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| <div class="title">CLDirectConvolutionLayerKernel.cpp</div> </div> |
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| <a href="_c_l_direct_convolution_layer_kernel_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2017-2019 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">#include "<a class="code" href="_c_l_direct_convolution_layer_kernel_8h.xhtml">arm_compute/core/CL/kernels/CLDirectConvolutionLayerKernel.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include "<a class="code" href="_access_window_static_8h.xhtml">arm_compute/core/AccessWindowStatic.h</a>"</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="core_2_c_l_2_c_l_helpers_8h.xhtml">arm_compute/core/CL/CLHelpers.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_c_l_kernel_library_8h.xhtml">arm_compute/core/CL/CLKernelLibrary.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="_c_l_validate_8h.xhtml">arm_compute/core/CL/CLValidate.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_i_c_l_tensor_8h.xhtml">arm_compute/core/CL/ICLTensor.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="_error_8h.xhtml">arm_compute/core/Error.h</a>"</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="arm__compute_2core_2_helpers_8h.xhtml">arm_compute/core/Helpers.h</a>"</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="_i_access_window_8h.xhtml">arm_compute/core/IAccessWindow.h</a>"</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include "<a class="code" href="_i_tensor_8h.xhtml">arm_compute/core/ITensor.h</a>"</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include "<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>"</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include "<a class="code" href="arm__compute_2core_2_utils_8h.xhtml">arm_compute/core/Utils.h</a>"</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include "<a class="code" href="_shape_calculator_8h.xhtml">arm_compute/core/utils/misc/ShapeCalculator.h</a>"</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include "<a class="code" href="_asymm_helpers_8h.xhtml">arm_compute/core/utils/quantization/AsymmHelpers.h</a>"</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include "<a class="code" href="_toolchain_support_8h.xhtml">support/ToolchainSupport.h</a>"</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword">using namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a>;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> {</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> validate_arguments(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, <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="l00046"></a><span class="lineno"> 46</span> {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="_c_l_validate_8h.xhtml#ab82bd5de18ef067ae5d9ba4af8065dd6">ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED</a>(input);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(input, 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> = input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>();</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> width_idx = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> height_idx = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> channel_idx = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">DataLayoutDimension::CHANNEL</a>);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx) != <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(height_idx), <span class="stringliteral">"Weights should have same width and height"</span>);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx) != 1 && <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx) != 3 && <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx) != 5 && <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx) != 9,</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="stringliteral">"Kernel sizes other than 1x1, 3x3, 5x5 or 9x9 are not supported"</span>);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(channel_idx) != input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(channel_idx),</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="stringliteral">"Weights feature map dimension should match the respective input's one"</span>);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->num_dimensions() > 4, <span class="stringliteral">"Weights can be at most 4 dimensional"</span>);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>((<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx) == 1) && std::get<0>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride()) > 3, <span class="stringliteral">"Strides larger than 3 not supported for 1x1 convolution."</span>);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>((<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx) == 3 || <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx) == 5) && std::get<0>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride()) > 2,</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="stringliteral">"Strides larger than 2 not supported for 3x3 convolution."</span>);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>((<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx) == 9) && <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>, <span class="stringliteral">"Only NHWC layout is supported for 9x9 convolution."</span>);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">if</span>(biases != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>()))</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  {</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(biases, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  }</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(biases-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0) != <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(3),</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="stringliteral">"Biases size and number of input feature maps should match"</span>);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(biases-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() > 1,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="stringliteral">"Biases should be one dimensional"</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> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="comment">// Checks performed when output is configured</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">if</span>(output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>() != 0)</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  {</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="_validate_8h.xhtml#a1da797d2762c1cdbb73bfc83136c3a38">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS</a>(output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>(),</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a5d320d308c16b8ddda3c9d3f60fad79c">misc::shape_calculator::compute_deep_convolution_shape</a>(*input, *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>));</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(input, output);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  }</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</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> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> can_run_optimized_kernel_for_bifrost(<a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_stride_x, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_stride_y, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernel_size,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>)</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> {</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">gpu_target_is_in</a>(gpu_target,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">GPUTarget::G76</a>,</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">GPUTarget::G51</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">GPUTarget::G51BIG</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">GPUTarget::G51LIT</a>,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">GPUTarget::G52</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">GPUTarget::G52LIT</a>)</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  && (kernel_size <= 5)</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  && (conv_stride_x == 1) && (conv_stride_y == 1)</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  && (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a> == <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  && (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</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> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> can_run_optimized_kernel_for_bifrost_nhwc(<a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_stride_x, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_stride_y, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernel_size,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>)</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> {</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">gpu_target_is_in</a>(gpu_target,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">GPUTarget::G76</a>,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">GPUTarget::G51</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">GPUTarget::G51BIG</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">GPUTarget::G51LIT</a>,</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">GPUTarget::G52</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">GPUTarget::G52LIT</a>)</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  && (kernel_size == 9)</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  && (conv_stride_x == 1) && (conv_stride_y == 1)</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  && (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a> == <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  && (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> }</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> setup_num_elems(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &num_elems_read_per_iteration_x, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &num_elems_read_per_iteration_y,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &num_elems_written_per_iteration_x, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &num_elems_written_per_iteration_y,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernel_size, <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="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> target, <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input)</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> {</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a> = input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>();</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> = input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>();</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_stride_x = std::get<0>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride());</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_stride_y = std::get<1>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride());</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> run_optimized_bifrost = can_run_optimized_kernel_for_bifrost(target, conv_stride_x, conv_stride_y, kernel_size, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">if</span>(run_optimized_bifrost)</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  {</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="comment">// Configure kernel window</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordflow">switch</span>(kernel_size)</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  {</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  num_elems_read_per_iteration_x = 4;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  num_elems_read_per_iteration_y = 4;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  num_elems_written_per_iteration_x = 4;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  num_elems_written_per_iteration_y = 4;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  }</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordflow">case</span> 3:</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  num_elems_read_per_iteration_x = 6;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  num_elems_read_per_iteration_y = 5;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  num_elems_written_per_iteration_x = 4;</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  num_elems_written_per_iteration_y = 3;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  }</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keywordflow">case</span> 5:</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  {</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  num_elems_read_per_iteration_x = 8;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  num_elems_read_per_iteration_y = 6;</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  num_elems_written_per_iteration_x = 4;</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  num_elems_written_per_iteration_y = 2;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  }</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  {</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Kernel size not optimized for Bifrost"</span>);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  }</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  }</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  }</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  {</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  num_elems_read_per_iteration_y = kernel_size;</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  num_elems_written_per_iteration_x = 8;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  num_elems_written_per_iteration_y = 1;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordflow">switch</span>(kernel_size)</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="keywordflow">case</span> 1:</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordflow">switch</span>(conv_stride_x)</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  {</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  num_elems_read_per_iteration_x = 8;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  num_elems_read_per_iteration_x = 16;</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordflow">case</span> 3:</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keywordflow">switch</span>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#aa459796b5489eca8a9160cb5dcf1a103">element_size</a>())</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  {</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  num_elems_read_per_iteration_x = 28;</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  num_elems_read_per_iteration_x = 24;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keywordflow">case</span> 4:</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  num_elems_read_per_iteration_x = 22;</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Invalid data size"</span>);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  }</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Invalid convolution stride X"</span>);</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  }</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">case</span> 3:</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordflow">switch</span>(conv_stride_x)</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  {</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  num_elems_read_per_iteration_x = 10;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  num_elems_read_per_iteration_x = 17;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Invalid convolution stride X"</span>);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  }</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="keywordflow">case</span> 5:</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordflow">switch</span>(conv_stride_x)</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  {</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  num_elems_read_per_iteration_x = 12;</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  num_elems_read_per_iteration_x = 20;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Invalid convolution stride X"</span>);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  }</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Invalid direct convolution size"</span>);</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  }</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  }</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keywordflow">else</span> <span class="comment">// data_layout == NHWC</span></div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  {</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> run_optimized_bifrost_nhwc = can_run_optimized_kernel_for_bifrost_nhwc(target, conv_stride_x, conv_stride_y, kernel_size, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>);</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> </div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  num_elems_written_per_iteration_x = 1;</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="keywordflow">if</span>(run_optimized_bifrost_nhwc)</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  {</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  num_elems_read_per_iteration_x = 4;</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  }</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  {</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  num_elems_read_per_iteration_x = 1;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  }</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> </div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="keywordflow">switch</span>(kernel_size)</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  {</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordflow">switch</span>(conv_stride_x)</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  {</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  num_elems_read_per_iteration_y = 8;</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  num_elems_written_per_iteration_y = 8;</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  num_elems_read_per_iteration_y = 16;</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  num_elems_written_per_iteration_y = 8;</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Invalid convolution stride X"</span>);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  }</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">case</span> 3:</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keywordflow">switch</span>(conv_stride_x)</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  {</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  num_elems_read_per_iteration_y = 10;</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  num_elems_written_per_iteration_y = 8;</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  num_elems_read_per_iteration_y = 17;</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  num_elems_written_per_iteration_y = 8;</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Invalid convolution stride X"</span>);</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  }</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="keywordflow">case</span> 5:</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keywordflow">switch</span>(conv_stride_x)</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="keywordflow">case</span> 1:</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  num_elems_read_per_iteration_y = 12;</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  num_elems_written_per_iteration_y = 8;</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  num_elems_read_per_iteration_y = 20;</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  num_elems_written_per_iteration_y = 8;</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Invalid convolution stride X"</span>);</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  }</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keywordflow">case</span> 9:</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordflow">switch</span>(conv_stride_x)</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  {</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  num_elems_read_per_iteration_y = 16;</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  num_elems_written_per_iteration_y = 8;</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  num_elems_read_per_iteration_y = 24;</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  num_elems_written_per_iteration_y = 8;</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Invalid convolution stride X"</span>);</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  }</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Not implemented."</span>);</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  }</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  }</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> }</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> std::pair<Status, Window> <a class="code" href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">validate_and_configure_window</a>(<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, <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>, <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>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> target)</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> {</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> = input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>();</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> width_idx = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>);</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernel_size = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(width_idx);</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="comment">// Get convolved dimensions</span></div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a> = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a5d320d308c16b8ddda3c9d3f60fad79c">misc::shape_calculator::compute_deep_convolution_shape</a>(*input, *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>);</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> </div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="comment">// Output auto inizialitation if not yet initialized</span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="comment">// TODO(COMPMID-2078): input->clone()->set_tensor_shape(output_shape) doesn't work with subtensors for grouped direct convolutions (AlexNet).</span></div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a>,</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  1,</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>(),</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>());</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> </div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_read_per_iteration_x = 0;</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_read_per_iteration_y = 0;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_written_per_iteration_x = 0;</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_written_per_iteration_y = 0;</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> </div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_pad_left = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_left();</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_pad_top = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_top();</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_stride_x = std::get<0>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride());</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_stride_y = std::get<1>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride());</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  setup_num_elems(num_elems_read_per_iteration_x, num_elems_read_per_iteration_y,</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  num_elems_written_per_iteration_x, num_elems_written_per_iteration_y,</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  kernel_size, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, target, input);</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="comment">// Create window and update padding</span></div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keywordtype">bool</span> window_changed = <span