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117 <div class="title">ConvolutionLayer.cpp</div> </div>
119 <div class="contents">
120 <a href="benchmark_2_n_e_o_n_2_convolution_layer_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) 2017-2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include "<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</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="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include "<a class="code" href="_n_e_convolution_layer_8h.xhtml">arm_compute/runtime/NEON/functions/NEConvolutionLayer.h</a>"</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_n_e_winograd_layer_8h.xhtml">arm_compute/runtime/NEON/functions/NEWinogradLayer.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="runtime_2_tensor_8h.xhtml">arm_compute/runtime/Tensor.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="_tensor_allocator_8h.xhtml">arm_compute/runtime/TensorAllocator.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_accessor_8h.xhtml">tests/NEON/Accessor.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="benchmark_2fixtures_2_convolution_layer_fixture_8h.xhtml">tests/benchmark/fixtures/ConvolutionLayerFixture.h</a>"</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="_alex_net_convolution_layer_dataset_8h.xhtml">tests/datasets/system_tests/alexnet/AlexNetConvolutionLayerDataset.h</a>"</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="_goog_le_net_inception_v1_convolution_layer_dataset_8h.xhtml">tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ConvolutionLayerDataset.h</a>"</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include "<a class="code" href="_goog_le_net_inception_v4_convolution_layer_dataset_8h.xhtml">tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ConvolutionLayerDataset.h</a>"</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include "<a class="code" href="_le_net5_convolution_layer_dataset_8h.xhtml">tests/datasets/system_tests/lenet5/LeNet5ConvolutionLayerDataset.h</a>"</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include "<a class="code" href="_squeeze_net_convolution_layer_dataset_8h.xhtml">tests/datasets/system_tests/squeezenet/SqueezeNetConvolutionLayerDataset.h</a>"</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include "<a class="code" href="_v_g_g16_convolution_layer_dataset_8h.xhtml">tests/datasets/system_tests/vgg/vgg16/VGG16ConvolutionLayerDataset.h</a>"</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include "<a class="code" href="_y_o_l_o_v2_convolution_layer_dataset_8h.xhtml">tests/datasets/system_tests/yolo/v2/YOLOV2ConvolutionLayerDataset.h</a>"</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include "<a class="code" href="tests_2framework_2_macros_8h.xhtml">tests/framework/Macros.h</a>"</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="preprocessor">#include "<a class="code" href="_datasets_8h.xhtml">tests/framework/datasets/Datasets.h</a>"</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor">#include "<a class="code" href="_type_printer_8h.xhtml">utils/TypePrinter.h</a>"</span></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><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></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> <span class="keyword">namespace </span>test</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> <span class="keyword">namespace</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="keyword">const</span> <span class="keyword">auto</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a> = <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a> });</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="preprocessor">#else </span><span class="comment">/* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */</span><span class="preprocessor"></span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="keyword">const</span> <span class="keyword">auto</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a> = <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a> });</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="preprocessor">#endif </span><span class="comment">/* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */</span><span class="preprocessor"></span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> } <span class="comment">// namespace</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test.xhtml#a0e36e58a8ee401995f556ef9d4a5ce80"> 57</a></span> <span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a> = <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">ConvolutionLayerFixture<Tensor, NEGEMMConvolutionLayer, Accessor></a>;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <a class="code" href="tests_2framework_2_macros_8h.xhtml#acd09bed517e43d28823e69494f259835">TEST_SUITE</a>(NEON)</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="preprocessor">#if