Ryan OShea | de36e4a | 2020-03-13 16:26:19 +0000 | [diff] [blame] | 1 | <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> |
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| 86 | <div class="title">OptimizerTests.cpp File Reference</div> </div> |
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| 88 | <div class="contents"> |
| 89 | <div class="textblock"><code>#include "<a class="el" href="_test_utils_8hpp_source.html">TestUtils.hpp</a>"</code><br /> |
| 90 | <code>#include <<a class="el" href="_graph_8hpp_source.html">Graph.hpp</a>></code><br /> |
| 91 | <code>#include <<a class="el" href="_optimizer_8hpp_source.html">Optimizer.hpp</a>></code><br /> |
| 92 | <code>#include <<a class="el" href="_floating_point_converter_8hpp_source.html">armnnUtils/FloatingPointConverter.hpp</a>></code><br /> |
| 93 | <code>#include <<a class="el" href="_cpu_tensor_handle_8hpp_source.html">backendsCommon/CpuTensorHandle.hpp</a>></code><br /> |
| 94 | <code>#include <boost/test/unit_test.hpp></code><br /> |
| 95 | </div> |
| 96 | <p><a href="_optimizer_tests_8cpp_source.html">Go to the source code of this file.</a></p> |
| 97 | <table class="memberdecls"> |
| 98 | <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> |
| 99 | Functions</h2></td></tr> |
| 100 | <tr class="memitem:a8839099137f1031b504d76090074142c"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a8839099137f1031b504d76090074142c">BOOST_AUTO_TEST_CASE</a> (LSTMValidateTensorShapesFromInputsCIFGDisabledTest)</td></tr> |
| 101 | <tr class="separator:a8839099137f1031b504d76090074142c"><td class="memSeparator" colspan="2"> </td></tr> |
| 102 | <tr class="memitem:a10342b734f73496052047f2b74b38cca"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a10342b734f73496052047f2b74b38cca">BOOST_AUTO_TEST_CASE</a> (LSTMValidateTensorShapesFromInputsCIFGEnabledTest)</td></tr> |
| 103 | <tr class="separator:a10342b734f73496052047f2b74b38cca"><td class="memSeparator" colspan="2"> </td></tr> |
| 104 | <tr class="memitem:a09fa0a0ab3199f1a7bfc169bce93925d"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a09fa0a0ab3199f1a7bfc169bce93925d">BOOST_AUTO_TEST_CASE</a> (InsertConvertersTest)</td></tr> |
| 105 | <tr class="separator:a09fa0a0ab3199f1a7bfc169bce93925d"><td class="memSeparator" colspan="2"> </td></tr> |
| 106 | <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.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr> |
| 107 | <tr class="separator:a5065b32dd0aa2c08ef75e953ebedbc16"><td class="memSeparator" colspan="2"> </td></tr> |
| 108 | <tr class="memitem:a6b7bebf2c0d384c3297a6c3b19346555"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a6b7bebf2c0d384c3297a6c3b19346555">BOOST_AUTO_TEST_CASE</a> (Conv2dValidateTensorShapesFromInputs)</td></tr> |
| 109 | <tr class="separator:a6b7bebf2c0d384c3297a6c3b19346555"><td class="memSeparator" colspan="2"> </td></tr> |
| 110 | <tr class="memitem:a67738cd9d506e11aa4f4f43b9dc30e2c"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a67738cd9d506e11aa4f4f43b9dc30e2c">BOOST_AUTO_TEST_CASE</a> (Conv2dValidateTensorShapesFromInputsNhwc)</td></tr> |
| 111 | <tr class="separator:a67738cd9d506e11aa4f4f43b9dc30e2c"><td class="memSeparator" colspan="2"> </td></tr> |
| 112 | <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.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr> |
| 113 | <tr class="separator:acd97facea671e23ec3e8b33c6c2ea321"><td class="memSeparator" colspan="2"> </td></tr> |
| 114 | <tr class="memitem:a93b5cb4143e78fec858fe77e86472bec"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a93b5cb4143e78fec858fe77e86472bec">BOOST_AUTO_TEST_CASE</a> (DepthwiseConv2dValidateTensorShapesFromInputs)</td></tr> |
| 115 | <tr class="separator:a93b5cb4143e78fec858fe77e86472bec"><td class="memSeparator" colspan="2"> </td></tr> |
| 116 | <tr class="memitem:aa678f54308701529660f9ee2a70bd042"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#aa678f54308701529660f9ee2a70bd042">BOOST_AUTO_TEST_CASE</a> (DepthwiseConv2dValidateTensorShapesFromInputsNhwc)</td></tr> |
| 117 | <tr class="separator:aa678f54308701529660f9ee2a70bd042"><td class="memSeparator" colspan="2"> </td></tr> |
| 118 | <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.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &graph, const unsigned int *inputShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr> |
| 119 | <tr class="separator:a4756218150e4ca0da09d0ecc390a7a17"><td class="memSeparator" colspan="2"> </td></tr> |
| 120 | <tr class="memitem:a8457188fd0859ae6a91c09c3266f58a5"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a8457188fd0859ae6a91c09c3266f58a5">BOOST_AUTO_TEST_CASE</a> (Pooling2dValidateTensorShapesFromInputs)</td></tr> |
| 121 | <tr class="separator:a8457188fd0859ae6a91c09c3266f58a5"><td class="memSeparator" colspan="2"> </td></tr> |
| 122 | <tr class="memitem:a1c7c22035e9b339dad1aedcf1d9c49e9"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a1c7c22035e9b339dad1aedcf1d9c49e9">BOOST_AUTO_TEST_CASE</a> (Pooling2dValidateTensorShapesFromInputsNhwc)</td></tr> |
| 123 | <tr class="separator:a1c7c22035e9b339dad1aedcf1d9c49e9"><td class="memSeparator" colspan="2"> </td></tr> |
| 124 | <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.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &graph, const unsigned int *inputShape, const unsigned int *outputShape, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout=DataLayout::NCHW)</td></tr> |
| 125 | <tr class="separator:aefb2c7f14f687a9432490a1bdee05458"><td class="memSeparator" colspan="2"> </td></tr> |
| 126 | <tr class="memitem:acee9ba1427bd42cc38a0402969dd0d35"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#acee9ba1427bd42cc38a0402969dd0d35">BOOST_AUTO_TEST_CASE</a> (ResizeBilinearValidateTensorShapesFromInputs)</td></tr> |
| 127 | <tr class="separator:acee9ba1427bd42cc38a0402969dd0d35"><td class="memSeparator" colspan="2"> </td></tr> |
| 128 | <tr class="memitem:abbc42a4387722b0b5e0c00038288dd4e"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#abbc42a4387722b0b5e0c00038288dd4e">BOOST_AUTO_TEST_CASE</a> (ResizeBilinearValidateTensorShapesFromInputsNhwc)</td></tr> |
| 129 | <tr class="separator:abbc42a4387722b0b5e0c00038288dd4e"><td class="memSeparator" colspan="2"> </td></tr> |
| 130 | <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.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &graph, const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> &paramsInfo, const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> &indicesInfo, const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> &outputInfo)</td></tr> |
| 131 | <tr class="separator:aa4e793c84e5dfea800d4dba921651e5b"><td class="memSeparator" colspan="2"> </td></tr> |
| 132 | <tr class="memitem:a57aa1f639ec35a976735c91889d463a4"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a57aa1f639ec35a976735c91889d463a4">BOOST_AUTO_TEST_CASE</a> (GatherValidateTensorShapesFromInputs)</td></tr> |
| 133 | <tr class="separator:a57aa1f639ec35a976735c91889d463a4"><td class="memSeparator" colspan="2"> </td></tr> |
| 134 | <tr class="memitem:af31e0d94eb9ec7e72b9d6d70da3070ec"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#af31e0d94eb9ec7e72b9d6d70da3070ec">BOOST_AUTO_TEST_CASE</a> (GatherValidateTensorShapesFromInputs1DParams)</td></tr> |
| 135 | <tr class="separator:af31e0d94eb9ec7e72b9d6d70da3070ec"><td class="memSeparator" colspan="2"> </td></tr> |
| 136 | <tr class="memitem:a65b5e30de580e14475b51da9b93c908b"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a65b5e30de580e14475b51da9b93c908b">BOOST_AUTO_TEST_CASE</a> (GatherValidateTensorShapesFromInputsMultiDimIndices)</td></tr> |
| 137 | <tr class="separator:a65b5e30de580e14475b51da9b93c908b"><td class="memSeparator" colspan="2"> </td></tr> |
| 138 | <tr class="memitem:a0ee7b0e1f8d1dd9a9e001720e69086eb"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a0ee7b0e1f8d1dd9a9e001720e69086eb">BOOST_AUTO_TEST_CASE</a> (DetectionPostProcessValidateTensorShapes)</td></tr> |
| 139 | <tr class="separator:a0ee7b0e1f8d1dd9a9e001720e69086eb"><td class="memSeparator" colspan="2"> </td></tr> |
| 140 | <tr class="memitem:a4ef49bab7a1b82c389b3b45ffb767833"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_optimizer_tests_8cpp.html#a4ef49bab7a1b82c389b3b45ffb767833">BOOST_AUTO_TEST_CASE</a> (FoldPadLayerIntoConvolution2dLayer)</td></tr> |
| 141 | <tr class="separator:a4ef49bab7a1b82c389b3b45ffb767833"><td class="memSeparator" colspan="2"> </td></tr> |
| 142 | </table> |
| 143 | <h2 class="groupheader">Function Documentation</h2> |
| 144 | <a id="a8839099137f1031b504d76090074142c"></a> |
| 145 | <h2 class="memtitle"><span class="permalink"><a href="#a8839099137f1031b504d76090074142c">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[1/16]</span></h2> |
| 146 | |
| 147 | <div class="memitem"> |
| 148 | <div class="memproto"> |
| 149 | <table class="memname"> |
| 150 | <tr> |
| 151 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 152 | <td>(</td> |
| 153 | <td class="paramtype">LSTMValidateTensorShapesFromInputsCIFGDisabledTest </td> |
| 154 | <td class="paramname"></td><td>)</td> |
| 155 | <td></td> |
| 156 | </tr> |
| 157 | </table> |
| 158 | </div><div class="memdoc"> |
| 159 | |
| 160 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00134">134</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 161 | |
| 162 | <p class="reference">References <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p> |
| 163 | <div class="fragment"><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> </div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="comment">//Helper function creates graph containing LSTM layer with required input and output layers</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  CreateLSTMLayerHelper(graph, <span class="keyword">false</span>);</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="comment">//This function used to call ValidateShapesFromInputs();</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> }</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 164 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 165 | </div><!-- fragment --> |
| 166 | </div> |
| 167 | </div> |
| 168 | <a id="a10342b734f73496052047f2b74b38cca"></a> |
| 169 | <h2 class="memtitle"><span class="permalink"><a href="#a10342b734f73496052047f2b74b38cca">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[2/16]</span></h2> |
| 170 | |
| 171 | <div class="memitem"> |
| 172 | <div class="memproto"> |
| 173 | <table class="memname"> |
| 174 | <tr> |
| 175 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 176 | <td>(</td> |
| 177 | <td class="paramtype">LSTMValidateTensorShapesFromInputsCIFGEnabledTest </td> |
| 178 | <td class="paramname"></td><td>)</td> |
| 179 | <td></td> |
| 180 | </tr> |
| 181 | </table> |
| 182 | </div><div class="memdoc"> |
| 183 | |
| 184 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00145">145</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 185 | |
| 186 | <p class="reference">References <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p> |
| 187 | <div class="fragment"><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> {</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="comment">//Helper function creates graph containing LSTM layer with required input and output layers</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  CreateLSTMLayerHelper(graph, <span class="keyword">true</span>);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="comment">//This function used to call ValidateShapesFromInputs();</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> }</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 188 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 189 | </div><!-- fragment --> |
| 190 | </div> |
| 191 | </div> |
| 192 | <a id="a09fa0a0ab3199f1a7bfc169bce93925d"></a> |
| 193 | <h2 class="memtitle"><span class="permalink"><a href="#a09fa0a0ab3199f1a7bfc169bce93925d">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[3/16]</span></h2> |
| 194 | |
| 195 | <div class="memitem"> |
| 196 | <div class="memproto"> |
| 197 | <table class="memname"> |
| 198 | <tr> |
| 199 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 200 | <td>(</td> |
| 201 | <td class="paramtype">InsertConvertersTest </td> |
| 202 | <td class="paramname"></td><td>)</td> |
| 203 | <td></td> |
| 204 | </tr> |
| 205 | </table> |
| 206 | </div><div class="memdoc"> |
| 207 | |
| 208 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00156">156</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 209 | |
