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   9 <title>Compute Library: MobileNetV1Network&lt; TensorType, Accessor, ActivationLayerFunction, BatchNormalizationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, DepthwiseConvolutionFunction, ReshapeFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt; Class Template Reference</title>
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 118   <div class="summary">
 119 <a href="#pub-methods">Public Member Functions</a>  </div>
 120   <div class="headertitle">
 121 <div class="title">MobileNetV1Network&lt; TensorType, Accessor, ActivationLayerFunction, BatchNormalizationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, DepthwiseConvolutionFunction, ReshapeFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt; Class Template Reference</div>  </div>
 122 </div><!--header-->
 123 <div class="contents">
 124
 125 <p>MobileNet model object.
 126  <a href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#details">More...</a></p>
 127
 128 <p><code>#include &lt;<a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>&gt;</code></p>
 129 <table class="memberdecls">
 130 <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
 131 Public Member Functions</h2></td></tr>
 132 <tr class="memitem:a3b81d78cb73291bea06a00d70ad09b5d"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#a3b81d78cb73291bea06a00d70ad09b5d">init</a> (unsigned int input_spatial_size, int batches)</td></tr>
 133 <tr class="separator:a3b81d78cb73291bea06a00d70ad09b5d"><td class="memSeparator" colspan="2">&#160;</td></tr>
 134 <tr class="memitem:a7740c7ab195c03ac140f1f75f633470f"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#a7740c7ab195c03ac140f1f75f633470f">build</a> ()</td></tr>
 135 <tr class="memdesc:a7740c7ab195c03ac140f1f75f633470f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Build the model.  <a href="#a7740c7ab195c03ac140f1f75f633470f">More...</a><br /></td></tr>
 136 <tr class="separator:a7740c7ab195c03ac140f1f75f633470f"><td class="memSeparator" colspan="2">&#160;</td></tr>
 137 <tr class="memitem:acaefe811b78a2fdc4a0dba0c4029c3ef"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#acaefe811b78a2fdc4a0dba0c4029c3ef">allocate</a> ()</td></tr>
 138 <tr class="separator:acaefe811b78a2fdc4a0dba0c4029c3ef"><td class="memSeparator" colspan="2">&#160;</td></tr>
 139 <tr class="memitem:a3b778cda9ac3fad08e7217edbcb942e0"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#a3b778cda9ac3fad08e7217edbcb942e0">fill_random</a> ()</td></tr>
 140 <tr class="memdesc:a3b778cda9ac3fad08e7217edbcb942e0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fills the trainable parameters and input with random data.  <a href="#a3b778cda9ac3fad08e7217edbcb942e0">More...</a><br /></td></tr>
 141 <tr class="separator:a3b778cda9ac3fad08e7217edbcb942e0"><td class="memSeparator" colspan="2">&#160;</td></tr>
 142 <tr class="memitem:a3a41262ce9aed70a248ecefae646013b"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#a3a41262ce9aed70a248ecefae646013b">feed</a> (std::string name)</td></tr>
 143 <tr class="memdesc:a3a41262ce9aed70a248ecefae646013b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Feed input to network from file.  <a href="#a3a41262ce9aed70a248ecefae646013b">More...</a><br /></td></tr>
 144 <tr class="separator:a3a41262ce9aed70a248ecefae646013b"><td class="memSeparator" colspan="2">&#160;</td></tr>
 145 <tr class="memitem:a1466ef70729f3c8b5da5ebfec3f53f26"><td class="memItemLeft" align="right" valign="top">std::vector&lt; unsigned int &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#a1466ef70729f3c8b5da5ebfec3f53f26">get_classifications</a> ()</td></tr>
 146 <tr class="memdesc:a1466ef70729f3c8b5da5ebfec3f53f26"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the classification results.  <a href="#a1466ef70729f3c8b5da5ebfec3f53f26">More...</a><br /></td></tr>
 147 <tr class="separator:a1466ef70729f3c8b5da5ebfec3f53f26"><td class="memSeparator" colspan="2">&#160;</td></tr>
 148 <tr class="memitem:ac8bb3912a3ce86b15842e79d0b421204"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#ac8bb3912a3ce86b15842e79d0b421204">clear</a> ()</td></tr>
 149 <tr class="memdesc:ac8bb3912a3ce86b15842e79d0b421204"><td class="mdescLeft">&#160;</td><td class="mdescRight">Clear all allocated memory from the tensor objects.  <a href="#ac8bb3912a3ce86b15842e79d0b421204">More...</a><br /></td></tr>
 150 <tr class="separator:ac8bb3912a3ce86b15842e79d0b421204"><td class="memSeparator" colspan="2">&#160;</td></tr>
 151 <tr class="memitem:a13a43e6d814de94978c515cb084873b1"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#a13a43e6d814de94978c515cb084873b1">run</a> ()</td></tr>
 152 <tr class="memdesc:a13a43e6d814de94978c515cb084873b1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Runs the model.  <a href="#a13a43e6d814de94978c515cb084873b1">More...</a><br /></td></tr>
 153 <tr class="separator:a13a43e6d814de94978c515cb084873b1"><td class="memSeparator" colspan="2">&#160;</td></tr>
 154 <tr class="memitem:ad55f80ed3cd8b6c4f247763b747016af"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#ad55f80ed3cd8b6c4f247763b747016af">sync</a> ()</td></tr>
 155 <tr class="memdesc:ad55f80ed3cd8b6c4f247763b747016af"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sync the results.  <a href="#ad55f80ed3cd8b6c4f247763b747016af">More...</a><br /></td></tr>
 156 <tr class="separator:ad55f80ed3cd8b6c4f247763b747016af"><td class="memSeparator" colspan="2">&#160;</td></tr>
 157 </table>
 158 <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
 159 <div class="textblock"><h3>template&lt;typename TensorType, typename Accessor, typename ActivationLayerFunction, typename BatchNormalizationLayerFunction, typename ConvolutionLayerFunction, typename DirectConvolutionLayerFunction, typename DepthwiseConvolutionFunction, typename ReshapeFunction, typename PoolingLayerFunction, typename SoftmaxLayerFunction&gt;<br />
