<tr style="height: 56px;">
<td style="padding-left: 0.5em;">
<div id="projectname">Compute Library
-  <span id="projectnumber">18.03</span>
+  <span id="projectnumber">18.05</span>
</div>
</td>
</tr>
<div class="title">NEDepthwiseConvolutionLayer3x3Kernel.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="_n_e_depthwise_convolution_layer3x3_kernel_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) 2017-2018 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_NEDEPTHWISECONVOLUTIONKERNEL3x3_H__</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define __ARM_COMPUTE_NEDEPTHWISECONVOLUTIONKERNEL3x3_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="_i_n_e_kernel_8h.xhtml">arm_compute/core/NEON/INEKernel.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "arm_compute/core/NEON/kernels/convolution/depthwise/depthwise.hpp"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <memory></span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> {</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">class </span>ITensor;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00037"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml"> 37</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml">INEKernel</a></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> {</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#ab5656bb5b6334bdbe6e606c715872828"> 40</a></span>  <span class="keyword">const</span> <span class="keywordtype">char</span> *<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#ab5656bb5b6334bdbe6e606c715872828">name</a>()<span class="keyword"> const override</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">return</span> <span class="stringliteral">"NEDepthwiseConvolutionLayer3x3Kernel"</span>;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  }</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#abf0a671d5f84d64b22c1baacbc30d42c">NEDepthwiseConvolutionLayer3x3Kernel</a>();</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#abf0a671d5f84d64b22c1baacbc30d42c">NEDepthwiseConvolutionLayer3x3Kernel</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &) = <span class="keyword">delete</span>;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a4f080336e12b8a0a378f008780eeff5a">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &) = <span class="keyword">delete</span>;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#abf0a671d5f84d64b22c1baacbc30d42c">NEDepthwiseConvolutionLayer3x3Kernel</a>(<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &&) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a4f080336e12b8a0a378f008780eeff5a">operator=</a>(<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &&) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a185cf08a1ed4b6dfbd36121492849ff4">configure</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *weights, <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> &conv_info, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> data_layout = <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#aceef5ed4bcd2b3691a06aea1b852446b">is_optimized_execution_possible</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> input_shape, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> conv_info, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dt, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> data_layout = <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#af77d9d6fcc740068192d3fca9421311f">generate_convolver</a>();</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// Inherited methods overridden:</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a112b35dd205c62ea6ed1447ef226da82">run</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>, <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a096668313a9a819d54a2e65ec21ff0cc">info</a>) <span class="keyword">override</span>;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordtype">void</span> configure_generic();</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordtype">void</span> configure_optimized();</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordtype">void</span> run_generic(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &window, <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &info);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordtype">void</span> run_optimized(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &window, <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &info);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  std::unique_ptr<depthwise::IDepthwiseConvolution> create_convolver_object(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> conv_info,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keyword">const</span> uint8_t *w_ptr, uint8_t *in_ptr, uint8_t *out_ptr);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a> _border_size;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *_input;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *_output;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *_weights;</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> _conv_info;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  std::unique_ptr<depthwise::IDepthwiseConvolution> _convolver;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> _num_elems_written_per_iteration;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keywordtype">bool</span> _run_optimized;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> };</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> } <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="preprocessor">#endif </span><span class="comment">/* __ARM_COMPUTE_NEDEPTHWISECONVOLUTIONKERNEL3x3_H__ */</span><span class="preprocessor"></span></div><div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml_a4f080336e12b8a0a378f008780eeff5a"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a4f080336e12b8a0a378f008780eeff5a">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel::operator=</a></div><div class="ttdeci">NEDepthwiseConvolutionLayer3x3Kernel & operator=(const NEDepthwiseConvolutionLayer3x3Kernel &)=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_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00133">Convolution.cpp:133</a></div></div>