| 210 | <p class="reference">References <a class="el" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">armnn::Addition</a>, <a class="el" href="_test_utils_8hpp_source.html#l00020">CheckSequence()</a>, <a class="el" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">armnn::ConvertFp16ToFp32</a>, <a class="el" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">armnn::ConvertFp32ToFp16</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::Float16</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::Floor</a>, <a class="el" href="_tensor_8hpp_source.html#l00095">TensorInfo::GetDataType()</a>, <a class="el" href="_layer_8cpp_source.html#l00272">Layer::GetDataType()</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00221">Layer::GetOutputHandler()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_layer_8cpp_source.html#l00063">OutputSlot::GetTensorInfo()</a>, <a class="el" href="_layer_8hpp_source.html#l00259">Layer::GetType()</a>, <a class="el" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="_network_utils_8cpp_source.html#l00040">armnn::InsertConvertFp16ToFp32LayersBefore()</a>, <a class="el" href="_network_utils_8cpp_source.html#l00079">armnn::InsertConvertFp32ToFp16LayersAfter()</a>, and <a class="el" href="_output_handler_8cpp_source.html#l00017">OutputHandler::SetTensorInfo()</a>.</p> |
| 211 | <div class="fragment"><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> {</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 5, 2, 3 }, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <a class="code" href="classarmnn_1_1_graph.html">armnn::Graph</a> graph;</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> </div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> inputId = 0;</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> </div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <a class="code" href="classarmnn_1_1_layer.html">armnn::Layer</a>* head = graph.AddLayer<<a class="code" href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> </div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  head = graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_addition_layer.html">armnn::AdditionLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), <span class="stringliteral">""</span>);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  head-><a class="code" href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>().<a class="code" href="classarmnn_1_1_output_handler.html#a97db12c41024f5545ef5cc4153e5443b">SetTensorInfo</a>(info);</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1), inputId++, <span class="stringliteral">""</span>)</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  ->GetOutputHandler().SetTensorInfo(info);</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> </div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  head = graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_floor_layer.html">armnn::FloorLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), <span class="stringliteral">""</span>);</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  head-><a class="code" href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>().<a class="code" href="classarmnn_1_1_output_handler.html#a97db12c41024f5545ef5cc4153e5443b">SetTensorInfo</a>(info);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  head = graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_mem_copy_layer.html">armnn::MemCopyLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), <span class="stringliteral">""</span>);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  head-><a class="code" href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>().<a class="code" href="classarmnn_1_1_output_handler.html#a97db12c41024f5545ef5cc4153e5443b">SetTensorInfo</a>(info);</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> </div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  graph.InsertNewLayer<<a class="code" href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a>>(head-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0), inputId++, <span class="stringliteral">""</span>)</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  ->GetOutputHandler().SetTensorInfo(info);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="comment">// Check graph layer sequence before inserting convert layers</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.cbegin(),</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  graph.cend(),</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  &IsLayerOfType<armnn::MemCopyLayer>,</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  &IsLayerOfType<armnn::FloorLayer>,</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  &IsLayerOfType<armnn::AdditionLayer>,</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  &IsLayerOfType<armnn::OutputLayer>));</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="comment">// Check layers have Float16 DataType</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& layer : graph)</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  {</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">if</span>(layer->GetType()==LayerType::Floor || layer->GetType() == LayerType::Addition)</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  {</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  BOOST_ASSERT(layer->GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float16);</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  BOOST_ASSERT(layer->GetDataType() == DataType::Float16);</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  }</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  }</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="comment">// Insert convert layers either side of unsupported layer</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& layer : graph)</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  {</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keywordflow">if</span>(layer->GetType()==LayerType::Floor || layer->GetType() == LayerType::Addition)</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>  <a class="code" href="namespacearmnn.html#ad31c56533e4f9f9f51719599fbfcf7bb">InsertConvertFp16ToFp32LayersBefore</a>(graph, *layer);</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <a class="code" href="namespacearmnn.html#abf625e50a5eaeafce5b39580dc95a9d3">InsertConvertFp32ToFp16LayersAfter</a>(graph, *layer);</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  }</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  }</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="comment">// Check layers have correct DataType after inserting convert layers</span></div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& layer : graph)</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  {</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keywordflow">if</span> (layer->GetType()==LayerType::Floor || layer->GetType() == LayerType::Addition)</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>  BOOST_ASSERT(layer->GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float32);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  BOOST_ASSERT(layer->GetDataType() == DataType::Float32);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  }</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer->GetType() == LayerType::ConvertFp16ToFp32)</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>  BOOST_ASSERT(layer->GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float32);</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  BOOST_ASSERT(layer->GetDataType() == DataType::Float16);</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  }</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer->GetType() == LayerType::ConvertFp32ToFp16)</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>  BOOST_ASSERT(layer->GetOutputSlot(0).GetTensorInfo().GetDataType() == DataType::Float16);</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  BOOST_ASSERT(layer->GetDataType() == DataType::Float32);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  }</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  }</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="comment">// Check sequence of layers after inserting convert layers</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.cbegin(),</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  graph.cend(),</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  &IsLayerOfType<armnn::ConvertFp16ToFp32Layer>,</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  &IsLayerOfType<armnn::MemCopyLayer>,</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  &IsLayerOfType<armnn::ConvertFp16ToFp32Layer>,</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  &IsLayerOfType<armnn::FloorLayer>,</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  &IsLayerOfType<armnn::ConvertFp16ToFp32Layer>,</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  &IsLayerOfType<armnn::AdditionLayer>,</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  &IsLayerOfType<armnn::OutputLayer>));</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> }</div><div class="ttc" id="classarmnn_1_1_layer_html_af2c0edc7ea62a8baaec4d3d9b2b09256"><div class="ttname"><a href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">armnn::Layer::GetOutputHandler</a></div><div class="ttdeci">const OutputHandler & GetOutputHandler(unsigned int i=0) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00221">Layer.hpp:221</a></div></div> |
| 212 | <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div> |
| 213 | <div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> |
| 214 | <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div> |
| 215 | <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 216 | <div class="ttc" id="classarmnn_1_1_mem_copy_layer_html"><div class="ttname"><a href="classarmnn_1_1_mem_copy_layer.html">armnn::MemCopyLayer</a></div><div class="ttdoc">This layer represents a memory copy operation. </div><div class="ttdef"><b>Definition:</b> <a href="_mem_copy_layer_8hpp_source.html#l00013">MemCopyLayer.hpp:13</a></div></div> |
| 217 | <div class="ttc" id="classarmnn_1_1_floor_layer_html"><div class="ttname"><a href="classarmnn_1_1_floor_layer.html">armnn::FloorLayer</a></div><div class="ttdoc">This layer represents a floor operation. </div><div class="ttdef"><b>Definition:</b> <a href="_floor_layer_8hpp_source.html#l00013">FloorLayer.hpp:13</a></div></div> |
| 218 | <div class="ttc" id="namespacearmnn_html_abf625e50a5eaeafce5b39580dc95a9d3"><div class="ttname"><a href="namespacearmnn.html#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.html#l00079">NetworkUtils.cpp:79</a></div></div> |
| 219 | <div class="ttc" id="_test_utils_8hpp_html_a0eedb278f57355b47fa983450d4e378c"><div class="ttname"><a href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a></div><div class="ttdeci">bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8hpp_source.html#l00020">TestUtils.hpp:20</a></div></div> |
| 220 | <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div> |
| 221 | <div class="ttc" id="classarmnn_1_1_output_handler_html_a97db12c41024f5545ef5cc4153e5443b"><div class="ttname"><a href="classarmnn_1_1_output_handler.html#a97db12c41024f5545ef5cc4153e5443b">armnn::OutputHandler::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo)</div><div class="ttdoc">Sets the TensorInfo used by this output handler. </div><div class="ttdef"><b>Definition:</b> <a href="_output_handler_8cpp_source.html#l00017">OutputHandler.cpp:17</a></div></div> |
| 222 | <div class="ttc" id="classarmnn_1_1_addition_layer_html"><div class="ttname"><a href="classarmnn_1_1_addition_layer.html">armnn::AdditionLayer</a></div><div class="ttdoc">This layer represents an addition operation. </div><div class="ttdef"><b>Definition:</b> <a href="_addition_layer_8hpp_source.html#l00013">AdditionLayer.hpp:13</a></div></div> |
| 223 | <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div> |
| 224 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 225 | <div class="ttc" id="namespacearmnn_html_ad31c56533e4f9f9f51719599fbfcf7bb"><div class="ttname"><a href="namespacearmnn.html#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.html#l00040">NetworkUtils.cpp:40</a></div></div> |
| 226 | <div class="ttc" id="namespacearmnn_html_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a></div><div class="ttdeci">int LayerBindingId</div><div class="ttdoc">Type of identifiers for bindable layers (inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00168">Types.hpp:168</a></div></div> |
| 227 | <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div> |
| 228 | </div><!-- fragment --> |
| 229 | </div> |
| 230 | </div> |
| 231 | <a id="a6b7bebf2c0d384c3297a6c3b19346555"></a> |
