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 <div class="textblock"><code>#include &quot;<a class="el" href="_test_utils_8hpp_source.html">TestUtils.hpp</a>&quot;</code><br />
 <code>#include &lt;<a class="el" href="_graph_8hpp_source.html">Graph.hpp</a>&gt;</code><br />
 <code>#include &lt;<a class="el" href="_optimizer_8hpp_source.html">Optimizer.hpp</a>&gt;</code><br />
 <code>#include &lt;<a class="el" href="_floating_point_converter_8hpp_source.html">armnnUtils/FloatingPointConverter.hpp</a>&gt;</code><br />
 <code>#include &lt;<a class="el" href="_cpu_tensor_handle_8hpp_source.html">backendsCommon/CpuTensorHandle.hpp</a>&gt;</code><br />
 <code>#include &lt;boost/test/unit_test.hpp&gt;</code><br />
 </div>
 <p><a href="_optimizer_tests_8cpp_source.html">Go to the source code of this file.</a></p>
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 Functions</h2></td></tr>
 <tr class="memitem:a8839099137f1031b504d76090074142c"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a8839099137f1031b504d76090074142c">BOOST_AUTO_TEST_CASE</a> (LSTMValidateTensorShapesFromInputsCIFGDisabledTest)</td></tr>
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 <tr class="memitem:a09fa0a0ab3199f1a7bfc169bce93925d"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a09fa0a0ab3199f1a7bfc169bce93925d">BOOST_AUTO_TEST_CASE</a> (InsertConvertersTest)</td></tr>
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 <tr class="memitem:a5065b32dd0aa2c08ef75e953ebedbc16"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr>
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 <tr class="separator:a6b7bebf2c0d384c3297a6c3b19346555"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a67738cd9d506e11aa4f4f43b9dc30e2c"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a67738cd9d506e11aa4f4f43b9dc30e2c">BOOST_AUTO_TEST_CASE</a> (Conv2dValidateTensorShapesFromInputsNhwc)</td></tr>
 <tr class="separator:a67738cd9d506e11aa4f4f43b9dc30e2c"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:acd97facea671e23ec3e8b33c6c2ea321"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr>
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 <tr class="memitem:a4756218150e4ca0da09d0ecc390a7a17"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;graph, const unsigned int *inputShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr>
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 <tr class="memitem:aefb2c7f14f687a9432490a1bdee05458"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;graph, const unsigned int *inputShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr>
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 <tr class="memitem:acee9ba1427bd42cc38a0402969dd0d35"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#acee9ba1427bd42cc38a0402969dd0d35">BOOST_AUTO_TEST_CASE</a> (ResizeBilinearValidateTensorShapesFromInputs)</td></tr>
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 <tr class="memitem:aa4e793c84e5dfea800d4dba921651e5b"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;graph, const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> &amp;paramsInfo, const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> &amp;indicesInfo, const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> &amp;outputInfo)</td></tr>
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 <h2 class="groupheader">Function Documentation</h2>
 <a id="a8839099137f1031b504d76090074142c"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#a8839099137f1031b504d76090074142c">&#9670;&nbsp;</a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[1/16]</span></h2>

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           <td class="memname">BOOST_AUTO_TEST_CASE </td>
           <td>(</td>
           <td class="paramtype">LSTMValidateTensorShapesFromInputsCIFGDisabledTest&#160;</td>
           <td class="paramname"></td><td>)</td>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00134">134</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;{</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    <span class="comment">//Helper function creates graph containing LSTM layer with required input and output layers</span></div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    CreateLSTMLayerHelper(graph, <span class="keyword">false</span>);</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    <span class="comment">//This function used to call ValidateShapesFromInputs();</span></div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
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 <a id="a10342b734f73496052047f2b74b38cca"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#a10342b734f73496052047f2b74b38cca">&#9670;&nbsp;</a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[2/16]</span></h2>

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           <td class="memname">BOOST_AUTO_TEST_CASE </td>
           <td>(</td>
           <td class="paramtype">LSTMValidateTensorShapesFromInputsCIFGEnabledTest&#160;</td>
           <td class="paramname"></td><td>)</td>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00145">145</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;{</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <span class="comment">//Helper function creates graph containing LSTM layer with required input and output layers</span></div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    CreateLSTMLayerHelper(graph, <span class="keyword">true</span>);</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    <span class="comment">//This function used to call ValidateShapesFromInputs();</span></div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
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 <h2 class="memtitle"><span class="permalink"><a href="#a09fa0a0ab3199f1a7bfc169bce93925d">&#9670;&nbsp;</a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[3/16]</span></h2>

