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arm_compute v18.03
[platform/upstream/armcl.git] / documentation / _squeeze_net_convolution_layer_dataset_8h_source.xhtml
diff --git a/documentation/_squeeze_net_convolution_layer_dataset_8h_source.xhtml b/documentation/_squeeze_net_convolution_layer_dataset_8h_source.xhtml
index 181c673..bb0226c 100644 (file)
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 <div class="title">SqueezeNetConvolutionLayerDataset.h</div>  </div>
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-<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div>
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-<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#ifndef ARM_COMPUTE_TEST_SQUEEZENET_CONVOLUTION_LAYER_DATASET</span></div>
-<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#define ARM_COMPUTE_TEST_SQUEEZENET_CONVOLUTION_LAYER_DATASET</span></div>
-<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="preprocessor"></span></div>
-<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_convolution_layer_dataset_8h.xhtml">tests/datasets/ConvolutionLayerDataset.h</a>&quot;</span></div>
-<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;</div>
-<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_type_printer_8h.xhtml">utils/TypePrinter.h</a>&quot;</span></div>
-<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;</div>
-<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>&quot;</span></div>
-<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>&quot;</span></div>
-<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;</div>
-<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="keyword">namespace </span>arm_compute</div>
-<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;{</div>
-<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">namespace </span>test</div>
-<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;{</div>
-<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="keyword">namespace </span>datasets</div>
-<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;{</div>
-<div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">   40</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">SqueezeNetConvolutionLayerDataset</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>&#160;{</div>
-<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<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_squeeze_net_convolution_layer_dataset.xhtml#abbc7600599ae6338fce43997e633f595">   43</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml#abbc7600599ae6338fce43997e633f595">SqueezeNetConvolutionLayerDataset</a>()</div>
-<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    {</div>
-<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;        <span class="comment">// conv1</span></div>
-<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;        <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>(111<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 111<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>(2, 2, 0, 0));</div>
-<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;        <span class="comment">// fire2/squeeze1x1</span></div>
-<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;        <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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<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, 0, 0));</div>
-<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;        <span class="comment">// fire2/expand1x1, fire3/expand1x1</span></div>
-<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;        <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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<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, 0, 0));</div>
-<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;        <span class="comment">// fire2/expand3x3, fire3/expand3x3</span></div>
-<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;        <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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<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>, 16<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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<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="l00053"></a><span class="lineno">   53</span>&#160;        <span class="comment">// fire3/squeeze1x1</span></div>
-<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;        <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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<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, 0, 0));</div>
-<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;        <span class="comment">// fire4/squeeze1x1</span></div>
-<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;        <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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<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, 0, 0));</div>
-<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;        <span class="comment">// fire4/expand1x1, fire5/expand1x1</span></div>
-<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;        <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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<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, 0, 0));</div>
-<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;        <span class="comment">// fire4/expand3x3, fire5/expand3x3</span></div>
-<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;        <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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<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>, 32<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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<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="l00061"></a><span class="lineno">   61</span>&#160;        <span class="comment">// fire5/squeeze1x1</span></div>
-<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;        <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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<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, 0, 0));</div>
-<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;        <span class="comment">// fire6/squeeze1x1</span></div>
-<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<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, 0, 0));</div>
-<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;        <span class="comment">// fire6/expand1x1, fire7/expand1x1</span></div>
-<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<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, 0, 0));</div>
-<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        <span class="comment">// fire6/expand3x3, fire7/expand3x3</span></div>
-<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<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>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<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="l00069"></a><span class="lineno">   69</span>&#160;        <span class="comment">// fire7/squeeze1x1</span></div>
-<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 384<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 384<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<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, 0, 0));</div>
-<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        <span class="comment">// fire8/squeeze1x1</span></div>
-<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 384<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 384<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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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, 0, 0));</div>
-<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        <span class="comment">// fire8/expand1x1, fire9/expand1x1</span></div>
-<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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, 0, 0));</div>
-<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;        <span class="comment">// fire8/expand3x3, fire9/expand3x3</span></div>
-<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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>, 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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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="l00077"></a><span class="lineno">   77</span>&#160;        <span class="comment">// fire9/squeeze1x1</span></div>
-<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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, 0, 0));</div>
-<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;        <span class="comment">// conv10</span></div>
-<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1000<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1000<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1000<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, 0, 0));</div>
-<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    }</div>
-<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;};</div>
-<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;} <span class="comment">// namespace datasets</span></div>
-<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;} <span class="comment">// namespace test</span></div>
-<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;} <span class="comment">// namespace arm_compute</span></div>
-<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* ARM_COMPUTE_TEST_SQUEEZENET_CONVOLUTION_LAYER_DATASET */</span><span class="preprocessor"></span></div>
-<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#l00040">SqueezeNetConvolutionLayerDataset.h:40</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00038">TensorShape.h:38</a></div></div>