| 232 | <h2 class="memtitle"><span class="permalink"><a href="#a6b7bebf2c0d384c3297a6c3b19346555">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[4/16]</span></h2> |
| 233 | |
| 234 | <div class="memitem"> |
| 235 | <div class="memproto"> |
| 236 | <table class="memname"> |
| 237 | <tr> |
| 238 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 239 | <td>(</td> |
| 240 | <td class="paramtype">Conv2dValidateTensorShapesFromInputs </td> |
| 241 | <td class="paramname"></td><td>)</td> |
| 242 | <td></td> |
| 243 | </tr> |
| 244 | </table> |
| 245 | </div><div class="memdoc"> |
| 246 | |
| 247 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00277">277</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 248 | |
| 249 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00249">CreateConvolution2dGraph()</a>, and <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p> |
| 250 | <div class="fragment"><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_graph.html">Graph</a> graph;</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</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="l00281"></a><span class="lineno"> 281</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="l00282"></a><span class="lineno"> 282</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="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="_optimizer_tests_8cpp.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape);</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> </div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> }</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 251 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 252 | <div class="ttc" id="_optimizer_tests_8cpp_html_a5065b32dd0aa2c08ef75e953ebedbc16"><div class="ttname"><a href="_optimizer_tests_8cpp.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a></div><div class="ttdeci">void CreateConvolution2dGraph(Graph &graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00249">OptimizerTests.cpp:249</a></div></div> |
| 253 | </div><!-- fragment --> |
| 254 | </div> |
| 255 | </div> |
| 256 | <a id="a67738cd9d506e11aa4f4f43b9dc30e2c"></a> |
| 257 | <h2 class="memtitle"><span class="permalink"><a href="#a67738cd9d506e11aa4f4f43b9dc30e2c">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[5/16]</span></h2> |
| 258 | |
| 259 | <div class="memitem"> |
| 260 | <div class="memproto"> |
| 261 | <table class="memname"> |
| 262 | <tr> |
| 263 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 264 | <td>(</td> |
| 265 | <td class="paramtype">Conv2dValidateTensorShapesFromInputsNhwc </td> |
| 266 | <td class="paramname"></td><td>)</td> |
| 267 | <td></td> |
| 268 | </tr> |
| 269 | </table> |
| 270 | </div><div class="memdoc"> |
| 271 | |
| 272 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00288">288</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 273 | |
| 274 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00249">CreateConvolution2dGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> |
| 275 | <div class="fragment"><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> {</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 8, 16, 3 };</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { 2, 5, 3, 3 };</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 4, 14, 2 };</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <a class="code" href="_optimizer_tests_8cpp.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> </div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> }</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 276 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 277 | <div class="ttc" id="_optimizer_tests_8cpp_html_a5065b32dd0aa2c08ef75e953ebedbc16"><div class="ttname"><a href="_optimizer_tests_8cpp.html#a5065b32dd0aa2c08ef75e953ebedbc16">CreateConvolution2dGraph</a></div><div class="ttdeci">void CreateConvolution2dGraph(Graph &graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00249">OptimizerTests.cpp:249</a></div></div> |
| 278 | </div><!-- fragment --> |
| 279 | </div> |
| 280 | </div> |
| 281 | <a id="a93b5cb4143e78fec858fe77e86472bec"></a> |
| 282 | <h2 class="memtitle"><span class="permalink"><a href="#a93b5cb4143e78fec858fe77e86472bec">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[6/16]</span></h2> |
| 283 | |
| 284 | <div class="memitem"> |
| 285 | <div class="memproto"> |
| 286 | <table class="memname"> |
| 287 | <tr> |
| 288 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 289 | <td>(</td> |
| 290 | <td class="paramtype">DepthwiseConv2dValidateTensorShapesFromInputs </td> |
| 291 | <td class="paramname"></td><td>)</td> |
| 292 | <td></td> |
| 293 | </tr> |
| 294 | </table> |
| 295 | </div><div class="memdoc"> |
| 296 | |
| 297 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00327">327</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 298 | |
| 299 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00299">CreateDepthwiseConvolution2dGraph()</a>, and <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p> |
| 300 | <div class="fragment"><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_graph.html">Graph</a> graph;</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</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="l00331"></a><span class="lineno"> 331</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="l00332"></a><span class="lineno"> 332</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="l00333"></a><span class="lineno"> 333</span>  <a class="code" href="_optimizer_tests_8cpp.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape);</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> </div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> }</div><div class="ttc" id="_optimizer_tests_8cpp_html_acd97facea671e23ec3e8b33c6c2ea321"><div class="ttname"><a href="_optimizer_tests_8cpp.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a></div><div class="ttdeci">void CreateDepthwiseConvolution2dGraph(Graph &graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00299">OptimizerTests.cpp:299</a></div></div> |
| 301 | <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 302 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 303 | </div><!-- fragment --> |
| 304 | </div> |
| 305 | </div> |
| 306 | <a id="aa678f54308701529660f9ee2a70bd042"></a> |
| 307 | <h2 class="memtitle"><span class="permalink"><a href="#aa678f54308701529660f9ee2a70bd042">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[7/16]</span></h2> |
| 308 | |
| 309 | <div class="memitem"> |
| 310 | <div class="memproto"> |
| 311 | <table class="memname"> |
| 312 | <tr> |
| 313 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 314 | <td>(</td> |
| 315 | <td class="paramtype">DepthwiseConv2dValidateTensorShapesFromInputsNhwc </td> |
| 316 | <td class="paramname"></td><td>)</td> |
| 317 | <td></td> |
| 318 | </tr> |
| 319 | </table> |
| 320 | </div><div class="memdoc"> |
| 321 | |
| 322 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00338">338</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 323 | |
| 324 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00299">CreateDepthwiseConvolution2dGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> |
| 325 | <div class="fragment"><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> {</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 3, 3, 2 };</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { 1, 2, 3, 3 };</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 1, 1, 2 };</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <a class="code" href="_optimizer_tests_8cpp.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a>(graph, inputShape, weightsShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> }</div><div class="ttc" id="_optimizer_tests_8cpp_html_acd97facea671e23ec3e8b33c6c2ea321"><div class="ttname"><a href="_optimizer_tests_8cpp.html#acd97facea671e23ec3e8b33c6c2ea321">CreateDepthwiseConvolution2dGraph</a></div><div class="ttdeci">void CreateDepthwiseConvolution2dGraph(Graph &graph, const unsigned int *inputShape, const unsigned int *weightsShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00299">OptimizerTests.cpp:299</a></div></div> |
| 326 | <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 327 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 328 | </div><!-- fragment --> |
| 329 | </div> |
| 330 | </div> |
| 331 | <a id="a8457188fd0859ae6a91c09c3266f58a5"></a> |
| 332 | <h2 class="memtitle"><span class="permalink"><a href="#a8457188fd0859ae6a91c09c3266f58a5">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[8/16]</span></h2> |
| 333 | |
| 334 | <div class="memitem"> |
| 335 | <div class="memproto"> |
| 336 | <table class="memname"> |
| 337 | <tr> |
| 338 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 339 | <td>(</td> |
| 340 | <td class="paramtype">Pooling2dValidateTensorShapesFromInputs </td> |
| 341 | <td class="paramname"></td><td>)</td> |
| 342 | <td></td> |
| 343 | </tr> |
| 344 | </table> |
| 345 | </div><div class="memdoc"> |
| 346 | |
| 347 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00377">377</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 348 | |
| 349 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00349">CreatePooling2dGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> |
| 350 | <div class="fragment"><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_graph.html">Graph</a> graph;</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</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="l00381"></a><span class="lineno"> 381</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="l00382"></a><span class="lineno"> 382</span>  <a class="code" href="_optimizer_tests_8cpp.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a>(graph, inputShape, outputShape, DataLayout::NCHW);</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> </div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> }</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 351 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 352 | <div class="ttc" id="_optimizer_tests_8cpp_html_a4756218150e4ca0da09d0ecc390a7a17"><div class="ttname"><a href="_optimizer_tests_8cpp.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a></div><div class="ttdeci">void CreatePooling2dGraph(Graph &graph, const unsigned int *inputShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00349">OptimizerTests.cpp:349</a></div></div> |
| 353 | </div><!-- fragment --> |
| 354 | </div> |
| 355 | </div> |
| 356 | <a id="a1c7c22035e9b339dad1aedcf1d9c49e9"></a> |
| 357 | <h2 class="memtitle"><span class="permalink"><a href="#a1c7c22035e9b339dad1aedcf1d9c49e9">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[9/16]</span></h2> |
| 358 | |
| 359 | <div class="memitem"> |
| 360 | <div class="memproto"> |
| 361 | <table class="memname"> |
| 362 | <tr> |
| 363 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 364 | <td>(</td> |
| 365 | <td class="paramtype">Pooling2dValidateTensorShapesFromInputsNhwc </td> |
| 366 | <td class="paramname"></td><td>)</td> |
| 367 | <td></td> |
| 368 | </tr> |
| 369 | </table> |
| 370 | </div><div class="memdoc"> |
| 371 | |
| 372 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00387">387</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 373 | |
| 374 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00349">CreatePooling2dGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> |
| 375 | <div class="fragment"><div class="line"><a name="l00388"></a><span class="lineno"> 388</span> {</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 5, 52, 60, 3 };</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 5, 11, 13, 3 };</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <a class="code" href="_optimizer_tests_8cpp.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a>(graph, inputShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> </div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> }</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 376 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 377 | <div class="ttc" id="_optimizer_tests_8cpp_html_a4756218150e4ca0da09d0ecc390a7a17"><div class="ttname"><a href="_optimizer_tests_8cpp.html#a4756218150e4ca0da09d0ecc390a7a17">CreatePooling2dGraph</a></div><div class="ttdeci">void CreatePooling2dGraph(Graph &graph, const unsigned int *inputShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00349">OptimizerTests.cpp:349</a></div></div> |
| 378 | </div><!-- fragment --> |
| 379 | </div> |
| 380 | </div> |
| 381 | <a id="acee9ba1427bd42cc38a0402969dd0d35"></a> |
| 382 | <h2 class="memtitle"><span class="permalink"><a href="#acee9ba1427bd42cc38a0402969dd0d35">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[10/16]</span></h2> |
