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diff --git a/20.02/_optimizer_tests_8cpp.xhtml b/20.02/_optimizer_tests_8cpp.xhtml new file mode 100644 index 0000000000..c049072e4e --- /dev/null +++ b/20.02/_optimizer_tests_8cpp.xhtml @@ -0,0 +1,1012 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/armnn/test/OptimizerTests.cpp File Reference</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" 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class="title">OptimizerTests.cpp File Reference</div> </div> +</div><!--header--> +<div class="contents"> +<div class="textblock"><code>#include "<a class="el" href="_test_utils_8hpp_source.xhtml">TestUtils.hpp</a>"</code><br /> +<code>#include <<a class="el" href="_backend_settings_8hpp_source.xhtml">BackendSettings.hpp</a>></code><br /> +<code>#include <<a class="el" href="_graph_8hpp_source.xhtml">Graph.hpp</a>></code><br /> +<code>#include <<a class="el" href="_network_8hpp_source.xhtml">Network.hpp</a>></code><br /> +<code>#include <<a class="el" href="_optimizer_8hpp_source.xhtml">Optimizer.hpp</a>></code><br /> +<code>#include <<a class="el" href="_backend_registry_8hpp_source.xhtml">armnn/BackendRegistry.hpp</a>></code><br /> +<code>#include <<a class="el" href="_i_network_8hpp_source.xhtml">armnn/INetwork.hpp</a>></code><br /> +<code>#include <<a class="el" href="_layer_visitor_base_8hpp_source.xhtml">armnn/LayerVisitorBase.hpp</a>></code><br /> +<code>#include <<a class="el" href="_floating_point_converter_8hpp_source.xhtml">armnnUtils/FloatingPointConverter.hpp</a>></code><br /> +<code>#include <<a class="el" href="_cpu_tensor_handle_8hpp_source.xhtml">backendsCommon/CpuTensorHandle.hpp</a>></code><br /> +<code>#include <<a class="el" href="src_2backends_2backends_common_2_i_backend_internal_8hpp_source.xhtml">backendsCommon/IBackendInternal.hpp</a>></code><br /> +<code>#include <<a class="el" href="_layer_support_base_8hpp_source.xhtml">backendsCommon/LayerSupportBase.hpp</a>></code><br /> +<code>#include <boost/test/unit_test.hpp></code><br /> +</div> +<p><a href="_optimizer_tests_8cpp_source.xhtml">Go to the source code of this file.</a></p> +<table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> +Functions</h2></td></tr> +<tr class="memitem:a8839099137f1031b504d76090074142c"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a8839099137f1031b504d76090074142c">BOOST_AUTO_TEST_CASE</a> (LSTMValidateTensorShapesFromInputsCIFGDisabledTest)</td></tr> +<tr class="separator:a8839099137f1031b504d76090074142c"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a10342b734f73496052047f2b74b38cca"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a10342b734f73496052047f2b74b38cca">BOOST_AUTO_TEST_CASE</a> (LSTMValidateTensorShapesFromInputsCIFGEnabledTest)</td></tr> +<tr class="separator:a10342b734f73496052047f2b74b38cca"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a09fa0a0ab3199f1a7bfc169bce93925d"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a09fa0a0ab3199f1a7bfc169bce93925d">BOOST_AUTO_TEST_CASE</a> (InsertConvertersTest)</td></tr> +<tr class="separator:a09fa0a0ab3199f1a7bfc169bce93925d"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a5065b32dd0aa2c08ef75e953ebedbc16"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a> (<a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> &graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr> +<tr class="separator:a5065b32dd0aa2c08ef75e953ebedbc16"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a6b7bebf2c0d384c3297a6c3b19346555"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a6b7bebf2c0d384c3297a6c3b19346555">BOOST_AUTO_TEST_CASE</a> (Conv2dValidateTensorShapesFromInputs)</td></tr> +<tr class="separator:a6b7bebf2c0d384c3297a6c3b19346555"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a67738cd9d506e11aa4f4f43b9dc30e2c"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a67738cd9d506e11aa4f4f43b9dc30e2c">BOOST_AUTO_TEST_CASE</a> (Conv2dValidateTensorShapesFromInputsNhwc)</td></tr> +<tr class="separator:a67738cd9d506e11aa4f4f43b9dc30e2c"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:acd97facea671e23ec3e8b33c6c2ea321"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a> (<a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> &graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr> +<tr class="separator:acd97facea671e23ec3e8b33c6c2ea321"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a93b5cb4143e78fec858fe77e86472bec"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a93b5cb4143e78fec858fe77e86472bec">BOOST_AUTO_TEST_CASE</a> (DepthwiseConv2dValidateTensorShapesFromInputs)</td></tr> +<tr class="separator:a93b5cb4143e78fec858fe77e86472bec"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aa678f54308701529660f9ee2a70bd042"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#aa678f54308701529660f9ee2a70bd042">BOOST_AUTO_TEST_CASE</a> (DepthwiseConv2dValidateTensorShapesFromInputsNhwc)</td></tr> +<tr class="separator:aa678f54308701529660f9ee2a70bd042"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a4756218150e4ca0da09d0ecc390a7a17"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a> (<a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> &graph, const unsigned int *inputShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr> +<tr class="separator:a4756218150e4ca0da09d0ecc390a7a17"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a8457188fd0859ae6a91c09c3266f58a5"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a8457188fd0859ae6a91c09c3266f58a5">BOOST_AUTO_TEST_CASE</a> (Pooling2dValidateTensorShapesFromInputs)</td></tr> +<tr class="separator:a8457188fd0859ae6a91c09c3266f58a5"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a1c7c22035e9b339dad1aedcf1d9c49e9"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a1c7c22035e9b339dad1aedcf1d9c49e9">BOOST_AUTO_TEST_CASE</a> (Pooling2dValidateTensorShapesFromInputsNhwc)</td></tr> +<tr class="separator:a1c7c22035e9b339dad1aedcf1d9c49e9"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aefb2c7f14f687a9432490a1bdee05458"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a> (<a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> &graph, const unsigned int *inputShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr> +<tr class="separator:aefb2c7f14f687a9432490a1bdee05458"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:acee9ba1427bd42cc38a0402969dd0d35"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#acee9ba1427bd42cc38a0402969dd0d35">BOOST_AUTO_TEST_CASE</a> (ResizeBilinearValidateTensorShapesFromInputs)</td></tr> +<tr class="separator:acee9ba1427bd42cc38a0402969dd0d35"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:abbc42a4387722b0b5e0c00038288dd4e"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#abbc42a4387722b0b5e0c00038288dd4e">BOOST_AUTO_TEST_CASE</a> (ResizeBilinearValidateTensorShapesFromInputsNhwc)</td></tr> +<tr class="separator:abbc42a4387722b0b5e0c00038288dd4e"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aa4e793c84e5dfea800d4dba921651e5b"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a> (<a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> &graph, const <a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> &paramsInfo, const <a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> &indicesInfo, const <a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> &outputInfo)</td></tr> +<tr class="separator:aa4e793c84e5dfea800d4dba921651e5b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a57aa1f639ec35a976735c91889d463a4"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a57aa1f639ec35a976735c91889d463a4">BOOST_AUTO_TEST_CASE</a> (GatherValidateTensorShapesFromInputs)</td></tr> +<tr class="separator:a57aa1f639ec35a976735c91889d463a4"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:af31e0d94eb9ec7e72b9d6d70da3070ec"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#af31e0d94eb9ec7e72b9d6d70da3070ec">BOOST_AUTO_TEST_CASE</a> (GatherValidateTensorShapesFromInputs1DParams)</td></tr> +<tr class="separator:af31e0d94eb9ec7e72b9d6d70da3070ec"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a65b5e30de580e14475b51da9b93c908b"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a65b5e30de580e14475b51da9b93c908b">BOOST_AUTO_TEST_CASE</a> (GatherValidateTensorShapesFromInputsMultiDimIndices)</td></tr> +<tr class="separator:a65b5e30de580e14475b51da9b93c908b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a0ee7b0e1f8d1dd9a9e001720e69086eb"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a0ee7b0e1f8d1dd9a9e001720e69086eb">BOOST_AUTO_TEST_CASE</a> (DetectionPostProcessValidateTensorShapes)</td></tr> +<tr class="separator:a0ee7b0e1f8d1dd9a9e001720e69086eb"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a4ef49bab7a1b82c389b3b45ffb767833"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a4ef49bab7a1b82c389b3b45ffb767833">BOOST_AUTO_TEST_CASE</a> (FoldPadLayerIntoConvolution2dLayer)</td></tr> +<tr class="separator:a4ef49bab7a1b82c389b3b45ffb767833"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a69de6f6ae1c2ba029453ce16bd4250a8"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.xhtml#a69de6f6ae1c2ba029453ce16bd4250a8">BOOST_AUTO_TEST_CASE</a> (BackendHintTest)</td></tr> +<tr class="separator:a69de6f6ae1c2ba029453ce16bd4250a8"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<h2 class="groupheader">Function Documentation</h2> +<a id="a8839099137f1031b504d76090074142c"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a8839099137f1031b504d76090074142c">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[1/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">LSTMValidateTensorShapesFromInputsCIFGDisabledTest </td> + <td class="paramname"></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.xhtml#l00141">141</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>.</p> +<div class="fragment"><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> {</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="comment">//Helper function creates graph containing LSTM layer with required input and output layers</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  CreateLSTMLayerHelper(graph, <span class="keyword">false</span>);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> </div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="comment">//This function used to call ValidateShapesFromInputs();</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> }</div><div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a10342b734f73496052047f2b74b38cca"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a10342b734f73496052047f2b74b38cca">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[2/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">LSTMValidateTensorShapesFromInputsCIFGEnabledTest </td> + <td class="paramname"></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.xhtml#l00152">152</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>.</p> +<div class="fragment"><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> {</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> </div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="comment">//Helper function creates graph containing LSTM layer with required input and output layers</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  CreateLSTMLayerHelper(graph, <span class="keyword">true</span>);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> </div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">//This function used to call ValidateShapesFromInputs();</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> }</div><div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a09fa0a0ab3199f1a7bfc169bce93925d"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a09fa0a0ab3199f1a7bfc169bce93925d">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[3/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">InsertConvertersTest </td> + <td class="paramname"></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.xhtml#l00163">163</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">armnn::Addition</a>, <a class="el" href="_test_utils_8hpp_source.xhtml#l00020">CheckSequence()</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">armnn::ConvertFp16ToFp32</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">armnn::ConvertFp32ToFp16</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::Float16</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::Floor</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00095">TensorInfo::GetDataType()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00273">Layer::GetDataType()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00221">Layer::GetOutputHandler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00063">OutputSlot::GetTensorInfo()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00259">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="_network_utils_8cpp_source.xhtml#l00040">armnn::InsertConvertFp16ToFp32LayersBefore()</a>, <a class="el" href="_network_utils_8cpp_source.xhtml#l00079">armnn::InsertConvertFp32ToFp16LayersAfter()</a>, and <a class="el" href="_output_handler_8cpp_source.xhtml#l00017">OutputHandler::SetTensorInfo()</a>.