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 </div><div class="memdoc">

 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00156">156</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">armnn::Addition</a>, <a class="el" href="_test_utils_8hpp_source.html#l00020">CheckSequence()</a>, <a class="el" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">armnn::ConvertFp16ToFp32</a>, <a class="el" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">armnn::ConvertFp32ToFp16</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::Float16</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::Floor</a>, <a class="el" href="_tensor_8hpp_source.html#l00095">TensorInfo::GetDataType()</a>, <a class="el" href="_layer_8cpp_source.html#l00272">Layer::GetDataType()</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00221">Layer::GetOutputHandler()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_layer_8cpp_source.html#l00063">OutputSlot::GetTensorInfo()</a>, <a class="el" href="_layer_8hpp_source.html#l00259">Layer::GetType()</a>, <a class="el" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="_network_utils_8cpp_source.html#l00040">armnn::InsertConvertFp16ToFp32LayersBefore()</a>, <a class="el" href="_network_utils_8cpp_source.html#l00079">armnn::InsertConvertFp32ToFp16LayersAfter()</a>, and <a class="el" href="_output_handler_8cpp_source.html#l00017">OutputHandler::SetTensorInfo()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;{</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 5, 2, 3 }, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">armnn::Graph</a> graph;</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> inputId = 0;</div><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;    <a class="code" href="classarmnn_1_1_layer.html">armnn::Layer</a>* head = graph.AddLayer&lt;<a class="code" href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    head = graph.InsertNewLayer&lt;<a class="code" href="classarmnn_1_1_addition_layer.html">armnn::AdditionLayer</a>&gt;(head-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), <span class="stringliteral">&quot;&quot;</span>);</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    head-&gt;<a class="code" href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>().<a class="code" href="classarmnn_1_1_output_handler.html#a97db12c41024f5545ef5cc4153e5443b">SetTensorInfo</a>(info);</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;    graph.InsertNewLayer&lt;<a class="code" href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a>&gt;(head-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1), inputId++, <span class="stringliteral">&quot;&quot;</span>)</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;        -&gt;GetOutputHandler().SetTensorInfo(info);</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;    head = graph.InsertNewLayer&lt;<a class="code" href="classarmnn_1_1_floor_layer.html">armnn::FloorLayer</a>&gt;(head-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), <span class="stringliteral">&quot;&quot;</span>);</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;    head-&gt;<a class="code" href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>().<a class="code" href="classarmnn_1_1_output_handler.html#a97db12c41024f5545ef5cc4153e5443b">SetTensorInfo</a>(info);</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    head = graph.InsertNewLayer&lt;<a class="code" href="classarmnn_1_1_mem_copy_layer.html">armnn::MemCopyLayer</a>&gt;(head-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), <span class="stringliteral">&quot;&quot;</span>);</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    head-&gt;<a class="code" href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>().<a class="code" href="classarmnn_1_1_output_handler.html#a97db12c41024f5545ef5cc4153e5443b">SetTensorInfo</a>(info);</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    graph.InsertNewLayer&lt;<a class="code" href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a>&gt;(head-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), inputId++, <span class="stringliteral">&quot;&quot;</span>)</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;        -&gt;GetOutputHandler().SetTensorInfo(info);</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;    <span class="comment">// Check graph layer sequence before inserting convert layers</span></div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    BOOST_TEST(<a class="code" href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.cbegin(),</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;                             graph.cend(),</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;                             &amp;IsLayerOfType&lt;armnn::InputLayer&gt;,</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;                             &amp;IsLayerOfType&lt;armnn::InputLayer&gt;,</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;                             &amp;IsLayerOfType&lt;armnn::MemCopyLayer&gt;,</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;                             &amp;IsLayerOfType&lt;armnn::FloorLayer&gt;,</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;                             &amp;IsLayerOfType&lt;armnn::AdditionLayer&gt;,</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;                             &amp;IsLayerOfType&lt;armnn::OutputLayer&gt;));</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;    <span class="comment">// Check layers have Float16 DataType</span></div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;    <span class="keywordflow">for</span> (<span class="keyword">auto</span>&amp; layer : graph)</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;    {</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;        <span class="keywordflow">if</span>(layer-&gt;GetType()==LayerType::Floor || layer-&gt;GetType() == LayerType::Addition)</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;        {</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;            BOOST_ASSERT(layer-&gt;GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float16);</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;            BOOST_ASSERT(layer-&gt;GetDataType() == DataType::Float16);</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;        }</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    }</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    <span class="comment">// Insert convert layers either side of unsupported layer</span></div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;    <span class="keywordflow">for</span> (<span class="keyword">auto</span>&amp; layer : graph)</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    {</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;        <span class="keywordflow">if</span>(layer-&gt;GetType()==LayerType::Floor || layer-&gt;GetType() == LayerType::Addition)</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        {</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;            <a class="code" href="namespacearmnn.html#ad31c56533e4f9f9f51719599fbfcf7bb">InsertConvertFp16ToFp32LayersBefore</a>(graph, *layer);</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;            <a class="code" href="namespacearmnn.html#abf625e50a5eaeafce5b39580dc95a9d3">InsertConvertFp32ToFp16LayersAfter</a>(graph, *layer);</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        }</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;</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    <span class="comment">// Check layers have correct DataType after inserting convert layers</span></div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;    <span class="keywordflow">for</span> (<span class="keyword">auto</span>&amp; layer : graph)</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;        <span class="keywordflow">if</span> (layer-&gt;GetType()==LayerType::Floor || layer-&gt;GetType() == LayerType::Addition)</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;            BOOST_ASSERT(layer-&gt;GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float32);</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;            BOOST_ASSERT(layer-&gt;GetDataType() == DataType::Float32);</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="keywordflow">else</span> <span class="keywordflow">if</span> (layer-&gt;GetType() == LayerType::ConvertFp16ToFp32)</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;        {</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;            BOOST_ASSERT(layer-&gt;GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float32);</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;            BOOST_ASSERT(layer-&gt;GetDataType() == DataType::Float16);</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="keywordflow">else</span> <span class="keywordflow">if</span> (layer-&gt;GetType() == LayerType::ConvertFp32ToFp16)</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;        {</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;            BOOST_ASSERT(layer-&gt;GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float16);</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;            BOOST_ASSERT(layer-&gt;GetDataType() == DataType::Float32);</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;        }</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;    <span class="comment">// Check sequence of layers after inserting convert layers</span></div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    BOOST_TEST(<a class="code" href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.cbegin(),</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;                             graph.cend(),</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;                             &amp;IsLayerOfType&lt;armnn::InputLayer&gt;,</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;                             &amp;IsLayerOfType&lt;armnn::InputLayer&gt;,</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;                             &amp;IsLayerOfType&lt;armnn::ConvertFp16ToFp32Layer&gt;,</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;                             &amp;IsLayerOfType&lt;armnn::MemCopyLayer&gt;,</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;                             &amp;IsLayerOfType&lt;armnn::ConvertFp16ToFp32Layer&gt;,</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;                             &amp;IsLayerOfType&lt;armnn::FloorLayer&gt;,</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;                             &amp;IsLayerOfType&lt;armnn::ConvertFp32ToFp16Layer&gt;,</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;                             &amp;IsLayerOfType&lt;armnn::ConvertFp16ToFp32Layer&gt;,</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;                             &amp;IsLayerOfType&lt;armnn::AdditionLayer&gt;,</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;                             &amp;IsLayerOfType&lt;armnn::ConvertFp32ToFp16Layer&gt;,</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;                             &amp;IsLayerOfType&lt;armnn::OutputLayer&gt;));</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_layer_html_af2c0edc7ea62a8baaec4d3d9b2b09256"><div class="ttname"><a href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">armnn::Layer::GetOutputHandler</a></div><div class="ttdeci">const OutputHandler &amp; GetOutputHandler(unsigned int i=0) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00221">Layer.hpp:221</a></div></div>
 <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div>
 <div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
 <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
 <div class="ttc" id="classarmnn_1_1_mem_copy_layer_html"><div class="ttname"><a href="classarmnn_1_1_mem_copy_layer.html">armnn::MemCopyLayer</a></div><div class="ttdoc">This layer represents a memory copy operation. </div><div class="ttdef"><b>Definition:</b> <a href="_mem_copy_layer_8hpp_source.html#l00013">MemCopyLayer.hpp:13</a></div></div>
 <div class="ttc" id="classarmnn_1_1_floor_layer_html"><div class="ttname"><a href="classarmnn_1_1_floor_layer.html">armnn::FloorLayer</a></div><div class="ttdoc">This layer represents a floor operation. </div><div class="ttdef"><b>Definition:</b> <a href="_floor_layer_8hpp_source.html#l00013">FloorLayer.hpp:13</a></div></div>
 <div class="ttc" id="namespacearmnn_html_abf625e50a5eaeafce5b39580dc95a9d3"><div class="ttname"><a href="namespacearmnn.html#abf625e50a5eaeafce5b39580dc95a9d3">armnn::InsertConvertFp32ToFp16LayersAfter</a></div><div class="ttdeci">std::vector&lt; ConvertFp32ToFp16Layer * &gt; InsertConvertFp32ToFp16LayersAfter(Graph &amp;graph, Layer &amp;layer)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.html#l00079">NetworkUtils.cpp:79</a></div></div>
 <div class="ttc" id="_test_utils_8hpp_html_a0eedb278f57355b47fa983450d4e378c"><div class="ttname"><a href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a></div><div class="ttdeci">bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8hpp_source.html#l00020">TestUtils.hpp:20</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_handler_html_a97db12c41024f5545ef5cc4153e5443b"><div class="ttname"><a href="classarmnn_1_1_output_handler.html#a97db12c41024f5545ef5cc4153e5443b">armnn::OutputHandler::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo)</div><div class="ttdoc">Sets the TensorInfo used by this output handler. </div><div class="ttdef"><b>Definition:</b> <a href="_output_handler_8cpp_source.html#l00017">OutputHandler.cpp:17</a></div></div>