class="keyword">false</span>;</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> win = <a class="code" href="namespacearm__compute.xhtml#ab7980fa5ee693e3282a76da047a1c3b5">calculate_max_window</a>(*output, <a class="code" href="classarm__compute_1_1_steps.xhtml">Steps</a>(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y));</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> </div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  {</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <a class="code" href="classarm__compute_1_1_access_window_static.xhtml">AccessWindowStatic</a> input_access(input, 0, -conv_pad_left,</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <a class="code" href="namespacearm__compute.xhtml#ab237a0a375cf382d52b61653248d3d4a">ceil_to_multiple</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0), num_elems_read_per_iteration_x),</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <a class="code" href="namespacearm__compute.xhtml#ab237a0a375cf382d52b61653248d3d4a">ceil_to_multiple</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1) + <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_right(), num_elems_read_per_iteration_y));</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <a class="code" href="classarm__compute_1_1_access_window_static.xhtml">AccessWindowStatic</a> weights_access(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, 0, 0, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(0), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(1));</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <a class="code" href="classarm__compute_1_1_access_window_rectangle.xhtml">AccessWindowRectangle</a> output_access(output, 0, 0, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y);</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  window_changed = <a class="code" href="namespacearm__compute.xhtml#afc4bd8e872567d9c4c57d89eb0bb3da1">update_window_and_padding</a>(win, input_access, weights_access, output_access);</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  output_access.set_valid_region(win, <a class="code" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a>(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(), output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()));</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> err = (window_changed) ? <a class="code" href="_error_8h.xhtml#a046fbca6a9505ce038bc02830c739fed">ARM_COMPUTE_CREATE_ERROR</a>(<a class="code" href="namespacearm__compute.xhtml#a59e56af19e754a6aa26a612ebf91d05fa62be47fdd89da032cf78dfce82239579">ErrorCode::RUNTIME_ERROR</a>, <span class="stringliteral">"Insufficient Padding!"</span>) : <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">return</span> std::make_pair(err, win);</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  }</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</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>  <a class="code" href="classarm__compute_1_1_access_window_rectangle.xhtml">AccessWindowRectangle</a> input_access(input, -conv_pad_left, -conv_pad_top, num_elems_read_per_iteration_x, num_elems_read_per_iteration_y, conv_stride_x, conv_stride_y);</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <a class="code" href="classarm__compute_1_1_access_window_static.xhtml">AccessWindowStatic</a> weights_access(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, 0, 0, kernel_size, kernel_size);</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <a class="code" href="classarm__compute_1_1_access_window_rectangle.xhtml">AccessWindowRectangle</a> output_access(output, 0, 0, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y);</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  window_changed = <a class="code" href="namespacearm__compute.xhtml#afc4bd8e872567d9c4c57d89eb0bb3da1">update_window_and_padding</a>(win, input_access, weights_access, output_access);</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  output_access.set_valid_region(win, <a class="code" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a>(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(), output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()));</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> err = (window_changed) ? <a class="code" href="_error_8h.xhtml#a046fbca6a9505ce038bc02830c739fed">ARM_COMPUTE_CREATE_ERROR</a>(<a class="code" href="namespacearm__compute.xhtml#a59e56af19e754a6aa26a612ebf91d05fa62be47fdd89da032cf78dfce82239579">ErrorCode::RUNTIME_ERROR</a>, <span class="stringliteral">"Insufficient Padding!"</span>) : <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keywordflow">return</span> std::make_pair(err, win);</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  }</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  {</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Not supported"</span>);</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  }</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> }</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> } <span class="comment">// namespace</span></div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> </div><div class="line"><a name="l00379"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a8c384e82445ca3f6f481f04295bcf3a9"> 379</a></span> <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a8c384e82445ca3f6f481f04295bcf3a9">CLDirectConvolutionLayerKernel::CLDirectConvolutionLayerKernel</a>()</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  : _input(nullptr), _biases(nullptr), _weights(nullptr), _output(nullptr), _border_size(0), _conv_stride_x(0), _conv_stride_y(0)</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span> {</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> }</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> </div><div class="line"><a name="l00384"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7"> 384</a></span> <a class="code" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a> <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">CLDirectConvolutionLayerKernel::border_size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> <span class="keyword"></span>{</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a2e0cdcd6999269beea6b9512ad41f3d4">_border_size</a>;</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> }</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span> </div><div class="line"><a name="l00389"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a0e2cfb6fb263bd6f761756c816574345"> 389</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a0e2cfb6fb263bd6f761756c816574345">CLDirectConvolutionLayerKernel::configure</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</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_c_l_tensor.xhtml">ICLTensor</a> *biases, <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</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="l00390"></a><span class="lineno"> 390</span> {</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, output);</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span> </div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> = input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>();</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> width_idx = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>);</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> height_idx = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>);</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> channel_idx = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">DataLayoutDimension::CHANNEL</a>);</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span> </div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernel_size = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a8813441b655b97c00139c6a5a6390e97">dimension</a>(width_idx);</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a> = input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>();</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span> </div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="comment">// Get convolved dimensions</span></div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a> = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a5d320d308c16b8ddda3c9d3f60fad79c">misc::shape_calculator::compute_deep_convolution_shape</a>(*input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>);</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> </div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="comment">// Output auto inizialitation if not yet initialized</span></div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="comment">// TODO(COMPMID-2078): input->clone()->set_tensor_shape(output_shape) doesn't work with subtensors for grouped direct convolutions (AlexNet).</span></div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(),</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a>,</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  1,</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>(),</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>());</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> </div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="comment">// Perform validation step</span></div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(validate_arguments(input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(),</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>(),</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  (biases != <span class="keyword">nullptr</span>) ? biases-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>() : <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(),</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>));</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> </div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#aeebcff33f13042b2527755e294f5d53e">_conv_stride_x</a> = std::get<0>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride());</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a862a2fc55a07b4d6a7e4e23cb11ff323">_conv_stride_y</a> = std::get<1>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride());</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  {</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a2e0cdcd6999269beea6b9512ad41f3d4">_border_size</a> = <a class="code" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_left(), 0, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_right(), 0);</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  }</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  {</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a2e0cdcd6999269beea6b9512ad41f3d4">_border_size</a> = <a class="code" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_top(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_right(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_bottom(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_left());</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  }</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  {</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Not supported"</span>);</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  }</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span> </div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1acfeaa60695d4df61d8d4b5c905aa53">_input</a> = input;</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a6fc108ac852099117f9c722f2afe2cb8">_weights</a> = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>;</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a62d192d931002b4866443cd7fc71419b">_output</a> = output;</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a95ba9da2ab49208dfa0d4642c8f7b23b">_biases</a> = biases;</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span> </div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#aa550ff0352ff2388e02f7b0a41bf5fe7">get_target</a>();</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span> </div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  std::stringstream kernel_name;</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  kernel_name << <span class="stringliteral">"direct_convolution"</span> << kernel_size << <span class="stringliteral">"x"</span> << kernel_size;</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  {</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  