</p> +<div class="fragment"><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> {</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 5, 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> inputId = 0;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* head = graph.AddLayer<<a class="code" href="classarmnn_1_1_output_layer.xhtml">armnn::OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  head = graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_addition_layer.xhtml">armnn::AdditionLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), <span class="stringliteral">""</span>);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  head-><a class="code" href="classarmnn_1_1_layer.xhtml#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>().<a class="code" href="classarmnn_1_1_output_handler.xhtml#a97db12c41024f5545ef5cc4153e5443b">SetTensorInfo</a>(info);</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1), inputId++, <span class="stringliteral">""</span>)</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  ->GetOutputHandler().SetTensorInfo(info);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  head = graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_floor_layer.xhtml">armnn::FloorLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), <span class="stringliteral">""</span>);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  head-><a class="code" href="classarmnn_1_1_layer.xhtml#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>().<a class="code" href="classarmnn_1_1_output_handler.xhtml#a97db12c41024f5545ef5cc4153e5443b">SetTensorInfo</a>(info);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> </div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  head = graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_mem_copy_layer.xhtml">armnn::MemCopyLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), <span class="stringliteral">""</span>);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  head-><a class="code" href="classarmnn_1_1_layer.xhtml#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>().<a class="code" href="classarmnn_1_1_output_handler.xhtml#a97db12c41024f5545ef5cc4153e5443b">SetTensorInfo</a>(info);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), inputId++, <span class="stringliteral">""</span>)</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  ->GetOutputHandler().SetTensorInfo(info);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="comment">// Check graph layer sequence before inserting convert layers</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.cbegin(),</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  graph.cend(),</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  &IsLayerOfType<armnn::MemCopyLayer>,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  &IsLayerOfType<armnn::FloorLayer>,</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  &IsLayerOfType<armnn::AdditionLayer>,</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  &IsLayerOfType<armnn::OutputLayer>));</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="comment">// Check layers have Float16 DataType</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& layer : graph)</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  {</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keywordflow">if</span>(layer->GetType()==LayerType::Floor || layer->GetType() == LayerType::Addition)</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  {</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  BOOST_ASSERT(layer->GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float16);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  BOOST_ASSERT(layer->GetDataType() == DataType::Float16);</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  }</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  }</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="comment">// Insert convert layers either side of unsupported layer</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& layer : graph)</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  {</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keywordflow">if</span>(layer->GetType()==LayerType::Floor || layer->GetType() == LayerType::Addition)</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  {</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <a class="code" href="namespacearmnn.xhtml#ad31c56533e4f9f9f51719599fbfcf7bb">InsertConvertFp16ToFp32LayersBefore</a>(graph, *layer);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <a class="code" href="namespacearmnn.xhtml#abf625e50a5eaeafce5b39580dc95a9d3">InsertConvertFp32ToFp16LayersAfter</a>(graph, *layer);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  }</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  }</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> </div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="comment">// Check layers have correct DataType after inserting convert layers</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& layer : graph)</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  {</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordflow">if</span> (layer->GetType()==LayerType::Floor || layer->GetType() == LayerType::Addition)</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  {</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  BOOST_ASSERT(layer->GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float32);</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  BOOST_ASSERT(layer->GetDataType() == DataType::Float32);</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  }</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer->GetType() == LayerType::ConvertFp16ToFp32)</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  {</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  BOOST_ASSERT(layer->GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float32);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  BOOST_ASSERT(layer->GetDataType() == DataType::Float16);</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  }</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer->GetType() == LayerType::ConvertFp32ToFp16)</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  {</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  BOOST_ASSERT(layer->GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float16);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  BOOST_ASSERT(layer->GetDataType() == DataType::Float32);</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  }</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  }</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="comment">// Check sequence of layers after inserting convert layers</span></div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.cbegin(),</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  graph.cend(),</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  &IsLayerOfType<armnn::ConvertFp16ToFp32Layer>,</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  &IsLayerOfType<armnn::MemCopyLayer>,</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  &IsLayerOfType<armnn::ConvertFp16ToFp32Layer>,</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  &IsLayerOfType<armnn::FloorLayer>,</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  &IsLayerOfType<armnn::ConvertFp16ToFp32Layer>,</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  &IsLayerOfType<armnn::AdditionLayer>,</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  &IsLayerOfType<armnn::OutputLayer>));</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> }</div><div class="ttc" id="namespacearmnn_xhtml_abf625e50a5eaeafce5b39580dc95a9d3"><div class="ttname"><a href="namespacearmnn.xhtml#abf625e50a5eaeafce5b39580dc95a9d3">armnn::InsertConvertFp32ToFp16LayersAfter</a></div><div class="ttdeci">std::vector< ConvertFp32ToFp16Layer * > InsertConvertFp32ToFp16LayersAfter(Graph &graph, Layer &layer)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.xhtml#l00079">NetworkUtils.cpp:79</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad31c56533e4f9f9f51719599fbfcf7bb"><div class="ttname"><a href="namespacearmnn.xhtml#ad31c56533e4f9f9f51719599fbfcf7bb">armnn::InsertConvertFp16ToFp32LayersBefore</a></div><div class="ttdeci">std::vector< ConvertFp16ToFp32Layer * > InsertConvertFp16ToFp32LayersBefore(Graph &graph, Layer &layer, bool expectCorrectInputType)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.xhtml#l00040">NetworkUtils.cpp:40</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00171">Types.hpp:171</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">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.xhtml#l00013">OutputLayer.hpp:13</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div> +<div class="ttc" id="classarmnn_1_1_mem_copy_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_mem_copy_layer.xhtml">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.xhtml#l00013">MemCopyLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_floor_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_floor_layer.xhtml">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.xhtml#l00013">FloorLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_addition_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_addition_layer.xhtml">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.xhtml#l00013">AdditionLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_handler_xhtml_a97db12c41024f5545ef5cc4153e5443b"><div class="ttname"><a href="classarmnn_1_1_output_handler.xhtml#a97db12c41024f5545ef5cc4153e5443b">armnn::OutputHandler::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &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.xhtml#l00017">OutputHandler.cpp:17</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_af2c0edc7ea62a8baaec4d3d9b2b09256"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#af2c0edc7ea62a8baaec4d3d9b2b09256">armnn::Layer::GetOutputHandler</a></div><div class="ttdeci">const OutputHandler & GetOutputHandler(unsigned int i=0) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00221">Layer.hpp:221</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">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.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="_test_utils_8hpp_xhtml_a0eedb278f57355b47fa983450d4e378c"><div class="ttname"><a href="_test_utils_8hpp.xhtml#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.xhtml#l00020">TestUtils.hpp:20</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a6b7bebf2c0d384c3297a6c3b19346555"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a6b7bebf2c0d384c3297a6c3b19346555">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[4/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">Conv2dValidateTensorShapesFromInputs </td> + <td class="paramname"></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.xhtml#l00284">284</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00256">CreateConvolution2dGraph()</a>, and <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>.