 <div class="ttc" id="classarmnn_1_1_addition_layer_html"><div class="ttname"><a href="classarmnn_1_1_addition_layer.html">armnn::AdditionLayer</a></div><div class="ttdoc">This layer represents an addition operation. </div><div class="ttdef"><b>Definition:</b> <a href="_addition_layer_8hpp_source.html#l00013">AdditionLayer.hpp:13</a></div></div>
 <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
 <div class="ttc" id="namespacearmnn_html_ad31c56533e4f9f9f51719599fbfcf7bb"><div class="ttname"><a href="namespacearmnn.html#ad31c56533e4f9f9f51719599fbfcf7bb">armnn::InsertConvertFp16ToFp32LayersBefore</a></div><div class="ttdeci">std::vector&lt; ConvertFp16ToFp32Layer * &gt; InsertConvertFp16ToFp32LayersBefore(Graph &amp;graph, Layer &amp;layer, bool expectCorrectInputType)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.html#l00040">NetworkUtils.cpp:40</a></div></div>
 <div class="ttc" id="namespacearmnn_html_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a></div><div class="ttdeci">int LayerBindingId</div><div class="ttdoc">Type of identifiers for bindable layers (inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00168">Types.hpp:168</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00277">277</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00249">CreateConvolution2dGraph()</a>, and <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;{</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 3, 8, 16 };</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { 2, 3, 5, 3 };</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 2, 4, 14 };</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape);</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
 <div class="ttc" id="_optimizer_tests_8cpp_html_a5065b32dd0aa2c08ef75e953ebedbc16"><div class="ttname"><a href="_optimizer_tests_8cpp.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a></div><div class="ttdeci">void CreateConvolution2dGraph(Graph &amp;graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00249">OptimizerTests.cpp:249</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00288">288</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00249">CreateConvolution2dGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p>
 <div class="fragment"><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;{</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 8, 16, 3 };</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { 2, 5, 3, 3 };</div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 4, 14, 2 };</div><div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
 <div class="ttc" id="_optimizer_tests_8cpp_html_a5065b32dd0aa2c08ef75e953ebedbc16"><div class="ttname"><a href="_optimizer_tests_8cpp.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a></div><div class="ttdeci">void CreateConvolution2dGraph(Graph &amp;graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00249">OptimizerTests.cpp:249</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00327">327</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00299">CreateDepthwiseConvolution2dGraph()</a>, and <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;{</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 2, 3, 3 };</div><div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { 1, 2, 3, 3 };</div><div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 2, 1, 1 };</div><div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape);</div><div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;</div><div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;}</div><div class="ttc" id="_optimizer_tests_8cpp_html_acd97facea671e23ec3e8b33c6c2ea321"><div class="ttname"><a href="_optimizer_tests_8cpp.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a></div><div class="ttdeci">void CreateDepthwiseConvolution2dGraph(Graph &amp;graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00299">OptimizerTests.cpp:299</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00338">338</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00299">CreateDepthwiseConvolution2dGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p>
 <div class="fragment"><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;{</div><div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 3, 3, 2 };</div><div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { 1, 2, 3, 3 };</div><div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 1, 1, 2 };</div><div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;</div><div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;}</div><div class="ttc" id="_optimizer_tests_8cpp_html_acd97facea671e23ec3e8b33c6c2ea321"><div class="ttname"><a href="_optimizer_tests_8cpp.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a></div><div class="ttdeci">void CreateDepthwiseConvolution2dGraph(Graph &amp;graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00299">OptimizerTests.cpp:299</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00377">377</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00349">CreatePooling2dGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p>
 <div class="fragment"><div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;{</div><div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 5, 3, 52, 60 };</div><div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 5, 3, 11, 13 };</div><div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a>(graph, inputShape, outputShape, DataLayout::NCHW);</div><div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;</div><div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
 <div class="ttc" id="_optimizer_tests_8cpp_html_a4756218150e4ca0da09d0ecc390a7a17"><div class="ttname"><a href="_optimizer_tests_8cpp.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a></div><div class="ttdeci">void CreatePooling2dGraph(Graph &amp;graph, const unsigned int *inputShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00349">OptimizerTests.cpp:349</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00387">387</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00349">CreatePooling2dGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p>
 <div class="fragment"><div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;{</div><div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 5, 52, 60, 3 };</div><div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 5, 11, 13, 3 };</div><div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a>(graph, inputShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;</div><div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
 <div class="ttc" id="_optimizer_tests_8cpp_html_a4756218150e4ca0da09d0ecc390a7a17"><div class="ttname"><a href="_optimizer_tests_8cpp.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a></div><div class="ttdeci">void CreatePooling2dGraph(Graph &amp;graph, const unsigned int *inputShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00349">OptimizerTests.cpp:349</a></div></div>
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           <td>(</td>
           <td class="paramtype">ResizeBilinearValidateTensorShapesFromInputs&#160;</td>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00420">420</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00397">CreateResizeBilinearGraph()</a>, and <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;{</div><div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 2, 4, 5 };</div><div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 2, 3, 4 };</div><div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a>(graph, inputShape, outputShape);</div><div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;</div><div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
 <div class="ttc" id="_optimizer_tests_8cpp_html_aefb2c7f14f687a9432490a1bdee05458"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a></div><div class="ttdeci">void CreateResizeBilinearGraph(Graph &amp;graph, const unsigned int *inputShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00397">OptimizerTests.cpp:397</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00430">430</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00397">CreateResizeBilinearGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p>
 <div class="fragment"><div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;{</div><div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 4, 5, 2 };</div><div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 3, 4, 2 };</div><div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a>(graph, inputShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;</div><div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
 <div class="ttc" id="_optimizer_tests_8cpp_html_aefb2c7f14f687a9432490a1bdee05458"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a></div><div class="ttdeci">void CreateResizeBilinearGraph(Graph &amp;graph, const unsigned int *inputShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00397">OptimizerTests.cpp:397</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00459">459</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00441">CreateGatherGraph()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p>
 <div class="fragment"><div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;{</div><div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> paramsInfo({10, 5}, DataType::Float32);</div><div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> indicesInfo({3}, DataType::Signed32);</div><div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo({3, 5}, DataType::Float32);</div><div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;</div><div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a>(graph, paramsInfo, indicesInfo, outputInfo);</div><div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;</div><div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="_optimizer_tests_8cpp_html_aa4e793c84e5dfea800d4dba921651e5b"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a></div><div class="ttdeci">void CreateGatherGraph(Graph &amp;graph, const armnn::TensorInfo &amp;paramsInfo, const armnn::TensorInfo &amp;indicesInfo, const armnn::TensorInfo &amp;outputInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00441">OptimizerTests.cpp:441</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00471">471</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00441">CreateGatherGraph()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p>
 <div class="fragment"><div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;{</div><div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> paramsInfo({8}, DataType::Float32);</div><div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> indicesInfo({5}, DataType::Signed32);</div><div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo( {5}, DataType::Float32);</div><div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;</div><div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a>(graph, paramsInfo, indicesInfo, outputInfo);</div><div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;</div><div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="_optimizer_tests_8cpp_html_aa4e793c84e5dfea800d4dba921651e5b"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a></div><div class="ttdeci">void CreateGatherGraph(Graph &amp;graph, const armnn::TensorInfo &amp;paramsInfo, const armnn::TensorInfo &amp;indicesInfo, const armnn::TensorInfo &amp;outputInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00441">OptimizerTests.cpp:441</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00483">483</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00441">CreateGatherGraph()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p>
 <div class="fragment"><div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;{</div><div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> paramsInfo({3, 2, 5}, DataType::Float32);</div><div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> indicesInfo({2, 2}, DataType::Signed32);</div><div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo({2, 2, 2, 5}, DataType::Float32);</div><div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;</div><div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;    <a class="code" href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a>(graph, paramsInfo, indicesInfo, outputInfo);</div><div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;</div><div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div>
 <div class="ttc" id="_optimizer_tests_8cpp_html_aa4e793c84e5dfea800d4dba921651e5b"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a></div><div class="ttdeci">void CreateGatherGraph(Graph &amp;graph, const armnn::TensorInfo &amp;paramsInfo, const armnn::TensorInfo &amp;indicesInfo, const armnn::TensorInfo &amp;outputInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00441">OptimizerTests.cpp:441</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
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 <h2 class="memtitle"><span class="permalink"><a href="#a0ee7b0e1f8d1dd9a9e001720e69086eb">&#9670;&nbsp;</a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[15/16]</span></h2>

