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<div class="title">NetworkExecutionUtils.hpp File Reference</div> </div>
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<div class="textblock"><code>#include <<a class="el" href="_arm_n_n_8hpp_source.xhtml">armnn/ArmNN.hpp</a>></code><br />
<code>#include <<a class="el" href="_types_utils_8hpp_source.xhtml">armnn/TypesUtils.hpp</a>></code><br />
<code>#include "<a class="el" href="_csv_reader_8hpp_source.xhtml">CsvReader.hpp</a>"</code><br />
<code>#include "<a class="el" href="_inference_test_8hpp_source.xhtml">../InferenceTest.hpp</a>"</code><br />
<code>#include <<a class="el" href="_profiling_8hpp_source.xhtml">Profiling.hpp</a>></code><br />
<code>#include <<a class="el" href="_resolve_type_8hpp_source.xhtml">ResolveType.hpp</a>></code><br />
<code>#include <boost/algorithm/string/trim.hpp></code><br />
<code>#include <boost/algorithm/string/split.hpp></code><br />
<code>#include <boost/algorithm/string/classification.hpp></code><br />
<code>#include <boost/program_options.hpp></code><br />
<code>#include <boost/variant.hpp></code><br />
<code>#include <iostream></code><br />
<code>#include <fstream></code><br />
<code>#include <functional></code><br />
<code>#include <future></code><br />
<code>#include <algorithm></code><br />
<code>#include <iterator></code><br />
</div>
<p><a href="_network_execution_utils_8hpp_source.xhtml">Go to the source code of this file.</a></p>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct  </td><td class="memItemRight" valign="bottom"><a class="el" href="struct_execute_network_params.xhtml">ExecuteNetworkParams</a></td></tr>
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Functions</h2></td></tr>
<tr class="memitem:afc1c3398fd2de1051edf23a171cfa01b"><td class="memTemplParams" colspan="2">template<typename TParser , typename TDataType > </td></tr>
<tr class="memitem:afc1c3398fd2de1051edf23a171cfa01b"><td class="memTemplItemLeft" align="right" valign="top">int </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_network_execution_utils_8hpp.xhtml#afc1c3398fd2de1051edf23a171cfa01b">MainImpl</a> (const <a class="el" href="struct_execute_network_params.xhtml">ExecuteNetworkParams</a> &params, const std::shared_ptr< <a class="el" href="classarmnn_1_1_i_runtime.xhtml">armnn::IRuntime</a> > &runtime=nullptr)</td></tr>
<tr class="separator:afc1c3398fd2de1051edf23a171cfa01b"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab182729acbd2161a0358d85906d30703"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="_network_execution_utils_8hpp.xhtml#ab182729acbd2161a0358d85906d30703">RunTest</a> (const std::string &format, const std::string &inputTensorShapesStr, const vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > &computeDevices, const std::string &dynamicBackendsPath, const std::string &path, const std::string &inputNames, const std::string &inputTensorDataFilePaths, const std::string &inputTypes, bool quantizeInput, const std::string &outputTypes, const std::string &outputNames, const std::string &outputTensorFiles, bool dequantizeOuput, bool enableProfiling, bool enableFp16TurboMode, const double &thresholdTime, bool printIntermediate, const size_t subgraphId, bool enableLayerDetails=<a class="el" href="_ref_layer_tests_8cpp.xhtml#af3b727ae5a13ff472892ab8bda2eb1b5">false</a>, bool parseUnsupported=<a class="el" href="_ref_layer_tests_8cpp.xhtml#af3b727ae5a13ff472892ab8bda2eb1b5">false</a>, const std::shared_ptr< <a class="el" href="classarmnn_1_1_i_runtime.xhtml">armnn::IRuntime</a> > &runtime=nullptr)</td></tr>
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<tr class="memitem:a31556a7bc4fe615f51dd68af510a9947"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="_network_execution_utils_8hpp.xhtml#a31556a7bc4fe615f51dd68af510a9947">RunCsvTest</a> (const <a class="el" href="structarmnn_utils_1_1_csv_row.xhtml">armnnUtils::CsvRow</a> &csvRow, const std::shared_ptr< <a class="el" href="classarmnn_1_1_i_runtime.xhtml">armnn::IRuntime</a> > &runtime, const bool enableProfiling, const bool enableFp16TurboMode, const double &thresholdTime, const bool printIntermediate, bool enableLayerDetails=<a class="el" href="_ref_layer_tests_8cpp.xhtml#af3b727ae5a13ff472892ab8bda2eb1b5">false</a>, bool parseUnuspported=<a class="el" href="_ref_layer_tests_8cpp.xhtml#af3b727ae5a13ff472892ab8bda2eb1b5">false</a>)</td></tr>
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Variables</h2></td></tr>
<tr class="memitem:ad7abdfb6c0cc99eb356c1eefdc6ff696"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="_network_execution_utils_8hpp.xhtml#ad7abdfb6c0cc99eb356c1eefdc6ff696">generateTensorData</a> = <a class="el" href="_ref_layer_tests_8cpp.xhtml#a37f1c3ccc9fc906be85185350dd83d48">true</a></td></tr>
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<h2 class="groupheader">Function Documentation</h2>
<a id="afc1c3398fd2de1051edf23a171cfa01b"></a>
<h2 class="memtitle"><span class="permalink"><a href="#afc1c3398fd2de1051edf23a171cfa01b">◆ </a></span>MainImpl()</h2>
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<td class="memname">int MainImpl </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="struct_execute_network_params.xhtml">ExecuteNetworkParams</a> & </td>
<td class="paramname"><em>params</em>, </td>
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<td></td>
