<tr style="height: 56px;">
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<div id="projectname">Compute Library
-  <span id="projectnumber">18.02</span>
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<a href="_v_g_g16_convolution_layer_dataset_8h.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2017 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#ifndef ARM_COMPUTE_TEST_VGG16_CONVOLUTION_LAYER_DATASET</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define ARM_COMPUTE_TEST_VGG16_CONVOLUTION_LAYER_DATASET</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_convolution_layer_dataset_8h.xhtml">tests/datasets/ConvolutionLayerDataset.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="_type_printer_8h.xhtml">utils/TypePrinter.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</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="l00032"></a><span class="lineno"> 32</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="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="keyword">namespace </span>test</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="keyword">namespace </span>datasets</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> {</div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml"> 40</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml">VGG16ConvolutionLayerDataset</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml">ConvolutionLayerDataset</a></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml#aa472ab388a573f7233dad1a8c4c3b4f0"> 43</a></span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml#aa472ab388a573f7233dad1a8c4c3b4f0">VGG16ConvolutionLayerDataset</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="comment">// conv1_1</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="comment">// conv1_2</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="comment">// conv2_1</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="comment">// conv2_2</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="comment">// conv3_1</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="comment">// conv3_2, conv3_3</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// conv4_1</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="comment">// conv4_2, conv4_3</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="comment">// conv5_1, conv5_2, conv5_3</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(14<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 14<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(14<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 14<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> };</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div><div class="line"><a name="l00066"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_direct_convolution_layer_dataset.xhtml"> 66</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_direct_convolution_layer_dataset.xhtml">VGG16DirectConvolutionLayerDataset</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml">ConvolutionLayerDataset</a></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> {</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00069"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_direct_convolution_layer_dataset.xhtml#a0f8cdd2cf87f5234f752360d554d0d67"> 69</a></span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_direct_convolution_layer_dataset.xhtml#a0f8cdd2cf87f5234f752360d554d0d67">VGG16DirectConvolutionLayerDataset</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>  <span class="comment">// conv1_1</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// conv1_2</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="comment">// conv2_1</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="comment">// conv2_2</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 112<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="comment">// conv3_1</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="comment">// conv3_2, conv3_3</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 56<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="comment">// conv4_1</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="comment">// conv4_2, conv4_3</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 28<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="comment">// conv5_1, conv5_2, conv5_3</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">add_config</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(14<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 14<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(14<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 14<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1));</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="comment">// namespace datasets</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> } <span class="comment">// namespace test</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> } <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="preprocessor">#endif </span><span class="comment">/* ARM_COMPUTE_TEST_VGG16_CONVOLUTION_LAYER_DATASET */</span><span class="preprocessor"></span></div><div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset_xhtml_a3f1ddb8fe464be68a02cc1b81ee5e3e7"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml#a3f1ddb8fe464be68a02cc1b81ee5e3e7">arm_compute::test::datasets::ConvolutionLayerDataset::add_config</a></div><div class="ttdeci">void add_config(TensorShape src, TensorShape weights, TensorShape biases, TensorShape dst, PadStrideInfo info)</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_layer_dataset_8h_source.xhtml#l00103">ConvolutionLayerDataset.h:103</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_direct_convolution_layer_dataset_xhtml_a0f8cdd2cf87f5234f752360d554d0d67"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_direct_convolution_layer_dataset.xhtml#a0f8cdd2cf87f5234f752360d554d0d67">arm_compute::test::datasets::VGG16DirectConvolutionLayerDataset::VGG16DirectConvolutionLayerDataset</a></div><div class="ttdeci">VGG16DirectConvolutionLayerDataset()</div><div class="ttdef"><b>Definition:</b> <a href="_v_g_g16_convolution_layer_dataset_8h_source.xhtml#l00069">VGG16ConvolutionLayerDataset.h:69</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">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>
+<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">This file contains all available output stages for GEMMLowp on OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00001">00_introduction.dox:1</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb"><div class="ttname"><a href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::Channel::U</a></div><div class="ttdoc">Cb/U channel. </div></div>
<div class="ttc" id="_type_printer_8h_xhtml"><div class="ttname"><a href="_type_printer_8h.xhtml">TypePrinter.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml">arm_compute::PadStrideInfo</a></div><div class="ttdoc">Padding and stride information class. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00491">Types.h:491</a></div></div>
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<li class="navelem"><a class="el" href="dir_59425e443f801f1f2fd8bbe4959a3ccf.xhtml">tests</a></li><li class="navelem"><a class="el" href="dir_e13277e8d7d14f3f15e64267bfca6477.xhtml">datasets</a></li><li class="navelem"><a class="el" href="dir_c71057a74ea67172e112f0f837c986c4.xhtml">system_tests</a></li><li class="navelem"><a class="el" href="dir_c99b4a303cfde599116bfef66dcbe457.xhtml">vgg</a></li><li class="navelem"><a class="el" href="dir_246d8741fe000f90e23698d7e8443699.xhtml">vgg16</a></li><li class="navelem"><a class="el" href="_v_g_g16_convolution_layer_dataset_8h.xhtml">VGG16ConvolutionLayerDataset.h</a></li>
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<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li>
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