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| <a href="_n_e_depthwise_convolution_layer_8h.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2017-2020 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#ifndef ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_n_e_depthwise_convolution_layer3x3_kernel_8h.xhtml">arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_n_e_depthwise_convolution_layer_native_kernel_8h.xhtml">arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="_n_e_direct_convolution_layer_output_stage_kernel_8h.xhtml">arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_n_e_fill_border_kernel_8h.xhtml">arm_compute/core/NEON/kernels/NEFillBorderKernel.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="_n_e_activation_layer_8h.xhtml">arm_compute/runtime/NEON/functions/NEActivationLayer.h</a>"</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="_n_e_permute_8h.xhtml">arm_compute/runtime/NEON/functions/NEPermute.h</a>"</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="_n_e_depthwise_convolution_assembly_dispatch_8h.xhtml">arm_compute/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.h</a>"</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment">// Forward declarations</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="keyword">class </span>ITensor;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"></span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment">/** Function to execute a depthwise convolution.</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"> */</span></div><div class="line"><a name="l00042"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml"> 42</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">NEDepthwiseConvolutionLayer</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> {</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"> /** Default constructor */</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aceb582e096b2871c92271876223eb7b6">NEDepthwiseConvolutionLayer</a>(std::shared_ptr<IMemoryManager> memory_manager = <span class="keyword">nullptr</span>);<span class="comment"></span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"> /** Prevent instances of this class from being copied (As this class contains pointers) */</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aceb582e096b2871c92271876223eb7b6">NEDepthwiseConvolutionLayer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">NEDepthwiseConvolutionLayer</a> &) = <span class="keyword">delete</span>;<span class="comment"></span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment"> /** Default move constructor */</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aceb582e096b2871c92271876223eb7b6">NEDepthwiseConvolutionLayer</a>(<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">NEDepthwiseConvolutionLayer</a> &&) = <span class="keywordflow">default</span>;<span class="comment"></span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> /** Prevent instances of this class from being copied (As this class contains pointers) */</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">NEDepthwiseConvolutionLayer</a> &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa450bb01e6984892ca2a04078b9c653d">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">NEDepthwiseConvolutionLayer</a> &) = <span class="keyword">delete</span>;<span class="comment"></span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"> /** Default move assignment operator */</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">NEDepthwiseConvolutionLayer</a> &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa450bb01e6984892ca2a04078b9c653d">operator=</a>(<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">NEDepthwiseConvolutionLayer</a> &&) = <span class="keywordflow">default</span>;<span class="comment"></span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"> /** Initialize the function's source, destination, weights and convolution information.</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"> *</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"> * @param[out] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM].</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="comment"> * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"> * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment"> * @param[in] act_info (Optional) Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="comment"> */</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#ac83f79ff17ee77e2b71166de83478c86">configure</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *biases, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a> = <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="comment"></span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment"> /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayer</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment"> *</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="comment"> * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="comment"> * @param[in] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM].</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="comment"> * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="comment"> * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="comment"> * @param[in] act_info (Optional) Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="comment"> *</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"> * @return a status</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment"> */</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keyword">static</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#a4bc5903a6da554c4cd38d2b123d30a4f">validate</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a> = <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="comment">// Inherited methods overriden:</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>() <span class="keyword">override</span>;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>() <span class="keyword">override</span>;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="keyword">private</span>:<span class="comment"></span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="comment"> /** Static function to choose the best depthwise convolution function for @ref NEDepthwiseConvolutionLayer</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="comment"> *</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="comment"> * @param[in] input Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="comment"> * @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM].</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="comment"> * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="comment"> * @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="comment"> * @param[in] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="comment"> * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="comment"> * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 quantized are supported.</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="comment"> *</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="comment"> * @return a Depthwise Convolution Function</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="comment"> */</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">static</span> <a class="code" href="namespacearm__compute.xhtml#a0255421478a6f5ab8a2596d966411a5b">DepthwiseConvolutionFunction</a> get_depthwiseconvolution_function(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a> = <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="comment"></span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="comment"> /** Basic function to execute optimized depthwise convolution routines. This function calls the following NEON kernels:</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"> *</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment"> * @note At the moment 3x3 and 5x5 convolution of stride 1, 2 are supported</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="comment"> *</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="comment"> * -# @ref NEFillBorderKernel (if pad_x or pad_y > 0) and no assembly kernel implementation is present</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="comment"> * -# @ref NEDepthwiseConvolutionLayer3x3Kernel if 3x3 and no assembly kernel implementation is present</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="comment"> * -# @ref NEDepthwiseConvolutionAssemblyDispatch if assembly kernel implementation is present</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="comment"> * -# @ref NEDirectConvolutionLayerOutputStageKernel if re-quantization of output is required</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="comment"> * -# @ref NEActivationLayer if fused activation is required</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="comment"> *</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="comment"> */</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">class </span>NEDepthwiseConvolutionLayerOptimizedInternal : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  {</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="comment"> /** Default constructor */</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  NEDepthwiseConvolutionLayerOptimizedInternal(std::shared_ptr<IMemoryManager> memory_manager = <span class="keyword">nullptr</span>);<span class="comment"></span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="comment"> /** Prevent instances of this class from being copied (As this class contains pointers) */</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  NEDepthwiseConvolutionLayerOptimizedInternal(<span class="keyword">const</span> NEDepthwiseConvolutionLayerOptimizedInternal &) = <span class="keyword">delete</span>;<span class="comment"></span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="comment"> /** Default move constructor */</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  NEDepthwiseConvolutionLayerOptimizedInternal(NEDepthwiseConvolutionLayerOptimizedInternal &&) = <span class="keywordflow">default</span>;<span class="comment"></span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="comment"> /** Prevent instances of this class from being copied (As this class contains pointers) */</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  NEDepthwiseConvolutionLayerOptimizedInternal &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa450bb01e6984892ca2a04078b9c653d">operator=</a>(<span class="keyword">const</span> NEDepthwiseConvolutionLayerOptimizedInternal &) = <span class="keyword">delete</span>;<span class="comment"></span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="comment"> /** Default move assignment operator */</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  NEDepthwiseConvolutionLayerOptimizedInternal &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa450bb01e6984892ca2a04078b9c653d">operator=</a>(NEDepthwiseConvolutionLayerOptimizedInternal &&) = <span class="keywordflow">default</span>;<span class="comment"></span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="comment"> /** Initialize the function's source, destination, kernels and border_size.</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="comment"> *</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="comment"> * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. (Written to only for border filling).</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment"> * @param[out] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="comment"> * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="comment"> * @param[in] act_info (Optional) Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="comment"> */</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#ac83f79ff17ee77e2b71166de83478c86">configure</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *biases, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a> = <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> <span class="comment"></span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="comment"> /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayer3x3</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> <span class="comment"> *</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="comment"> * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. (Written to only for border filling).