defined(__aarch64__)</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="keyword">using</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a453926f3b79e574aa31f56b259e1a781">NEWinogradLayerFixture</a> = <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">ConvolutionLayerFixture<Tensor, NEWinogradLayer, Accessor></a>;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(AlexNetWinogradLayer, NEWinogradLayerFixture, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_winograd_layer_dataset.xhtml">datasets::AlexNetWinogradLayerDataset</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)),</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, 1)));</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> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(GoogLeNetInceptionV1WinogradLayer, NEWinogradLayerFixture, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_winograd_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1WinogradLayerDataset</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)),</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, 1)));</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="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(GoogLeNetInceptionV4WinogradLayer, NEWinogradLayerFixture, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_winograd_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4WinogradLayerDataset</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)),</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, 1)));</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="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(SqueezeNetWinogradLayer, NEWinogradLayerFixture, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_winograd_layer_dataset.xhtml">datasets::SqueezeNetWinogradLayerDataset</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)),</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, 1)));</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="preprocessor">#endif </span><span class="comment">/* __aarch64__ */</span><span class="preprocessor"></span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(AlexNetConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_convolution_layer_dataset.xhtml">datasets::AlexNetConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, 1)));</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(LeNet5ConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_convolution_layer_dataset.xhtml">datasets::LeNet5ConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, 1)));</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(GoogLeNetInceptionV1ConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1ConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, 1)));</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(GoogLeNetInceptionV4ConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4ConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, 1)));</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(SqueezeNetConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, 1)));</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <a class="code" href="tests_2framework_2_macros_8h.xhtml#acd09bed517e43d28823e69494f259835">TEST_SUITE</a>(NIGHTLY)</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(AlexNetConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, framework::<a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cf">DatasetMode</a>::NIGHTLY,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  framework::dataset::<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">combine</a>(framework::dataset::<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">combine</a>(datasets::AlexNetConvolutionLayerDataset(), data_types),</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  framework::dataset::<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">make</a>("Batches", { 4, 8 })));</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(LeNet5ConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_convolution_layer_dataset.xhtml">datasets::LeNet5ConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 4, 8 })));</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(GoogLeNetInceptionV1ConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1ConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 4, 8 })));</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(GoogLeNetInceptionV4ConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4ConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 4, 8 })));</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(SqueezeNetConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 4, 8 })));</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="comment">// 8 batches use about 2GB of memory which is too much for most devices!