</p> +<div class="fragment"><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> {</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <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="l00288"></a><span class="lineno"> 288</span>  <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="l00289"></a><span class="lineno"> 289</span>  <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="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> }</div><div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +<div class="ttc" id="_optimizer_tests_8cpp_xhtml_a5065b32dd0aa2c08ef75e953ebedbc16"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a></div><div class="ttdeci">void CreateConvolution2dGraph(Graph &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.xhtml#l00256">OptimizerTests.cpp:256</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a67738cd9d506e11aa4f4f43b9dc30e2c"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a67738cd9d506e11aa4f4f43b9dc30e2c">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[5/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">Conv2dValidateTensorShapesFromInputsNhwc </td> + <td class="paramname"></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.xhtml#l00295">295</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00256">CreateConvolution2dGraph()</a>, <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> +<div class="fragment"><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> {</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <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="l00299"></a><span class="lineno"> 299</span>  <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="l00300"></a><span class="lineno"> 300</span>  <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="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> </div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> }</div><div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +<div class="ttc" id="_optimizer_tests_8cpp_xhtml_a5065b32dd0aa2c08ef75e953ebedbc16"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a></div><div class="ttdeci">void CreateConvolution2dGraph(Graph &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.xhtml#l00256">OptimizerTests.cpp:256</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a93b5cb4143e78fec858fe77e86472bec"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a93b5cb4143e78fec858fe77e86472bec">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[6/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">DepthwiseConv2dValidateTensorShapesFromInputs </td> + <td class="paramname"></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.xhtml#l00334">334</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00306">CreateDepthwiseConvolution2dGraph()</a>, and <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>.</p> +<div class="fragment"><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> {</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <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="l00338"></a><span class="lineno"> 338</span>  <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="l00339"></a><span class="lineno"> 339</span>  <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="l00340"></a><span class="lineno"> 340</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape);</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> }</div><div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +<div class="ttc" id="_optimizer_tests_8cpp_xhtml_acd97facea671e23ec3e8b33c6c2ea321"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a></div><div class="ttdeci">void CreateDepthwiseConvolution2dGraph(Graph &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.xhtml#l00306">OptimizerTests.cpp:306</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aa678f54308701529660f9ee2a70bd042"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aa678f54308701529660f9ee2a70bd042">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[7/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">DepthwiseConv2dValidateTensorShapesFromInputsNhwc </td> + <td class="paramname"></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.xhtml#l00345">345</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00306">CreateDepthwiseConvolution2dGraph()</a>, <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> +<div class="fragment"><div class="line"><a name="l00346"></a><span class="lineno"> 346</span> {</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <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="l00349"></a><span class="lineno"> 349</span>  <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="l00350"></a><span class="lineno"> 350</span>  <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="l00351"></a><span class="lineno"> 351</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> </div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> }</div><div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +<div class="ttc" id="_optimizer_tests_8cpp_xhtml_acd97facea671e23ec3e8b33c6c2ea321"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a></div><div class="ttdeci">void CreateDepthwiseConvolution2dGraph(Graph &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.xhtml#l00306">OptimizerTests.cpp:306</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a8457188fd0859ae6a91c09c3266f58a5"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a8457188fd0859ae6a91c09c3266f58a5">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[8/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">Pooling2dValidateTensorShapesFromInputs </td> + <td class="paramname"></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.xhtml#l00384">384</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00356">CreatePooling2dGraph()</a>, <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> +<div class="fragment"><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> {</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <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="l00388"></a><span class="lineno"> 388</span>  <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="l00389"></a><span class="lineno"> 389</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a>(graph, inputShape, outputShape, DataLayout::NCHW);</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span> </div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span> }</div><div class="ttc" id="_optimizer_tests_8cpp_xhtml_a4756218150e4ca0da09d0ecc390a7a17"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a></div><div class="ttdeci">void CreatePooling2dGraph(Graph &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.xhtml#l00356">OptimizerTests.cpp:356</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a1c7c22035e9b339dad1aedcf1d9c49e9"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a1c7c22035e9b339dad1aedcf1d9c49e9">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[9/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">Pooling2dValidateTensorShapesFromInputsNhwc </td> + <td class="paramname"></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.xhtml#l00394">394</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00356">CreatePooling2dGraph()</a>, <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> +<div class="fragment"><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> {</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <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="l00398"></a><span class="lineno"> 398</span>  <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="l00399"></a><span class="lineno"> 399</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a>(graph, inputShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span> </div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> }</div><div class="ttc" id="_optimizer_tests_8cpp_xhtml_a4756218150e4ca0da09d0ecc390a7a17"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a></div><div class="ttdeci">void CreatePooling2dGraph(Graph &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.xhtml#l00356">OptimizerTests.cpp:356</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="acee9ba1427bd42cc38a0402969dd0d35"></a> +<h2 class="memtitle"><span class="permalink"><a href="#acee9ba1427bd42cc38a0402969dd0d35">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[10/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">ResizeBilinearValidateTensorShapesFromInputs </td> + <td class="paramname"></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.xhtml#l00427">427</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00404">CreateResizeBilinearGraph()</a>, and <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>.</p> +<div class="fragment"><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> {</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <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="l00431"></a><span class="lineno"> 431</span>  <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="l00432"></a><span class="lineno"> 432</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a>(graph, inputShape, outputShape);</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span> </div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span> }</div><div class="ttc" id="_optimizer_tests_8cpp_xhtml_aefb2c7f14f687a9432490a1bdee05458"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a></div><div class="ttdeci">void CreateResizeBilinearGraph(Graph &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.xhtml#l00404">OptimizerTests.cpp:404</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="abbc42a4387722b0b5e0c00038288dd4e"></a> +<h2 class="memtitle"><span class="permalink"><a href="#abbc42a4387722b0b5e0c00038288dd4e">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[11/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">ResizeBilinearValidateTensorShapesFromInputsNhwc </td> + <td class="paramname"></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.xhtml#l00437">437</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00404">CreateResizeBilinearGraph()</a>, <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> +<div class="fragment"><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> {</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <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="l00441"></a><span class="lineno"> 441</span>  <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="l00442"></a><span class="lineno"> 442</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a>(graph, inputShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span> </div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span> }</div><div class="ttc" id="_optimizer_tests_8cpp_xhtml_aefb2c7f14f687a9432490a1bdee05458"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a></div><div class="ttdeci">void CreateResizeBilinearGraph(Graph &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.xhtml#l00404">OptimizerTests.cpp:404</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a57aa1f639ec35a976735c91889d463a4"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a57aa1f639ec35a976735c91889d463a4">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[12/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">GatherValidateTensorShapesFromInputs </td> + <td class="paramname"></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.xhtml#l00466">466</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00448">CreateGatherGraph()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p> +<div class="fragment"><div class="line"><a name="l00467"></a><span class="lineno"> 467</span> {</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> paramsInfo({10, 5}, DataType::Float32);</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> indicesInfo({3}, DataType::Signed32);</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({3, 5}, DataType::Float32);</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span> </div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a>(graph, paramsInfo, indicesInfo, outputInfo);</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span> </div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="_optimizer_tests_8cpp_xhtml_aa4e793c84e5dfea800d4dba921651e5b"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a></div><div class="ttdeci">void CreateGatherGraph(Graph &graph, const armnn::TensorInfo &paramsInfo, const armnn::TensorInfo &indicesInfo, const armnn::TensorInfo &outputInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.xhtml#l00448">OptimizerTests.cpp:448</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="af31e0d94eb9ec7e72b9d6d70da3070ec"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af31e0d94eb9ec7e72b9d6d70da3070ec">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[13/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">GatherValidateTensorShapesFromInputs1DParams </td> + <td class="paramname"></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.xhtml#l00478">478</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00448">CreateGatherGraph()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p> +<div class="fragment"><div class="line"><a name="l00479"></a><span class="lineno"> 479</span> {</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> paramsInfo({8}, DataType::Float32);</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> indicesInfo({5}, DataType::Signed32);</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo( {5}, DataType::Float32);</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span> </div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a>(graph, paramsInfo, indicesInfo, outputInfo);</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span> </div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="_optimizer_tests_8cpp_xhtml_aa4e793c84e5dfea800d4dba921651e5b"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a></div><div class="ttdeci">void