</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="comment"> * @param[in] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> <span class="comment"> * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="comment"> * @param[in] act_info (Optional) Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="comment"> *</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> <span class="comment"> * @return a status</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> <span class="comment"> */</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keyword">static</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#a4bc5903a6da554c4cd38d2b123d30a4f">validate</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a> = <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="comment">// Inherited methods overriden:</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>() <span class="keyword">override</span>;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>() <span class="keyword">override</span>;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keyword">private</span>:<span class="comment"></span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <span class="comment"> /** Configure the kernels/functions for the generic pipeline.</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> <span class="comment"> *</span></div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="comment"> * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. (Written to only for border filling).</span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> <span class="comment"> * @param[out] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> <span class="comment"> * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> <span class="comment"> * @param[in] act_info Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> <span class="comment"> *</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> <span class="comment"> */</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keywordtype">void</span> configure_generic(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *biases, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));<span class="comment"></span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> <span class="comment"> /** Configure the kernels/functions for the optimized pipeline.</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> <span class="comment"> *</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="comment"> * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. (Written to only for border filling).</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> <span class="comment"> * @param[out] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> <span class="comment"> * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> <span class="comment"> * @param[in] act_info Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> <span class="comment"> */</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keywordtype">void</span> configure_optimized(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *biases, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));<span class="comment"></span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> <span class="comment"> /** Run generic kernel */</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordtype">void</span> run_generic();<span class="comment"></span></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> <span class="comment"> /** Run optimized function */</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordtype">void</span> run_optimized();</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <a class="code" href="classarm__compute_1_1_memory_group.xhtml">MemoryGroup</a> _memory_group;</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> _dwc_kernel;</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_assembly_dispatch.xhtml">NEDepthwiseConvolutionAssemblyDispatch</a> _dwc_optimized_func;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <a class="code" href="classarm__compute_1_1_n_e_direct_convolution_layer_output_stage_kernel.xhtml">NEDirectConvolutionLayerOutputStageKernel</a> _output_stage_kernel;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <a class="code" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml">NEFillBorderKernel</a> _border_handler;</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <a class="code" href="classarm__compute_1_1_n_e_permute.xhtml">NEPermute</a> _permute_input;</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <a class="code" href="classarm__compute_1_1_n_e_permute.xhtml">NEPermute</a> _permute_weights;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <a class="code" href="classarm__compute_1_1_n_e_permute.xhtml">NEPermute</a> _permute_output;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <a class="code" href="classarm__compute_1_1_n_e_activation_layer.xhtml">NEActivationLayer</a> _activationlayer_function;</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> _accumulator;</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> _permuted_input;</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> _permuted_weights;</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> _permuted_output;</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *_original_weights;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordtype">bool</span> _has_bias;</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <span class="keywordtype">bool</span> _is_quantized;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <span class="keywordtype">bool</span> _is_optimized;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordtype">bool</span> _is_nchw;</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordtype">bool</span> _permute;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="keywordtype">bool</span> _is_activationlayer_enabled;</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordtype">bool</span> _is_prepared;</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  };</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="comment"></span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="comment"> /** Basic function to execute a generic depthwise convolution. This function calls the following NEON kernel:</span></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> <span