 160 class arm_compute::test::networks::MobileNetV1Network&lt; TensorType, Accessor, ActivationLayerFunction, BatchNormalizationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, DepthwiseConvolutionFunction, ReshapeFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;</h3>
 161
 162 <p>MobileNet model object. </p>
 163
 164 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00055">55</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 165 </div><h2 class="groupheader">Member Function Documentation</h2>
 166 <a class="anchor" id="acaefe811b78a2fdc4a0dba0c4029c3ef"></a>
 167 <div class="memitem">
 168 <div class="memproto">
 169 <table class="mlabels">
 170   <tr>
 171   <td class="mlabels-left">
 172       <table class="memname">
 173         <tr>
 174           <td class="memname">void allocate </td>
 175           <td>(</td>
 176           <td class="paramname"></td><td>)</td>
 177           <td></td>
 178         </tr>
 179       </table>
 180   </td>
 181   <td class="mlabels-right">
 182 <span class="mlabels"><span class="mlabel">inline</span></span>  </td>
 183   </tr>
 184 </table>
 185 </div><div class="memdoc">
 186
 187 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00120">120</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 188 <div class="fragment"><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    {</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        input.allocator()-&gt;allocate();</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;        output.allocator()-&gt;allocate();</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;        w_conv3x3.allocator()-&gt;allocate();</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;        mean_conv3x3.allocator()-&gt;allocate();</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        var_conv3x3.allocator()-&gt;allocate();</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;        beta_conv3x3.allocator()-&gt;allocate();</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;        gamma_conv3x3.allocator()-&gt;allocate();</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;        <a class="code" href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(w_conv.size() != w_dwc.size());</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; w_conv.size(); ++i)</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;        {</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;            w_dwc[i].allocator()-&gt;allocate();</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;            bn_mean[2 * i].allocator()-&gt;allocate();</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;            bn_var[2 * i].allocator()-&gt;allocate();</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;            bn_beta[2 * i].allocator()-&gt;allocate();</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;            bn_gamma[2 * i].allocator()-&gt;allocate();</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;            w_conv[i].allocator()-&gt;allocate();</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;            bn_mean[2 * i + 1].allocator()-&gt;allocate();</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;            bn_var[2 * i + 1].allocator()-&gt;allocate();</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;            bn_beta[2 * i + 1].allocator()-&gt;allocate();</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;            bn_gamma[2 * i + 1].allocator()-&gt;allocate();</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;        }</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;        w_conv1c.allocator()-&gt;allocate();</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;        b_conv1c.allocator()-&gt;allocate();</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;        <span class="comment">// Allocate intermediate buffers</span></div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;        <span class="keywordflow">for</span>(<span class="keyword">auto</span> &amp;o : conv_out)</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;        {</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;            o.allocator()-&gt;allocate();</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;        }</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;        <span class="keywordflow">for</span>(<span class="keyword">auto</span> &amp;o : dwc_out)</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        {</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;            o.allocator()-&gt;allocate();</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;        }</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;        pool_out.allocator()-&gt;allocate();</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;        reshape_out.allocator()-&gt;allocate();</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    }</div><div class="ttc" id="core_2_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00306">Error.h:306</a></div></div>
 189 </div><!-- fragment -->
 190 </div>
 191 </div>
 192 <a class="anchor" id="a7740c7ab195c03ac140f1f75f633470f"></a>
 193 <div class="memitem">
 194 <div class="memproto">
 195 <table class="mlabels">
 196   <tr>
 197   <td class="mlabels-left">
 198       <table class="memname">
 199         <tr>
 200           <td class="memname">void build </td>
 201           <td>(</td>
 202           <td class="paramname"></td><td>)</td>
 203           <td></td>
 204         </tr>
 205       </table>
 206   </td>
 207   <td class="mlabels-right">
 208 <span class="mlabels"><span class="mlabel">inline</span></span>  </td>
 209   </tr>
 210 </table>
 211 </div><div class="memdoc">
 212
 213 <p>Build the model. </p>
 214