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           <td class="memname">BOOST_AUTO_TEST_CASE </td>
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           <td class="paramtype">DetectionPostProcessValidateTensorShapes&#160;</td>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00495">495</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_neon_end_to_end_tests_8cpp.html#ac0981848e4ae57729f14f72bd4caa9f8">anchors()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, <a class="el" href="_detection_post_process_layer_8hpp_source.html#l00020">DetectionPostProcessLayer::m_Anchors</a>, <a class="el" href="_descriptors_8hpp_source.html#l00527">DetectionPostProcessDescriptor::m_MaxDetections</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::QAsymmU8</a>, <a class="el" href="_neon_end_to_end_tests_8cpp.html#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;{</div><div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> boxEncodingsInfo({1, 10, 4}, DataType::QAsymmU8);</div><div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> <a class="code" href="_neon_end_to_end_tests_8cpp.html#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>({1, 10, 4}, DataType::QAsymmU8);</div><div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;    std::vector&lt;uint8_t&gt; anchorsVector(40);</div><div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> <a class="code" href="_neon_end_to_end_tests_8cpp.html#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({10, 4}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>), anchorsVector);</div><div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;</div><div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> detectionBoxesInfo({1, 3, 4}, DataType::QAsymmU8);</div><div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> detectionScoresInfo({1, 3}, DataType::QAsymmU8);</div><div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> detectionClassesInfo({1, 3}, DataType::QAsymmU8);</div><div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> numDetectionInfo({1}, DataType::QAsymmU8);</div><div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;</div><div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input0 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;boxEncodings&quot;</span>);</div><div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;    input0-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(boxEncodingsInfo);</div><div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;</div><div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input1 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(1, <span class="stringliteral">&quot;score&quot;</span>);</div><div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;    input1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(<a class="code" href="_neon_end_to_end_tests_8cpp.html#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>);</div><div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;</div><div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;    <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html">DetectionPostProcessDescriptor</a> descriptor;</div><div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a> = 3;</div><div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;</div><div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;    <a class="code" href="classarmnn_1_1_detection_post_process_layer.html">DetectionPostProcessLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_detection_post_process_layer.html">DetectionPostProcessLayer</a>&gt;(descriptor, <span class="stringliteral">&quot;detectionPostProcess&quot;</span>);</div><div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_detection_post_process_layer.html#a6844fecab0edaf324de5a57fee8b65f1">m_Anchors</a> = std::make_unique&lt;armnn::ScopedCpuTensorHandle&gt;(<a class="code" href="_neon_end_to_end_tests_8cpp.html#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>);</div><div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(detectionBoxesInfo);</div><div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(detectionScoresInfo);</div><div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(detectionClassesInfo);</div><div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(3).<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(numDetectionInfo);</div><div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;</div><div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;    input0-&gt;GetOutputSlot().Connect(layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;    input1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;</div><div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;    BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_detection_post_process_layer_html_a6844fecab0edaf324de5a57fee8b65f1"><div class="ttname"><a href="classarmnn_1_1_detection_post_process_layer.html#a6844fecab0edaf324de5a57fee8b65f1">armnn::DetectionPostProcessLayer::m_Anchors</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_Anchors</div><div class="ttdoc">A unique pointer to store Anchor values. </div><div class="ttdef"><b>Definition:</b> <a href="_detection_post_process_layer_8hpp_source.html#l00020">DetectionPostProcessLayer.hpp:20</a></div></div>
 <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div>
 <div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div>
 <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
 <div class="ttc" id="classarmnn_1_1_detection_post_process_layer_html"><div class="ttname"><a href="classarmnn_1_1_detection_post_process_layer.html">armnn::DetectionPostProcessLayer</a></div><div class="ttdoc">This layer represents a detection postprocess operator. </div><div class="ttdef"><b>Definition:</b> <a href="_detection_post_process_layer_8hpp_source.html#l00016">DetectionPostProcessLayer.hpp:16</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
 <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &amp;destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div>
 <div class="ttc" id="_neon_end_to_end_tests_8cpp_html_a64c1dd1b6dd60be9f4a16db9c8f427a5"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.html#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a></div><div class="ttdeci">armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::Float32)</div></div>
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 <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div>
 <div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00495">Descriptors.hpp:495</a></div></div>
 <div class="ttc" id="_neon_end_to_end_tests_8cpp_html_ac0981848e4ae57729f14f72bd4caa9f8"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.html#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a></div><div class="ttdeci">std::vector&lt; float &gt; anchors({ 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 100.5f, 1.0f, 1.0f })</div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div>
 <div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_html_ae72089bcab60ac175557f4241b16a014"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html#ae72089bcab60ac175557f4241b16a014">armnn::DetectionPostProcessDescriptor::m_MaxDetections</a></div><div class="ttdeci">uint32_t m_MaxDetections</div><div class="ttdoc">Maximum numbers of detections. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00527">Descriptors.hpp:527</a></div></div>
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           <td class="memname">BOOST_AUTO_TEST_CASE </td>
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           <td class="paramtype">FoldPadLayerIntoConvolution2dLayer&#160;</td>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00530">530</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END()</a>, <a class="el" href="_graph_8hpp_source.html#l00168">Graph::cbegin()</a>, <a class="el" href="_graph_8hpp_source.html#l00170">Graph::cend()</a>, <a class="el" href="_test_utils_8hpp_source.html#l00020">CheckSequence()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00216">Layer::GetNameStr()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_layer_with_parameters_8hpp_source.html#l00018">LayerWithParameters&lt; Parameters &gt;::GetParameters()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00438">Convolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.html#l00440">Convolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00430">Convolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l00432">Convolution2dDescriptor::m_StrideY</a>, <a class="el" href="_convolution2d_layer_8hpp_source.html#l00020">Convolution2dLayer::m_Weight</a>, <a class="el" href="_optimizer_8hpp_source.html#l00043">armnn::MakeOptimizations()</a>, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>, <a class="el" href="_optimizer_8cpp_source.html#l00016">Optimizer::Pass()</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;{</div><div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 2, 2, 3 };</div><div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paddedShape[] = { 1, 6, 6, 3 };</div><div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { 1, 2, 3, 3 };</div><div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 2, 1, 1 };</div><div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;</div><div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;</div><div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> paddedInfo(4, paddedShape, DataType::Float32);</div><div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;</div><div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;</div><div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;    <a class="code" href="structarmnn_1_1_pad_descriptor.html">PadDescriptor</a> padDescriptor({{ 0, 0 }, { 2, 2 }, { 2, 2 }, { 0, 0 }});</div><div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;</div><div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;    <a class="code" href="classarmnn_1_1_pad_layer.html">PadLayer</a>* padLayer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_pad_layer.html">PadLayer</a>&gt;(padDescriptor, <span class="stringliteral">&quot;pad&quot;</span>);</div><div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;    padLayer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(paddedInfo);</div><div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;</div><div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;    <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a> convolution2dDescriptor;</div><div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;    convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;    convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;    convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;    convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = DataLayout::NHWC;</div><div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;</div><div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;    std::vector&lt;float&gt; weightsVector(18);</div><div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, weightsShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), weightsVector);</div><div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;</div><div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;    <a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>* conv2dLayer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>&gt;(convolution2dDescriptor,<span class="stringliteral">&quot;conv2d&quot;</span>);</div><div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;    conv2dLayer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique&lt;armnn::ScopedCpuTensorHandle&gt;(weights);</div><div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;    conv2dLayer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;</div><div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;</div><div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;    <span class="comment">// Connect up layers - input -&gt; pad -&gt; conv2d -&gt; output</span></div><div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(padLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;    padLayer-&gt;GetOutputSlot().Connect(conv2dLayer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;    conv2dLayer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;</div><div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160;    <span class="keyword">auto</span> checkSimpleConv2d = [ ](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.html">armnn::Layer</a>* <span class="keyword">const</span> layer) -&gt; <span class="keywordtype">bool</span></div><div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;    {</div><div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;        <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayer = <span class="keyword">static_cast&lt;</span><span class="keyword">const </span><a class="code" href="classarmnn_1_1_convolution2d_layer.html">armnn::Convolution2dLayer</a>*<span class="keyword">&gt;</span>(layer);</div><div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;        <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayerParams = conv2dLayer-&gt;<a class="code" href="classarmnn_1_1_layer_with_parameters.html#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>();</div><div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;        <span class="keywordflow">return</span> IsLayerOfType&lt;armnn::Convolution2dLayer&gt;(layer) &amp;&amp;</div><div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;            (layer-&gt;GetNameStr() == <span class="stringliteral">&quot;conv2d&quot;</span>) &amp;&amp;</div><div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;            (conv2dLayerParams.m_PadLeft == 0) &amp;&amp;</div><div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;            (conv2dLayerParams.m_PadRight == 0) &amp;&amp;</div><div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;            (conv2dLayerParams.m_PadTop == 0) &amp;&amp;</div><div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;            (conv2dLayerParams.m_PadBottom == 0) &amp;&amp;</div><div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;            (conv2dLayerParams.m_BiasEnabled == <span class="keyword">false</span>) &amp;&amp;</div><div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;            (conv2dLayerParams.m_StrideX == 1) &amp;&amp;</div><div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;            (conv2dLayerParams.m_StrideY == 1) &amp;&amp;</div><div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;            (conv2dLayerParams.m_DataLayout == DataLayout::NHWC);</div><div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;    };</div><div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;</div><div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;    BOOST_TEST(<a class="code" href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.html#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(),</div><div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;        graph.<a class="code" href="classarmnn_1_1_graph.html#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;        &amp;IsLayerOfType&lt;armnn::InputLayer&gt;,</div><div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;        &amp;IsLayerOfType&lt;armnn::PadLayer&gt;,</div><div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;        checkSimpleConv2d,</div><div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;        &amp;IsLayerOfType&lt;armnn::OutputLayer&gt;));</div><div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;</div><div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;    <a class="code" href="classarmnn_1_1_optimizer.html#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.html#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.html#add2180a15cdcf5a229de32bb956cb224">FoldPadIntoConvolution2d</a>()));</div><div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;</div><div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;    <span class="keyword">auto</span> checkPadFoldedIntoConv2d = [ ](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.html">armnn::Layer</a>* <span class="keyword">const</span> layer) -&gt; <span class="keywordtype">bool</span></div><div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;    {</div><div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;        <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayer = <span class="keyword">static_cast&lt;</span><span class="keyword">const </span><a class="code" href="classarmnn_1_1_convolution2d_layer.html">armnn::Convolution2dLayer</a>*<span class="keyword">&gt;</span>(layer);</div><div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;        <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayerParams = conv2dLayer-&gt;<a class="code" href="classarmnn_1_1_layer_with_parameters.html#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>();</div><div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;        <span class="keywordflow">return</span> IsLayerOfType&lt;armnn::Convolution2dLayer&gt;(layer) &amp;&amp;</div><div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;               (layer-&gt;GetNameStr() == <span class="stringliteral">&quot;folded-pad-into-conv2d&quot;</span>) &amp;&amp;</div><div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;               (conv2dLayerParams.m_PadLeft == 2) &amp;&amp;</div><div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;               (conv2dLayerParams.m_PadRight == 2) &amp;&amp;</div><div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;               (conv2dLayerParams.m_PadTop == 2) &amp;&amp;</div><div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;               (conv2dLayerParams.m_PadBottom == 2) &amp;&amp;</div><div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;               (conv2dLayerParams.m_BiasEnabled == <span class="keyword">false</span>) &amp;&amp;</div><div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;               (conv2dLayerParams.m_StrideX == 1) &amp;&amp;</div><div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;               (conv2dLayerParams.m_StrideY == 1) &amp;&amp;</div><div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;               (conv2dLayerParams.m_DataLayout == DataLayout::NHWC);</div><div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;    };</div><div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;</div><div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;    BOOST_TEST(<a class="code" href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.html#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(),</div><div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160;        graph.<a class="code" href="classarmnn_1_1_graph.html#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;        &amp;IsLayerOfType&lt;armnn::InputLayer&gt;,</div><div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;        checkPadFoldedIntoConv2d,</div><div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;        &amp;IsLayerOfType&lt;armnn::OutputLayer&gt;));</div><div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_pad_layer_html"><div class="ttname"><a href="classarmnn_1_1_pad_layer.html">armnn::PadLayer</a></div><div class="ttdoc">This layer represents a pad operation. </div><div class="ttdef"><b>Definition:</b> <a href="_pad_layer_8hpp_source.html#l00014">PadLayer.hpp:14</a></div></div>
 <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00440">Descriptors.hpp:440</a></div></div>
 <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div>
 <div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
 <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html">armnn::Convolution2dLayer</a></div><div class="ttdoc">This layer represents a convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00015">Convolution2dLayer.hpp:15</a></div></div>
 <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">armnn::Convolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00020">Convolution2dLayer.hpp:20</a></div></div>
 <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
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 <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div>
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 <div class="ttc" id="_test_utils_8hpp_html_a0eedb278f57355b47fa983450d4e378c"><div class="ttname"><a href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a></div><div class="ttdeci">bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8hpp_source.html#l00020">TestUtils.hpp:20</a></div></div>
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 <div class="ttc" id="classarmnn_1_1_graph_html_a98b1109a9006f8cc7d4566146a3bd737"><div class="ttname"><a href="classarmnn_1_1_graph.html#a98b1109a9006f8cc7d4566146a3bd737">armnn::Graph::cbegin</a></div><div class="ttdeci">ConstIterator cbegin() const</div><div class="ttdoc">Returns const iterator pointing to the beginning of the list. Lowercase for range-based for loops...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00168">Graph.hpp:168</a></div></div>
 <div class="ttc" id="namespacearmnn_html_aa7427025a851113a492de0b68b23d22a"><div class="ttname"><a href="namespacearmnn.html#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a></div><div class="ttdeci">Optimizer::Optimizations MakeOptimizations(Args &amp;&amp;... args)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8hpp_source.html#l00043">Optimizer.hpp:43</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a02fd29b6dc3e21fbe4484362d85893bc"><div class="ttname"><a href="classarmnn_1_1_graph.html#a02fd29b6dc3e21fbe4484362d85893bc">armnn::Graph::cend</a></div><div class="ttdeci">ConstIterator cend() const</div><div class="ttdoc">Returns const iterator pointing to the end of the list. Lowercase for range-based for loops...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00170">Graph.hpp:170</a></div></div>
 <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00392">Descriptors.hpp:392</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div>
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 <h2 class="memtitle"><span class="permalink"><a href="#a5065b32dd0aa2c08ef75e953ebedbc16">&#9670;&nbsp;</a></span>CreateConvolution2dGraph()</h2>