class="comment"> *</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> <span class="comment"> * -# @ref NEDepthwiseConvolutionLayerNativeKernel</span></div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> <span class="comment"> *</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> <span class="comment"> */</span></div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keyword">class </span>NEDepthwiseConvolutionLayerGeneric : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  {</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="comment"> /** Default constructor */</span></div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  NEDepthwiseConvolutionLayerGeneric();<span class="comment"></span></div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="comment"> /** Prevent instances of this class from being copied (As this class contains pointers) */</span></div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  NEDepthwiseConvolutionLayerGeneric(<span class="keyword">const</span> NEDepthwiseConvolutionLayerGeneric &) = <span class="keyword">delete</span>;<span class="comment"></span></div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> <span class="comment"> /** Default move constructor */</span></div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  NEDepthwiseConvolutionLayerGeneric(NEDepthwiseConvolutionLayerGeneric &&) = <span class="keywordflow">default</span>;<span class="comment"></span></div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> <span class="comment"> /** Prevent instances of this class from being copied (As this class contains pointers) */</span></div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  NEDepthwiseConvolutionLayerGeneric &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa450bb01e6984892ca2a04078b9c653d">operator=</a>(<span class="keyword">const</span> NEDepthwiseConvolutionLayerGeneric &) = <span class="keyword">delete</span>;<span class="comment"></span></div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <span class="comment"> /** Default move assignment operator */</span></div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  NEDepthwiseConvolutionLayerGeneric &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa450bb01e6984892ca2a04078b9c653d">operator=</a>(NEDepthwiseConvolutionLayerGeneric &&) = <span class="keywordflow">default</span>;<span class="comment"></span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="comment"> /** Initialize the function's source, destination, weights and convolution information.</span></div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <span class="comment"> *</span></div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> <span class="comment"> * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. (Written to only for border filling).</span></div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="comment"> * @param[out] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM].</span></div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> <span class="comment"> * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> <span class="comment"> * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> <span class="comment"> * @param[in] act_info (Optional) Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> <span class="comment"> */</span></div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#ac83f79ff17ee77e2b71166de83478c86">configure</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *biases, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a> = <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <span class="comment"></span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> <span class="comment"> /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayerGeneric</span></div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> <span class="comment"> *</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> <span class="comment"> * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. (Written to only for border filling).</span></div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> <span class="comment"> * @param[in] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM].</span></div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> <span class="comment"> * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> <span class="comment"> * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> <span class="comment"> * @param[in] act_info (Optional) Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> <span class="comment"> *</span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="comment"> * @return a status</span></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> <span class="comment"> */</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="keyword">static</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#a4bc5903a6da554c4cd38d2b123d30a4f">validate</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a> = <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="comment">// Inherited methods overriden:</span></div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>() <span class="keyword">override</span>;</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>() <span class="keyword">override</span>;</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> </div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keyword">private</span>:</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_native_kernel.xhtml">NEDepthwiseConvolutionLayerNativeKernel</a> _depthwise_conv_kernel;</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <a class="code" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml">NEFillBorderKernel</a> _fill_border;</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <a class="code" href="classarm__compute_1_1_n_e_permute.xhtml">NEPermute</a> _permute_input;</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="classarm__compute_1_1_n_e_permute.xhtml">NEPermute</a> _permute_weights;</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <a class="code" href="classarm__compute_1_1_n_e_permute.xhtml">NEPermute</a> _permute_output;</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <a class="code" href="classarm__compute_1_1_n_e_activation_layer.xhtml">NEActivationLayer</a> _activationlayer_function;</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> _permuted_input;</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> _permuted_weights;</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> _permuted_output;</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keywordtype">bool</span> _is_prepared;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keywordtype">bool</span> _is_nchw;</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordtype">bool</span> _is_activationlayer_enabled;</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *_original_weights;</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  };</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> </div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <a class="code" href="namespacearm__compute.xhtml#a0255421478a6f5ab8a2596d966411a5b">DepthwiseConvolutionFunction</a> _depth_conv_func;</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  NEDepthwiseConvolutionLayerOptimizedInternal _func_optimized;</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  NEDepthwiseConvolutionLayerGeneric _func_generic;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> };</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> <span class="comment"></span></div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="comment">/** Basic function to execute optimized depthwise convolution routines. This function calls the following NEON kernels:</span></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="comment"> *</span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="comment"> * @note At the moment 3x3 and 5x5 convolution of stride 1, 2 are supported</span></div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> <span class="comment"> *</span></div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> <span class="comment"> * -# @ref NEFillBorderKernel (if pad_x or pad_y > 0) and no assembly kernel implementation is present</span></div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="comment"> * -# @ref NEDepthwiseConvolutionLayer3x3Kernel if 3x3 and no assembly kernel implementation is present</span></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> <span class="comment"> * -# @ref NEDepthwiseConvolutionAssemblyDispatch if assembly kernel implementation is present</span></div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="comment"> * -# @ref NEDirectConvolutionLayerOutputStageKernel if re-quantization of output is required</span></div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> <span class="comment"> * -# @ref NEActivationLayer if fused activation is required</span></div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> <span class="comment"> *</span></div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <span class="comment"> */</span></div><div class="line"><a name="l00318"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml"> 318</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml">NEDepthwiseConvolutionLayerOptimized</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> {</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> <span class="comment"> /** Default constructor */</span></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#afbb9307112fea2f5f71a94702bc104d7">NEDepthwiseConvolutionLayerOptimized</a>(std::shared_ptr<IMemoryManager> memory_manager = <span class="keyword">nullptr</span>);<span class="comment"></span></div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> <span class="comment"> /** Prevent instances of this class from being copied (As this class contains pointers) */</span></div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#afbb9307112fea2f5f71a94702bc104d7">NEDepthwiseConvolutionLayerOptimized</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml">NEDepthwiseConvolutionLayerOptimized</a> &) = <span class="keyword">delete</span>;<span class="comment"></span></div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> <span class="comment"> /** Default move constructor */</span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#afbb9307112fea2f5f71a94702bc104d7">NEDepthwiseConvolutionLayerOptimized</a>(<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml">NEDepthwiseConvolutionLayerOptimized</a> &&) = <span class="keywordflow">default</span>;<span class="comment"></span></div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> <span class="comment"> /** Prevent instances of this class from being copied (As this class contains pointers) */</span></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml">NEDepthwiseConvolutionLayerOptimized</a> &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#a7e043a4a3c6fa18bf7fa308eff583ca8">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml">NEDepthwiseConvolutionLayerOptimized</a> &) = <span class="keyword">delete</span>;<span class="comment"></span></div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> <span class="comment"> /** Default move assignment operator */</span></div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml">NEDepthwiseConvolutionLayerOptimized</a> &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#a7e043a4a3c6fa18bf7fa308eff583ca8">operator=</a>(<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml">NEDepthwiseConvolutionLayerOptimized</a> &&) = <span class="keywordflow">default</span>;<span class="comment"></span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> <span class="comment"> /** Initialize the function's source, destination, kernels and border_size.</span></div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> <span class="comment"> *</span></div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> <span class="comment"> * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. (Written to only for border filling).</span></div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [W, H, IFM]. Data type supported: Same as @p input.