| 383 | |
| 384 | <div class="memitem"> |
| 385 | <div class="memproto"> |
| 386 | <table class="memname"> |
| 387 | <tr> |
| 388 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 389 | <td>(</td> |
| 390 | <td class="paramtype">ResizeBilinearValidateTensorShapesFromInputs </td> |
| 391 | <td class="paramname"></td><td>)</td> |
| 392 | <td></td> |
| 393 | </tr> |
| 394 | </table> |
| 395 | </div><div class="memdoc"> |
| 396 | |
| 397 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00420">420</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 398 | |
| 399 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00397">CreateResizeBilinearGraph()</a>, and <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>.</p> |
| 400 | <div class="fragment"><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_graph.html">Graph</a> graph;</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</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="l00424"></a><span class="lineno"> 424</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="l00425"></a><span class="lineno"> 425</span>  <a class="code" href="_optimizer_tests_8cpp.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a>(graph, inputShape, outputShape);</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> </div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> }</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 401 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 402 | <div class="ttc" id="_optimizer_tests_8cpp_html_aefb2c7f14f687a9432490a1bdee05458"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a></div><div class="ttdeci">void CreateResizeBilinearGraph(Graph &graph, const unsigned int *inputShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00397">OptimizerTests.cpp:397</a></div></div> |
| 403 | </div><!-- fragment --> |
| 404 | </div> |
| 405 | </div> |
| 406 | <a id="abbc42a4387722b0b5e0c00038288dd4e"></a> |
| 407 | <h2 class="memtitle"><span class="permalink"><a href="#abbc42a4387722b0b5e0c00038288dd4e">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[11/16]</span></h2> |
| 408 | |
| 409 | <div class="memitem"> |
| 410 | <div class="memproto"> |
| 411 | <table class="memname"> |
| 412 | <tr> |
| 413 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 414 | <td>(</td> |
| 415 | <td class="paramtype">ResizeBilinearValidateTensorShapesFromInputsNhwc </td> |
| 416 | <td class="paramname"></td><td>)</td> |
| 417 | <td></td> |
| 418 | </tr> |
| 419 | </table> |
| 420 | </div><div class="memdoc"> |
| 421 | |
| 422 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00430">430</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 423 | |
| 424 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00397">CreateResizeBilinearGraph()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> |
| 425 | <div class="fragment"><div class="line"><a name="l00431"></a><span class="lineno"> 431</span> {</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 4, 5, 2 };</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 3, 4, 2 };</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <a class="code" href="_optimizer_tests_8cpp.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a>(graph, inputShape, outputShape, DataLayout::NHWC);</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> }</div><div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 426 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 427 | <div class="ttc" id="_optimizer_tests_8cpp_html_aefb2c7f14f687a9432490a1bdee05458"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aefb2c7f14f687a9432490a1bdee05458">CreateResizeBilinearGraph</a></div><div class="ttdeci">void CreateResizeBilinearGraph(Graph &graph, const unsigned int *inputShape, const unsigned int *outputShape, DataLayout dataLayout=DataLayout::NCHW)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_tests_8cpp_source.html#l00397">OptimizerTests.cpp:397</a></div></div> |
| 428 | </div><!-- fragment --> |
| 429 | </div> |
| 430 | </div> |
| 431 | <a id="a57aa1f639ec35a976735c91889d463a4"></a> |
| 432 | <h2 class="memtitle"><span class="permalink"><a href="#a57aa1f639ec35a976735c91889d463a4">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[12/16]</span></h2> |
| 433 | |
| 434 | <div class="memitem"> |
| 435 | <div class="memproto"> |
| 436 | <table class="memname"> |
| 437 | <tr> |
| 438 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 439 | <td>(</td> |
| 440 | <td class="paramtype">GatherValidateTensorShapesFromInputs </td> |
| 441 | <td class="paramname"></td><td>)</td> |
| 442 | <td></td> |
| 443 | </tr> |
| 444 | </table> |
| 445 | </div><div class="memdoc"> |
| 446 | |
| 447 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00459">459</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 448 | |
| 449 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00441">CreateGatherGraph()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p> |
| 450 | <div class="fragment"><div class="line"><a name="l00460"></a><span class="lineno"> 460</span> {</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> paramsInfo({10, 5}, DataType::Float32);</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> indicesInfo({3}, DataType::Signed32);</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo({3, 5}, DataType::Float32);</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span> </div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <a class="code" href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a>(graph, paramsInfo, indicesInfo, outputInfo);</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span> </div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 451 | <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 452 | <div class="ttc" id="_optimizer_tests_8cpp_html_aa4e793c84e5dfea800d4dba921651e5b"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a></div><div class="ttdeci">void CreateGatherGraph(Graph &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.html#l00441">OptimizerTests.cpp:441</a></div></div> |
| 453 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 454 | </div><!-- fragment --> |
| 455 | </div> |
| 456 | </div> |
| 457 | <a id="af31e0d94eb9ec7e72b9d6d70da3070ec"></a> |
| 458 | <h2 class="memtitle"><span class="permalink"><a href="#af31e0d94eb9ec7e72b9d6d70da3070ec">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[13/16]</span></h2> |
| 459 | |
| 460 | <div class="memitem"> |
| 461 | <div class="memproto"> |
| 462 | <table class="memname"> |
| 463 | <tr> |
| 464 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 465 | <td>(</td> |
| 466 | <td class="paramtype">GatherValidateTensorShapesFromInputs1DParams </td> |
| 467 | <td class="paramname"></td><td>)</td> |
| 468 | <td></td> |
| 469 | </tr> |
| 470 | </table> |
| 471 | </div><div class="memdoc"> |
| 472 | |
| 473 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00471">471</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 474 | |
| 475 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00441">CreateGatherGraph()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p> |
| 476 | <div class="fragment"><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="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> paramsInfo({8}, DataType::Float32);</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> indicesInfo({5}, DataType::Signed32);</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo( {5}, DataType::Float32);</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span> </div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <a class="code" href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a>(graph, paramsInfo, indicesInfo, outputInfo);</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span> </div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 477 | <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 478 | <div class="ttc" id="_optimizer_tests_8cpp_html_aa4e793c84e5dfea800d4dba921651e5b"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a></div><div class="ttdeci">void CreateGatherGraph(Graph &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.html#l00441">OptimizerTests.cpp:441</a></div></div> |
| 479 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 480 | </div><!-- fragment --> |
| 481 | </div> |
| 482 | </div> |
| 483 | <a id="a65b5e30de580e14475b51da9b93c908b"></a> |
| 484 | <h2 class="memtitle"><span class="permalink"><a href="#a65b5e30de580e14475b51da9b93c908b">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[14/16]</span></h2> |
| 485 | |
| 486 | <div class="memitem"> |
| 487 | <div class="memproto"> |
| 488 | <table class="memname"> |
| 489 | <tr> |
| 490 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 491 | <td>(</td> |
| 492 | <td class="paramtype">GatherValidateTensorShapesFromInputsMultiDimIndices </td> |
| 493 | <td class="paramname"></td><td>)</td> |
| 494 | <td></td> |
| 495 | </tr> |
| 496 | </table> |
| 497 | </div><div class="memdoc"> |
| 498 | |
| 499 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00483">483</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 500 | |
| 501 | <p class="reference">References <a class="el" href="_optimizer_tests_8cpp_source.html#l00441">CreateGatherGraph()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, and <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::Signed32</a>.</p> |
| 502 | <div class="fragment"><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="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> paramsInfo({3, 2, 5}, DataType::Float32);</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> indicesInfo({2, 2}, DataType::Signed32);</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo({2, 2, 2, 5}, DataType::Float32);</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> </div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <a class="code" href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a>(graph, paramsInfo, indicesInfo, outputInfo);</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span> </div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 503 | <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 504 | <div class="ttc" id="_optimizer_tests_8cpp_html_aa4e793c84e5dfea800d4dba921651e5b"><div class="ttname"><a href="_optimizer_tests_8cpp.html#aa4e793c84e5dfea800d4dba921651e5b">CreateGatherGraph</a></div><div class="ttdeci">void CreateGatherGraph(Graph &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.html#l00441">OptimizerTests.cpp:441</a></div></div> |
| 505 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 506 | </div><!-- fragment --> |
| 507 | </div> |
| 508 | </div> |
| 509 | <a id="a0ee7b0e1f8d1dd9a9e001720e69086eb"></a> |
| 510 | <h2 class="memtitle"><span class="permalink"><a href="#a0ee7b0e1f8d1dd9a9e001720e69086eb">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[15/16]</span></h2> |
| 511 | |
| 512 | <div class="memitem"> |
| 513 | <div class="memproto"> |
| 514 | <table class="memname"> |
| 515 | <tr> |
| 516 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 517 | <td>(</td> |
| 518 | <td class="paramtype">DetectionPostProcessValidateTensorShapes </td> |
| 519 | <td class="paramname"></td><td>)</td> |
| 520 | <td></td> |
| 521 | </tr> |
| 522 | </table> |
| 523 | </div><div class="memdoc"> |
| 524 | |
| 525 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00495">495</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 526 | |
| 527 | <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_neon_end_to_end_tests_8cpp.html#ac0981848e4ae57729f14f72bd4caa9f8">anchors()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_graph_8cpp_source.html#l00493">Graph::InferTensorInfos()</a>, <a class="el" href="_detection_post_process_layer_8hpp_source.html#l00020">DetectionPostProcessLayer::m_Anchors</a>, <a class="el" href="_descriptors_8hpp_source.html#l00527">DetectionPostProcessDescriptor::m_MaxDetections</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::QAsymmU8</a>, <a class="el" href="_neon_end_to_end_tests_8cpp.html#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p> |