+<a href="_n_e_depthwise_convolution_layer3x3_kernel_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) 2017-2018 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_NEDEPTHWISECONVOLUTIONKERNEL3x3_H__</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define __ARM_COMPUTE_NEDEPTHWISECONVOLUTIONKERNEL3x3_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="_i_n_e_kernel_8h.xhtml">arm_compute/core/NEON/INEKernel.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "arm_compute/core/NEON/kernels/convolution/depthwise/depthwise.hpp"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <memory></span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> {</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">class </span>ITensor;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00037"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml"> 37</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml">INEKernel</a></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> {</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#ab5656bb5b6334bdbe6e606c715872828"> 40</a></span>  <span class="keyword">const</span> <span class="keywordtype">char</span> *<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#ab5656bb5b6334bdbe6e606c715872828">name</a>()<span class="keyword"> const override</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">return</span> <span class="stringliteral">"NEDepthwiseConvolutionLayer3x3Kernel"</span>;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  }</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#abf0a671d5f84d64b22c1baacbc30d42c">NEDepthwiseConvolutionLayer3x3Kernel</a>();</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#abf0a671d5f84d64b22c1baacbc30d42c">NEDepthwiseConvolutionLayer3x3Kernel</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &) = <span class="keyword">delete</span>;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a4f080336e12b8a0a378f008780eeff5a">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &) = <span class="keyword">delete</span>;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#abf0a671d5f84d64b22c1baacbc30d42c">NEDepthwiseConvolutionLayer3x3Kernel</a>(<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &&) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a4f080336e12b8a0a378f008780eeff5a">operator=</a>(<a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml">NEDepthwiseConvolutionLayer3x3Kernel</a> &&) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a4b9e97a619f7222a14a9c61009b57920">configure</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *weights, <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#acbf8f8a6dd185de04c1981c57a8963cf">conv_info</a>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> data_layout = <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a1f5245ff1a8acbc154295f17e4571465">is_optimized_execution_possible</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> input_shape, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> conv_info, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dt, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier = 1, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> data_layout = <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#af77d9d6fcc740068192d3fca9421311f">generate_convolver</a>();</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// Inherited methods overridden:</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a112b35dd205c62ea6ed1447ef226da82">run</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>, <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a096668313a9a819d54a2e65ec21ff0cc">info</a>) <span class="keyword">override</span>;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a> <a class="code" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordtype">void</span> configure_generic();</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordtype">void</span> configure_optimized();</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keywordtype">void</span> run_generic(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &window, <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &info);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordtype">void</span> run_optimized(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &window, <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &info);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  std::unique_ptr<depthwise::IDepthwiseConvolution> create_convolver_object(<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> conv_info,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *w,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *in,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *out,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordtype">bool</span> setup_strides = <span class="keyword">false</span>);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <a class="code" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a> _border_size;</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *_input;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</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_i_tensor.xhtml">ITensor</a> *_weights;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> _conv_info;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  std::unique_ptr<depthwise::IDepthwiseConvolution> _convolver;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> _num_elems_written_per_iteration;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordtype">bool</span> _run_optimized;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> _depth_multiplier;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> };</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> } <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="preprocessor">#endif </span><span class="comment">/* __ARM_COMPUTE_NEDEPTHWISECONVOLUTIONKERNEL3x3_H__ */</span><span class="preprocessor"></span></div><div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml_a4f080336e12b8a0a378f008780eeff5a"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a4f080336e12b8a0a378f008780eeff5a">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel::operator=</a></div><div class="ttdeci">NEDepthwiseConvolutionLayer3x3Kernel & operator=(const NEDepthwiseConvolutionLayer3x3Kernel &)=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_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml_ab5656bb5b6334bdbe6e606c715872828"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#ab5656bb5b6334bdbe6e606c715872828">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel::name</a></div><div class="ttdeci">const char * name() const override</div><div class="ttdoc">Name of the kernel. </div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer3x3_kernel_8h_source.xhtml#l00040">NEDepthwiseConvolutionLayer3x3Kernel.h:40</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml_a185cf08a1ed4b6dfbd36121492849ff4"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a185cf08a1ed4b6dfbd36121492849ff4">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel::configure</a></div><div class="ttdeci">void configure(const ITensor *input, const ITensor *weights, ITensor *output, const PadStrideInfo &conv_info, DataLayout data_layout=DataLayout::NCHW)</div><div class="ttdoc">Initialize the function&#39;s source, destination, conv and border_size. </div></div>