</span></div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> <span class="comment"> * @param[out] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> <span class="comment"> * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> <span class="comment"> * @param[in] act_info (Optional) Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span> <span class="comment"> */</span></div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <a class="code" href="arm__compute_2core_2utils_2misc_2_macros_8h.xhtml#a751a15de75311d62d12f9fc9998368e1">ARM_COMPUTE_DEPRECATED_REL_REPLACE</a>(20.02, <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">NEDepthwiseConvolutionLayer</a>)</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#ac83f79ff17ee77e2b71166de83478c86">configure</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *biases, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a> = <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span> <span class="comment"></span></div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> <span class="comment"> /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayerOptimized</span></div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span> <span class="comment"> *</span></div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> <span class="comment"> * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. (Written to only for border filling).</span></div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span> <span class="comment"> * @param[in] weights Weights tensor. These are 3D tensors with shape [W, H, IFM]. Data type supported: Same as @p input.</span></div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> <span class="comment"> * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.</span></div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> <span class="comment"> * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.</span></div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> <span class="comment"> * @param[in] output Destination tensor. Data type supported: same as @p input.</span></div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> <span class="comment"> * @param[in] conv_info Padding and stride information to use for the convolution.</span></div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> <span class="comment"> * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.</span></div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> <span class="comment"> * @param[in] act_info (Optional) Activation layer information in case of a fused activation.</span></div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> <span class="comment"> * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</span></div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> <span class="comment"> *</span></div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> <span class="comment"> * @return a status</span></div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span> <span class="comment"> */</span></div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keyword">static</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#a4bc5903a6da554c4cd38d2b123d30a4f">validate</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a> = <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> </div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="comment">// Inherited methods overriden:</span></div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>() <span class="keyword">override</span>;</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>() <span class="keyword">override</span>;</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span> </div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">NEDepthwiseConvolutionLayer</a> _func;</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> };</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span> } <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> <span class="preprocessor">#endif </span><span class="comment">/* ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H */</span><span class="preprocessor"></span></div><div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized_xhtml_ac83f79ff17ee77e2b71166de83478c86"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#ac83f79ff17ee77e2b71166de83478c86">arm_compute::NEDepthwiseConvolutionLayerOptimized::configure</a></div><div class="ttdeci">void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier=1, const ActivationLayerInfo &act_info=ActivationLayerInfo(), const Size2D &dilation=Size2D(1U, 1U))</div><div class="ttdoc">Initialize the function's source, destination, kernels and border_size.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00094">NEDepthwiseConvolutionLayer.cpp:94</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_memory_group_xhtml"><div class="ttname"><a href="classarm__compute_1_1_memory_group.xhtml">arm_compute::MemoryGroup</a></div><div class="ttdoc">Memory group.</div><div class="ttdef"><b>Definition:</b> <a href="_memory_group_8h_source.xhtml#l00043">MemoryGroup.h:43</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a0255421478a6f5ab8a2596d966411a5b"><div class="ttname"><a href="namespacearm__compute.xhtml#a0255421478a6f5ab8a2596d966411a5b">arm_compute::DepthwiseConvolutionFunction</a></div><div class="ttdeci">DepthwiseConvolutionFunction</div><div class="ttdoc">Available DepthwiseConvolutionFunction.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00144">Types.h:144</a></div></div> |
| <div class="ttc" id="_n_e_depthwise_convolution_layer3x3_kernel_8h_xhtml"><div class="ttname"><a href="_n_e_depthwise_convolution_layer3x3_kernel_8h.xhtml">NEDepthwiseConvolutionLayer3x3Kernel.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_direct_convolution_layer_output_stage_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_direct_convolution_layer_output_stage_kernel.xhtml">arm_compute::NEDirectConvolutionLayerOutputStageKernel</a></div><div class="ttdoc">NEON kernel to accumulate the biases, if provided, or downscale in case of quantized input.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution_layer_output_stage_kernel_8h_source.xhtml#l00039">NEDirectConvolutionLayerOutputStageKernel.h:39</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_function_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_function.xhtml">arm_compute::IFunction</a></div><div class="ttdoc">Base class for all functions.