CreateGatherGraph(Graph &graph, const armnn::TensorInfo &paramsInfo, const armnn::TensorInfo &indicesInfo, const armnn::TensorInfo &outputInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.xhtml#l00448">OptimizerTests.cpp:448</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a65b5e30de580e14475b51da9b93c908b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a65b5e30de580e14475b51da9b93c908b">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[14/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">GatherValidateTensorShapesFromInputsMultiDimIndices </td> + <td class="paramname"></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.xhtml#l00490">490</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00448">CreateGatherGraph()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p> +<div class="fragment"><div class="line"><a name="l00491"></a><span class="lineno"> 491</span> {</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> paramsInfo({3, 2, 5}, DataType::Float32);</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> indicesInfo({2, 2}, DataType::Signed32);</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({2, 2, 2, 5}, DataType::Float32);</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span> </div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <a class="code" href="_optimizer_tests_8cpp.xhtml#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a>(graph, paramsInfo, indicesInfo, outputInfo);</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span> </div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="_optimizer_tests_8cpp_xhtml_aa4e793c84e5dfea800d4dba921651e5b"><div class="ttname"><a href="_optimizer_tests_8cpp.xhtml#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a></div><div class="ttdeci">void CreateGatherGraph(Graph &graph, const armnn::TensorInfo &paramsInfo, const armnn::TensorInfo &indicesInfo, const armnn::TensorInfo &outputInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.xhtml#l00448">OptimizerTests.cpp:448</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a0ee7b0e1f8d1dd9a9e001720e69086eb"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a0ee7b0e1f8d1dd9a9e001720e69086eb">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[15/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">DetectionPostProcessValidateTensorShapes </td> + <td class="paramname"></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.xhtml#l00502">502</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_graph_8hpp_source.xhtml#l00397">Graph::AddLayer()</a>, <a class="el" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00079">OutputSlot::Connect()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_graph_8cpp_source.xhtml#l00493">Graph::InferTensorInfos()</a>, <a class="el" href="_detection_post_process_layer_8hpp_source.xhtml#l00020">DetectionPostProcessLayer::m_Anchors</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00527">DetectionPostProcessDescriptor::m_MaxDetections</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::QAsymmU8</a>, <a class="el" href="_neon_end_to_end_tests_8cpp.xhtml#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>, and <a class="el" href="_layer_8cpp_source.xhtml#l00058">OutputSlot::SetTensorInfo()</a>.</p> +<div class="fragment"><div class="line"><a name="l00503"></a><span class="lineno"> 503</span> {</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> boxEncodingsInfo({1, 10, 4}, DataType::QAsymmU8);</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>({1, 10, 4}, DataType::QAsymmU8);</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  std::vector<uint8_t> anchorsVector(40);</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({10, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>), anchorsVector);</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span> </div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> detectionBoxesInfo({1, 3, 4}, DataType::QAsymmU8);</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> detectionScoresInfo({1, 3}, DataType::QAsymmU8);</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> detectionClassesInfo({1, 3}, DataType::QAsymmU8);</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> numDetectionInfo({1}, DataType::QAsymmU8);</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span> </div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* input0 = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"boxEncodings"</span>);</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  input0-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(boxEncodingsInfo);</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span> </div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* input1 = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(1, <span class="stringliteral">"score"</span>);</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(<a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>);</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span> </div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">DetectionPostProcessDescriptor</a> descriptor;</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a> = 3;</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span> </div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  <a class="code" href="classarmnn_1_1_detection_post_process_layer.xhtml">DetectionPostProcessLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_detection_post_process_layer.xhtml">DetectionPostProcessLayer</a>>(descriptor, <span class="stringliteral">"detectionPostProcess"</span>);</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  layer-><a class="code" href="classarmnn_1_1_detection_post_process_layer.xhtml#a6844fecab0edaf324de5a57fee8b65f1">m_Anchors</a> = std::make_unique<armnn::ScopedCpuTensorHandle>(<a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>);</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(detectionBoxesInfo);</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(detectionScoresInfo);</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(detectionClassesInfo);</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(3).<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(numDetectionInfo);</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span> </div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  input0->GetOutputSlot().Connect(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span> </div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... 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.xhtml#l00397">Graph.hpp:397</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00079">Layer.cpp:79</a></div></div> +<div class="ttc" id="classarmnn_1_1_detection_post_process_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_detection_post_process_layer.xhtml">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.xhtml#l00016">DetectionPostProcessLayer.hpp:16</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae72089bcab60ac175557f4241b16a014"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#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.xhtml#l00527">Descriptors.hpp:527</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="classarmnn_1_1_detection_post_process_layer_xhtml_a6844fecab0edaf324de5a57fee8b65f1"><div class="ttname"><a href="classarmnn_1_1_detection_post_process_layer.xhtml#a6844fecab0edaf324de5a57fee8b65f1">armnn::DetectionPostProcessLayer::m_Anchors</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > 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.xhtml#l00020">DetectionPostProcessLayer.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">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.xhtml#l00199">Tensor.hpp:199</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00493">Graph.cpp:493</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">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.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div> +<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_a64c1dd1b6dd60be9f4a16db9c8f427a5"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a></div><div class="ttdeci">armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::Float32)</div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00495">Descriptors.hpp:495</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_ac0981848e4ae57729f14f72bd4caa9f8"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a></div><div class="ttdeci">std::vector< float > 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><!-- fragment --> +</div> +</div> +<a id="a4ef49bab7a1b82c389b3b45ffb767833"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a4ef49bab7a1b82c389b3b45ffb767833">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[16/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">FoldPadLayerIntoConvolution2dLayer </td> + <td class="paramname"></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.xhtml#l00537">537</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_graph_8hpp_source.xhtml#l00397">Graph::AddLayer()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00168">Graph::cbegin()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00170">Graph::cend()</a>, <a class="el" href="_test_utils_8hpp_source.xhtml#l00020">CheckSequence()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00216">Layer::GetNameStr()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_layer_with_parameters_8hpp_source.xhtml#l00018">LayerWithParameters< Parameters >::GetParameters()</a>, <a class="el" href="_layer_support_8cpp_source.xhtml#l00069">armnn::IsActivationSupported()</a>, <a class="el" href="_layer_support_8cpp_source.xhtml#l00333">armnn::IsInputSupported()</a>, <a class="el" href="_layer_support_8cpp_source.xhtml#l00458">armnn::IsOutputSupported()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00438">Convolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00440">Convolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00430">Convolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00432">Convolution2dDescriptor::m_StrideY</a>, <a class="el" href="_convolution2d_layer_8hpp_source.xhtml#l00020">Convolution2dLayer::m_Weight</a>, <a class="el" href="_optimizer_8hpp_source.xhtml#l00043">armnn::MakeOptimizations()</a>, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>, <a class="el" href="_optimizer_8cpp_source.xhtml#l00016">Optimizer::Pass()</a>, and <a class="el" href="_layer_8cpp_source.xhtml#l00058">OutputSlot::SetTensorInfo()</a>.</p> +<div class="fragment"><div class="line"><a name="l00538"></a><span class="lineno"> 538</span> {</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <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="l00541"></a><span class="lineno"> 541</span>  <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="l00542"></a><span class="lineno"> 542</span>  <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="l00543"></a><span class="lineno"> 543</span>  <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="l00544"></a><span class="lineno"> 544</span> </div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span> </div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> paddedInfo(4, paddedShape, DataType::Float32);</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span> </div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span> </div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <a class="code" href="structarmnn_1_1_pad_descriptor.xhtml">PadDescriptor</a> padDescriptor({{ 0, 0 }, { 2, 2 }, { 2, 2 }, { 0, 0 }});</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span> </div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <a class="code" href="classarmnn_1_1_pad_layer.xhtml">PadLayer</a>* padLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_pad_layer.xhtml">PadLayer</a>>(padDescriptor, <span class="stringliteral">"pad"</span>);</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  padLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(paddedInfo);</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span> </div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a> convolution2dDescriptor;</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = DataLayout::NHWC;</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span> </div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  std::vector<float> weightsVector(18);</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, weightsShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), weightsVector);</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span> </div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">Convolution2dLayer</a>* conv2dLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">Convolution2dLayer</a>>(convolution2dDescriptor,<span