 215 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00095">95</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 216 <div class="fragment"><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    {</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;        <span class="comment">// Configure Layers</span></div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;        conv3x3.configure(&amp;input, &amp;w_conv3x3, <span class="keyword">nullptr</span>, &amp;conv_out[0], <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(2, 2, 0, 1, 0, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</a>));</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;        conv3x3_bn.configure(&amp;conv_out[0], <span class="keyword">nullptr</span>, &amp;mean_conv3x3, &amp;var_conv3x3, &amp;beta_conv3x3, &amp;gamma_conv3x3, 0.001f);</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        conv3x3_act.configure(&amp;conv_out[0], <span class="keyword">nullptr</span>, <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaacc516ab03b98f1c908ddf6ed4a7c45e9">ActivationLayerInfo::ActivationFunction::BOUNDED_RELU</a>, 6.f));</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        depthwise_conv_block_build(0, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 0, 0));</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;        depthwise_conv_block_build(1, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(2, 2, 0, 1, 0, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00103"></a><span class="lineno">  103</span>&#160;        depthwise_conv_block_build(2, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1, 1, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00104"></a><span class="lineno">  104</span>&#160;        depthwise_conv_block_build(3, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(2, 2, 0, 1, 0, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00105"></a><span class="lineno">  105</span>&#160;        depthwise_conv_block_build(4, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1, 1, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00106"></a><span class="lineno">  106</span>&#160;        depthwise_conv_block_build(5, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(2, 2, 0, 1, 0, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00107"></a><span class="lineno">  107</span>&#160;        depthwise_conv_block_build(6, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1, 1, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00108"></a><span class="lineno">  108</span>&#160;        depthwise_conv_block_build(7, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1, 1, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00109"></a><span class="lineno">  109</span>&#160;        depthwise_conv_block_build(8, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1, 1, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00110"></a><span class="lineno">  110</span>&#160;        depthwise_conv_block_build(9, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1, 1, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00111"></a><span class="lineno">  111</span>&#160;        depthwise_conv_block_build(10, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1, 1, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00112"></a><span class="lineno">  112</span>&#160;        depthwise_conv_block_build(11, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(2, 2, 0, 1, 0, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00113"></a><span class="lineno">  113</span>&#160;        depthwise_conv_block_build(12, <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 1, 1, 1, 1, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</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="l00114"></a><span class="lineno">  114</span>&#160;        pool.configure(&amp;conv_out[13], &amp;pool_out, <a class="code" href="classarm__compute_1_1_pooling_layer_info.xhtml">PoolingLayerInfo</a>(<a class="code" href="namespacearm__compute.xhtml#a9172da722f0a434e5cc07c0a3c115d93afcefd647d6a866603c627b11347c707a">PoolingType::AVG</a>));</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;        conv1c.configure(&amp;pool_out, &amp;w_conv1c, &amp;b_conv1c, &amp;conv_out[14], <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1, 1, 0, 0));</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;        reshape.configure(&amp;conv_out[14], &amp;reshape_out);</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;        smx.configure(&amp;reshape_out, &amp;output);</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    }</div><div class="ttc" id="namespacearm__compute_xhtml_a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe"><div class="ttname"><a href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">arm_compute::DimensionRoundingType::FLOOR</a></div><div class="ttdoc">Floor rounding. </div></div>
 217 <div class="ttc" id="classarm__compute_1_1_activation_layer_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_activation_layer_info.xhtml">arm_compute::ActivationLayerInfo</a></div><div class="ttdoc">Activation Layer Information class. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00701">Types.h:701</a></div></div>
 218 <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml">arm_compute::PadStrideInfo</a></div><div class="ttdoc">Padding and stride information class. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00491">Types.h:491</a></div></div>
 219 <div class="ttc" id="classarm__compute_1_1_activation_layer_info_xhtml_a56297e0f7b215eea46c818cb7528d9eaacc516ab03b98f1c908ddf6ed4a7c45e9"><div class="ttname"><a href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaacc516ab03b98f1c908ddf6ed4a7c45e9">arm_compute::ActivationLayerInfo::ActivationFunction::BOUNDED_RELU</a></div><div class="ttdoc">Upper Bounded Rectifier (  ) </div></div>