| 528 | <div class="fragment"><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="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> boxEncodingsInfo({1, 10, 4}, DataType::QAsymmU8);</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> <a class="code" href="_neon_end_to_end_tests_8cpp.html#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>({1, 10, 4}, DataType::QAsymmU8);</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  std::vector<uint8_t> anchorsVector(40);</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> <a class="code" href="_neon_end_to_end_tests_8cpp.html#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({10, 4}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>), anchorsVector);</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span> </div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> detectionBoxesInfo({1, 3, 4}, DataType::QAsymmU8);</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> detectionScoresInfo({1, 3}, DataType::QAsymmU8);</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> detectionClassesInfo({1, 3}, DataType::QAsymmU8);</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> numDetectionInfo({1}, DataType::QAsymmU8);</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span> </div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input0 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>>(0, <span class="stringliteral">"boxEncodings"</span>);</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  input0-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(boxEncodingsInfo);</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span> </div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input1 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>>(1, <span class="stringliteral">"score"</span>);</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  input1-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(<a class="code" href="_neon_end_to_end_tests_8cpp.html#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>);</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span> </div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html">DetectionPostProcessDescriptor</a> descriptor;</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.html#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a> = 3;</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span> </div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <a class="code" href="classarmnn_1_1_detection_post_process_layer.html">DetectionPostProcessLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_detection_post_process_layer.html">DetectionPostProcessLayer</a>>(descriptor, <span class="stringliteral">"detectionPostProcess"</span>);</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  layer-><a class="code" href="classarmnn_1_1_detection_post_process_layer.html#a6844fecab0edaf324de5a57fee8b65f1">m_Anchors</a> = std::make_unique<armnn::ScopedCpuTensorHandle>(<a class="code" href="_neon_end_to_end_tests_8cpp.html#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>);</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(detectionBoxesInfo);</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(detectionScoresInfo);</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(detectionClassesInfo);</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(3).<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(numDetectionInfo);</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span> </div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  input0->GetOutputSlot().Connect(layer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  input1-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span> </div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span> }</div><div class="ttc" id="classarmnn_1_1_detection_post_process_layer_html_a6844fecab0edaf324de5a57fee8b65f1"><div class="ttname"><a href="classarmnn_1_1_detection_post_process_layer.html#a6844fecab0edaf324de5a57fee8b65f1">armnn::DetectionPostProcessLayer::m_Anchors</a></div><div class="ttdeci">std::unique_ptr< 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.html#l00020">DetectionPostProcessLayer.hpp:20</a></div></div> |
| 529 | <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div> |
| 530 | <div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div> |
| 531 | <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div> |
| 532 | <div class="ttc" id="classarmnn_1_1_detection_post_process_layer_html"><div class="ttname"><a href="classarmnn_1_1_detection_post_process_layer.html">armnn::DetectionPostProcessLayer</a></div><div class="ttdoc">This layer represents a detection postprocess operator. </div><div class="ttdef"><b>Definition:</b> <a href="_detection_post_process_layer_8hpp_source.html#l00016">DetectionPostProcessLayer.hpp:16</a></div></div> |
| 533 | <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div> |
| 534 | <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 535 | <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div> |
| 536 | <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div> |
| 537 | <div class="ttc" id="_neon_end_to_end_tests_8cpp_html_a64c1dd1b6dd60be9f4a16db9c8f427a5"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.html#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a></div><div class="ttdeci">armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::Float32)</div></div> |
| 538 | <div class="ttc" id="classarmnn_1_1_graph_html_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.html#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00493">Graph.cpp:493</a></div></div> |
| 539 | <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div> |
| 540 | <div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00495">Descriptors.hpp:495</a></div></div> |
| 541 | <div class="ttc" id="_neon_end_to_end_tests_8cpp_html_ac0981848e4ae57729f14f72bd4caa9f8"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.html#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a></div><div class="ttdeci">std::vector< 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> |
| 542 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 543 | <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div> |
| 544 | <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div> |
| 545 | <div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_html_ae72089bcab60ac175557f4241b16a014"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.html#ae72089bcab60ac175557f4241b16a014">armnn::DetectionPostProcessDescriptor::m_MaxDetections</a></div><div class="ttdeci">uint32_t m_MaxDetections</div><div class="ttdoc">Maximum numbers of detections. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00527">Descriptors.hpp:527</a></div></div> |
| 546 | </div><!-- fragment --> |
| 547 | </div> |
| 548 | </div> |
| 549 | <a id="a4ef49bab7a1b82c389b3b45ffb767833"></a> |
| 550 | <h2 class="memtitle"><span class="permalink"><a href="#a4ef49bab7a1b82c389b3b45ffb767833">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[16/16]</span></h2> |
| 551 | |
| 552 | <div class="memitem"> |
| 553 | <div class="memproto"> |
| 554 | <table class="memname"> |
| 555 | <tr> |
| 556 | <td class="memname">BOOST_AUTO_TEST_CASE </td> |
| 557 | <td>(</td> |
| 558 | <td class="paramtype">FoldPadLayerIntoConvolution2dLayer </td> |
| 559 | <td class="paramname"></td><td>)</td> |
| 560 | <td></td> |
| 561 | </tr> |
| 562 | </table> |
| 563 | </div><div class="memdoc"> |
| 564 | |
| 565 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00530">530</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 566 | |
| 567 | <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END()</a>, <a class="el" href="_graph_8hpp_source.html#l00168">Graph::cbegin()</a>, <a class="el" href="_graph_8hpp_source.html#l00170">Graph::cend()</a>, <a class="el" href="_test_utils_8hpp_source.html#l00020">CheckSequence()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00216">Layer::GetNameStr()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_layer_with_parameters_8hpp_source.html#l00018">LayerWithParameters< Parameters >::GetParameters()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00438">Convolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.html#l00440">Convolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00430">Convolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l00432">Convolution2dDescriptor::m_StrideY</a>, <a class="el" href="_convolution2d_layer_8hpp_source.html#l00020">Convolution2dLayer::m_Weight</a>, <a class="el" href="_optimizer_8hpp_source.html#l00043">armnn::MakeOptimizations()</a>, <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>, <a class="el" href="_optimizer_8cpp_source.html#l00016">Optimizer::Pass()</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p> |
| 568 | <div class="fragment"><div class="line"><a name="l00531"></a><span class="lineno"> 531</span> {</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 1, 2, 2, 3 };</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paddedShape[] = { 1, 6, 6, 3 };</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { 1, 2, 3, 3 };</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 1, 2, 1, 1 };</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span> </div><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_tensor_info.html">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> paddedInfo(4, paddedShape, DataType::Float32);</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span> </div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span> </div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <a class="code" href="structarmnn_1_1_pad_descriptor.html">PadDescriptor</a> padDescriptor({{ 0, 0 }, { 2, 2 }, { 2, 2 }, { 0, 0 }});</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span> </div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <a class="code" href="classarmnn_1_1_pad_layer.html">PadLayer</a>* padLayer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_pad_layer.html">PadLayer</a>>(padDescriptor, <span class="stringliteral">"pad"</span>);</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  padLayer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(paddedInfo);</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span> </div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a> convolution2dDescriptor;</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = DataLayout::NHWC;</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span> </div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  std::vector<float> weightsVector(18);</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, weightsShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), weightsVector);</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span> </div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>* conv2dLayer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>>(convolution2dDescriptor,<span class="stringliteral">"conv2d"</span>);</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  conv2dLayer-><a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  conv2dLayer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span> </div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span> </div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <span class="comment">// Connect up layers - input -> pad -> conv2d -> output</span></div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(padLayer->GetInputSlot(0));</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  padLayer->GetOutputSlot().Connect(conv2dLayer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  conv2dLayer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span> </div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <span class="keyword">auto</span> checkSimpleConv2d = [ ](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.html">armnn::Layer</a>* <span class="keyword">const</span> layer) -> <span class="keywordtype">bool</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="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.html">armnn::Convolution2dLayer</a>*<span class="keyword">></span>(layer);</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayerParams = conv2dLayer-><a class="code" href="classarmnn_1_1_layer_with_parameters.html#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>();</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <span class="keywordflow">return</span> IsLayerOfType<armnn::Convolution2dLayer>(layer) &&</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  (layer->GetNameStr() == <span class="stringliteral">"conv2d"</span>) &&</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  (conv2dLayerParams.m_PadLeft == 0) &&</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  (conv2dLayerParams.m_PadRight == 0) &&</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  (conv2dLayerParams.m_PadTop == 0) &&</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  (conv2dLayerParams.m_PadBottom == 0) &&</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  (conv2dLayerParams.m_BiasEnabled == <span class="keyword">false</span>) &&</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  (conv2dLayerParams.m_StrideX == 1) &&</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  (conv2dLayerParams.m_StrideY == 1) &&</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  (conv2dLayerParams.m_DataLayout == DataLayout::NHWC);</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  };</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span> </div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.html#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(),</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  graph.