kernel_name << <span class="stringliteral">"_"</span> << <a class="code" href="namespacearm__compute.xhtml#a0a7bb17a0a0414a7162f635776a02eb5">lower_string</a>(<a class="code" href="namespacearm__compute.xhtml#a56b9e25c2e8731ca5488e7b3ccd66f58">string_from_data_layout</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>));</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  }</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span> </div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml">CLBuildOptions</a> build_options;</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a95b46e69297fad10b27a1baa000f92cc">add_option_if</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a95ba9da2ab49208dfa0d4642c8f7b23b">_biases</a> != <span class="keyword">nullptr</span>, std::string(<span class="stringliteral">"-DHAS_BIAS"</span>));</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> </div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> run_optimized_for_bifrost = can_run_optimized_kernel_for_bifrost(gpu_target, <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#aeebcff33f13042b2527755e294f5d53e">_conv_stride_x</a>, <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a862a2fc55a07b4d6a7e4e23cb11ff323">_conv_stride_y</a>, kernel_size, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>);</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span> </div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <span class="keywordflow">if</span>(run_optimized_for_bifrost)</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  {</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DWEIGHTS_DEPTH="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a6fc108ac852099117f9c722f2afe2cb8">_weights</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(channel_idx))));</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span> </div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  kernel_name << <span class="stringliteral">"_f32_bifrost"</span>;</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  _kernel = static_cast<cl::Kernel>(<a class="code" href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">CLKernelLibrary::get</a>().<a class="code" href="namespacearm__compute.xhtml#abc72c95941485d8a068fa38372308574">create_kernel</a>(kernel_name.str(), build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#ae3b08139a1e57323c5d7dd93f30496c8">options</a>()));</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  }</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  {</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> is_quantized_asymm = <a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>);</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a95b46e69297fad10b27a1baa000f92cc">add_option_if</a>(is_quantized_asymm, std::string(<span class="stringliteral">"-DKERNEL_SIZE="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(kernel_size)));</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DDATA_TYPE="</span> + <a class="code" href="namespacearm__compute.xhtml#a545eeda2eaa3f5a54345ce8169e21184">get_cl_type_from_data_type</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>)));</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DDATA_SIZE="</span> + <a class="code" href="namespacearm__compute.xhtml#ab631f49c436b1f18beff3248c4b1a19e">get_data_size_from_data_type</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>)));</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DWEIGHTS_DEPTH="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a6fc108ac852099117f9c722f2afe2cb8">_weights</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(channel_idx))));</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DSTRIDE_X="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#aeebcff33f13042b2527755e294f5d53e">_conv_stride_x</a>)));</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  {</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> run_optimized_for_bifrost_nhwc = can_run_optimized_kernel_for_bifrost_nhwc(gpu_target, <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#aeebcff33f13042b2527755e294f5d53e">_conv_stride_x</a>, <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a862a2fc55a07b4d6a7e4e23cb11ff323">_conv_stride_y</a>, kernel_size, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>);</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DDATA_LAYOUT_NHWC=1"</span>));</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DDST_HEIGHT="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a62d192d931002b4866443cd7fc71419b">_output</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(height_idx))));</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DDST_WIDTH="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a62d192d931002b4866443cd7fc71419b">_output</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(width_idx))));</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DSRC_HEIGHT="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1acfeaa60695d4df61d8d4b5c905aa53">_input</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(height_idx))));</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DSRC_WIDTH="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1acfeaa60695d4df61d8d4b5c905aa53">_input</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(width_idx))));</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DPAD_LEFT="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_left())));</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DPAD_TOP="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_top())));</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DSTRIDE_Y="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a862a2fc55a07b4d6a7e4e23cb11ff323">_conv_stride_y</a>)));</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <span class="keywordflow">if</span>(run_optimized_for_bifrost_nhwc)</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  {</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_read_per_iteration_x = 4;</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a2e0cdcd6999269beea6b9512ad41f3d4">_border_size</a>.<a class="code" href="structarm__compute_1_1_border_size.xhtml#a78b0fed184c642b78f32fd34b228a5f9">right</a> = num_elems_read_per_iteration_x;</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(<span class="stringliteral">"-DVEC_SIZE="</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(num_elems_read_per_iteration_x));</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  }</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  }</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(std::string(<span class="stringliteral">"-DDATA_TYPE_PROMOTED="</span> + <a class="code" href="namespacearm__compute.xhtml#a545eeda2eaa3f5a54345ce8169e21184">get_cl_type_from_data_type</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>)));</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <span class="comment">// Create kernel</span></div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  _kernel = static_cast<cl::Kernel>(<a class="code" href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">CLKernelLibrary::get</a>().<a class="code" href="namespacearm__compute.xhtml#abc72c95941485d8a068fa38372308574">create_kernel</a>(is_quantized_asymm ? <span class="stringliteral">"direct_convolution_1x1_3x3_5x5_quantized"</span> : kernel_name.str(),</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  build_options.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#ae3b08139a1e57323c5d7dd93f30496c8">options</a>()));</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  }</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span> </div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <span class="comment">// Configure kernel window</span></div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="keyword">auto</span> win_config = <a class="code" href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">validate_and_configure_window</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>(), output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, gpu_target);</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(win_config.first);</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  ICLKernel::configure_internal(win_config.second);</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span> </div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="comment">// Set static kernel arguments</span></div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>))</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  {</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml">UniformQuantizationInfo</a> iqinfo = <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1acfeaa60695d4df61d8d4b5c905aa53">_input</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>().<a class="code" href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">uniform</a>();</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml">UniformQuantizationInfo</a> wqinfo = <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a6fc108ac852099117f9c722f2afe2cb8">_weights</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>().<a class="code" href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">uniform</a>();</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml">UniformQuantizationInfo</a> oqinfo = <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a62d192d931002b4866443cd7fc71419b">_output</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>().<a class="code" href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">uniform</a>();</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span> </div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <span class="keywordtype">int</span> output_multiplier = 0;</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <span class="keywordtype">int</span> output_shift = 0;</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span> </div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="keywordtype">float</span> multiplier = iqinfo.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a> * wqinfo.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a> / oqinfo.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a>;</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <a class="code" href="_error_8h.xhtml#a51e206ee52bcfb358919ee478d9fdc47">ARM_COMPUTE_THROW_ON_ERROR</a>(<a class="code" href="namespacearm__compute_1_1quantization.xhtml#a22032f9cf47deae265eafb65ff55b594">quantization::calculate_quantized_multiplier_less_than_one</a>(multiplier, &output_multiplier, &output_shift));</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span> </div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 3 * <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c9c1e7a7d96743375ca40847f0f12e2">num_arguments_per_3D_tensor</a>() + ((<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a95ba9da2ab49208dfa0d4642c8f7b23b">_biases</a> != <span class="keyword">nullptr</span>) ? <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a43b6c5e4b57069c5f61e96dff24c212d">num_arguments_per_1D_tensor</a>() : 0) + 1;</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  _kernel.setArg(idx++, -iqinfo.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">offset</a>);</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  _kernel.setArg(idx++, -wqinfo.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">offset</a>);</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  _kernel.setArg(idx++, oqinfo.