-<div class="ttc" id="structarm__compute_1_1_border_size_xhtml"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml">arm_compute::BorderSize</a></div><div class="ttdoc">Container for 2D border size. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00229">Types.h:229</a></div></div>
+<div class="ttc" id="structarm__compute_1_1_border_size_xhtml"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml">arm_compute::BorderSize</a></div><div class="ttdoc">Container for 2D border size. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00291">Types.h:291</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_c_p_p_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_c_p_p_kernel.xhtml">arm_compute::ICPPKernel</a></div><div class="ttdoc">Common interface for all kernels implemented in C++. </div><div class="ttdef"><b>Definition:</b> <a href="_i_c_p_p_kernel_8h_source.xhtml#l00035">ICPPKernel.h:35</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_1_1test_1_1validation_xhtml_a096668313a9a819d54a2e65ec21ff0cc"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a096668313a9a819d54a2e65ec21ff0cc">arm_compute::test::validation::info</a></div><div class="ttdeci">src info() -> set_format(Format::S16)</div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">This file contains all available output stages for GEMMLowp on OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00001">00_introduction.dox:1</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#l00491">Types.h:491</a></div></div>
-<div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</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#l00571">Types.h:571</a></div></div>
+<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_acbf8f8a6dd185de04c1981c57a8963cf"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#acbf8f8a6dd185de04c1981c57a8963cf">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#l00360">Winograd.cpp:360</a></div></div>
+<div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width. </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#l00037">NEDepthwiseConvolutionLayer3x3Kernel.h:37</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml_a112b35dd205c62ea6ed1447ef226da82"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a112b35dd205c62ea6ed1447ef226da82">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel::run</a></div><div class="ttdeci">void run(const Window &window, const ThreadInfo &info) override</div><div class="ttdoc">Execute the kernel on the passed window. </div></div>
-<div class="ttc" id="structarm__compute_1_1_thread_info_xhtml"><div class="ttname"><a href="structarm__compute_1_1_thread_info.xhtml">arm_compute::ThreadInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_types_8h_source.xhtml#l00058">CPPTypes.h:58</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml_aceef5ed4bcd2b3691a06aea1b852446b"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#aceef5ed4bcd2b3691a06aea1b852446b">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel::is_optimized_execution_possible</a></div><div class="ttdeci">static bool is_optimized_execution_possible(TensorShape input_shape, PadStrideInfo conv_info, DataType dt, DataLayout data_layout=DataLayout::NCHW)</div><div class="ttdoc">Static method that checks if optimized execution is supported for the given parameters. </div></div>
+<div class="ttc" id="structarm__compute_1_1_thread_info_xhtml"><div class="ttname"><a href="structarm__compute_1_1_thread_info.xhtml">arm_compute::ThreadInfo</a></div><div class="ttdoc">Information about executing thread and CPU. </div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_types_8h_source.xhtml#l00131">CPPTypes.h:131</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml_a4b9e97a619f7222a14a9c61009b57920"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a4b9e97a619f7222a14a9c61009b57920">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel::configure</a></div><div class="ttdeci">void configure(const ITensor *input, const ITensor *weights, ITensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier=1, DataLayout data_layout=DataLayout::NCHW)</div><div class="ttdoc">Initialize the function&#39;s source, destination, conv and border_size. </div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml_af77d9d6fcc740068192d3fca9421311f"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#af77d9d6fcc740068192d3fca9421311f">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel::generate_convolver</a></div><div class="ttdeci">void generate_convolver()</div><div class="ttdoc">Generates the convolver object. </div></div>
+<div class="ttc" id="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel_xhtml_a1f5245ff1a8acbc154295f17e4571465"><div class="ttname"><a href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#a1f5245ff1a8acbc154295f17e4571465">arm_compute::NEDepthwiseConvolutionLayer3x3Kernel::is_optimized_execution_possible</a></div><div class="ttdeci">static bool is_optimized_execution_possible(TensorShape input_shape, PadStrideInfo conv_info, DataType dt, unsigned int depth_multiplier=1, DataLayout data_layout=DataLayout::NCHW)</div><div class="ttdoc">Static method that checks if optimized execution is supported for the given parameters. </div></div>
<div class="ttc" id="_i_n_e_kernel_8h_xhtml"><div class="ttname"><a href="_i_n_e_kernel_8h.xhtml">INEKernel.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00072">Types.h:72</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdoc">Supported tensor data layouts. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00110">Types.h:110</a></div></div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="dir_214608ef36d61442cb2b0c1c4e9a7def.xhtml">arm_compute</a></li><li class="navelem"><a class="el" href="dir_1fb090f0c6070330bfaccc4236d3ca0d.xhtml">core</a></li><li class="navelem"><a class="el" href="dir_315f6cf1ec0b2df3ae747ff8286a19f5.xhtml">NEON</a></li><li class="navelem"><a class="el" href="dir_2c3c4cb85e732569e2614ad40a451d53.xhtml">kernels</a></li><li class="navelem"><a class="el" href="_n_e_depthwise_convolution_layer3x3_kernel_8h.xhtml">NEDepthwiseConvolutionLayer3x3Kernel.h</a></li>
- <li class="footer">Generated on Fri Mar 2 2018 12:37:52 for Compute Library by
+ <li class="footer">Generated on Wed May 23 2018 11:36:35 for Compute Library by
<a href="http://www.doxygen.org/index.html">
<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li>
</ul>