</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(VGG16ConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml">datasets::VGG16ConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 1, 2 })));</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(YOLOV2ConvolutionLayer, <a class="code" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">NEGEMMConvolutionLayerFixture</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_convolution_layer_dataset.xhtml">datasets::YOLOV2ConvolutionLayerDataset</a>(), data_types),</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 1, 4, 8 })));</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="preprocessor">#if defined(__aarch64__)</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(AlexNetWinogradLayer, NEWinogradLayerFixture, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_winograd_layer_dataset.xhtml">datasets::AlexNetWinogradLayerDataset</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)),</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 4, 8 })));</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(GoogLeNetInceptionV1WinogradLayer, NEWinogradLayerFixture, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_winograd_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1WinogradLayerDataset</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)),</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 4, 8 })));</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(GoogLeNetInceptionV4WinogradLayer, NEWinogradLayerFixture, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_winograd_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4WinogradLayerDataset</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)),</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 4, 8 })));</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">REGISTER_FIXTURE_DATA_TEST_CASE</a>(SqueezeNetWinogradLayer, NEWinogradLayerFixture, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_winograd_layer_dataset.xhtml">datasets::SqueezeNetWinogradLayerDataset</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DataType"</span>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)),</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Batches"</span>, { 4, 8 })));</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="preprocessor">#endif </span><span class="comment">/* __aarch64__ */</span><span class="preprocessor"></span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> </div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <a class="code" href="tests_2framework_2_macros_8h.xhtml#a603cb7f45efd81606e51686da9aeebd9">TEST_SUITE_END</a>()</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <a class="code" href="tests_2framework_2_macros_8h.xhtml#a603cb7f45efd81606e51686da9aeebd9">TEST_SUITE_END</a>()</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> } <span class="comment">// namespace test</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> } <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="_accessor_8h_xhtml"><div class="ttname"><a href="_accessor_8h.xhtml">Accessor.h</a></div></div>
121 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">arm_compute::test::datasets::SqueezeNetConvolutionLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_squeeze_net_convolution_layer_dataset_8h_source.xhtml#l00056">SqueezeNetConvolutionLayerDataset.h:56</a></div></div>
122 <div class="ttc" id="_n_e_convolution_layer_8h_xhtml"><div class="ttname"><a href="_n_e_convolution_layer_8h.xhtml">NEConvolutionLayer.h</a></div></div>
123 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_alex_net_convolution_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_convolution_layer_dataset.xhtml">arm_compute::test::datasets::AlexNetConvolutionLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_alex_net_convolution_layer_dataset_8h_source.xhtml#l00051">AlexNetConvolutionLayerDataset.h:51</a></div></div>
124 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_winograd_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_winograd_layer_dataset.xhtml">arm_compute::test::datasets::SqueezeNetWinogradLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_squeeze_net_convolution_layer_dataset_8h_source.xhtml#l00040">SqueezeNetConvolutionLayerDataset.h:40</a></div></div>
125 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a453926f3b79e574aa31f56b259e1a781"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a453926f3b79e574aa31f56b259e1a781">arm_compute::test::validation::NEWinogradLayerFixture</a></div><div class="ttdeci">WinogradLayerValidationFixture< Tensor, Accessor, NEWinogradLayer, T > NEWinogradLayerFixture</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_n_e_o_n_2_convolution_layer_8cpp_source.xhtml#l00112">ConvolutionLayer.cpp:112</a></div></div>
126 <div class="ttc" id="_v_g_g16_convolution_layer_dataset_8h_xhtml"><div class="ttname"><a href="_v_g_g16_convolution_layer_dataset_8h.xhtml">VGG16ConvolutionLayerDataset.h</a></div></div>
127 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_winograd_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_winograd_layer_dataset.xhtml">arm_compute::test::datasets::GoogLeNetInceptionV1WinogradLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_goog_le_net_inception_v1_convolution_layer_dataset_8h_source.xhtml#l00040">GoogLeNetInceptionV1ConvolutionLayerDataset.h:40</a></div></div>