</div><div class="ttdef"><b>Definition:</b> <a href="_i_function_8h_source.xhtml#l00030">IFunction.h:30</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized_xhtml_afbb9307112fea2f5f71a94702bc104d7"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#afbb9307112fea2f5f71a94702bc104d7">arm_compute::NEDepthwiseConvolutionLayerOptimized::NEDepthwiseConvolutionLayerOptimized</a></div><div class="ttdeci">NEDepthwiseConvolutionLayerOptimized(std::shared_ptr< IMemoryManager > memory_manager=nullptr)</div><div class="ttdoc">Default constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00089">NEDepthwiseConvolutionLayer.cpp:89</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized_xhtml_aa9b93ef660fc3c5b4b19d3fc7b891b77"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">arm_compute::NEDepthwiseConvolutionLayerOptimized::prepare</a></div><div class="ttdeci">void prepare() override</div><div class="ttdoc">Prepare the function for executing.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00116">NEDepthwiseConvolutionLayer.cpp:116</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ad3fd4136244e42ad89b01c02b904336d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">arm_compute::test::validation::dilation</a></div><div class="ttdeci">dilation</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">ConvolutionLayer.cpp:182</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a1f8aca235c095df227e7444f6b237eb1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">arm_compute::test::validation::act_info</a></div><div class="ttdeci">act_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00183">ConvolutionLayer.cpp:183</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml">arm_compute::NEDepthwiseConvolutionLayerOptimized</a></div><div class="ttdoc">Basic function to execute optimized depthwise convolution routines.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8h_source.xhtml#l00318">NEDepthwiseConvolutionLayer.h:318</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00597">Winograd.cpp:597</a></div></div> |
| <div class="ttc" id="_n_e_depthwise_convolution_assembly_dispatch_8h_xhtml"><div class="ttname"><a href="_n_e_depthwise_convolution_assembly_dispatch_8h.xhtml">NEDepthwiseConvolutionAssemblyDispatch.h</a></div></div> |
| <div class="ttc" id="_n_e_depthwise_convolution_layer_native_kernel_8h_xhtml"><div class="ttname"><a href="_n_e_depthwise_convolution_layer_native_kernel_8h.xhtml">NEDepthwiseConvolutionLayerNativeKernel.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_native_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer_native_kernel.xhtml">arm_compute::NEDepthwiseConvolutionLayerNativeKernel</a></div><div class="ttdoc">Interface for the kernel to run a depthwise convolution native on a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_native_kernel_8h_source.xhtml#l00040">NEDepthwiseConvolutionLayerNativeKernel.h:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml">arm_compute::ITensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_info_8h_source.xhtml#l00040">ITensorInfo.h:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_status_xhtml"><div class="ttname"><a href="classarm__compute_1_1_status.xhtml">arm_compute::Status</a></div><div class="ttdoc">Status class.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00052">Error.h:52</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_permute_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_permute.xhtml">arm_compute::NEPermute</a></div><div class="ttdoc">Basic function to run NEPermuteKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_permute_8h_source.xhtml#l00037">NEPermute.h:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_activation_layer_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_activation_layer_info.xhtml">arm_compute::ActivationLayerInfo</a></div><div class="ttdoc">Activation Layer Information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01615">Types.h:1615</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml">arm_compute::ITensor</a></div><div class="ttdoc">Interface for NEON tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00036">ITensor.h:36</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2020 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a8fcf2ddd9a1d58b1b280f5c0aed71845"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">arm_compute::test::validation::input</a></div><div class="ttdeci">auto input</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_l_s_t_m_layer_quantized_8cpp_source.xhtml#l00487">LSTMLayerQuantized.cpp:487</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_xhtml_aa9b93ef660fc3c5b4b19d3fc7b891b77"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">arm_compute::NEDepthwiseConvolutionLayer::prepare</a></div><div class="ttdeci">void prepare() override</div><div class="ttdoc">Prepare the function for executing.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00605">NEDepthwiseConvolutionLayer.cpp:605</a></div></div> |
| <div class="ttc" id="_n_e_fill_border_kernel_8h_xhtml"><div class="ttname"><a href="_n_e_fill_border_kernel_8h.xhtml">NEFillBorderKernel.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized_xhtml_a4bc5903a6da554c4cd38d2b123d30a4f"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#a4bc5903a6da554c4cd38d2b123d30a4f">arm_compute::NEDepthwiseConvolutionLayerOptimized::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier=1, const ActivationLayerInfo &act_info=ActivationLayerInfo(), const Size2D &dilation=Size2D(1U, 1U))</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of NEDepthwiseConvolutionLa...</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00105">NEDepthwiseConvolutionLayer.cpp:105</a></div></div> |