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           <td class="memname">void CreateConvolution2dGraph </td>
           <td>(</td>
           <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;&#160;</td>
           <td class="paramname"><em>graph</em>, </td>
         </tr>
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           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>inputShape</em>, </td>
         </tr>
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           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>weightsShape</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>outputShape</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype"><a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a>&#160;</td>
           <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code>&#160;</td>
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           <td>)</td>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00249">249</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00438">Convolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.html#l00440">Convolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00430">Convolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l00432">Convolution2dDescriptor::m_StrideY</a>, <a class="el" href="_convolution2d_layer_8hpp_source.html#l00020">Convolution2dLayer::m_Weight</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p>

 <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00277">BOOST_AUTO_TEST_CASE()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;{</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    std::vector&lt;float&gt; weightsVector(90);</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, weightsShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), weightsVector);</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;    <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a> desc;</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;    desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;    desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;    desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</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;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</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;    <a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>&gt;(desc, <span class="stringliteral">&quot;conv2d&quot;</span>);</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique&lt;armnn::ScopedCpuTensorHandle&gt;(weights);</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</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;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;}</div><div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00440">Descriptors.hpp:440</a></div></div>
 <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div>
 <div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
 <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html">armnn::Convolution2dLayer</a></div><div class="ttdoc">This layer represents a convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00015">Convolution2dLayer.hpp:15</a></div></div>
 <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">armnn::Convolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00020">Convolution2dLayer.hpp:20</a></div></div>
 <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &amp;destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div>
 <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00432">Descriptors.hpp:432</a></div></div>
 <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
 <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00430">Descriptors.hpp:430</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div>
 <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00438">Descriptors.hpp:438</a></div></div>
 <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00392">Descriptors.hpp:392</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div>
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 <h2 class="memtitle"><span class="permalink"><a href="#acd97facea671e23ec3e8b33c6c2ea321">&#9670;&nbsp;</a></span>CreateDepthwiseConvolution2dGraph()</h2>