128 <div class="ttc" id="_tensor_allocator_8h_xhtml"><div class="ttname"><a href="_tensor_allocator_8h.xhtml">TensorAllocator.h</a></div></div>
129 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_convolution_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_convolution_layer_dataset.xhtml">arm_compute::test::datasets::GoogLeNetInceptionV4ConvolutionLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_goog_le_net_inception_v4_convolution_layer_dataset_8h_source.xhtml#l00061">GoogLeNetInceptionV4ConvolutionLayerDataset.h:61</a></div></div>
130 <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>
131 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_winograd_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_winograd_layer_dataset.xhtml">arm_compute::test::datasets::GoogLeNetInceptionV4WinogradLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_goog_le_net_inception_v4_convolution_layer_dataset_8h_source.xhtml#l00040">GoogLeNetInceptionV4ConvolutionLayerDataset.h:40</a></div></div>
132 <div class="ttc" id="_y_o_l_o_v2_convolution_layer_dataset_8h_xhtml"><div class="ttname"><a href="_y_o_l_o_v2_convolution_layer_dataset_8h.xhtml">YOLOV2ConvolutionLayerDataset.h</a></div></div>
133 <div class="ttc" id="namespacearm__compute_1_1test_1_1framework_1_1dataset_xhtml_a352791fb808d42a82ad70df5efa3508b"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">arm_compute::test::framework::dataset::make</a></div><div class="ttdeci">std::enable_if< is_container< T >::value, ContainerDataset< T > >::type make(std::string name, T &&values)</div><div class="ttdoc">Helper function to create a ContainerDataset. </div><div class="ttdef"><b>Definition:</b> <a href="_container_dataset_8h_source.xhtml#l00141">ContainerDataset.h:141</a></div></div>
134 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_alex_net_winograd_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_winograd_layer_dataset.xhtml">arm_compute::test::datasets::AlexNetWinogradLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_alex_net_convolution_layer_dataset_8h_source.xhtml#l00040">AlexNetConvolutionLayerDataset.h:40</a></div></div>
135 <div class="ttc" id="classarm__compute_1_1test_1_1_convolution_layer_fixture_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">arm_compute::test::ConvolutionLayerFixture</a></div><div class="ttdoc">Fixture that can be used for NEON and CL. </div><div class="ttdef"><b>Definition:</b> <a href="benchmark_2fixtures_2_convolution_layer_fixture_8h_source.xhtml#l00039">ConvolutionLayerFixture.h:39</a></div></div>
136 <div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">This file contains all available output stages for GEMMLowp on OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="01__library_8dox_source.xhtml#l00001">01_library.dox:1</a></div></div>
137 <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>
138 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_convolution_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_convolution_layer_dataset.xhtml">arm_compute::test::datasets::YOLOV2ConvolutionLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_y_o_l_o_v2_convolution_layer_dataset_8h_source.xhtml#l00040">YOLOV2ConvolutionLayerDataset.h:40</a></div></div>
139 <div class="ttc" id="tests_2framework_2_macros_8h_xhtml_acd09bed517e43d28823e69494f259835"><div class="ttname"><a href="tests_2framework_2_macros_8h.xhtml#acd09bed517e43d28823e69494f259835">TEST_SUITE</a></div><div class="ttdeci">#define TEST_SUITE(SUITE_NAME)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2framework_2_macros_8h_source.xhtml#l00034">Macros.h:34</a></div></div>
140 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_convolution_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_convolution_layer_dataset.xhtml">arm_compute::test::datasets::GoogLeNetInceptionV1ConvolutionLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_goog_le_net_inception_v1_convolution_layer_dataset_8h_source.xhtml#l00068">GoogLeNetInceptionV1ConvolutionLayerDataset.h:68</a></div></div>
141 <div class="ttc" id="namespacearm__compute_1_1test_xhtml_aab9a2ff74a27ae837d32a79a38952228"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">arm_compute::test::data_types</a></div><div class="ttdeci">const auto data_types</div><div class="ttdef"><b>Definition:</b> <a href="benchmark_2_c_l_2_depthwise_convolution_layer_8cpp_source.xhtml#l00040">DepthwiseConvolutionLayer.cpp:40</a></div></div>
142 <div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_a7edf31944a6144ffd493d2f9a7bfb5cf"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cf">arm_compute::test::framework::DatasetMode</a></div><div class="ttdeci">DatasetMode</div><div class="ttdoc">Possible dataset modes. </div><div class="ttdef"><b>Definition:</b> <a href="_dataset_modes_8h_source.xhtml#l00040">DatasetModes.h:40</a></div></div>