 220 <div class="ttc" id="namespacearm__compute_xhtml_a9172da722f0a434e5cc07c0a3c115d93afcefd647d6a866603c627b11347c707a"><div class="ttname"><a href="namespacearm__compute.xhtml#a9172da722f0a434e5cc07c0a3c115d93afcefd647d6a866603c627b11347c707a">arm_compute::PoolingType::AVG</a></div><div class="ttdoc">Average Pooling. </div></div>
 221 <div class="ttc" id="classarm__compute_1_1_pooling_layer_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pooling_layer_info.xhtml">arm_compute::PoolingLayerInfo</a></div><div class="ttdoc">Pooling Layer Information class. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00588">Types.h:588</a></div></div>
 222 </div><!-- fragment -->
 223 </div>
 224 </div>
 225 <a class="anchor" id="ac8bb3912a3ce86b15842e79d0b421204"></a>
 226 <div class="memitem">
 227 <div class="memproto">
 228 <table class="mlabels">
 229   <tr>
 230   <td class="mlabels-left">
 231       <table class="memname">
 232         <tr>
 233           <td class="memname">void clear </td>
 234           <td>(</td>
 235           <td class="paramname"></td><td>)</td>
 236           <td></td>
 237         </tr>
 238       </table>
 239   </td>
 240   <td class="mlabels-right">
 241 <span class="mlabels"><span class="mlabel">inline</span></span>  </td>
 242   </tr>
 243 </table>
 244 </div><div class="memdoc">
 245
 246 <p>Clear all allocated memory from the tensor objects. </p>
 247
 248 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00237">237</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 249 <div class="fragment"><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    {</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;        input.allocator()-&gt;free();</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;        output.allocator()-&gt;free();</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;        w_conv3x3.allocator()-&gt;free();</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;        mean_conv3x3.allocator()-&gt;free();</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;        var_conv3x3.allocator()-&gt;free();</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;        beta_conv3x3.allocator()-&gt;free();</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;        gamma_conv3x3.allocator()-&gt;free();</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;        <a class="code" href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(w_conv.size() != w_dwc.size());</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; w_conv.size(); ++i)</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;        {</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;            w_dwc[i].allocator()-&gt;free();</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;            bn_mean[2 * i].allocator()-&gt;free();</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;            bn_var[2 * i].allocator()-&gt;free();</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;            bn_beta[2 * i].allocator()-&gt;free();</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;            bn_gamma[2 * i].allocator()-&gt;free();</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;            w_conv[i].allocator()-&gt;free();</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;            bn_mean[2 * i + 1].allocator()-&gt;free();</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;            bn_var[2 * i + 1].allocator()-&gt;free();</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;            bn_beta[2 * i + 1].allocator()-&gt;free();</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;            bn_gamma[2 * i + 1].allocator()-&gt;free();</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;        }</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;        w_conv1c.allocator()-&gt;free();</div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;        b_conv1c.allocator()-&gt;free();</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;        <span class="comment">// Free intermediate buffers</span></div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;        <span class="keywordflow">for</span>(<span class="keyword">auto</span> &amp;o : conv_out)</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;        {</div><div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;            o.allocator()-&gt;free();</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;        }</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;        <span class="keywordflow">for</span>(<span class="keyword">auto</span> &amp;o : dwc_out)</div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;        {</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;            o.allocator()-&gt;free();</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;        }</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;        pool_out.allocator()-&gt;free();</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        reshape_out.allocator()-&gt;free();</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;    }</div><div class="ttc" id="core_2_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00306">Error.h:306</a></div></div>
 250 </div><!-- fragment -->
 251 </div>
 252 </div>
 253 <a class="anchor" id="a3a41262ce9aed70a248ecefae646013b"></a>
 254 <div class="memitem">
 255 <div class="memproto">
 256 <table class="mlabels">
 257   <tr>
 258   <td class="mlabels-left">
 259       <table class="memname">
 260         <tr>
 261           <td class="memname">void feed </td>
 262           <td>(</td>
 263           <td class="paramtype">std::string&#160;</td>
 264           <td class="paramname"><em>name</em></td><td>)</td>
 265           <td></td>
 266         </tr>
 267       </table>
 268   </td>
 269   <td class="mlabels-right">
 270 <span class="mlabels"><span class="mlabel">inline</span></span>  </td>