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 <div class="memproto">
       <table class="memname">
         <tr>
           <td class="memname">void CreateDepthwiseConvolution2dGraph </td>
           <td>(</td>
           <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;&#160;</td>
           <td class="paramname"><em>graph</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>inputShape</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>weightsShape</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>outputShape</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype"><a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a>&#160;</td>
           <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code>&#160;</td>
         </tr>
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           <td></td>
           <td>)</td>
           <td></td><td></td>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00299">299</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00490">DepthwiseConvolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.html#l00492">DepthwiseConvolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00482">DepthwiseConvolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l00484">DepthwiseConvolution2dDescriptor::m_StrideY</a>, <a class="el" href="_depthwise_convolution2d_layer_8hpp_source.html#l00019">DepthwiseConvolution2dLayer::m_Weight</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p>

 <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00327">BOOST_AUTO_TEST_CASE()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;{</div><div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><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;    std::vector&lt;float&gt; weightsVector(18);</div><div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, weightsShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), weightsVector);</div><div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;</div><div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;    <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">DepthwiseConvolution2dDescriptor</a> desc;</div><div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;    desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;    desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;    desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;    desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;</div><div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;</div><div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;    <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html">DepthwiseConvolution2dLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html">DepthwiseConvolution2dLayer</a>&gt;(desc, <span class="stringliteral">&quot;depthwiseConv2d&quot;</span>);</div><div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique&lt;armnn::ScopedCpuTensorHandle&gt;(weights);</div><div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;}</div><div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::DepthwiseConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00482">Descriptors.hpp:482</a></div></div>
 <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div>
 <div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
 <div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.html">armnn::DepthwiseConvolution2dLayer</a></div><div class="ttdoc">This layer represents a depthwise convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.html#l00015">DepthwiseConvolution2dLayer.hpp:15</a></div></div>
 <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &amp;destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div>
 <div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00492">Descriptors.hpp:492</a></div></div>
 <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
 <div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_html_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">armnn::DepthwiseConvolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.html#l00019">DepthwiseConvolution2dLayer.hpp:19</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div>
 <div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00490">Descriptors.hpp:490</a></div></div>
 <div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00444">Descriptors.hpp:444</a></div></div>
 <div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::DepthwiseConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00484">Descriptors.hpp:484</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div>
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 <h2 class="memtitle"><span class="permalink"><a href="#aa4e793c84e5dfea800d4dba921651e5b">&#9670;&nbsp;</a></span>CreateGatherGraph()</h2>

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           <td class="memname">void CreateGatherGraph </td>
           <td>(</td>
           <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;&#160;</td>
           <td class="paramname"><em>graph</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> &amp;&#160;</td>
           <td class="paramname"><em>paramsInfo</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> &amp;&#160;</td>
           <td class="paramname"><em>indicesInfo</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> &amp;&#160;</td>
           <td class="paramname"><em>outputInfo</em>&#160;</td>
         </tr>
         <tr>
           <td></td>
           <td>)</td>
           <td></td><td></td>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00441">441</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p>

 <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00459">BOOST_AUTO_TEST_CASE()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;{</div><div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input0 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;params&quot;</span>);</div><div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;    input0-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(paramsInfo);</div><div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;</div><div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input1 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(1, <span class="stringliteral">&quot;indices&quot;</span>);</div><div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;    input1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(indicesInfo);</div><div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;</div><div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;    <a class="code" href="classarmnn_1_1_gather_layer.html">GatherLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_gather_layer.html">GatherLayer</a>&gt;(<span class="stringliteral">&quot;gather&quot;</span>);</div><div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;</div><div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;    input0-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;    input1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &amp;destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div>
 <div class="ttc" id="classarmnn_1_1_gather_layer_html"><div class="ttname"><a href="classarmnn_1_1_gather_layer.html">armnn::GatherLayer</a></div><div class="ttdoc">This layer represents a Gather operator. </div><div class="ttdef"><b>Definition:</b> <a href="_gather_layer_8hpp_source.html#l00014">GatherLayer.hpp:14</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div>
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 <h2 class="memtitle"><span class="permalink"><a href="#a4756218150e4ca0da09d0ecc390a7a17">&#9670;&nbsp;</a></span>CreatePooling2dGraph()</h2>

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           <td class="memname">void CreatePooling2dGraph </td>
           <td>(</td>
           <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;&#160;</td>
           <td class="paramname"><em>graph</em>, </td>
         </tr>
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           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>inputShape</em>, </td>
         </tr>
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           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>outputShape</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype"><a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a>&#160;</td>
           <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code>&#160;</td>
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           <td></td>
           <td>)</td>
           <td></td><td></td>
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 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00349">349</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::Average</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::Exclude</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00369">Pooling2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00355">Pooling2dDescriptor::m_PadBottom</a>, <a class="el" href="_descriptors_8hpp_source.html#l00367">Pooling2dDescriptor::m_PaddingMethod</a>, <a class="el" href="_descriptors_8hpp_source.html#l00349">Pooling2dDescriptor::m_PadLeft</a>, <a class="el" href="_descriptors_8hpp_source.html#l00351">Pooling2dDescriptor::m_PadRight</a>, <a class="el" href="_descriptors_8hpp_source.html#l00353">Pooling2dDescriptor::m_PadTop</a>, <a class="el" href="_descriptors_8hpp_source.html#l00359">Pooling2dDescriptor::m_PoolHeight</a>, <a class="el" href="_descriptors_8hpp_source.html#l00347">Pooling2dDescriptor::m_PoolType</a>, <a class="el" href="_descriptors_8hpp_source.html#l00357">Pooling2dDescriptor::m_PoolWidth</a>, <a class="el" href="_descriptors_8hpp_source.html#l00361">Pooling2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l00363">Pooling2dDescriptor::m_StrideY</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p>