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">offset</a>);</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  _kernel.setArg(idx++, output_multiplier);</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  _kernel.setArg(idx++, output_shift);</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  }</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span> </div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="comment">// Set config_id for enabling LWS tuning</span></div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  _config_id = <span class="stringliteral">"direct_convolution_"</span>;</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  _config_id += <a class="code" href="namespacearm__compute.xhtml#a0a7bb17a0a0414a7162f635776a02eb5">lower_string</a>(<a class="code" href="namespacearm__compute.xhtml#a142b55a483cadf4e1068a1a09a55e8e9">string_from_data_type</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>));</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(kernel_size);</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>().left);</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>().top);</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>().right);</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>().bottom);</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#aeebcff33f13042b2527755e294f5d53e">_conv_stride_x</a>);</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a862a2fc55a07b4d6a7e4e23cb11ff323">_conv_stride_y</a>);</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(width_idx));</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(height_idx));</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  _config_id += <span class="stringliteral">"_"</span>;</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  _config_id += <a class="code" href="namespacearm__compute.xhtml#a0a7bb17a0a0414a7162f635776a02eb5">lower_string</a>(<a class="code" href="namespacearm__compute.xhtml#a56b9e25c2e8731ca5488e7b3ccd66f58">string_from_data_layout</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>));</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span> }</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span> </div><div class="line"><a name="l00544"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1e6b576c45f94ebf95097f045ba55002"> 544</a></span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1e6b576c45f94ebf95097f045ba55002">CLDirectConvolutionLayerKernel::validate</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, <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="l00545"></a><span class="lineno"> 545</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> target)</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span> {</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(validate_arguments(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>));</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">validate_and_configure_window</a>(input-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>().get(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->clone().get(), output-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>().get(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, target).first);</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span> </div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span> }</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span> </div><div class="line"><a name="l00553"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e"> 553</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDirectConvolutionLayerKernel::run</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &window, cl::CommandQueue &queue)</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span> {</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <a class="code" href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a>(<span class="keyword">this</span>);</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  <a class="code" href="_validate_8h.xhtml#a6eb9ce82815fe429250189da7592ba75">ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW</a>(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">IKernel::window</a>(), <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span> </div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <span class="comment">// Get initial windows</span></div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a> = <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>.<a class="code" href="classarm__compute_1_1_window.xhtml#a30ca5bdbb60ee281d7f1ab34f7a4ee40">first_slice_window_3D</a>();</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> win_in = <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>;</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span> </div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  win_in.<a class="code" href="classarm__compute_1_1_window.xhtml#a69496c7cb46a4101813d7456a6bd097b">adjust</a>(<a class="code" href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">Window::DimX</a>, -<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a2e0cdcd6999269beea6b9512ad41f3d4">_border_size</a>.<a class="code" href="structarm__compute_1_1_border_size.xhtml#a05374b750b0fc472c34ee61e6f028bba">left</a>, <span class="keyword">true</span>);</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  win_in.<a class="code" href="classarm__compute_1_1_window.xhtml#a69496c7cb46a4101813d7456a6bd097b">adjust</a>(<a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>, -<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a2e0cdcd6999269beea6b9512ad41f3d4">_border_size</a>.<a class="code" href="structarm__compute_1_1_border_size.xhtml#a3fdd42ea34070a54e696b3adc28c4be3">top</a>, <span class="keyword">true</span>);</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span> </div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> = <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1acfeaa60695d4df61d8d4b5c905aa53">_input</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>();</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> width_idx = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>);</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> height_idx = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>);</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span> </div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  win_in.<a class="code" href="classarm__compute_1_1_window.xhtml#a55ed4ad2395fd25ba847cbf6c54b85e4">set_dimension_step</a>(width_idx, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>[width_idx].<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a75b73e17c4ebe901e44af3b2b9846ab3">step</a>() * <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#aeebcff33f13042b2527755e294f5d53e">_conv_stride_x</a>);</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  win_in.<a class="code" href="classarm__compute_1_1_window.xhtml#a55ed4ad2395fd25ba847cbf6c54b85e4">set_dimension_step</a>(height_idx, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>[height_idx].<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a75b73e17c4ebe901e44af3b2b9846ab3">step</a>() * <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a862a2fc55a07b4d6a7e4e23cb11ff323">_conv_stride_y</a>);</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span> </div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> slice_in = win_in.<a class="code" href="classarm__compute_1_1_window.xhtml#a30ca5bdbb60ee281d7f1ab34f7a4ee40">first_slice_window_3D</a>();</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx1 = 2 * <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c9c1e7a7d96743375ca40847f0f12e2">num_arguments_per_3D_tensor</a>();</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a28f5847162f352444c6ac1825d0e99c7">add_3D_tensor_argument</a>(idx1, <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a6fc108ac852099117f9c722f2afe2cb8">_weights</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a>);</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span> </div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="keywordflow">if</span>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a95ba9da2ab49208dfa0d4642c8f7b23b">_biases</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  {</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> slice_biases;</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  slice_biases.<a class="code" href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">use_tensor_dimensions</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a95ba9da2ab49208dfa0d4642c8f7b23b">_biases</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>());</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a479e7043e65dc87de35d374e108510f7">add_1D_tensor_argument</a>(idx1, <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a95ba9da2ab49208dfa0d4642c8f7b23b">_biases</a>, slice_biases);</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  }</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span> </div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  _kernel.setArg(idx1++, static_cast<unsigned int>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a6fc108ac852099117f9c722f2afe2cb8">_weights</a>-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a6b14f175bf5281f57b561e2d4e4b1f1f">strides_in_bytes</a>()[3]));</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span> </div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  <span class="keywordflow">do</span></div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  {</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0;</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a28f5847162f352444c6ac1825d0e99c7">add_3D_tensor_argument</a>(idx, <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1acfeaa60695d4df61d8d4b5c905aa53">_input</a>, slice_in);</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a28f5847162f352444c6ac1825d0e99c7">add_3D_tensor_argument</a>(idx, <a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a62d192d931002b4866443cd7fc71419b">_output</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a>);</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  <a class="code" href="namespacearm__compute.xhtml#a6e51ab3789678d3e0b0b72178dd6c4c6">enqueue</a>(queue, *<span class="keyword">this</span>, <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a>, <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">lws_hint</a>());</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  }</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="keywordflow">while</span>(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>.<a class="code" href="classarm__compute_1_1_window.xhtml#aac792e3a11bc73bafafc4f4284c7f215">slide_window_slice_3D</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a>) && win_in.<a class="code" href="classarm__compute_1_1_window.xhtml#aac792e3a11bc73bafafc4f4284c7f215">slide_window_slice_3D</a>(slice_in));</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span> }</div><div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a43b6c5e4b57069c5f61e96dff24c212d"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a43b6c5e4b57069c5f61e96dff24c212d">arm_compute::ICLKernel::num_arguments_per_1D_tensor</a></div><div class="ttdeci">static constexpr unsigned int num_arguments_per_1D_tensor()</div><div class="ttdoc">Returns the number of arguments enqueued per 1D tensor object.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00184">ICLKernel.h:184</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00261">Error.h:261</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_border_size_xhtml_a3fdd42ea34070a54e696b3adc28c4be3"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml#a3fdd42ea34070a54e696b3adc28c4be3">arm_compute::BorderSize::top</a></div><div class="ttdeci">unsigned int top</div><div class="ttdoc">top of the border</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00339">Types.h:339</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a1f4e725b8e1ea36b30e09dc08ae6961d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">arm_compute::ITensorInfo::num_dimensions</a></div><div class="ttdeci">virtual size_t num_dimensions() const =0</div><div class="ttdoc">The number of dimensions of the tensor (rank)</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1quantization_xhtml_a22032f9cf47deae265eafb65ff55b594"><div class="ttname"><a href="namespacearm__compute_1_1quantization.xhtml#a22032f9cf47deae265eafb65ff55b594">arm_compute::quantization::calculate_quantized_multiplier_less_than_one</a></div><div class="ttdeci">arm_compute::Status calculate_quantized_multiplier_less_than_one(float multiplier, int *quant_multiplier, int *right_shift)</div><div class="ttdoc">Calculate quantized representation of multiplier with value less than one.</div><div class="ttdef"><b>Definition:</b> <a href="_asymm_helpers_8cpp_source.xhtml#l00035">AsymmHelpers.cpp:35</a></div></div> |