143 <div class="ttc" id="_goog_le_net_inception_v1_convolution_layer_dataset_8h_xhtml"><div class="ttname"><a href="_goog_le_net_inception_v1_convolution_layer_dataset_8h.xhtml">GoogLeNetInceptionV1ConvolutionLayerDataset.h</a></div></div>
144 <div class="ttc" id="_datasets_8h_xhtml"><div class="ttname"><a href="_datasets_8h.xhtml">Datasets.h</a></div></div>
145 <div class="ttc" id="_type_printer_8h_xhtml"><div class="ttname"><a href="_type_printer_8h.xhtml">TypePrinter.h</a></div></div>
146 <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div></div>
147 <div class="ttc" id="_le_net5_convolution_layer_dataset_8h_xhtml"><div class="ttname"><a href="_le_net5_convolution_layer_dataset_8h.xhtml">LeNet5ConvolutionLayerDataset.h</a></div></div>
148 <div class="ttc" id="tests_2framework_2_macros_8h_xhtml"><div class="ttname"><a href="tests_2framework_2_macros_8h.xhtml">Macros.h</a></div></div>
149 <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a2be51cbb1f1e5aaf0a5baeccdb2e3354"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a2be51cbb1f1e5aaf0a5baeccdb2e3354">arm_compute::test::REGISTER_FIXTURE_DATA_TEST_CASE</a></div><div class="ttdeci">REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))), data_types), framework::dataset::make("Batches", 1)))</div></div>
150 <div class="ttc" id="_n_e_winograd_layer_8h_xhtml"><div class="ttname"><a href="_n_e_winograd_layer_8h.xhtml">NEWinogradLayer.h</a></div></div>
151 <div class="ttc" id="namespacearm__compute_1_1test_1_1framework_1_1dataset_xhtml_a6f4fa4bb0583f29e77138fb1e7d77411"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">arm_compute::test::framework::dataset::combine</a></div><div class="ttdeci">CartesianProductDataset< T, U > combine(T &&dataset1, U &&dataset2)</div><div class="ttdoc">Helper function to create a CartesianProductDataset. </div><div class="ttdef"><b>Definition:</b> <a href="_cartesian_product_dataset_8h_source.xhtml#l00157">CartesianProductDataset.h:157</a></div></div>
152 <div class="ttc" id="_squeeze_net_convolution_layer_dataset_8h_xhtml"><div class="ttname"><a href="_squeeze_net_convolution_layer_dataset_8h.xhtml">SqueezeNetConvolutionLayerDataset.h</a></div></div>
153 <div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">arm_compute::test::framework::DatasetMode::NIGHTLY</a></div></div>
154 <div class="ttc" id="benchmark_2fixtures_2_convolution_layer_fixture_8h_xhtml"><div class="ttname"><a href="benchmark_2fixtures_2_convolution_layer_fixture_8h.xhtml">ConvolutionLayerFixture.h</a></div></div>
155 <div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">arm_compute::test::framework::DatasetMode::ALL</a></div></div>
156 <div class="ttc" id="_goog_le_net_inception_v4_convolution_layer_dataset_8h_xhtml"><div class="ttname"><a href="_goog_le_net_inception_v4_convolution_layer_dataset_8h.xhtml">GoogLeNetInceptionV4ConvolutionLayerDataset.h</a></div></div>
157 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_le_net5_convolution_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_convolution_layer_dataset.xhtml">arm_compute::test::datasets::LeNet5ConvolutionLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_le_net5_convolution_layer_dataset_8h_source.xhtml#l00040">LeNet5ConvolutionLayerDataset.h:40</a></div></div>
158 <div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml">arm_compute::test::datasets::VGG16ConvolutionLayerDataset</a></div><div class="ttdef"><b>Definition:</b> <a href="_v_g_g16_convolution_layer_dataset_8h_source.xhtml#l00040">VGG16ConvolutionLayerDataset.h:40</a></div></div>
159 <div class="ttc" id="_alex_net_convolution_layer_dataset_8h_xhtml"><div class="ttname"><a href="_alex_net_convolution_layer_dataset_8h.xhtml">AlexNetConvolutionLayerDataset.h</a></div></div>
160 <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>
161 <div class="ttc" id="runtime_2_tensor_8h_xhtml"><div class="ttname"><a href="runtime_2_tensor_8h.xhtml">Tensor.h</a></div></div>
162 <div class="ttc" id="_tensor_shape_8h_xhtml"><div class="ttname"><a href="_tensor_shape_8h.xhtml">TensorShape.h</a></div></div>
163 <div class="ttc" id="tests_2framework_2_macros_8h_xhtml_a603cb7f45efd81606e51686da9aeebd9"><div class="ttname"><a href="tests_2framework_2_macros_8h.xhtml#a603cb7f45efd81606e51686da9aeebd9">TEST_SUITE_END</a></div><div class="ttdeci">#define TEST_SUITE_END()</div><div class="ttdef"><b>Definition:</b> <a href="tests_2framework_2_macros_8h_source.xhtml#l00039">Macros.h:39</a></div></div>
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169 <li class="navelem"><a class="el" href="dir_59425e443f801f1f2fd8bbe4959a3ccf.xhtml">tests</a></li><li class="navelem"><a class="el" href="dir_4f2df8950dc650bf7cf9176fae02facc.xhtml">benchmark</a></li><li class="navelem"><a class="el" href="dir_ec05701f68bea22653d08da5856c9ffc.xhtml">NEON</a></li><li class="navelem"><a class="el" href="benchmark_2_n_e_o_n_2_convolution_layer_8cpp.xhtml">ConvolutionLayer.cpp</a></li>
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