 271   </tr>
 272 </table>
 273 </div><div class="memdoc">
 274
 275 <p>Feed input to network from file. </p>
 276 <dl class="params"><dt>Parameters</dt><dd>
 277   <table class="params">
 278     <tr><td class="paramname">name</td><td>File name of containing the input data. </td></tr>
 279   </table>
 280   </dd>
 281 </dl>
 282
 283 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00196">196</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 284 <div class="fragment"><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;    {</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill_layer_data(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(input), name);</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    }</div><div class="ttc" id="classarm__compute_1_1test_1_1_accessor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_accessor.xhtml">arm_compute::test::Accessor</a></div><div class="ttdoc">Accessor implementation for Tensor objects. </div><div class="ttdef"><b>Definition:</b> <a href="_accessor_8h_source.xhtml#l00035">Accessor.h:35</a></div></div>
 285 <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a71326f0909d77386e29b511e1990a11f"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">arm_compute::test::library</a></div><div class="ttdeci">std::unique_ptr&lt; AssetsLibrary &gt; library</div><div class="ttdef"><b>Definition:</b> <a href="main_8cpp_source.xhtml#l00059">main.cpp:59</a></div></div>
 286 </div><!-- fragment -->
 287 </div>
 288 </div>
 289 <a class="anchor" id="a3b778cda9ac3fad08e7217edbcb942e0"></a>
 290 <div class="memitem">
 291 <div class="memproto">
 292 <table class="mlabels">
 293   <tr>
 294   <td class="mlabels-left">
 295       <table class="memname">
 296         <tr>
 297           <td class="memname">void fill_random </td>
 298           <td>(</td>
 299           <td class="paramname"></td><td>)</td>
 300           <td></td>
 301         </tr>
 302       </table>
 303   </td>
 304   <td class="mlabels-right">
 305 <span class="mlabels"><span class="mlabel">inline</span></span>  </td>
 306   </tr>
 307 </table>
 308 </div><div class="memdoc">
 309
 310 <p>Fills the trainable parameters and input with random data. </p>
 311
 312 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00162">162</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 313 <div class="fragment"><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    {</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>                     seed_idx = 0;</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;        std::uniform_real_distribution&lt;&gt; distribution(-1, 1);</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(input), distribution, seed_idx++);</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(w_conv3x3), distribution, seed_idx++);</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(mean_conv3x3), distribution, seed_idx++);</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(var_conv3x3), distribution, seed_idx++);</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(beta_conv3x3), distribution, seed_idx++);</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(gamma_conv3x3), distribution, seed_idx++);</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;        <a class="code" href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(w_conv.size() != w_dwc.size());</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; w_conv.size(); ++i)</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        {</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(w_dwc[i]), distribution, seed_idx++);</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(bn_mean[2 * i]), distribution, seed_idx++);</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(bn_var[2 * i]), distribution, seed_idx++);</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(bn_beta[2 * i]), distribution, seed_idx++);</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(bn_gamma[2 * i]), distribution, seed_idx++);</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(w_conv[i]), distribution, seed_idx++);</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(bn_mean[2 * i + 1]), distribution, seed_idx++);</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(bn_var[2 * i + 1]), distribution, seed_idx++);</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(bn_beta[2 * i + 1]), distribution, seed_idx++);</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;            <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(bn_gamma[2 * i + 1]), distribution, seed_idx++);</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;        }</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(w_conv1c), distribution, seed_idx++);</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(b_conv1c), distribution, seed_idx++);</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    }</div><div class="ttc" id="core_2_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00306">Error.h:306</a></div></div>
 314 <div class="ttc" id="classarm__compute_1_1test_1_1_accessor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_accessor.xhtml">arm_compute::test::Accessor</a></div><div class="ttdoc">Accessor implementation for Tensor objects. </div><div class="ttdef"><b>Definition:</b> <a href="_accessor_8h_source.xhtml#l00035">Accessor.h:35</a></div></div>
 315 <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a71326f0909d77386e29b511e1990a11f"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">arm_compute::test::library</a></div><div class="ttdeci">std::unique_ptr&lt; AssetsLibrary &gt; library</div><div class="ttdef"><b>Definition:</b> <a href="main_8cpp_source.xhtml#l00059">main.cpp:59</a></div></div>
 316 </div><!-- fragment -->
 317 </div>
 318 </div>
 319 <a class="anchor" id="a1466ef70729f3c8b5da5ebfec3f53f26"></a>