+<a href="_squeeze_net_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>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<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>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<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>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#ifndef ARM_COMPUTE_TEST_SQUEEZENET_CONVOLUTION_LAYER_DATASET</span></div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor">#define ARM_COMPUTE_TEST_SQUEEZENET_CONVOLUTION_LAYER_DATASET</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_convolution_layer_dataset_8h.xhtml">tests/datasets/ConvolutionLayerDataset.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_type_printer_8h.xhtml">utils/TypePrinter.h</a>&quot;</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>&quot;</span></div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>&quot;</span></div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<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>&#160;{</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">namespace </span>test</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;{</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="keyword">namespace </span>datasets</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;{</div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_winograd_layer_dataset.xhtml">   40</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_winograd_layer_dataset.xhtml">SqueezeNetWinogradLayerDataset</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>&#160;{</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<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_squeeze_net_winograd_layer_dataset.xhtml#a6120780c00669e2640d8bce8d532f9be">   43</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_winograd_layer_dataset.xhtml#a6120780c00669e2640d8bce8d532f9be">SqueezeNetWinogradLayerDataset</a>()</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    {</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;        <span class="comment">// fire2/expand3x3, fire3/expand3x3</span></div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;        <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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<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>, 16<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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<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>&#160;        <span class="comment">// fire4/expand3x3, fire5/expand3x3</span></div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;        <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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<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>, 32<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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<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="l00049"></a><span class="lineno">   49</span>&#160;        <span class="comment">// fire6/expand3x3, fire7/expand3x3</span></div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<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>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<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>&#160;        <span class="comment">// fire8/expand3x3, fire9/expand3x3</span></div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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>, 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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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="l00053"></a><span class="lineno">   53</span>&#160;    }</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;};</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">   56</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">SqueezeNetConvolutionLayerDataset</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="l00057"></a><span class="lineno">   57</span>&#160;{</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml#abbc7600599ae6338fce43997e633f595">   59</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml#abbc7600599ae6338fce43997e633f595">SqueezeNetConvolutionLayerDataset</a>()</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    {</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;        <span class="comment">// conv1</span></div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;        <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>(111<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 111<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>(2, 2, 0, 0));</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;        <span class="comment">// fire2/squeeze1x1</span></div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;        <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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<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, 0, 0));</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;        <span class="comment">// fire2/expand1x1, fire3/expand1x1</span></div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;        <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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<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, 0, 0));</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        <span class="comment">// fire2/expand3x3, fire3/expand3x3</span></div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;        <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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<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>, 16<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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<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="l00069"></a><span class="lineno">   69</span>&#160;        <span class="comment">// fire3/squeeze1x1</span></div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;        <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>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(16<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 55<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 16<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, 0, 0));</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        <span class="comment">// fire4/squeeze1x1</span></div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        <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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<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, 0, 0));</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        <span class="comment">// fire4/expand1x1, fire5/expand1x1</span></div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;        <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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<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, 0, 0));</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;        <span class="comment">// fire4/expand3x3, fire5/expand3x3</span></div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;        <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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<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>, 32<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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<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>&#160;        <span class="comment">// fire5/squeeze1x1</span></div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;        <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>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<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, 0, 0));</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;        <span class="comment">// fire6/squeeze1x1</span></div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<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, 0, 0));</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;        <span class="comment">// fire6/expand1x1, fire7/expand1x1</span></div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<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, 0, 0));</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;        <span class="comment">// fire6/expand3x3, fire7/expand3x3</span></div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<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>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(192<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 192<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>&#160;        <span class="comment">// fire7/squeeze1x1</span></div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 384<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 384<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 48<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, 0, 0));</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;        <span class="comment">// fire8/squeeze1x1</span></div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 384<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 384<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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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, 0, 0));</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;        <span class="comment">// fire8/expand1x1, fire9/expand1x1</span></div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796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/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, 0, 0));</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        <span class="comment">// conv10</span></div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        <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>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 512<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1000<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1000<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1000<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, 0, 0));</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    }</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;};</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;} <span class="comment">// namespace datasets</span></div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* ARM_COMPUTE_TEST_SQUEEZENET_CONVOLUTION_LAYER_DATASET */</span><span class="preprocessor"></span></div><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>
+<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_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>
+<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_winograd_layer_dataset_xhtml_a6120780c00669e2640d8bce8d532f9be"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_winograd_layer_dataset.xhtml#a6120780c00669e2640d8bce8d532f9be">arm_compute::test::datasets::SqueezeNetWinogradLayerDataset::SqueezeNetWinogradLayerDataset</a></div><div class="ttdeci">SqueezeNetWinogradLayerDataset()</div><div class="ttdef"><b>Definition:</b> <a href="_squeeze_net_convolution_layer_dataset_8h_source.xhtml#l00043">SqueezeNetConvolutionLayerDataset.h:43</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_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset_xhtml_abbc7600599ae6338fce43997e633f595"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml#abbc7600599ae6338fce43997e633f595">arm_compute::test::datasets::SqueezeNetConvolutionLayerDataset::SqueezeNetConvolutionLayerDataset</a></div><div class="ttdeci">SqueezeNetConvolutionLayerDataset()</div><div class="ttdef"><b>Definition:</b> <a href="_squeeze_net_convolution_layer_dataset_8h_source.xhtml#l00043">SqueezeNetConvolutionLayerDataset.h:43</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#l00406">Types.h:406</a></div></div>
+<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset_xhtml_abbc7600599ae6338fce43997e633f595"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml#abbc7600599ae6338fce43997e633f595">arm_compute::test::datasets::SqueezeNetConvolutionLayerDataset::SqueezeNetConvolutionLayerDataset</a></div><div class="ttdeci">SqueezeNetConvolutionLayerDataset()</div><div class="ttdef"><b>Definition:</b> <a href="_squeeze_net_convolution_layer_dataset_8h_source.xhtml#l00059">SqueezeNetConvolutionLayerDataset.h:59</a></div></div>
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Domain: Machine Learning / ML Framework;