<a class="code" href="classarmnn_1_1_graph.html#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  &IsLayerOfType<armnn::PadLayer>,</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  checkSimpleConv2d,</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  &IsLayerOfType<armnn::OutputLayer>));</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>  <a class="code" href="classarmnn_1_1_optimizer.html#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.html#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.html#add2180a15cdcf5a229de32bb956cb224">FoldPadIntoConvolution2d</a>()));</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span> </div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keyword">auto</span> checkPadFoldedIntoConv2d = [ ](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.html">armnn::Layer</a>* <span class="keyword">const</span> layer) -> <span class="keywordtype">bool</span></div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  {</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</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.html">armnn::Convolution2dLayer</a>*<span class="keyword">></span>(layer);</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <span class="keyword">const</span> <span class="keyword">auto</span> conv2dLayerParams = conv2dLayer-><a class="code" href="classarmnn_1_1_layer_with_parameters.html#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>();</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keywordflow">return</span> IsLayerOfType<armnn::Convolution2dLayer>(layer) &&</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  (layer->GetNameStr() == <span class="stringliteral">"folded-pad-into-conv2d"</span>) &&</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  (conv2dLayerParams.m_PadLeft == 2) &&</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  (conv2dLayerParams.m_PadRight == 2) &&</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  (conv2dLayerParams.m_PadTop == 2) &&</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  (conv2dLayerParams.m_PadBottom == 2) &&</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  (conv2dLayerParams.m_BiasEnabled == <span class="keyword">false</span>) &&</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  (conv2dLayerParams.m_StrideX == 1) &&</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  (conv2dLayerParams.m_StrideY == 1) &&</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  (conv2dLayerParams.m_DataLayout == DataLayout::NHWC);</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  };</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span> </div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.html#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(),</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  graph.<a class="code" href="classarmnn_1_1_graph.html#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  &IsLayerOfType<armnn::InputLayer>,</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  checkPadFoldedIntoConv2d,</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  &IsLayerOfType<armnn::OutputLayer>));</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span> }</div><div class="ttc" id="classarmnn_1_1_pad_layer_html"><div class="ttname"><a href="classarmnn_1_1_pad_layer.html">armnn::PadLayer</a></div><div class="ttdoc">This layer represents a pad operation. </div><div class="ttdef"><b>Definition:</b> <a href="_pad_layer_8hpp_source.html#l00014">PadLayer.hpp:14</a></div></div> |
| 569 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00440">Descriptors.hpp:440</a></div></div> |
| 570 | <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div> |
| 571 | <div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div> |
| 572 | <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div> |
| 573 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html">armnn::Convolution2dLayer</a></div><div class="ttdoc">This layer represents a convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00015">Convolution2dLayer.hpp:15</a></div></div> |
| 574 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">armnn::Convolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< 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.html#l00020">Convolution2dLayer.hpp:20</a></div></div> |
| 575 | <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 576 | <div class="ttc" id="structarmnn_1_1_pad_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_pad_descriptor.html">armnn::PadDescriptor</a></div><div class="ttdoc">A PadDescriptor for the PadLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00901">Descriptors.hpp:901</a></div></div> |
| 577 | <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div> |
| 578 | <div class="ttc" id="classarmnn_1_1_optimizer_html_a1f48ba622b76ea04d15c9b62f642bf08"><div class="ttname"><a href="classarmnn_1_1_optimizer.html#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.html#l00016">Optimizer.cpp:16</a></div></div> |
| 579 | <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div> |
| 580 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00432">Descriptors.hpp:432</a></div></div> |
| 581 | <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> |
| 582 | <div class="ttc" id="namespacearmnn_1_1optimizations_html_add2180a15cdcf5a229de32bb956cb224"><div class="ttname"><a href="namespacearmnn_1_1optimizations.html#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.html#l00088">FoldPadIntoConvolution2d.hpp:88</a></div></div> |
| 583 | <div class="ttc" id="_test_utils_8hpp_html_a0eedb278f57355b47fa983450d4e378c"><div class="ttname"><a href="_test_utils_8hpp.html#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a></div><div class="ttdeci">bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8hpp_source.html#l00020">TestUtils.hpp:20</a></div></div> |
| 584 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00430">Descriptors.hpp:430</a></div></div> |
| 585 | <div class="ttc" id="classarmnn_1_1_layer_with_parameters_html_a502c06a1b13e6d90a6cbf47c081f1444"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#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.html#l00018">LayerWithParameters.hpp:18</a></div></div> |
| 586 | <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div> |
| 587 | <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div> |
| 588 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00438">Descriptors.hpp:438</a></div></div> |
| 589 | <div class="ttc" id="classarmnn_1_1_graph_html_a98b1109a9006f8cc7d4566146a3bd737"><div class="ttname"><a href="classarmnn_1_1_graph.html#a98b1109a9006f8cc7d4566146a3bd737">armnn::Graph::cbegin</a></div><div class="ttdeci">ConstIterator cbegin() const</div><div class="ttdoc">Returns const iterator pointing to the beginning of the list. Lowercase for range-based for loops...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00168">Graph.hpp:168</a></div></div> |
| 590 | <div class="ttc" id="namespacearmnn_html_aa7427025a851113a492de0b68b23d22a"><div class="ttname"><a href="namespacearmnn.html#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a></div><div class="ttdeci">Optimizer::Optimizations MakeOptimizations(Args &&... args)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8hpp_source.html#l00043">Optimizer.hpp:43</a></div></div> |
| 591 | <div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div> |
| 592 | <div class="ttc" id="classarmnn_1_1_graph_html_a02fd29b6dc3e21fbe4484362d85893bc"><div class="ttname"><a href="classarmnn_1_1_graph.html#a02fd29b6dc3e21fbe4484362d85893bc">armnn::Graph::cend</a></div><div class="ttdeci">ConstIterator cend() const</div><div class="ttdoc">Returns const iterator pointing to the end of the list. Lowercase for range-based for loops...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00170">Graph.hpp:170</a></div></div> |
| 593 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00392">Descriptors.hpp:392</a></div></div> |
| 594 | <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div> |
| 595 | <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div> |
| 596 | </div><!-- fragment --> |
| 597 | </div> |
| 598 | </div> |
| 599 | <a id="a5065b32dd0aa2c08ef75e953ebedbc16"></a> |
| 600 | <h2 class="memtitle"><span class="permalink"><a href="#a5065b32dd0aa2c08ef75e953ebedbc16">◆ </a></span>CreateConvolution2dGraph()</h2> |
| 601 | |
| 602 | <div class="memitem"> |
| 603 | <div class="memproto"> |
| 604 | <table class="memname"> |
| 605 | <tr> |
| 606 | <td class="memname">void CreateConvolution2dGraph </td> |
| 607 | <td>(</td> |
| 608 | <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> & </td> |
| 609 | <td class="paramname"><em>graph</em>, </td> |
| 610 | </tr> |
| 611 | <tr> |
| 612 | <td class="paramkey"></td> |
| 613 | <td></td> |
| 614 | <td class="paramtype">const unsigned int * </td> |
| 615 | <td class="paramname"><em>inputShape</em>, </td> |
| 616 | </tr> |
| 617 | <tr> |
| 618 | <td class="paramkey"></td> |
| 619 | <td></td> |
| 620 | <td class="paramtype">const unsigned int * </td> |
| 621 | <td class="paramname"><em>weightsShape</em>, </td> |
| 622 | </tr> |
| 623 | <tr> |
| 624 | <td class="paramkey"></td> |
| 625 | <td></td> |
| 626 | <td class="paramtype">const unsigned int * </td> |
| 627 | <td class="paramname"><em>outputShape</em>, </td> |
| 628 | </tr> |
| 629 | <tr> |
| 630 | <td class="paramkey"></td> |
| 631 | <td></td> |
| 632 | <td class="paramtype"><a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> </td> |
| 633 | <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code> </td> |
| 634 | </tr> |
| 635 | <tr> |
| 636 | <td></td> |
| 637 | <td>)</td> |
| 638 | <td></td><td></td> |
| 639 | </tr> |
| 640 | </table> |
| 641 | </div><div class="memdoc"> |
| 642 | |
| 643 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00249">249</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 644 | |
| 645 | <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00438">Convolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.html#l00440">Convolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00430">Convolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l00432">Convolution2dDescriptor::m_StrideY</a>, <a class="el" href="_convolution2d_layer_8hpp_source.html#l00020">Convolution2dLayer::m_Weight</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p> |
| 646 | |
| 647 | <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00277">BOOST_AUTO_TEST_CASE()</a>.</p> |
| 648 | <div class="fragment"><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> {</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> </div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  std::vector<float> weightsVector(90);</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, weightsShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), weightsVector);</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> </div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a> desc;</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  desc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> </div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> </div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>>(desc, <span class="stringliteral">"conv2d"</span>);</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> }</div><div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00440">Descriptors.hpp:440</a></div></div> |
| 649 | <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div> |
| 650 | <div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div> |
| 651 | <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div> |
| 652 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html">armnn::Convolution2dLayer</a></div><div class="ttdoc">This layer represents a convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00015">Convolution2dLayer.hpp:15</a></div></div> |
| 653 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">armnn::Convolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< 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.html#l00020">Convolution2dLayer.hpp:20</a></div></div> |