| <div class="ttc" id="_c_l_validate_8h_xhtml_ab82bd5de18ef067ae5d9ba4af8065dd6"><div class="ttname"><a href="_c_l_validate_8h.xhtml#ab82bd5de18ef067ae5d9ba4af8065dd6">ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(tensor)</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_validate_8h_source.xhtml#l00034">CLValidate.h:34</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_ad34a46f53686c12a5c5e717cc9617fb6"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window & window() const</div><div class="ttdoc">The maximum window the kernel can be executed on.</div><div class="ttdef"><b>Definition:</b> <a href="_i_kernel_8cpp_source.xhtml#l00028">IKernel.cpp:28</a></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="namespacearm__compute_1_1test_1_1validation_xhtml_acf5f12bbab64dd614bd8220c97fe484f"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">arm_compute::test::validation::data_layout</a></div><div class="ttdeci">const DataLayout data_layout</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00146">Im2Col.cpp:146</a></div></div> |
| <div class="ttc" id="_toolchain_support_8h_xhtml"><div class="ttname"><a href="_toolchain_support_8h.xhtml">ToolchainSupport.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">arm_compute::GPUTarget::G76</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a6fc108ac852099117f9c722f2afe2cb8"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a6fc108ac852099117f9c722f2afe2cb8">arm_compute::CLDirectConvolutionLayerKernel::_weights</a></div><div class="ttdeci">const ICLTensor * _weights</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8h_source.xhtml#l00095">CLDirectConvolutionLayerKernel.h:95</a></div></div> |
| <div class="ttc" id="_i_tensor_8h_xhtml"><div class="ttname"><a href="_i_tensor_8h.xhtml">ITensor.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_ad45f0c01a0713dfb6bd7232c7f396fc4"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">arm_compute::CLTensor::info</a></div><div class="ttdeci">TensorInfo * info() const override</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00035">CLTensor.cpp:35</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension.</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#l00259">Types.h:259</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a6e51ab3789678d3e0b0b72178dd6c4c6"><div class="ttname"><a href="namespacearm__compute.xhtml#a6e51ab3789678d3e0b0b72178dd6c4c6">arm_compute::enqueue</a></div><div class="ttdeci">void enqueue(cl::CommandQueue &queue, ICLKernel &kernel, const Window &window, const cl::NDRange &lws_hint=CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items=false)</div><div class="ttdoc">Add the kernel to the command queue with the given window.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8cpp_source.xhtml#l00039">ICLKernel.cpp:39</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_build_options_xhtml_ae3b08139a1e57323c5d7dd93f30496c8"><div class="ttname"><a href="classarm__compute_1_1_c_l_build_options.xhtml#ae3b08139a1e57323c5d7dd93f30496c8">arm_compute::CLBuildOptions::options</a></div><div class="ttdeci">const StringSet & options() const</div><div class="ttdoc">Gets the current options list set.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l00074">CLKernelLibrary.cpp:74</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a8f3ff7da485ff7e75dab07baadf5b4bd"><div class="ttname"><a href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00545">Validate.h:545</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_a5d320d308c16b8ddda3c9d3f60fad79c"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a5d320d308c16b8ddda3c9d3f60fad79c">arm_compute::misc::shape_calculator::compute_deep_convolution_shape</a></div><div class="ttdeci">TensorShape compute_deep_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, PadStrideInfo conv_info)</div><div class="ttdoc">Calculate the deep convolution shape output shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l00702">ShapeCalculator.h:702</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad6630777dc2d315531f1e0b02491051f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">arm_compute::validate_and_configure_window</a></div><div class="ttdeci">std::pair< Status, Window > validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_native_kernel_8cpp_source.xhtml#l00221">NEDepthwiseConvolutionLayerNativeKernel.cpp:221</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_ab9f813c25ed75ea7b7ac2fa3926a8f55"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">arm_compute::ICLKernel::lws_hint</a></div><div class="ttdeci">cl::NDRange lws_hint() const</div><div class="ttdoc">Return the Local-Workgroup-Size hint.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00247">ICLKernel.h:247</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#l00599">Winograd.cpp:599</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a8a1e1c105f0bdaf37db408c7cfcb77a4"><div class="ttname"><a href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ON_ERROR(status)</div><div class="ttdoc">Checks if a status contains an error and returns it.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00193">Error.h:193</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1support_1_1cpp11_xhtml_acc5dddee1cbe93a4eaf0a9f74ee96bb7"><div class="ttname"><a href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">arm_compute::support::cpp11::to_string</a></div><div class="ttdeci">std::string to_string(T &&value)</div><div class="ttdoc">Convert integer and float values to string.</div><div class="ttdef"><b>Definition:</b> <a href="_toolchain_support_8h_source.xhtml#l00242">ToolchainSupport.h:242</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a8813441b655b97c00139c6a5a6390e97"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a8813441b655b97c00139c6a5a6390e97">arm_compute::TensorInfo::dimension</a></div><div class="ttdeci">size_t dimension(size_t index) const override</div><div class="ttdoc">Return the size of the requested dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00223">TensorInfo.h:223</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">arm_compute::GPUTarget::G52LIT</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor.</div></div> |
| <div class="ttc" id="_validate_8h_xhtml_ae7eed178dac535c6e727061b1f5bc6eb"><div class="ttname"><a href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00791">Validate.h:791</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">arm_compute::GPUTarget::G71</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">arm_compute::DataLayoutDimension::HEIGHT</a></div><div class="ttdoc">height</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a62d192d931002b4866443cd7fc71419b"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a62d192d931002b4866443cd7fc71419b">arm_compute::CLDirectConvolutionLayerKernel::_output</a></div><div class="ttdeci">ICLTensor * _output</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8h_source.xhtml#l00096">CLDirectConvolutionLayerKernel.h:96</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_kernel_library_xhtml_acba005f5ce2c62cbf3f94d074d9007aa"><div class="ttname"><a href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">arm_compute::CLKernelLibrary::get</a></div><div class="ttdeci">static CLKernelLibrary & get()</div><div class="ttdoc">Access the KernelLibrary singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l01037">CLKernelLibrary.cpp:1037</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="_error_8h_xhtml_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00327">Error.h:327</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_uniform_quantization_info_xhtml"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml">arm_compute::UniformQuantizationInfo</a></div><div class="ttdoc">Quantization info when assuming per layer quantization.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00039">QuantizationInfo.h:39</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_uniform_quantization_info_xhtml_a1d28dec57cce925ad92342891bd71e7c"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">arm_compute::UniformQuantizationInfo::scale</a></div><div class="ttdeci">float scale</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00061">QuantizationInfo.h:61</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="_error_8h_xhtml_a046fbca6a9505ce038bc02830c739fed"><div class="ttname"><a href="_error_8h.xhtml#a046fbca6a9505ce038bc02830c739fed">ARM_COMPUTE_CREATE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_CREATE_ERROR(error_code,...)</div><div class="ttdoc">Creates an error with a given message.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00167">Error.h:167</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">arm_compute::GPUTarget::G51LIT</a></div></div> |
| <div class="ttc" id="core_2_c_l_2_c_l_helpers_8h_xhtml"><div class="ttname"><a href="core_2_c_l_2_c_l_helpers_8h.xhtml">CLHelpers.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a0a7bb17a0a0414a7162f635776a02eb5"><div class="ttname"><a href="namespacearm__compute.xhtml#a0a7bb17a0a0414a7162f635776a02eb5">arm_compute::lower_string</a></div><div class="ttdeci">std::string lower_string(const std::string &val)</div><div class="ttdoc">Lower a given string.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_utils_8cpp_source.xhtml#l00327">Utils.cpp:327</a></div></div> |
| <div class="ttc" id="_c_l_direct_convolution_layer_kernel_8h_xhtml"><div class="ttname"><a href="_c_l_direct_convolution_layer_kernel_8h.xhtml">CLDirectConvolutionLayerKernel.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab7980fa5ee693e3282a76da047a1c3b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab7980fa5ee693e3282a76da047a1c3b5">arm_compute::calculate_max_window</a></div><div class="ttdeci">Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps=Steps(), bool skip_border=false, BorderSize border_size=BorderSize())</div><div class="ttdoc">Calculate the maximum window for a given tensor shape and border setting.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_helpers_8cpp_source.xhtml#l00028">Helpers.cpp:28</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a1e6b576c45f94ebf95097f045ba55002"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1e6b576c45f94ebf95097f045ba55002">arm_compute::CLDirectConvolutionLayerKernel::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, const GPUTarget target)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLDirectConvolutionLayer...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8cpp_source.xhtml#l00544">CLDirectConvolutionLayerKernel.cpp:544</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a28f5847162f352444c6ac1825d0e99c7"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a28f5847162f352444c6ac1825d0e99c7">arm_compute::ICLKernel::add_3D_tensor_argument</a></div><div class="ttdeci">void add_3D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)</div><div class="ttdoc">Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00158">ICLKernel.h:158</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml_a14470b4cb59140a1b6ff3b8f16c89ab6"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">arm_compute::Window::use_tensor_dimensions</a></div><div class="ttdeci">void use_tensor_dimensions(const TensorShape &shape, size_t first_dimension=Window::DimX)</div><div class="ttdoc">Use the tensor's dimensions to fill the window dimensions.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8inl_source.xhtml#l00250">Window.inl:250</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) 2017-2018 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_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00201">Helpers.inl:201</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1_access_window_static_xhtml"><div class="ttname"><a href="classarm__compute_1_1_access_window_static.xhtml">arm_compute::AccessWindowStatic</a></div><div class="ttdoc">Implementation of a static rectangular access pattern.</div><div class="ttdef"><b>Definition:</b> <a href="_access_window_static_8h_source.xhtml#l00046">AccessWindowStatic.h:46</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a75b73e17c4ebe901e44af3b2b9846ab3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a75b73e17c4ebe901e44af3b2b9846ab3">arm_compute::test::validation::step</a></div><div class="ttdeci">const int step</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_select_8cpp_source.xhtml#l00172">Select.cpp:172</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 S32 per channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_build_options_xhtml_a3e2b80ff5463b7d2017de847f5c32a30"><div class="ttname"><a href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">arm_compute::CLBuildOptions::add_option</a></div><div class="ttdeci">void add_option(std::string option)</div><div class="ttdoc">Adds option to the existing build option list.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l00043">CLKernelLibrary.cpp:43</a></div></div> |