 320 <div class="memitem">
 321 <div class="memproto">
 322 <table class="mlabels">
 323   <tr>
 324   <td class="mlabels-left">
 325       <table class="memname">
 326         <tr>
 327           <td class="memname">std::vector&lt;unsigned int&gt; get_classifications </td>
 328           <td>(</td>
 329           <td class="paramname"></td><td>)</td>
 330           <td></td>
 331         </tr>
 332       </table>
 333   </td>
 334   <td class="mlabels-right">
 335 <span class="mlabels"><span class="mlabel">inline</span></span>  </td>
 336   </tr>
 337 </table>
 338 </div><div class="memdoc">
 339
 340 <p>Get the classification results. </p>
 341 <dl class="section return"><dt>Returns</dt><dd><a class="el" href="struct_vector.xhtml" title="Structure to hold Vector information. ">Vector</a> containing the classified labels </dd></dl>
 342
 343 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00205">205</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 344 <div class="fragment"><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    {</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;        std::vector&lt;unsigned int&gt; classified_labels;</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        <a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>                  output_accessor(output);</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;        <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> window;</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;        window.<a class="code" href="classarm__compute_1_1_window.xhtml#acd3d2bba51cb84d34dd7656ad2375a6e">set</a>(<a class="code" href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">Window::DimX</a>, <a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml">Window::Dimension</a>(0, 1, 1));</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> d = 1; d &lt; output_accessor.shape().num_dimensions(); ++d)</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;        {</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;            window.<a class="code" href="classarm__compute_1_1_window.xhtml#acd3d2bba51cb84d34dd7656ad2375a6e">set</a>(d, <a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml">Window::Dimension</a>(0, output_accessor.shape()[d], 1));</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;        }</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;        <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(window, [&amp;](<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp; <span class="keywordtype">id</span>)</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;        {</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;            <span class="keywordtype">int</span>               max_idx = 0;</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;            <span class="keywordtype">float</span>             val     = 0;</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;            <span class="keyword">const</span> <span class="keywordtype">void</span> *<span class="keyword">const</span> out_ptr = output_accessor(<span class="keywordtype">id</span>);</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;            <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> l = 0; l &lt; output_accessor.shape().x(); ++l)</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;            {</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;                <span class="keywordtype">float</span> curr_val = <span class="keyword">reinterpret_cast&lt;</span><span class="keyword">const </span><span class="keywordtype">float</span> *<span class="keyword">&gt;</span>(out_ptr)[l];</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;                <span class="keywordflow">if</span>(curr_val &gt; val)</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;                {</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;                    max_idx = l;</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;                    val     = curr_val;</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;                }</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;            }</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;            classified_labels.push_back(max_idx);</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;        });</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;        <span class="keywordflow">return</span> classified_labels;</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;    }</div><div class="ttc" id="classarm__compute_1_1_window_1_1_dimension_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window_1_1_dimension.xhtml">arm_compute::Window::Dimension</a></div><div class="ttdoc">Describe one of the image&amp;#39;s dimensions with a start, end and step. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00068">Window.h:68</a></div></div>
 345 <div class="ttc" id="classarm__compute_1_1test_1_1_accessor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_accessor.xhtml">arm_compute::test::Accessor</a></div><div class="ttdoc">Accessor implementation for Tensor objects. </div><div class="ttdef"><b>Definition:</b> <a href="_accessor_8h_source.xhtml#l00035">Accessor.h:35</a></div></div>
 346 <div class="ttc" id="classarm__compute_1_1_window_xhtml_aa96e81276ee4f87ab386cd05a5539a7d"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">arm_compute::Window::DimX</a></div><div class="ttdeci">static constexpr size_t DimX</div><div class="ttdoc">Alias for dimension 0 also known as X dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00043">Window.h:43</a></div></div>