| 654 | <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 655 | <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div> |
| 656 | <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div> |
| 657 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00432">Descriptors.hpp:432</a></div></div> |
| 658 | <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> |
| 659 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00430">Descriptors.hpp:430</a></div></div> |
| 660 | <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div> |
| 661 | <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div> |
| 662 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00438">Descriptors.hpp:438</a></div></div> |
| 663 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00392">Descriptors.hpp:392</a></div></div> |
| 664 | <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div> |
| 665 | <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div> |
| 666 | </div><!-- fragment --> |
| 667 | </div> |
| 668 | </div> |
| 669 | <a id="acd97facea671e23ec3e8b33c6c2ea321"></a> |
| 670 | <h2 class="memtitle"><span class="permalink"><a href="#acd97facea671e23ec3e8b33c6c2ea321">◆ </a></span>CreateDepthwiseConvolution2dGraph()</h2> |
| 671 | |
| 672 | <div class="memitem"> |
| 673 | <div class="memproto"> |
| 674 | <table class="memname"> |
| 675 | <tr> |
| 676 | <td class="memname">void CreateDepthwiseConvolution2dGraph </td> |
| 677 | <td>(</td> |
| 678 | <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> & </td> |
| 679 | <td class="paramname"><em>graph</em>, </td> |
| 680 | </tr> |
| 681 | <tr> |
| 682 | <td class="paramkey"></td> |
| 683 | <td></td> |
| 684 | <td class="paramtype">const unsigned int * </td> |
| 685 | <td class="paramname"><em>inputShape</em>, </td> |
| 686 | </tr> |
| 687 | <tr> |
| 688 | <td class="paramkey"></td> |
| 689 | <td></td> |
| 690 | <td class="paramtype">const unsigned int * </td> |
| 691 | <td class="paramname"><em>weightsShape</em>, </td> |
| 692 | </tr> |
| 693 | <tr> |
| 694 | <td class="paramkey"></td> |
| 695 | <td></td> |
| 696 | <td class="paramtype">const unsigned int * </td> |
| 697 | <td class="paramname"><em>outputShape</em>, </td> |
| 698 | </tr> |
| 699 | <tr> |
| 700 | <td class="paramkey"></td> |
| 701 | <td></td> |
| 702 | <td class="paramtype"><a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> </td> |
| 703 | <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code> </td> |
| 704 | </tr> |
| 705 | <tr> |
| 706 | <td></td> |
| 707 | <td>)</td> |
| 708 | <td></td><td></td> |
| 709 | </tr> |
| 710 | </table> |
| 711 | </div><div class="memdoc"> |
| 712 | |
| 713 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00299">299</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 714 | |
| 715 | <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00490">DepthwiseConvolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.html#l00492">DepthwiseConvolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00482">DepthwiseConvolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l00484">DepthwiseConvolution2dDescriptor::m_StrideY</a>, <a class="el" href="_depthwise_convolution2d_layer_8hpp_source.html#l00019">DepthwiseConvolution2dLayer::m_Weight</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p> |
| 716 | |
| 717 | <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00327">BOOST_AUTO_TEST_CASE()</a>.</p> |
| 718 | <div class="fragment"><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>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> </div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  std::vector<float> weightsVector(18);</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, weightsShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), weightsVector);</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> </div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">DepthwiseConvolution2dDescriptor</a> desc;</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  desc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> </div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> </div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html">DepthwiseConvolution2dLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html">DepthwiseConvolution2dLayer</a>>(desc, <span class="stringliteral">"depthwiseConv2d"</span>);</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> }</div><div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::DepthwiseConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00482">Descriptors.hpp:482</a></div></div> |
| 719 | <div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div> |
| 720 | <div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div> |
| 721 | <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div> |
| 722 | <div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.html">armnn::DepthwiseConvolution2dLayer</a></div><div class="ttdoc">This layer represents a depthwise convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.html#l00015">DepthwiseConvolution2dLayer.hpp:15</a></div></div> |
| 723 | <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 724 | <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div> |
| 725 | <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div> |
| 726 | <div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00492">Descriptors.hpp:492</a></div></div> |
| 727 | <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> |
| 728 | <div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_html_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">armnn::DepthwiseConvolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< 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.html#l00019">DepthwiseConvolution2dLayer.hpp:19</a></div></div> |
| 729 | <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div> |
| 730 | <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div> |
| 731 | <div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00490">Descriptors.hpp:490</a></div></div> |
| 732 | <div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00444">Descriptors.hpp:444</a></div></div> |
| 733 | <div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::DepthwiseConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00484">Descriptors.hpp:484</a></div></div> |
| 734 | <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div> |
| 735 | <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div> |
| 736 | </div><!-- fragment --> |
| 737 | </div> |
| 738 | </div> |
| 739 | <a id="aa4e793c84e5dfea800d4dba921651e5b"></a> |
| 740 | <h2 class="memtitle"><span class="permalink"><a href="#aa4e793c84e5dfea800d4dba921651e5b">◆ </a></span>CreateGatherGraph()</h2> |
| 741 | |
| 742 | <div class="memitem"> |
| 743 | <div class="memproto"> |
| 744 | <table class="memname"> |
| 745 | <tr> |
| 746 | <td class="memname">void CreateGatherGraph </td> |
| 747 | <td>(</td> |
| 748 | <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> & </td> |
| 749 | <td class="paramname"><em>graph</em>, </td> |
| 750 | </tr> |
| 751 | <tr> |
| 752 | <td class="paramkey"></td> |
| 753 | <td></td> |
| 754 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> & </td> |
| 755 | <td class="paramname"><em>paramsInfo</em>, </td> |
| 756 | </tr> |
| 757 | <tr> |
| 758 | <td class="paramkey"></td> |
| 759 | <td></td> |
| 760 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> & </td> |
| 761 | <td class="paramname"><em>indicesInfo</em>, </td> |
| 762 | </tr> |
| 763 | <tr> |
| 764 | <td class="paramkey"></td> |
| 765 | <td></td> |
| 766 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> & </td> |
| 767 | <td class="paramname"><em>outputInfo</em> </td> |
| 768 | </tr> |
| 769 | <tr> |
| 770 | <td></td> |
| 771 | <td>)</td> |
| 772 | <td></td><td></td> |
| 773 | </tr> |
| 774 | </table> |
| 775 | </div><div class="memdoc"> |
| 776 | |
| 777 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00441">441</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 778 | |
| 779 | <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p> |
| 780 | |
| 781 | <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00459">BOOST_AUTO_TEST_CASE()</a>.</p> |
| 782 | <div class="fragment"><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>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input0 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>>(0, <span class="stringliteral">"params"</span>);</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  input0-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(paramsInfo);</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span> </div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input1 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>>(1, <span class="stringliteral">"indices"</span>);</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  input1-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(indicesInfo);</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span> </div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <a class="code" href="classarmnn_1_1_gather_layer.html">GatherLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_gather_layer.html">GatherLayer</a>>(<span class="stringliteral">"gather"</span>);</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span> </div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  input0-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  input1-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span> }</div><div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div> |
| 783 | <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div> |
| 784 | <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div> |
| 785 | <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div> |
| 786 | <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div> |
| 787 | <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div> |
| 788 | <div class="ttc" id="classarmnn_1_1_gather_layer_html"><div class="ttname"><a href="classarmnn_1_1_gather_layer.html">armnn::GatherLayer</a></div><div class="ttdoc">This layer represents a Gather operator. </div><div class="ttdef"><b>Definition:</b> <a href="_gather_layer_8hpp_source.html#l00014">GatherLayer.hpp:14</a></div></div> |
| 789 | <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div> |
| 790 | <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div> |
| 791 | </div><!-- fragment --> |
| 792 | </div> |
| 793 | </div> |
| 794 | <a id="a4756218150e4ca0da09d0ecc390a7a17"></a> |
| 795 | <h2 class="memtitle"><span class="permalink"><a href="#a4756218150e4ca0da09d0ecc390a7a17">◆ </a></span>CreatePooling2dGraph()</h2> |
| 796 | |
| 797 | <div class="memitem"> |
| 798 | <div class="memproto"> |
| 799 | <table class="memname"> |
| 800 | <tr> |
| 801 | <td class="memname">void CreatePooling2dGraph </td> |
| 802 | <td>(</td> |
| 803 | <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> & </td> |
| 804 | <td class="paramname"><em>graph</em>, </td> |
| 805 | </tr> |
| 806 | <tr> |
| 807 | <td class="paramkey"></td> |
| 808 | <td></td> |
| 809 | <td class="paramtype">const unsigned int * </td> |
| 810 | <td class="paramname"><em>inputShape</em>, </td> |
| 811 | </tr> |
| 812 | <tr> |
| 813 | <td class="paramkey"></td> |
| 814 | <td></td> |
| 815 | <td class="paramtype">const unsigned int * </td> |
| 816 | <td class="paramname"><em>outputShape</em>, </td> |
| 817 | </tr> |
| 818 | <tr> |
| 819 | <td class="paramkey"></td> |
| 820 | <td></td> |
| 821 | <td class="paramtype"><a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> </td> |
| 822 | <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code> </td> |
| 823 | </tr> |
| 824 | <tr> |
| 825 | <td></td> |
| 826 | <td>)</td> |
| 827 | <td></td><td></td> |
| 828 | </tr> |
| 829 | </table> |
| 830 | </div><div class="memdoc"> |
| 831 | |
| 832 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00349">349</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 833 | |
| 834 | <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::Average</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::Exclude</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00369">Pooling2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00355">Pooling2dDescriptor::m_PadBottom</a>, <a class="el" href="_descriptors_8hpp_source.html#l00367">Pooling2dDescriptor::m_PaddingMethod</a>, <a class="el" href="_descriptors_8hpp_source.html#l00349">Pooling2dDescriptor::m_PadLeft</a>, <a class="el" href="_descriptors_8hpp_source.html#l00351">Pooling2dDescriptor::m_PadRight</a>, <a class="el" href="_descriptors_8hpp_source.html#l00353">Pooling2dDescriptor::m_PadTop</a>, <a class="el" href="_descriptors_8hpp_source.html#l00359">Pooling2dDescriptor::m_PoolHeight</a>, <a class="el" href="_descriptors_8hpp_source.html#l00347">Pooling2dDescriptor::m_PoolType</a>, <a class="el" href="_descriptors_8hpp_source.html#l00357">Pooling2dDescriptor::m_PoolWidth</a>, <a class="el" href="_descriptors_8hpp_source.html#l00361">Pooling2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l00363">Pooling2dDescriptor::m_StrideY</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p> |
