp_source.xhtml#l00028">NeonDepthwiseConvolutionWorkload.cpp:28</a></div></div>
<div class="ttc" id="_cpu_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_scoped_cpu_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">armnn::ScopedCpuTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.xhtml#l00106">CpuTensorHandle.hpp:106</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#l00031">WorkloadData.hpp:31</a></div></div>
<div class="ttc" id="namespacearmnn_utils_xhtml"><div class="ttname"><a href="namespacearmnn_utils.xhtml">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00013">DataLayoutIndexed.hpp:13</a></div></div>
<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div>
<div class="ttc" id="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#l00030">WorkloadData.hpp:30</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#l00072">NeonDepthwiseConvolutionWorkload.cpp:72</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_cpu_tensor_handle_xhtml_a66e8f43a5b42b500871ed96e15419567"><div class="ttname"><a href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">armnn::ConstCpuTensorHandle::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.xhtml#l00037">CpuTensorHandle.hpp:37</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#l00444">Descriptors.hpp:444</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="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00183">WorkloadData.hpp:183</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>
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