class="stringliteral">"conv2d"</span>);</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  conv2dLayer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  conv2dLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span> </div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span> </div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="comment">// Connect up layers - input -> pad -> conv2d -> output</span></div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(padLayer->GetInputSlot(0));</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  padLayer->GetOutputSlot().Connect(conv2dLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  conv2dLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span> </div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <span class="keyword">auto</span> checkSimpleConv2d = [ ](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer) -> <span class="keywordtype">bool</span></div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  {</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayer = <span class="keyword">static_cast<</span><span class="keyword">const </span><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">armnn::Convolution2dLayer</a>*<span class="keyword">></span>(layer);</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayerParams = conv2dLayer-><a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>();</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <span class="keywordflow">return</span> IsLayerOfType<armnn::Convolution2dLayer>(layer) &&</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  (layer->GetNameStr() == <span class="stringliteral">"conv2d"</span>) &&</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  (conv2dLayerParams.m_PadLeft == 0) &&</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  (conv2dLayerParams.m_PadRight == 0) &&</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  (conv2dLayerParams.m_PadTop == 0) &&</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  (conv2dLayerParams.m_PadBottom == 0) &&</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  (conv2dLayerParams.m_BiasEnabled == <span class="keyword">false</span>) &&</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  (conv2dLayerParams.m_StrideX == 1) &&</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  (conv2dLayerParams.m_StrideY == 1) &&</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  (conv2dLayerParams.m_DataLayout == DataLayout::NHWC);</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  };</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span> </div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(),</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  &IsLayerOfType<armnn::PadLayer>,</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  checkSimpleConv2d,</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  &IsLayerOfType<armnn::OutputLayer>));</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span> </div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#add2180a15cdcf5a229de32bb956cb224">FoldPadIntoConvolution2d</a>()));</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span> </div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <span class="keyword">auto</span> checkPadFoldedIntoConv2d = [ ](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer) -> <span class="keywordtype">bool</span></div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  {</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayer = <span class="keyword">static_cast<</span><span class="keyword">const </span><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">armnn::Convolution2dLayer</a>*<span class="keyword">></span>(layer);</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayerParams = conv2dLayer-><a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>();</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keywordflow">return</span> IsLayerOfType<armnn::Convolution2dLayer>(layer) &&</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  (layer->GetNameStr() == <span class="stringliteral">"folded-pad-into-conv2d"</span>) &&</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  (conv2dLayerParams.m_PadLeft == 2) &&</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  (conv2dLayerParams.m_PadRight == 2) &&</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  (conv2dLayerParams.m_PadTop == 2) &&</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  (conv2dLayerParams.m_PadBottom == 2) &&</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  (conv2dLayerParams.m_BiasEnabled == <span class="keyword">false</span>) &&</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  (conv2dLayerParams.m_StrideX == 1) &&</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  (conv2dLayerParams.m_StrideY == 1) &&</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  (conv2dLayerParams.m_DataLayout == DataLayout::NHWC);</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  };</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span> </div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(),</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  checkPadFoldedIntoConv2d,</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  &IsLayerOfType<armnn::OutputLayer>));</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span> }</div><div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00438">Descriptors.hpp:438</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00440">Descriptors.hpp:440</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml_a502c06a1b13e6d90a6cbf47c081f1444"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml#a502c06a1b13e6d90a6cbf47c081f1444">armnn::LayerWithParameters::GetParameters</a></div><div class="ttdeci">const Parameters & GetParameters() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.xhtml#l00018">LayerWithParameters.hpp:18</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa7427025a851113a492de0b68b23d22a"><div class="ttname"><a href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a></div><div class="ttdeci">Optimizer::Optimizations MakeOptimizations(Args &&... args)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8hpp_source.xhtml#l00043">Optimizer.hpp:43</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... 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.xhtml#l00397">Graph.hpp:397</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a98b1109a9006f8cc7d4566146a3bd737"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#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.xhtml#l00168">Graph.hpp:168</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00392">Descriptors.hpp:392</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00079">Layer.cpp:79</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimizer_xhtml_a1f48ba622b76ea04d15c9b62f642bf08"><div class="ttname"><a href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a></div><div class="ttdeci">static void Pass(Graph &graph, const Optimizations &optimizations)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8cpp_source.xhtml#l00016">Optimizer.cpp:16</a></div></div> +<div class="ttc" id="classarmnn_1_1_pad_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_pad_layer.xhtml">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.xhtml#l00014">PadLayer.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_add2180a15cdcf5a229de32bb956cb224"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#add2180a15cdcf5a229de32bb956cb224">armnn::optimizations::FoldPadIntoConvolution2d</a></div><div class="ttdeci">OptimizeForConnection< PadLayer, Convolution2dLayer, FoldPadIntoConvolution2dImpl > FoldPadIntoConvolution2d</div><div class="ttdef"><b>Definition:</b> <a href="_fold_pad_into_convolution2d_8hpp_source.xhtml#l00088">FoldPadIntoConvolution2d.hpp:88</a></div></div> +<div class="ttc" id="structarmnn_1_1_pad_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pad_descriptor.xhtml">armnn::PadDescriptor</a></div><div class="ttdoc">A PadDescriptor for the PadLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00901">Descriptors.hpp:901</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00430">Descriptors.hpp:430</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">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.xhtml#l00013">OutputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::Convolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > 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.xhtml#l00020">Convolution2dLayer.hpp:20</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">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.xhtml#l00199">Tensor.hpp:199</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00432">Descriptors.hpp:432</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">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.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="_test_utils_8hpp_xhtml_a0eedb278f57355b47fa983450d4e378c"><div class="ttname"><a href="_test_utils_8hpp.xhtml#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.xhtml#l00020">TestUtils.hpp:20</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a02fd29b6dc3e21fbe4484362d85893bc"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#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.xhtml#l00170">Graph.hpp:170</a></div></div> +<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml">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.xhtml#l00015">Convolution2dLayer.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a69de6f6ae1c2ba029453ce16bd4250a8"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a69de6f6ae1c2ba029453ce16bd4250a8">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[17/17]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">BackendHintTest </td> + <td class="paramname"></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.xhtml#l00685">685</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_network_8cpp_source.xhtml#l00269">armnn::AssignBackends()</a>, <a class="el" href="_backend_registry_8cpp_source.xhtml#l00013">armnn::BackendRegistryInstance()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00324">Layer::BackendSelectionHint()</a>, <a class="el" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00079">OutputSlot::Connect()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00049">INetwork::Create()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00059">IOptimizedNetwork::Destroy()</a>, <a class="el" href="_network_8hpp_source.xhtml#l00276">OptimizedNetwork::GetGraph()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_network_8hpp_source.xhtml#l00299">OptimizationResult::IsOk()</a>, <a class="el" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b">armnn::Linear</a>, and <a class="el" href="_descriptors_8hpp_source.xhtml#l00035">ActivationDescriptor::m_Function</a>.