| <div class="ttc" id="_n_e_activation_layer_8h_xhtml"><div class="ttname"><a href="_n_e_activation_layer_8h.xhtml">NEActivationLayer.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized_xhtml_a7e043a4a3c6fa18bf7fa308eff583ca8"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#a7e043a4a3c6fa18bf7fa308eff583ca8">arm_compute::NEDepthwiseConvolutionLayerOptimized::operator=</a></div><div class="ttdeci">NEDepthwiseConvolutionLayerOptimized & operator=(const NEDepthwiseConvolutionLayerOptimized &)=delete</div><div class="ttdoc">Prevent instances of this class from being copied (As this class contains pointers)</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb"><div class="ttname"><a href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::Channel::U</a></div><div class="ttdoc">Cb/U channel.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_xhtml_a4bc5903a6da554c4cd38d2b123d30a4f"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#a4bc5903a6da554c4cd38d2b123d30a4f">arm_compute::NEDepthwiseConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier=1, const ActivationLayerInfo &act_info=ActivationLayerInfo(), const Size2D &dilation=Size2D(1U, 1U))</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of NEDepthwiseConvolutionLa...</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00559">NEDepthwiseConvolutionLayer.cpp:559</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_xhtml_aceb582e096b2871c92271876223eb7b6"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aceb582e096b2871c92271876223eb7b6">arm_compute::NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayer</a></div><div class="ttdeci">NEDepthwiseConvolutionLayer(std::shared_ptr< IMemoryManager > memory_manager=nullptr)</div><div class="ttdoc">Default constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00537">NEDepthwiseConvolutionLayer.cpp:537</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml">arm_compute::Tensor</a></div><div class="ttdoc">Basic implementation of the tensor interface.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8h_source.xhtml#l00037">Tensor.h:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml">arm_compute::PadStrideInfo</a></div><div class="ttdoc">Padding and stride information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00686">Types.h:686</a></div></div> |
| <div class="ttc" id="_n_e_direct_convolution_layer_output_stage_kernel_8h_xhtml"><div class="ttname"><a href="_n_e_direct_convolution_layer_output_stage_kernel_8h.xhtml">NEDirectConvolutionLayerOutputStageKernel.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer_optimized.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEDepthwiseConvolutionLayerOptimized::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00111">NEDepthwiseConvolutionLayer.cpp:111</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_activation_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_activation_layer.xhtml">arm_compute::NEActivationLayer</a></div><div class="ttdoc">Basic function to run NEActivationLayerKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_activation_layer_8h_source.xhtml#l00040">NEActivationLayer.h:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel</a></div><div class="ttdoc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer3x3_kernel_8h_source.xhtml#l00035">NEDepthwiseConvolutionLayer3x3Kernel.h:35</a></div></div> |
| <div class="ttc" id="_n_e_permute_8h_xhtml"><div class="ttname"><a href="_n_e_permute_8h.xhtml">NEPermute.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_xhtml_aa450bb01e6984892ca2a04078b9c653d"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#aa450bb01e6984892ca2a04078b9c653d">arm_compute::NEDepthwiseConvolutionLayer::operator=</a></div><div class="ttdeci">NEDepthwiseConvolutionLayer & operator=(const NEDepthwiseConvolutionLayer &)=delete</div><div class="ttdoc">Prevent instances of this class from being copied (As this class contains pointers)</div></div> |
| <div class="ttc" id="classarm__compute_1_1_size2_d_xhtml"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml">arm_compute::Size2D</a></div><div class="ttdoc">Class for specifying the size of an image or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00034">Size2D.h:34</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_assembly_dispatch_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_assembly_dispatch.xhtml">arm_compute::NEDepthwiseConvolutionAssemblyDispatch</a></div><div class="ttdoc">Depthwise convolution assembly kernel glue.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_assembly_dispatch_8h_source.xhtml#l00036">NEDepthwiseConvolutionAssemblyDispatch.h:36</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a64a08a9fec5aeee8650e7182b6d171d0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">arm_compute::test::validation::weights</a></div><div class="ttdeci">CLTensor weights</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00188">ConvolutionLayer.cpp:188</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_fill_border_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml">arm_compute::NEFillBorderKernel</a></div><div class="ttdoc">Interface for the kernel to fill borders.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_fill_border_kernel_8h_source.xhtml#l00037">NEFillBorderKernel.h:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml">arm_compute::NEDepthwiseConvolutionLayer</a></div><div class="ttdoc">Function to execute a depthwise convolution.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8h_source.xhtml#l00042">NEDepthwiseConvolutionLayer.h:42</a></div></div> |
| <div class="ttc" id="arm__compute_2core_2utils_2misc_2_macros_8h_xhtml_a751a15de75311d62d12f9fc9998368e1"><div class="ttname"><a href="arm__compute_2core_2utils_2misc_2_macros_8h.xhtml#a751a15de75311d62d12f9fc9998368e1">ARM_COMPUTE_DEPRECATED_REL_REPLACE</a></div><div class="ttdeci">#define ARM_COMPUTE_DEPRECATED_REL_REPLACE(rel, replace)</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2utils_2misc_2_macros_8h_source.xhtml#l00043">Macros.h:43</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_xhtml_ac83f79ff17ee77e2b71166de83478c86"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#ac83f79ff17ee77e2b71166de83478c86">arm_compute::NEDepthwiseConvolutionLayer::configure</a></div><div class="ttdeci">void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier=1, const ActivationLayerInfo &act_info=ActivationLayerInfo(), const Size2D &dilation=Size2D(1U, 1U))</div><div class="ttdoc">Initialize the function's source, destination, weights and convolution information.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00542">NEDepthwiseConvolutionLayer.cpp:542</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEDepthwiseConvolutionLayer::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_8cpp_source.xhtml#l00590">NEDepthwiseConvolutionLayer.cpp:590</a></div></div> |
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