| <div class="ttc" id="arm__compute_2core_2_utils_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_utils_8h.xhtml">Utils.h</a></div></div> |
| <div class="ttc" id="_c_l_validate_8h_xhtml"><div class="ttname"><a href="_c_l_validate_8h.xhtml">CLValidate.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_access_window_rectangle_xhtml"><div class="ttname"><a href="classarm__compute_1_1_access_window_rectangle.xhtml">arm_compute::AccessWindowRectangle</a></div><div class="ttdoc">Implementation of a rectangular access pattern.</div><div class="ttdef"><b>Definition:</b> <a href="_i_access_window_8h_source.xhtml#l00107">IAccessWindow.h:107</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a142b55a483cadf4e1068a1a09a55e8e9"><div class="ttname"><a href="namespacearm__compute.xhtml#a142b55a483cadf4e1068a1a09a55e8e9">arm_compute::string_from_data_type</a></div><div class="ttdeci">const std::string & string_from_data_type(DataType dt)</div><div class="ttdoc">Convert a data type identity into a string.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_utils_8cpp_source.xhtml#l00144">Utils.cpp:144</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab631f49c436b1f18beff3248c4b1a19e"><div class="ttname"><a href="namespacearm__compute.xhtml#ab631f49c436b1f18beff3248c4b1a19e">arm_compute::get_data_size_from_data_type</a></div><div class="ttdeci">std::string get_data_size_from_data_type(const DataType &dt)</div><div class="ttdoc">Get the size of a data type in number of bits.</div><div class="ttdef"><b>Definition:</b> <a href="core_2_c_l_2_c_l_helpers_8cpp_source.xhtml#l00099">CLHelpers.cpp:99</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml_aa96e81276ee4f87ab386cd05a5539a7d"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">arm_compute::Window::DimX</a></div><div class="ttdeci">static constexpr size_t DimX</div><div class="ttdoc">Alias for dimension 0 also known as X dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00043">Window.h:43</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_afc4bd8e872567d9c4c57d89eb0bb3da1"><div class="ttname"><a href="namespacearm__compute.xhtml#afc4bd8e872567d9c4c57d89eb0bb3da1">arm_compute::update_window_and_padding</a></div><div class="ttdeci">bool update_window_and_padding(Window &win, Ts &&... patterns)</div><div class="ttdoc">Update window and padding size for each of the access patterns.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00402">Helpers.h:402</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a6c9c1e7a7d96743375ca40847f0f12e2"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c9c1e7a7d96743375ca40847f0f12e2">arm_compute::ICLKernel::num_arguments_per_3D_tensor</a></div><div class="ttdeci">static constexpr unsigned int num_arguments_per_3D_tensor()</div><div class="ttdoc">Returns the number of arguments enqueued per 3D tensor object.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00200">ICLKernel.h:200</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape & tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab237a0a375cf382d52b61653248d3d4a"><div class="ttname"><a href="namespacearm__compute.xhtml#ab237a0a375cf382d52b61653248d3d4a">arm_compute::ceil_to_multiple</a></div><div class="ttdeci">auto ceil_to_multiple(S value, T divisor) -> decltype(((value+divisor - 1)/divisor) *divisor)</div><div class="ttdoc">Computes the smallest number larger or equal to value that is a multiple of divisor.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00066">Utils.h:66</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a1da797d2762c1cdbb73bfc83136c3a38"><div class="ttname"><a href="_validate_8h.xhtml#a1da797d2762c1cdbb73bfc83136c3a38">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00288">Validate.h:288</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div><div class="ttdoc">quantized, asymmetric fixed-point 8-bit number</div></div> |
| <div class="ttc" id="classarm__compute_1_1_steps_xhtml"><div class="ttname"><a href="classarm__compute_1_1_steps.xhtml">arm_compute::Steps</a></div><div class="ttdoc">Class to describe a number of elements in each dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_steps_8h_source.xhtml#l00040">Steps.h:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a493987e85723a8000eb26d1f00e2ad0e"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">arm_compute::CLDirectConvolutionLayerKernel::run</a></div><div class="ttdeci">void run(const Window &window, cl::CommandQueue &queue) override</div><div class="ttdoc">Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8cpp_source.xhtml#l00553">CLDirectConvolutionLayerKernel.cpp:553</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7fc93f37dac131a1a40b7921f9df3a9a"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">arm_compute::test::validation::output_shape</a></div><div class="ttdeci">output_shape</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item.</div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a86084036bd3851575ef871ad5bf079a7"><div class="ttname"><a href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MSG(cond,...)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00214">Error.h:214</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_aa550ff0352ff2388e02f7b0a41bf5fe7"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#aa550ff0352ff2388e02f7b0a41bf5fe7">arm_compute::ICLKernel::get_target</a></div><div class="ttdeci">GPUTarget get_target() const</div><div class="ttdoc">Get the targeted GPU architecture.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00286">ICLKernel.h:286</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_quantization_info_xhtml_a706fc156bcd4c45441bcaad05884b57d"><div class="ttname"><a href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">arm_compute::QuantizationInfo::uniform</a></div><div class="ttdeci">UniformQuantizationInfo uniform() const</div><div class="ttdoc">Return per layer quantization info.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00134">QuantizationInfo.h:134</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a545eeda2eaa3f5a54345ce8169e21184"><div class="ttname"><a href="namespacearm__compute.xhtml#a545eeda2eaa3f5a54345ce8169e21184">arm_compute::get_cl_type_from_data_type</a></div><div class="ttdeci">std::string get_cl_type_from_data_type(const DataType &dt)</div><div class="ttdoc">Translates a tensor data type to the appropriate OpenCL type.</div><div class="ttdef"><b>Definition:</b> <a href="core_2_c_l_2_c_l_helpers_8cpp_source.xhtml#l00035">CLHelpers.cpp:35</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a2e0cdcd6999269beea6b9512ad41f3d4"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a2e0cdcd6999269beea6b9512ad41f3d4">arm_compute::CLDirectConvolutionLayerKernel::_border_size</a></div><div class="ttdeci">BorderSize _border_size</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8h_source.xhtml#l00097">CLDirectConvolutionLayerKernel.h:97</a></div></div> |
| <div class="ttc" id="_shape_calculator_8h_xhtml"><div class="ttname"><a href="_shape_calculator_8h.xhtml">ShapeCalculator.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a862a2fc55a07b4d6a7e4e23cb11ff323"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a862a2fc55a07b4d6a7e4e23cb11ff323">arm_compute::CLDirectConvolutionLayerKernel::_conv_stride_y</a></div><div class="ttdeci">int _conv_stride_y</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8h_source.xhtml#l00099">CLDirectConvolutionLayerKernel.h:99</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1misc_1_1_i_cloneable_xhtml_a4d10e5012a872e7f78f2b539b673049d"><div class="ttname"><a href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">arm_compute::misc::ICloneable::clone</a></div><div class="ttdeci">virtual std::unique_ptr< T > clone() const =0</div><div class="ttdoc">Provide a clone of the current object of class T.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_build_options_xhtml_a95b46e69297fad10b27a1baa000f92cc"><div class="ttname"><a href="classarm__compute_1_1_c_l_build_options.xhtml#a95b46e69297fad10b27a1baa000f92cc">arm_compute::CLBuildOptions::add_option_if</a></div><div class="ttdeci">void add_option_if(bool cond, std::string option)</div><div class="ttdoc">Adds option if a given condition is true;.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l00048">CLKernelLibrary.cpp:48</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">arm_compute::GPUTarget::G72</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#l00676">Types.h:676</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_aa459796b5489eca8a9160cb5dcf1a103"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#aa459796b5489eca8a9160cb5dcf1a103">arm_compute::ITensorInfo::element_size</a></div><div class="ttdeci">virtual size_t element_size() const =0</div><div class="ttdoc">Element size in bytes calculated as data_size() * num_channels()</div></div> |
| <div class="ttc" id="_error_8h_xhtml"><div class="ttname"><a href="_error_8h.xhtml">Error.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_build_options_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_build_options.xhtml">arm_compute::CLBuildOptions</a></div><div class="ttdoc">Build options.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8h_source.xhtml#l00037">CLKernelLibrary.h:37</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">arm_compute::DataLayoutDimension::CHANNEL</a></div><div class="ttdoc">channel</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_abc72c95941485d8a068fa38372308574"><div class="ttname"><a href="namespacearm__compute.xhtml#abc72c95941485d8a068fa38372308574">arm_compute::create_kernel</a></div><div class="ttdeci">std::unique_ptr< Kernel > create_kernel()</div><div class="ttdoc">Helper function to create and return a unique_ptr pointed to a CL/GLES kernel object.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00086">Helpers.h:86</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_border_size_xhtml_a05374b750b0fc472c34ee61e6f028bba"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml#a05374b750b0fc472c34ee61e6f028bba">arm_compute::BorderSize::left</a></div><div class="ttdeci">unsigned int left</div><div class="ttdoc">left of the border</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00342">Types.h:342</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml_aac792e3a11bc73bafafc4f4284c7f215"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#aac792e3a11bc73bafafc4f4284c7f215">arm_compute::Window::slide_window_slice_3D</a></div><div class="ttdeci">bool slide_window_slice_3D(Window &slice) const</div><div class="ttdoc">Slide the passed 3D window slice.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00319">Window.h:319</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a59e56af19e754a6aa26a612ebf91d05fa62be47fdd89da032cf78dfce82239579"><div class="ttname"><a href="namespacearm__compute.xhtml#a59e56af19e754a6aa26a612ebf91d05fa62be47fdd89da032cf78dfce82239579">arm_compute::ErrorCode::RUNTIME_ERROR</a></div><div class="ttdoc">Generic runtime error.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a3f3e1a3200223e6a304a533b1016e749"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">arm_compute::ITensorInfo::quantization_info</a></div><div class="ttdeci">virtual QuantizationInfo quantization_info() const =0</div><div class="ttdoc">Get the quantization settings (scale and offset) of the tensor.</div></div> |