</p> +<div class="fragment"><div class="line"><a name="l00686"></a><span class="lineno"> 686</span> {</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  <span class="keyword">class </span>TestBackendAssignment : <span class="keyword">public</span> <a class="code" href="classarmnn_1_1_layer_visitor_base.xhtml">LayerVisitorBase</a><VisitorNoThrowPolicy></div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  {</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  <span class="keyword">public</span>:</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_layer_visitor_base.xhtml#a6c23f9e9d8427775925d071feee5dbd1">VisitInputLayer</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer,</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span>,</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name = <span class="keyword">nullptr</span>)<span class="keyword"> override</span></div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(<span class="keywordtype">id</span>, name);</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <span class="keyword">auto</span> inputLayer = boost::polymorphic_downcast<const InputLayer*>(layer);</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  BOOST_TEST((inputLayer->GetBackendId() == <span class="stringliteral">"MockBackend"</span>));</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  }</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span> </div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_layer_visitor_base.xhtml#acc39ddb06acfd91cf3cfb0fcd9337005">VisitOutputLayer</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer,</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span>,</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name = <span class="keyword">nullptr</span>)<span class="keyword"> override</span></div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(<span class="keywordtype">id</span>, name);</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  <span class="keyword">auto</span> outputLayer = boost::polymorphic_downcast<const OutputLayer*>(layer);</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  BOOST_TEST((outputLayer->GetBackendId() == <span class="stringliteral">"MockBackend"</span>));</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  }</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span> </div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_layer_visitor_base.xhtml#a30b99e5202fc77b02f92d5c44e5ca86d">VisitActivationLayer</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer,</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">ActivationDescriptor</a>& activationDescriptor,</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name = <span class="keyword">nullptr</span>)<span class="keyword"> override</span></div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(activationDescriptor, name);</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <span class="keyword">auto</span> activation = boost::polymorphic_downcast<const ActivationLayer*>(layer);</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  BOOST_TEST((activation->GetBackendId() == <span class="stringliteral">"CustomBackend"</span>));</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  }</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  };</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span> </div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  <span class="keyword">struct </span>CustomPolicy</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  {</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <span class="keyword">static</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a>& GetIdStatic()</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  {</div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <span class="keyword">static</span> <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a> <span class="keywordtype">id</span>=<span class="stringliteral">"CustomBackend"</span>;</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  <span class="keywordflow">return</span> id;</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  }</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  };</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span> </div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  <span class="keyword">struct </span>MockPolicy</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  {</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  <span class="keyword">static</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a>& GetIdStatic()</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  {</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  <span class="keyword">static</span> <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a> <span class="keywordtype">id</span>=<span class="stringliteral">"MockBackend"</span>;</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <span class="keywordflow">return</span> id;</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  }</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  };</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span> </div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  <span class="keyword">auto</span>& backendRegistry = <a class="code" href="namespacearmnn.xhtml#ac2807505b850738bc8a1991ce669dd47">BackendRegistryInstance</a>();</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span> </div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  backendRegistry.Register(<span class="stringliteral">"MockBackend"</span>, [](){</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  <span class="keywordflow">return</span> std::make_unique<MockBackend<MockPolicy>>();</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  });</div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span> </div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  backendRegistry.Register(<span class="stringliteral">"CustomBackend"</span>, [](){</div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  <span class="keywordflow">return</span> std::make_unique<MockBackend<CustomPolicy>>();</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  });</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span> </div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <span class="comment">// Define the network</span></div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  <span class="keyword">auto</span> network = INetwork::Create();</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">ActivationDescriptor</a> desc;</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  desc.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = ActivationFunction::Linear;</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span> </div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  std::unique_ptr<Graph> graph = std::make_unique<Graph>();</div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <span class="keyword">auto</span> input = graph->AddLayer<<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  <span class="keyword">auto</span> act = graph->AddLayer<<a class="code" href="classarmnn_1_1_activation_layer.xhtml">ActivationLayer</a>>(desc, <span class="stringliteral">"activation"</span>);</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  <span class="keyword">auto</span> output = graph->AddLayer<<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span> </div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a> customBackendId(<span class="stringliteral">"CustomBackend"</span>);</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  act-><a class="code" href="classarmnn_1_1_layer.xhtml#a43a46eafee5c08787ab17b4342730c20">BackendSelectionHint</a>(customBackendId);</div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span> </div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  input->GetOutputSlot(0).Connect(act-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  act-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span> </div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span> </div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  <span class="keyword">auto</span> optNet = <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a>(<span class="keyword">new</span> <a class="code" href="classarmnn_1_1_optimized_network.xhtml">OptimizedNetwork</a>(std::move(graph)), &IOptimizedNetwork::Destroy);</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span> </div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <a class="code" href="classarmnn_1_1_optimized_network.xhtml">OptimizedNetwork</a>* optNetObjPtr = boost::polymorphic_downcast<OptimizedNetwork*>(optNet.get());</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span> </div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  <span class="comment">// Get the optimized graph</span></div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& optGraph = optNetObjPtr-><a class="code" href="classarmnn_1_1_optimized_network.xhtml#a49800ad35ea869aa5569519760d3b339">GetGraph</a>();</div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span> </div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span> </div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  std::vector<BackendId> prefs{<span class="stringliteral">"MockBackend"</span>, <span class="stringliteral">"CustomBackend"</span>};</div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span> </div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  <a class="code" href="namespacearmnn.xhtml#a1854d9cda81304325664363c1fd0fb27">BackendIdSet</a> availableBackends = {<span class="stringliteral">"CustomBackend"</span>, <span class="stringliteral">"MockBackend"</span>};</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  <a class="code" href="classarmnn_1_1_device_spec.xhtml">DeviceSpec</a> spec(availableBackends);</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span> </div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a> backendSettings(prefs, spec);</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span> </div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  <span class="comment">// Assign an available backend to each layer</span></div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a> firstLayer = optGraph.begin();</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a> lastLayer = optGraph.end();</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> res = <a class="code" href="namespacearmnn.xhtml#a8acab870a91373c720c9822b59ecf3b8">AssignBackends</a>(optNetObjPtr,</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  backendSettings,</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  firstLayer,</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  lastLayer,</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>());</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span> </div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  BOOST_TEST(res.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a955b65059e7f9429a5d6041136bc1487">IsOk</a>());</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span> </div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  TestBackendAssignment visitor;</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it =firstLayer; it != lastLayer; ++it)</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  {</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  (*it)->Accept(visitor);</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  }</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span> }</div><div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00061">INetwork.hpp:61</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_visitor_base_xhtml_a6c23f9e9d8427775925d071feee5dbd1"><div class="ttname"><a href="classarmnn_1_1_layer_visitor_base.xhtml#a6c23f9e9d8427775925d071feee5dbd1">armnn::LayerVisitorBase::VisitInputLayer</a></div><div class="ttdeci">void VisitInputLayer(const IConnectableLayer *, LayerBindingId, const char *) override</div><div class="ttdoc">Function that an InputLayer should call back to when its Accept(ILayerVisitor&) function is invoked...</div><div class="ttdef"><b>Definition:</b> <a href="_layer_visitor_base_8hpp_source.xhtml#l00119">LayerVisitorBase.hpp:119</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a1854d9cda81304325664363c1fd0fb27"><div class="ttname"><a href="namespacearmnn.xhtml#a1854d9cda81304325664363c1fd0fb27">armnn::BackendIdSet</a></div><div class="ttdeci">std::unordered_set< BackendId > BackendIdSet</div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.xhtml#l00191">BackendId.hpp:191</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a43a46eafee5c08787ab17b4342730c20"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a43a46eafee5c08787ab17b4342730c20">armnn::Layer::BackendSelectionHint</a></div><div class="ttdeci">void BackendSelectionHint(Optional< BackendId > backend) final</div><div class="ttdoc">Provide a hint for the optimizer as to which backend to prefer for this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00324">Layer.hpp:324</a></div></div> +<div class="ttc" id="classarmnn_1_1_device_spec_xhtml"><div class="ttname"><a href="classarmnn_1_1_device_spec.xhtml">armnn::DeviceSpec</a></div><div class="ttdef"><b>Definition:</b> <a href="_device_spec_8hpp_source.xhtml#l00014">DeviceSpec.