 <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00377">BOOST_AUTO_TEST_CASE()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;{</div><div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;</div><div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;    <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">Pooling2dDescriptor</a> desc;</div><div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;    desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;    desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 100;</div><div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;    desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 5;</div><div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;    desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 50;</div><div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;    desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 50;</div><div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;    desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 50;</div><div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;    desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 50;</div><div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;    desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;    desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;</div><div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;</div><div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;    <a class="code" href="classarmnn_1_1_pooling2d_layer.html">Pooling2dLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_pooling2d_layer.html">Pooling2dLayer</a>&gt;(desc, <span class="stringliteral">&quot;pooling2d&quot;</span>);</div><div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;</div><div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">armnn::Pooling2dDescriptor::m_PoolHeight</a></div><div class="ttdeci">uint32_t m_PoolHeight</div><div class="ttdoc">Pooling height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00359">Descriptors.hpp:359</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
 <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">armnn::Pooling2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00353">Descriptors.hpp:353</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::Pooling2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00351">Descriptors.hpp:351</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &amp;destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div>
 <div class="ttc" id="classarmnn_1_1_pooling2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_pooling2d_layer.html">armnn::Pooling2dLayer</a></div><div class="ttdoc">This layer represents a pooling 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_layer_8hpp_source.html#l00013">Pooling2dLayer.hpp:13</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">armnn::Pooling2dDescriptor::m_PoolWidth</a></div><div class="ttdeci">uint32_t m_PoolWidth</div><div class="ttdoc">Pooling width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00357">Descriptors.hpp:357</a></div></div>
 <div class="ttc" id="namespacearmnn_html_a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6"><div class="ttname"><a href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a></div><div class="ttdoc">The padding fields don&amp;#39;t count and are ignored. </div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Pooling2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00349">Descriptors.hpp:349</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a8c29d6ea9b4186d69aad5961c910939c"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">armnn::Pooling2dDescriptor::m_PaddingMethod</a></div><div class="ttdeci">PaddingMethod m_PaddingMethod</div><div class="ttdoc">The padding method to be used. (Exclude, IgnoreValue). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00367">Descriptors.hpp:367</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Pooling2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00363">Descriptors.hpp:363</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">armnn::Pooling2dDescriptor::m_PoolType</a></div><div class="ttdeci">PoolingAlgorithm m_PoolType</div><div class="ttdoc">The pooling algorithm to use (Max. Average, L2). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00347">Descriptors.hpp:347</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00313">Descriptors.hpp:313</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Pooling2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00369">Descriptors.hpp:369</a></div></div>
 <div class="ttc" id="namespacearmnn_html_a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021"><div class="ttname"><a href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::Pooling2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00355">Descriptors.hpp:355</a></div></div>
 <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Pooling2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00361">Descriptors.hpp:361</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div>
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 <h2 class="memtitle"><span class="permalink"><a href="#aefb2c7f14f687a9432490a1bdee05458">&#9670;&nbsp;</a></span>CreateResizeBilinearGraph()</h2>

 <div class="memitem">
 <div class="memproto">
       <table class="memname">
         <tr>
           <td class="memname">void CreateResizeBilinearGraph </td>
           <td>(</td>
           <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> &amp;&#160;</td>
           <td class="paramname"><em>graph</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>inputShape</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const unsigned int *&#160;</td>
           <td class="paramname"><em>outputShape</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype"><a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a>&#160;</td>
           <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code>&#160;</td>
         </tr>
         <tr>
           <td></td>
           <td>)</td>
           <td></td><td></td>
         </tr>
       </table>
 </div><div class="memdoc">

 <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00397">397</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p>

 <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::Bilinear</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00751">ResizeDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00749">ResizeDescriptor::m_Method</a>, <a class="el" href="_descriptors_8hpp_source.html#l00746">ResizeDescriptor::m_TargetHeight</a>, <a class="el" href="_descriptors_8hpp_source.html#l00744">ResizeDescriptor::m_TargetWidth</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p>

 <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00420">BOOST_AUTO_TEST_CASE()</a>.</p>
 <div class="fragment"><div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;{</div><div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;</div><div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;    <a class="code" href="structarmnn_1_1_resize_descriptor.html">ResizeDescriptor</a> desc;</div><div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;    desc.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a869254cb56968986a78a79e1d6d4a86b">m_Method</a>       = ResizeMethod::Bilinear;</div><div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;    desc.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = 3;</div><div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;    desc.<a class="code" href="structarmnn_1_1_resize_descriptor.html#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a>  = 4;</div><div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;    desc.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>   = dataLayout;</div><div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;</div><div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;</div><div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;    <a class="code" href="classarmnn_1_1_resize_layer.html">ResizeLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_resize_layer.html">ResizeLayer</a>&gt;(desc, <span class="stringliteral">&quot;resizeBilinear&quot;</span>);</div><div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;</div><div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div>
 <div class="ttc" id="structarmnn_1_1_resize_descriptor_html_a46c3fa15c46fb0d1dcdc24d0ea5cb5cd"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">armnn::ResizeDescriptor::m_TargetHeight</a></div><div class="ttdeci">uint32_t m_TargetHeight</div><div class="ttdoc">Target height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00746">Descriptors.hpp:746</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
 <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
 <div class="ttc" id="structarmnn_1_1_resize_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::ResizeDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00751">Descriptors.hpp:751</a></div></div>
 <div class="ttc" id="structarmnn_1_1_resize_descriptor_html_a869254cb56968986a78a79e1d6d4a86b"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#a869254cb56968986a78a79e1d6d4a86b">armnn::ResizeDescriptor::m_Method</a></div><div class="ttdeci">ResizeMethod m_Method</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00749">Descriptors.hpp:749</a></div></div>
 <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &amp;destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div>
 <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div>
 <div class="ttc" id="structarmnn_1_1_resize_descriptor_html_adcf5037208faac36c0788239a073f75c"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#adcf5037208faac36c0788239a073f75c">armnn::ResizeDescriptor::m_TargetWidth</a></div><div class="ttdeci">uint32_t m_TargetWidth</div><div class="ttdoc">Target width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00744">Descriptors.hpp:744</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div>
 <div class="ttc" id="structarmnn_1_1_resize_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html">armnn::ResizeDescriptor</a></div><div class="ttdoc">A ResizeDescriptor for the ResizeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00724">Descriptors.hpp:724</a></div></div>
 <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div>
 <div class="ttc" id="classarmnn_1_1_resize_layer_html"><div class="ttname"><a href="classarmnn_1_1_resize_layer.html">armnn::ResizeLayer</a></div><div class="ttdoc">This layer represents a resize operation. </div><div class="ttdef"><b>Definition:</b> <a href="_resize_layer_8hpp_source.html#l00013">ResizeLayer.hpp:13</a></div></div>
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