| <div class="ttc" id="structarm__compute_1_1_border_size_xhtml_a78b0fed184c642b78f32fd34b228a5f9"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml#a78b0fed184c642b78f32fd34b228a5f9">arm_compute::BorderSize::right</a></div><div class="ttdeci">unsigned int right</div><div class="ttdoc">right of the border</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00340">Types.h:340</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="namespacearm__compute_xhtml_a14f46283f316e7f0fad301d5c1507e9f"><div class="ttname"><a href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">arm_compute::is_data_type_quantized_asymmetric</a></div><div class="ttdeci">bool is_data_type_quantized_asymmetric(DataType dt)</div><div class="ttdoc">Check if a given data type is of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01030">Utils.h:1030</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a1acfeaa60695d4df61d8d4b5c905aa53"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a1acfeaa60695d4df61d8d4b5c905aa53">arm_compute::CLDirectConvolutionLayerKernel::_input</a></div><div class="ttdeci">const ICLTensor * _input</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8h_source.xhtml#l00093">CLDirectConvolutionLayerKernel.h:93</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_aeebcff33f13042b2527755e294f5d53e"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#aeebcff33f13042b2527755e294f5d53e">arm_compute::CLDirectConvolutionLayerKernel::_conv_stride_x</a></div><div class="ttdeci">int _conv_stride_x</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8h_source.xhtml#l00098">CLDirectConvolutionLayerKernel.h:98</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a423f9a45a52983b4de5e2b347f4369c7"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">arm_compute::CLDirectConvolutionLayerKernel::border_size</a></div><div class="ttdeci">BorderSize border_size() const override</div><div class="ttdoc">The size of the border for that kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8cpp_source.xhtml#l00384">CLDirectConvolutionLayerKernel.cpp:384</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml_ad2d402364fa822b0b7775081291eeca9"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">arm_compute::Window::DimY</a></div><div class="ttdeci">static constexpr size_t DimY</div><div class="ttdoc">Alias for dimension 1 also known as Y dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00045">Window.h:45</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml_a55ed4ad2395fd25ba847cbf6c54b85e4"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a55ed4ad2395fd25ba847cbf6c54b85e4">arm_compute::Window::set_dimension_step</a></div><div class="ttdeci">void set_dimension_step(size_t dimension, int step)</div><div class="ttdoc">Set the step of a given dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8inl_source.xhtml#l00153">Window.inl:153</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a921b705e9e3e0fe928928447869e62a5"><div class="ttname"><a href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00161">Validate.h:161</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a8c384e82445ca3f6f481f04295bcf3a9"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a8c384e82445ca3f6f481f04295bcf3a9">arm_compute::CLDirectConvolutionLayerKernel::CLDirectConvolutionLayerKernel</a></div><div class="ttdeci">CLDirectConvolutionLayerKernel()</div><div class="ttdoc">Default constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8cpp_source.xhtml#l00379">CLDirectConvolutionLayerKernel.cpp:379</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_tensor.xhtml">arm_compute::ICLTensor</a></div><div class="ttdoc">Interface for OpenCL tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_tensor_8h_source.xhtml#l00042">ICLTensor.h:42</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a56b9e25c2e8731ca5488e7b3ccd66f58"><div class="ttname"><a href="namespacearm__compute.xhtml#a56b9e25c2e8731ca5488e7b3ccd66f58">arm_compute::string_from_data_layout</a></div><div class="ttdeci">const std::string & string_from_data_layout(DataLayout dl)</div><div class="ttdoc">Convert a data layout identity into a string.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_utils_8cpp_source.xhtml#l00132">Utils.cpp:132</a></div></div> |
| <div class="ttc" id="_i_c_l_tensor_8h_xhtml"><div class="ttname"><a href="_i_c_l_tensor_8h.xhtml">ICLTensor.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a18064e0011c3869d884653e9e7c47b66"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">arm_compute::ITensorInfo::total_size</a></div><div class="ttdeci">virtual size_t total_size() const =0</div><div class="ttdoc">Returns the total size of the tensor in bytes.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">arm_compute::GPUTarget</a></div><div class="ttdeci">GPUTarget</div><div class="ttdoc">Available GPU Targets.</div><div class="ttdef"><b>Definition:</b> <a href="_g_p_u_target_8h_source.xhtml#l00034">GPUTarget.h:34</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a95ba9da2ab49208dfa0d4642c8f7b23b"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a95ba9da2ab49208dfa0d4642c8f7b23b">arm_compute::CLDirectConvolutionLayerKernel::_biases</a></div><div class="ttdeci">const ICLTensor * _biases</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8h_source.xhtml#l00094">CLDirectConvolutionLayerKernel.h:94</a></div></div> |
| <div class="ttc" id="_c_l_kernel_library_8h_xhtml"><div class="ttname"><a href="_c_l_kernel_library_8h.xhtml">CLKernelLibrary.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::DataLayout::NHWC</a></div><div class="ttdoc">Num samples, height, width, channels.</div></div> |
| <div class="ttc" id="structarm__compute_1_1_uniform_quantization_info_xhtml_a97bd6c077f3c7769f575b82988b9b668"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">arm_compute::UniformQuantizationInfo::offset</a></div><div class="ttdeci">int32_t offset</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00062">QuantizationInfo.h:62</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="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">ConvolutionLayer.cpp:180</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::DataLayoutDimension::WIDTH</a></div><div class="ttdoc">width</div></div> |
| <div class="ttc" id="arm__compute_2core_2_helpers_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_helpers_8h.xhtml">Helpers.h</a></div></div> |
| <div class="ttc" id="_access_window_static_8h_xhtml"><div class="ttname"><a href="_access_window_static_8h.xhtml">AccessWindowStatic.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">arm_compute::GPUTarget::G51BIG</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a6b14f175bf5281f57b561e2d4e4b1f1f"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a6b14f175bf5281f57b561e2d4e4b1f1f">arm_compute::ITensorInfo::strides_in_bytes</a></div><div class="ttdeci">virtual const Strides & strides_in_bytes() const =0</div><div class="ttdoc">The strides in bytes for accessing each dimension of the tensor.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5f5b6c4337eac9e2e0046ca2304d80dc"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">arm_compute::test::validation::data_type</a></div><div class="ttdeci">data_type</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_arithmetic_addition_8cpp_source.xhtml#l00135">ArithmeticAddition.cpp:135</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_valid_region_xhtml"><div class="ttname"><a href="structarm__compute_1_1_valid_region.xhtml">arm_compute::ValidRegion</a></div><div class="ttdoc">Container for valid region of a window.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00174">Types.h:174</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a46e938020a3ac8c926d0590b7fe957db"><div class="ttname"><a href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">arm_compute::get_data_layout_dimension_index</a></div><div class="ttdeci">size_t get_data_layout_dimension_index(const DataLayout data_layout, const DataLayoutDimension data_layout_dimension)</div><div class="ttdoc">Get the index of the given dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00326">Helpers.inl:326</a></div></div> |
| <div class="ttc" id="_asymm_helpers_8h_xhtml"><div class="ttname"><a href="_asymm_helpers_8h.xhtml">AsymmHelpers.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml_a69496c7cb46a4101813d7456a6bd097b"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a69496c7cb46a4101813d7456a6bd097b">arm_compute::Window::adjust</a></div><div class="ttdeci">void adjust(size_t dimension, int adjust_value, bool is_at_start)</div><div class="ttdoc">Adjust the start or end of a given dimension by the given value.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8inl_source.xhtml#l00126">Window.inl:126</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a51e206ee52bcfb358919ee478d9fdc47"><div class="ttname"><a href="_error_8h.xhtml#a51e206ee52bcfb358919ee478d9fdc47">ARM_COMPUTE_THROW_ON_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_THROW_ON_ERROR(error)</div><div class="ttdoc">Checks if an error value is valid if not throws an exception with the error.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00206">Error.h:206</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a479e7043e65dc87de35d374e108510f7"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a479e7043e65dc87de35d374e108510f7">arm_compute::ICLKernel::add_1D_tensor_argument</a></div><div class="ttdeci">void add_1D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)</div><div class="ttdoc">Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00110">ICLKernel.h:110</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml_a30ca5bdbb60ee281d7f1ab34f7a4ee40"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a30ca5bdbb60ee281d7f1ab34f7a4ee40">arm_compute::Window::first_slice_window_3D</a></div><div class="ttdeci">Window first_slice_window_3D() const</div><div class="ttdoc">First 3D slice of the window.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00275">Window.h:275</a></div></div> |
| <div class="ttc" id="arm__compute_2core_2_types_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_types_8h.xhtml">Types.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#l00074">Types.h:74</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a6eb9ce82815fe429250189da7592ba75"><div class="ttname"><a href="_validate_8h.xhtml#a6eb9ce82815fe429250189da7592ba75">ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00205">Validate.h:205</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">[DataLayout enum definition]</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00114">Types.h:114</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml">arm_compute::Window</a></div><div class="ttdoc">Describe a multidimensional execution window.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00039">Window.h:39</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a1b35b0d258183cf9ef36adf684d0b88c"><div class="ttname"><a href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00940">Validate.h:940</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">arm_compute::GPUTarget::G52</a></div></div> |
| <div class="ttc" id="_i_access_window_8h_xhtml"><div class="ttname"><a href="_i_access_window_8h.xhtml">IAccessWindow.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a1da498e9b2c2d24883087f62c6bbe75d"><div class="ttname"><a href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">arm_compute::gpu_target_is_in</a></div><div class="ttdeci">bool gpu_target_is_in(GPUTarget target_to_check, GPUTarget target, Args... targets)</div><div class="ttdoc">Helper function to check whether a gpu target is equal to the provided targets.</div><div class="ttdef"><b>Definition:</b> <a href="_g_p_u_target_8h_source.xhtml#l00096">GPUTarget.h:96</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a548131b3d37da47a2e9d32111c88dfe1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">arm_compute::test::validation::reference::slice</a></div><div class="ttdeci">SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)</div><div class="ttdef"><b>Definition:</b> <a href="_slice_operations_8cpp_source.xhtml#l00038">SliceOperations.cpp:38</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a367b5090ab432bc7de2c32369e087ab1"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">arm_compute::ITensorInfo::data_layout</a></div><div class="ttdeci">virtual DataLayout data_layout() const =0</div><div class="ttdoc">Get the data layout of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_kernel_xhtml_a0e2cfb6fb263bd6f761756c816574345"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a0e2cfb6fb263bd6f761756c816574345">arm_compute::CLDirectConvolutionLayerKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info)</div><div class="ttdoc">Set the input, weights, biases and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_kernel_8cpp_source.xhtml#l00389">CLDirectConvolutionLayerKernel.cpp:389</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">arm_compute::GPUTarget::G51</a></div></div> |
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