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00079">Layer.cpp:79</a></div></div> +<div class="ttc" id="classarmnn_1_1_activation_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_activation_layer.xhtml">armnn::ActivationLayer</a></div><div class="ttdoc">This layer represents an activation operation with the specified activation function. </div><div class="ttdef"><b>Definition:</b> <a href="_activation_layer_8hpp_source.xhtml#l00012">ActivationLayer.hpp:12</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ac2807505b850738bc8a1991ce669dd47"><div class="ttname"><a href="namespacearmnn.xhtml#ac2807505b850738bc8a1991ce669dd47">armnn::BackendRegistryInstance</a></div><div class="ttdeci">BackendRegistry & BackendRegistryInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.xhtml#l00013">BackendRegistry.cpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_xhtml_a49800ad35ea869aa5569519760d3b339"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml#a49800ad35ea869aa5569519760d3b339">armnn::OptimizedNetwork::GetGraph</a></div><div class="ttdeci">Graph & GetGraph()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00276">Network.hpp:276</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_acc25db0641c1c22faf95af3bb49080c9"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">armnn::Graph::Iterator</a></div><div class="ttdeci">LayerList::const_iterator Iterator</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00050">Graph.hpp:50</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00171">Types.hpp:171</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">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.xhtml#l00013">OutputLayer.hpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimization_result_xhtml_a955b65059e7f9429a5d6041136bc1487"><div class="ttname"><a href="structarmnn_1_1_optimization_result.xhtml#a955b65059e7f9429a5d6041136bc1487">armnn::OptimizationResult::IsOk</a></div><div class="ttdeci">bool IsOk() const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00299">Network.hpp:299</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00566">INetwork.hpp:566</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00020">Descriptors.hpp:20</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimization_result_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimization_result.xhtml">armnn::OptimizationResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00285">Network.hpp:285</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_visitor_base_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer_visitor_base.xhtml">armnn::LayerVisitorBase</a></div><div class="ttdoc">Visitor base class with empty implementations. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_visitor_base_8hpp_source.xhtml#l00025">LayerVisitorBase.hpp:25</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8acab870a91373c720c9822b59ecf3b8"><div class="ttname"><a href="namespacearmnn.xhtml#a8acab870a91373c720c9822b59ecf3b8">armnn::AssignBackends</a></div><div class="ttdeci">OptimizationResult AssignBackends(OptimizedNetwork *optNetObjPtr, BackendSettings &backendSettings, Graph::Iterator &firstLayer, Graph::Iterator &lastLayer, Optional< std::vector< std::string > &> errMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00269">Network.cpp:269</a></div></div> +<div class="ttc" id="structarmnn_1_1_empty_optional_xhtml"><div class="ttname"><a href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a></div><div class="ttdoc">EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00032">Optional.hpp:32</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">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.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_visitor_base_xhtml_acc39ddb06acfd91cf3cfb0fcd9337005"><div class="ttname"><a href="classarmnn_1_1_layer_visitor_base.xhtml#acc39ddb06acfd91cf3cfb0fcd9337005">armnn::LayerVisitorBase::VisitOutputLayer</a></div><div class="ttdeci">void VisitOutputLayer(const IConnectableLayer *, LayerBindingId, const char *) override</div><div class="ttdoc">Function an output layer should call back to when its Accept(ILayerVisitor&) function is invoked...</div><div class="ttdef"><b>Definition:</b> <a href="_layer_visitor_base_8hpp_source.xhtml#l00164">LayerVisitorBase.hpp:164</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="structarmnn_1_1_backend_settings_xhtml"><div class="ttname"><a href="structarmnn_1_1_backend_settings.xhtml">armnn::BackendSettings</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_settings_8hpp_source.xhtml#l00017">BackendSettings.hpp:17</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_af10fa7883e3579950f477bee92a64844"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">armnn::ActivationDescriptor::m_Function</a></div><div class="ttdeci">ActivationFunction m_Function</div><div class="ttdoc">The activation function to use (Sigmoid, TanH, Linear, ReLu, BoundedReLu, SoftReLu, LeakyReLu, Abs, Sqrt, Square). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00035">Descriptors.hpp:35</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml">armnn::OptimizedNetwork</a></div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00265">Network.hpp:265</a></div></div> +<div class="ttc" id="classarmnn_1_1_backend_id_xhtml"><div class="ttname"><a href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.xhtml#l00075">BackendId.hpp:75</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_visitor_base_xhtml_a30b99e5202fc77b02f92d5c44e5ca86d"><div class="ttname"><a href="classarmnn_1_1_layer_visitor_base.xhtml#a30b99e5202fc77b02f92d5c44e5ca86d">armnn::LayerVisitorBase::VisitActivationLayer</a></div><div class="ttdeci">void VisitActivationLayer(const IConnectableLayer *, const ActivationDescriptor &, const char *) override</div><div class="ttdoc">Function that an activation layer should call back to when its Accept(ILayerVisitor&) function is inv...</div><div class="ttdef"><b>Definition:</b> <a href="_layer_visitor_base_8hpp_source.xhtml#l00035">LayerVisitorBase.hpp:35</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a5065b32dd0aa2c08ef75e953ebedbc16"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a5065b32dd0aa2c08ef75e953ebedbc16">◆ </a></span>CreateConvolution2dGraph()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void CreateConvolution2dGraph </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> & </td> + <td class="paramname"><em>graph</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>inputShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>weightsShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>outputShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> </td> + <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code> </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.xhtml#l00256">256</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_graph_8hpp_source.xhtml#l00397">Graph::AddLayer()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00438">Convolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00440">Convolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00430">Convolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00432">Convolution2dDescriptor::m_StrideY</a>, <a class="el" href="_convolution2d_layer_8hpp_source.xhtml#l00020">Convolution2dLayer::m_Weight</a>, and <a class="el" href="_layer_8cpp_source.xhtml#l00058">OutputSlot::SetTensorInfo()</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00284">BOOST_AUTO_TEST_CASE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> {</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> </div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  std::vector<float> weightsVector(90);</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, weightsShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), weightsVector);</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> </div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a> desc;</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> </div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">Convolution2dLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">Convolution2dLayer</a>>(desc, <span class="stringliteral">"conv2d"</span>);</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> </div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> }</div><div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00438">Descriptors.hpp:438</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00440">Descriptors.hpp:440</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... 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.xhtml#l00397">Graph.hpp:397</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00392">Descriptors.hpp:392</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00079">Layer.cpp:79</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00430">Descriptors.hpp:430</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">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.xhtml#l00013">OutputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::Convolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > 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.xhtml#l00020">Convolution2dLayer.hpp:20</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">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.xhtml#l00199">Tensor.hpp:199</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00432">Descriptors.hpp:432</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">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.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml">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.xhtml#l00015">Convolution2dLayer.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="acd97facea671e23ec3e8b33c6c2ea321"></a> +<h2 class="memtitle"><span class="permalink"><a href="#acd97facea671e23ec3e8b33c6c2ea321">◆ </a></span>CreateDepthwiseConvolution2dGraph()</h2> + +<div class="memitem"> +<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.xhtml">Graph</a> & </td> + <td class="paramname"><em>graph</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>inputShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>weightsShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>outputShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> </td> + <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code> </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.xhtml#l00306">306</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_graph_8hpp_source.xhtml#l00397">Graph::AddLayer()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00490">DepthwiseConvolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00492">DepthwiseConvolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00482">DepthwiseConvolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00484">DepthwiseConvolution2dDescriptor::m_StrideY</a>, <a class="el" href="_depthwise_convolution2d_layer_8hpp_source.xhtml#l00019">DepthwiseConvolution2dLayer::m_Weight</a>, and <a class="el" href="_layer_8cpp_source.xhtml#l00058">OutputSlot::SetTensorInfo()</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00334">BOOST_AUTO_TEST_CASE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> {</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  std::vector<float> weightsVector(18);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, weightsShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), weightsVector);</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a> desc;</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> </div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">DepthwiseConvolution2dLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">DepthwiseConvolution2dLayer</a>>(desc, <span class="stringliteral">"depthwiseConv2d"</span>);</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> </div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> }</div><div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#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.xhtml#l00490">Descriptors.hpp:490</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#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.xhtml#l00492">Descriptors.hpp:492</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">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.xhtml#l00015">DepthwiseConvolution2dLayer.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... 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.xhtml#l00397">Graph.hpp:397</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00079">Layer.cpp:79</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#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.xhtml#l00482">Descriptors.hpp:482</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">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.xhtml#l00013">OutputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">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.xhtml#l00199">Tensor.hpp:199</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#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.xhtml#l00484">Descriptors.hpp:484</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">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.