| 835 | |
| 836 | <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00377">BOOST_AUTO_TEST_CASE()</a>.</p> |
| 837 | <div class="fragment"><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> {</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> </div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">Pooling2dDescriptor</a> desc;</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 100;</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 5;</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 50;</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 50;</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 50;</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 50;</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> </div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> </div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <a class="code" href="classarmnn_1_1_pooling2d_layer.html">Pooling2dLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_pooling2d_layer.html">Pooling2dLayer</a>>(desc, <span class="stringliteral">"pooling2d"</span>);</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span> </div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> }</div><div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div> |
| 838 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">armnn::Pooling2dDescriptor::m_PoolHeight</a></div><div class="ttdeci">uint32_t m_PoolHeight</div><div class="ttdoc">Pooling height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00359">Descriptors.hpp:359</a></div></div> |
| 839 | <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div> |
| 840 | <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 841 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">armnn::Pooling2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00353">Descriptors.hpp:353</a></div></div> |
| 842 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::Pooling2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00351">Descriptors.hpp:351</a></div></div> |
| 843 | <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div> |
| 844 | <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div> |
| 845 | <div class="ttc" id="classarmnn_1_1_pooling2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_pooling2d_layer.html">armnn::Pooling2dLayer</a></div><div class="ttdoc">This layer represents a pooling 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_layer_8hpp_source.html#l00013">Pooling2dLayer.hpp:13</a></div></div> |
| 846 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">armnn::Pooling2dDescriptor::m_PoolWidth</a></div><div class="ttdeci">uint32_t m_PoolWidth</div><div class="ttdoc">Pooling width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00357">Descriptors.hpp:357</a></div></div> |
| 847 | <div class="ttc" id="namespacearmnn_html_a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6"><div class="ttname"><a href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a></div><div class="ttdoc">The padding fields don&#39;t count and are ignored. </div></div> |
| 848 | <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div> |
| 849 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Pooling2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00349">Descriptors.hpp:349</a></div></div> |
| 850 | <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div> |
| 851 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a8c29d6ea9b4186d69aad5961c910939c"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a8c29d6ea9b4186d69aad5961c910939c">armnn::Pooling2dDescriptor::m_PaddingMethod</a></div><div class="ttdeci">PaddingMethod m_PaddingMethod</div><div class="ttdoc">The padding method to be used. (Exclude, IgnoreValue). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00367">Descriptors.hpp:367</a></div></div> |
| 852 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Pooling2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00363">Descriptors.hpp:363</a></div></div> |
| 853 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">armnn::Pooling2dDescriptor::m_PoolType</a></div><div class="ttdeci">PoolingAlgorithm m_PoolType</div><div class="ttdoc">The pooling algorithm to use (Max. Average, L2). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00347">Descriptors.hpp:347</a></div></div> |
| 854 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00313">Descriptors.hpp:313</a></div></div> |
| 855 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Pooling2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00369">Descriptors.hpp:369</a></div></div> |
| 856 | <div class="ttc" id="namespacearmnn_html_a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021"><div class="ttname"><a href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a></div></div> |
| 857 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::Pooling2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00355">Descriptors.hpp:355</a></div></div> |
| 858 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Pooling2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00361">Descriptors.hpp:361</a></div></div> |
| 859 | <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div> |
| 860 | <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div> |
| 861 | </div><!-- fragment --> |
| 862 | </div> |
| 863 | </div> |
| 864 | <a id="aefb2c7f14f687a9432490a1bdee05458"></a> |
| 865 | <h2 class="memtitle"><span class="permalink"><a href="#aefb2c7f14f687a9432490a1bdee05458">◆ </a></span>CreateResizeBilinearGraph()</h2> |
| 866 | |
| 867 | <div class="memitem"> |
| 868 | <div class="memproto"> |
| 869 | <table class="memname"> |
| 870 | <tr> |
| 871 | <td class="memname">void CreateResizeBilinearGraph </td> |
| 872 | <td>(</td> |
| 873 | <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> & </td> |
| 874 | <td class="paramname"><em>graph</em>, </td> |
| 875 | </tr> |
| 876 | <tr> |
| 877 | <td class="paramkey"></td> |
| 878 | <td></td> |
| 879 | <td class="paramtype">const unsigned int * </td> |
| 880 | <td class="paramname"><em>inputShape</em>, </td> |
| 881 | </tr> |
| 882 | <tr> |
| 883 | <td class="paramkey"></td> |
| 884 | <td></td> |
| 885 | <td class="paramtype">const unsigned int * </td> |
| 886 | <td class="paramname"><em>outputShape</em>, </td> |
| 887 | </tr> |
| 888 | <tr> |
| 889 | <td class="paramkey"></td> |
| 890 | <td></td> |
| 891 | <td class="paramtype"><a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> </td> |
| 892 | <td class="paramname"><em>dataLayout</em> = <code>DataLayout::NCHW</code> </td> |
| 893 | </tr> |
| 894 | <tr> |
| 895 | <td></td> |
| 896 | <td>)</td> |
| 897 | <td></td><td></td> |
| 898 | </tr> |
| 899 | </table> |
| 900 | </div><div class="memdoc"> |
| 901 | |
| 902 | <p class="definition">Definition at line <a class="el" href="_optimizer_tests_8cpp_source.html#l00397">397</a> of file <a class="el" href="_optimizer_tests_8cpp_source.html">OptimizerTests.cpp</a>.</p> |
| 903 | |
| 904 | <p class="reference">References <a class="el" href="_graph_8hpp_source.html#l00397">Graph::AddLayer()</a>, <a class="el" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::Bilinear</a>, <a class="el" href="_layer_8cpp_source.html#l00079">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.html#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00751">ResizeDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00749">ResizeDescriptor::m_Method</a>, <a class="el" href="_descriptors_8hpp_source.html#l00746">ResizeDescriptor::m_TargetHeight</a>, <a class="el" href="_descriptors_8hpp_source.html#l00744">ResizeDescriptor::m_TargetWidth</a>, and <a class="el" href="_layer_8cpp_source.html#l00058">OutputSlot::SetTensorInfo()</a>.</p> |
| 905 | |
| 906 | <p class="reference">Referenced by <a class="el" href="_optimizer_tests_8cpp_source.html#l00420">BOOST_AUTO_TEST_CASE()</a>.</p> |
| 907 | <div class="fragment"><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> {</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo(4, inputShape, DataType::Float32);</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo(4, outputShape, DataType::Float32);</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> </div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.html">ResizeDescriptor</a> desc;</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  desc.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a869254cb56968986a78a79e1d6d4a86b">m_Method</a> = ResizeMethod::Bilinear;</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  desc.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = 3;</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  desc.<a class="code" href="structarmnn_1_1_resize_descriptor.html#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = 4;</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  desc.<a class="code" href="structarmnn_1_1_resize_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span> </div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> </div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <a class="code" href="classarmnn_1_1_resize_layer.html">ResizeLayer</a>* layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_resize_layer.html">ResizeLayer</a>>(desc, <span class="stringliteral">"resizeBilinear"</span>);</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> </div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  input-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(layer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> }</div><div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div> |
| 908 | <div class="ttc" id="structarmnn_1_1_resize_descriptor_html_a46c3fa15c46fb0d1dcdc24d0ea5cb5cd"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">armnn::ResizeDescriptor::m_TargetHeight</a></div><div class="ttdeci">uint32_t m_TargetHeight</div><div class="ttdoc">Target height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00746">Descriptors.hpp:746</a></div></div> |
| 909 | <div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div> |
| 910 | <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 911 | <div class="ttc" id="structarmnn_1_1_resize_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::ResizeDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00751">Descriptors.hpp:751</a></div></div> |
| 912 | <div class="ttc" id="structarmnn_1_1_resize_descriptor_html_a869254cb56968986a78a79e1d6d4a86b"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#a869254cb56968986a78a79e1d6d4a86b">armnn::ResizeDescriptor::m_Method</a></div><div class="ttdeci">ResizeMethod m_Method</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00749">Descriptors.hpp:749</a></div></div> |
| 913 | <div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div> |
| 914 | <div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div> |
| 915 | <div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div> |
| 916 | <div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div> |
| 917 | <div class="ttc" id="structarmnn_1_1_resize_descriptor_html_adcf5037208faac36c0788239a073f75c"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html#adcf5037208faac36c0788239a073f75c">armnn::ResizeDescriptor::m_TargetWidth</a></div><div class="ttdeci">uint32_t m_TargetWidth</div><div class="ttdoc">Target width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00744">Descriptors.hpp:744</a></div></div> |
| 918 | <div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div> |
| 919 | <div class="ttc" id="structarmnn_1_1_resize_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.html">armnn::ResizeDescriptor</a></div><div class="ttdoc">A ResizeDescriptor for the ResizeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00724">Descriptors.hpp:724</a></div></div> |
| 920 | <div class="ttc" id="classarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div> |
| 921 | <div class="ttc" id="classarmnn_1_1_resize_layer_html"><div class="ttname"><a href="classarmnn_1_1_resize_layer.html">armnn::ResizeLayer</a></div><div class="ttdoc">This layer represents a resize operation. </div><div class="ttdef"><b>Definition:</b> <a href="_resize_layer_8hpp_source.html#l00013">ResizeLayer.hpp:13</a></div></div> |
| 922 | </div><!-- fragment --> |
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