 347 <div class="ttc" id="namespacearm__compute_xhtml_a6c0dcc38187027dcb89cd9724bc5a823"><div class="ttname"><a href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">arm_compute::execute_window_loop</a></div><div class="ttdeci">void execute_window_loop(const Window &amp;w, L &amp;&amp;lambda_function, Ts &amp;&amp;...iterators)</div><div class="ttdoc">Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00122">Helpers.inl:122</a></div></div>
 348 <div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item. </div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
 349 <div class="ttc" id="classarm__compute_1_1_window_xhtml_acd3d2bba51cb84d34dd7656ad2375a6e"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#acd3d2bba51cb84d34dd7656ad2375a6e">arm_compute::Window::set</a></div><div class="ttdeci">void set(size_t dimension, const Dimension &amp;dim)</div><div class="ttdoc">Set the values of a given dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8inl_source.xhtml#l00041">Window.inl:41</a></div></div>
 350 <div class="ttc" id="classarm__compute_1_1_window_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml">arm_compute::Window</a></div><div class="ttdoc">Describe a multidimensional execution window. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00039">Window.h:39</a></div></div>
 351 </div><!-- fragment -->
 352 </div>
 353 </div>
 354 <a class="anchor" id="a3b81d78cb73291bea06a00d70ad09b5d"></a>
 355 <div class="memitem">
 356 <div class="memproto">
 357 <table class="mlabels">
 358   <tr>
 359   <td class="mlabels-left">
 360       <table class="memname">
 361         <tr>
 362           <td class="memname">void init </td>
 363           <td>(</td>
 364           <td class="paramtype">unsigned int&#160;</td>
 365           <td class="paramname"><em>input_spatial_size</em>, </td>
 366         </tr>
 367         <tr>
 368           <td class="paramkey"></td>
 369           <td></td>
 370           <td class="paramtype">int&#160;</td>
 371           <td class="paramname"><em>batches</em>&#160;</td>
 372         </tr>
 373         <tr>
 374           <td></td>
 375           <td>)</td>
 376           <td></td><td></td>
 377         </tr>
 378       </table>
 379   </td>
 380   <td class="mlabels-right">
 381 <span class="mlabels"><span class="mlabel">inline</span></span>  </td>
 382   </tr>
 383 </table>
 384 </div><div class="memdoc">
 385
 386 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00058">58</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 387 <div class="fragment"><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    {</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;        _batches            = batches;</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;        _input_spatial_size = input_spatial_size;</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;        <span class="comment">// Currently supported sizes</span></div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;        <a class="code" href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(input_spatial_size != 128 &amp;&amp; input_spatial_size != 224);</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;        <span class="comment">// Initialize input, output</span></div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        input.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(input_spatial_size, input_spatial_size, 3U, _batches), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;        output.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1001U, _batches), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;        <span class="comment">// Initialize weights and biases</span></div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;        w_conv3x3.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U, 3U, 3U, 32U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        mean_conv3x3.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(32U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        var_conv3x3.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(32U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        beta_conv3x3.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(32U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;        gamma_conv3x3.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(32U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;        depthwise_conv_block_init(0, 32, 32);</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;        depthwise_conv_block_init(1, 32, 64);</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;        depthwise_conv_block_init(2, 64, 64);</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;        depthwise_conv_block_init(3, 64, 128);</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;        depthwise_conv_block_init(4, 128, 256);</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;        depthwise_conv_block_init(5, 256, 512);</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;        depthwise_conv_block_init(6, 512, 512);</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;        depthwise_conv_block_init(7, 512, 512);</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;        depthwise_conv_block_init(8, 512, 512);</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;        depthwise_conv_block_init(9, 512, 512);</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;        depthwise_conv_block_init(10, 512, 512);</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;        depthwise_conv_block_init(11, 512, 1024);</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;        depthwise_conv_block_init(12, 1024, 1024);</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        w_conv1c.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1U, 1U, 1024U, 1001U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;        b_conv1c.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1001U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        <span class="comment">// Init reshaped output</span></div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;        reshape_out.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1001U, _batches), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    }</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>