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::DepthwiseConvolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > 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.xhtml#l00019">DepthwiseConvolution2dLayer.hpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00444">Descriptors.hpp:444</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aa4e793c84e5dfea800d4dba921651e5b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aa4e793c84e5dfea800d4dba921651e5b">◆ </a></span>CreateGatherGraph()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void CreateGatherGraph </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> & </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.xhtml">armnn::TensorInfo</a> & </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.xhtml">armnn::TensorInfo</a> & </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.xhtml">armnn::TensorInfo</a> & </td> + <td class="paramname"><em>outputInfo</em> </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.xhtml#l00448">448</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_graph_8hpp_source.xhtml#l00397">Graph::AddLayer()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00079">OutputSlot::Connect()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, and <a class="el" href="_layer_8cpp_source.xhtml#l00058">OutputSlot::SetTensorInfo()</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00466">BOOST_AUTO_TEST_CASE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00450"></a><span class="lineno"> 450</span> {</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* input0 = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"params"</span>);</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  input0-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(paramsInfo);</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span> </div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* input1 = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(1, <span class="stringliteral">"indices"</span>);</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(indicesInfo);</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <a class="code" href="classarmnn_1_1_gather_layer.xhtml">GatherLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_gather_layer.xhtml">GatherLayer</a>>(<span class="stringliteral">"gather"</span>);</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span> </div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  input0-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span> }</div><div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... 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.xhtml#l00397">Graph.hpp:397</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00079">Layer.cpp:79</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">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.xhtml#l00013">OutputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_gather_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_gather_layer.xhtml">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.xhtml#l00014">GatherLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">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.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a4756218150e4ca0da09d0ecc390a7a17"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a4756218150e4ca0da09d0ecc390a7a17">◆ </a></span>CreatePooling2dGraph()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void CreatePooling2dGraph </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> & </td> + <td class="paramname"><em>graph</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>inputShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>outputShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> </td> + <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code> </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.xhtml#l00356">356</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_graph_8hpp_source.xhtml#l00397">Graph::AddLayer()</a>, <a class="el" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::Average</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::Exclude</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00369">Pooling2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00355">Pooling2dDescriptor::m_PadBottom</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00367">Pooling2dDescriptor::m_PaddingMethod</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00349">Pooling2dDescriptor::m_PadLeft</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00351">Pooling2dDescriptor::m_PadRight</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00353">Pooling2dDescriptor::m_PadTop</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00359">Pooling2dDescriptor::m_PoolHeight</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00347">Pooling2dDescriptor::m_PoolType</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00357">Pooling2dDescriptor::m_PoolWidth</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00361">Pooling2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00363">Pooling2dDescriptor::m_StrideY</a>, and <a class="el" href="_layer_8cpp_source.xhtml#l00058">OutputSlot::SetTensorInfo()</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00384">BOOST_AUTO_TEST_CASE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> {</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span> </div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">Pooling2dDescriptor</a> desc;</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 100;</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 5;</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 50;</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 50;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 50;</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 50;</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> </div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> </div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <a class="code" href="classarmnn_1_1_pooling2d_layer.xhtml">Pooling2dLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_pooling2d_layer.xhtml">Pooling2dLayer</a>>(desc, <span class="stringliteral">"pooling2d"</span>);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> </div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> }</div><div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00355">Descriptors.hpp:355</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00349">Descriptors.hpp:349</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... 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.xhtml#l00397">Graph.hpp:397</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00357">Descriptors.hpp:357</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00079">Layer.cpp:79</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6"><div class="ttname"><a href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a></div><div class="ttdoc">The padding fields don&#39;t count and are ignored. </div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a8c29d6ea9b4186d69aad5961c910939c"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00367">Descriptors.hpp:367</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00353">Descriptors.hpp:353</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00361">Descriptors.hpp:361</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00359">Descriptors.hpp:359</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">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.xhtml#l00013">OutputLayer.hpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00351">Descriptors.hpp:351</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a></div></div> +<div class="ttc" id="classarmnn_1_1_pooling2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_pooling2d_layer.xhtml">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.xhtml#l00013">Pooling2dLayer.hpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00369">Descriptors.hpp:369</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00347">Descriptors.hpp:347</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">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.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00313">Descriptors.hpp:313</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#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.xhtml#l00363">Descriptors.hpp:363</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aefb2c7f14f687a9432490a1bdee05458"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aefb2c7f14f687a9432490a1bdee05458">◆ </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.xhtml">Graph</a> & </td> + <td class="paramname"><em>graph</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>inputShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const unsigned int * </td> + <td class="paramname"><em>outputShape</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> </td> + <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code> </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.xhtml#l00404">404</a> of file <a class="el" href="_optimizer_tests_8cpp_source.xhtml">OptimizerTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_graph_8hpp_source.xhtml#l00397">Graph::AddLayer()</a>, <a class="el" href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::Bilinear</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00751">ResizeDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00749">ResizeDescriptor::m_Method</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00746">ResizeDescriptor::m_TargetHeight</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00744">ResizeDescriptor::m_TargetWidth</a>, and <a class="el" href="_layer_8cpp_source.xhtml#l00058">OutputSlot::SetTensorInfo()</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.xhtml#l00427">BOOST_AUTO_TEST_CASE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00406"></a><span class="lineno"> 406</span> {</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> </div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">ResizeDescriptor</a> desc;</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  desc.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a869254cb56968986a78a79e1d6d4a86b">m_Method</a> = ResizeMethod::Bilinear;</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  desc.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = 3;</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  desc.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = 4;</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  desc.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> </div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> </div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <a class="code" href="classarmnn_1_1_resize_layer.xhtml">ResizeLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_resize_layer.xhtml">ResizeLayer</a>>(desc, <span class="stringliteral">"resizeBilinear"</span>);</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... 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.xhtml#l00397">Graph.hpp:397</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00079">Layer.cpp:79</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a869254cb56968986a78a79e1d6d4a86b"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a869254cb56968986a78a79e1d6d4a86b">armnn::ResizeDescriptor::m_Method</a></div><div class="ttdeci">ResizeMethod m_Method</div><div class="ttdoc">The Interpolation method to use (Bilinear, NearestNeighbor). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00749">Descriptors.hpp:749</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml">armnn::ResizeDescriptor</a></div><div class="ttdoc">A ResizeDescriptor for the ResizeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00724">Descriptors.hpp:724</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">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.xhtml#l00013">OutputLayer.hpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_adcf5037208faac36c0788239a073f75c"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#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.xhtml#l00744">Descriptors.hpp:744</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a46c3fa15c46fb0d1dcdc24d0ea5cb5cd"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#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.xhtml#l00746">Descriptors.hpp:746</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">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.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#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.xhtml#l00751">Descriptors.hpp:751</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +<div class="ttc" id="classarmnn_1_1_resize_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_resize_layer.xhtml">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.xhtml#l00013">ResizeLayer.hpp:13</a></div></div> +</div><!-- fragment --> +</div> +</div> +</div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_e0a84d05c80a2ef4231141dcbbeac5c8.xhtml">armnn</a></li><li class="navelem"><a class="el" href="dir_9d86fd1fbecbedf5bdb69c7e7235fe5f.xhtml">test</a></li><li class="navelem"><a class="el" href="_optimizer_tests_8cpp.xhtml">OptimizerTests.cpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:13 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> +</div> +</body> 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