 388 <div class="ttc" id="core_2_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00306">Error.h:306</a></div></div>
 389 <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel </div></div>
 390 <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor&amp;#39;s metadata. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00044">TensorInfo.h:44</a></div></div>
 391 </div><!-- fragment -->
 392 </div>
 393 </div>
 394 <a class="anchor" id="a13a43e6d814de94978c515cb084873b1"></a>
 395 <div class="memitem">
 396 <div class="memproto">
 397 <table class="mlabels">
 398   <tr>
 399   <td class="mlabels-left">
 400       <table class="memname">
 401         <tr>
 402           <td class="memname">void run </td>
 403           <td>(</td>
 404           <td class="paramname"></td><td>)</td>
 405           <td></td>
 406         </tr>
 407       </table>
 408   </td>
 409   <td class="mlabels-right">
 410 <span class="mlabels"><span class="mlabel">inline</span></span>  </td>
 411   </tr>
 412 </table>
 413 </div><div class="memdoc">
 414
 415 <p>Runs the model. </p>
 416
 417 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00279">279</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 418 <div class="fragment"><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;    {</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;        conv3x3.run();</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;        conv3x3_bn.run();</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;        conv3x3_act.run();</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;        depthwise_conv_block_run(0);</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;        depthwise_conv_block_run(1);</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;        depthwise_conv_block_run(2);</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;        depthwise_conv_block_run(3);</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;        depthwise_conv_block_run(4);</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;        depthwise_conv_block_run(5);</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;        depthwise_conv_block_run(6);</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;        depthwise_conv_block_run(7);</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;        depthwise_conv_block_run(8);</div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;        depthwise_conv_block_run(9);</div><div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;        depthwise_conv_block_run(10);</div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;        depthwise_conv_block_run(11);</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;        depthwise_conv_block_run(12);</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;        pool.run();</div><div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;        conv1c.run();</div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;        reshape.run();</div><div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;        smx.run();</div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;    }</div></div><!-- fragment -->
 419 </div>
 420 </div>
 421 <a class="anchor" id="ad55f80ed3cd8b6c4f247763b747016af"></a>
 422 <div class="memitem">
 423 <div class="memproto">
 424 <table class="mlabels">
 425   <tr>
 426   <td class="mlabels-left">
 427       <table class="memname">
 428         <tr>
 429           <td class="memname">void sync </td>
 430           <td>(</td>
 431           <td class="paramname"></td><td>)</td>
 432           <td></td>
 433         </tr>
 434       </table>
 435   </td>
 436   <td class="mlabels-right">
 437 <span class="mlabels"><span class="mlabel">inline</span></span>  </td>
 438   </tr>
 439 </table>
 440 </div><div class="memdoc">
 441
 442 <p>Sync the results. </p>
 443
 444 <p>Definition at line <a class="el" href="_mobile_net_v1_network_8h_source.xhtml#l00304">304</a> of file <a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a>.</p>
 445 <div class="fragment"><div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    {</div><div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;        sync_if_necessary&lt;TensorType&gt;();</div><div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;        sync_tensor_if_necessary&lt;TensorType&gt;(output);</div><div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;    }</div></div><!-- fragment -->
 446 </div>
 447 </div>
 448 <hr/>The documentation for this class was generated from the following file:<ul>
 449 <li>tests/networks/<a class="el" href="_mobile_net_v1_network_8h_source.xhtml">MobileNetV1Network.h</a></li>
 450 </ul>
 451 </div><!-- contents -->
 452 </div><!-- doc-content -->
 453 <!-- start footer part -->
 454 <div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
 455   <ul>
 456     <li class="navelem"><a class="el" href="namespacearm__compute.xhtml">arm_compute</a></li><li class="navelem"><a class="el" href="namespacearm__compute_1_1test.xhtml">test</a></li><li class="navelem"><a class="el" href="namespacearm__compute_1_1test_1_1networks.xhtml">networks</a></li><li class="navelem"><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml">MobileNetV1Network</a></li>
 457     <li class="footer">Generated on Thu Feb 22 2018 15:45:26 for Compute Library by
 458     <a href="http://www.doxygen.org/index.html">
 459     <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li>
 460   </ul>
 461 </div>
 462 </body>
 463 </html>