<td class="paramtype">const std::shared_ptr< <a class="el" href="classarmnn_1_1_i_runtime.xhtml">armnn::IRuntime</a> > & </td>
<td class="paramname"><em>runtime</em> = <code>nullptr</code> </td>
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<td>)</td>
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<p class="definition">Definition at line <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00391">391</a> of file <a class="el" href="_network_execution_utils_8hpp_source.xhtml">NetworkExecutionUtils.hpp</a>.</p>
<p class="reference">References <a class="el" href="_logging_8hpp_source.xhtml#l00163">ARMNN_LOG</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00543">InferenceModel< IParser, TDataType >::GetInputQuantizationParams()</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00449">InferenceModel< IParser, TDataType >::GetInputSize()</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00531">InferenceModel< IParser, TDataType >::GetOutputBindingInfos()</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00455">InferenceModel< IParser, TDataType >::GetOutputSize()</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00088">Params::m_ComputeDevices</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00369">ExecuteNetworkParams::m_ComputeDevices</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00379">ExecuteNetworkParams::m_DequantizeOutput</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00089">Params::m_DynamicBackendsPath</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00370">ExecuteNetworkParams::m_DynamicBackendsPath</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00093">Params::m_EnableFp16TurboMode</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00381">ExecuteNetworkParams::m_EnableFp16TurboMode</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00385">ExecuteNetworkParams::m_EnableLayerDetails</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00380">ExecuteNetworkParams::m_EnableProfiling</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00386">ExecuteNetworkParams::m_GenerateTensorData</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00085">Params::m_InputBindings</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00371">ExecuteNetworkParams::m_InputNames</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00086">Params::m_InputShapes</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00373">ExecuteNetworkParams::m_InputTensorDataFilePaths</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00372">ExecuteNetworkParams::m_InputTensorShapes</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00374">ExecuteNetworkParams::m_InputTypes</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00091">Params::m_IsModelBinary</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00368">ExecuteNetworkParams::m_IsModelBinary</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00084">Params::m_ModelPath</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00367">ExecuteNetworkParams::m_ModelPath</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00087">Params::m_OutputBindings</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00377">ExecuteNetworkParams::m_OutputNames</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00378">ExecuteNetworkParams::m_OutputTensorFiles</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00376">ExecuteNetworkParams::m_OutputTypes</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00095">Params::m_ParseUnsupported</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00387">ExecuteNetworkParams::m_ParseUnsupported</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00383">ExecuteNetworkParams::m_PrintIntermediate</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00094">Params::m_PrintIntermediateLayers</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00375">ExecuteNetworkParams::m_QuantizeInput</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00090">Params::m_SubgraphId</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00384">ExecuteNetworkParams::m_SubgraphId</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00382">ExecuteNetworkParams::m_ThresholdTime</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00092">Params::m_VisualizePostOptimizationModel</a>, <a class="el" href="_inference_model_8hpp_source.xhtml#l00461">InferenceModel< IParser, TDataType >::Run()</a>, and <a class="el" href="_exceptions_8cpp_source.xhtml#l00032">Exception::what()</a>.</p>
<div class="fragment"><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>  <span class="keyword">using</span> <a class="code" href="_model_accuracy_checker_test_8cpp.xhtml#a9eb69ebdaf4ceb8014e7c8a540266100">TContainer</a> = boost::variant<std::vector<float>, std::vector<int>, std::vector<unsigned char>>;</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> </div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  std::vector<TContainer> inputDataContainers;</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span> </div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keywordflow">try</span></div><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>  <span class="comment">// Creates an InferenceModel, which will parse the model and load it into an IRuntime.</span></div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keyword">typename</span> <a class="code" href="struct_inference_model_internal_1_1_params.xhtml">InferenceModel<TParser, TDataType>::Params</a> inferenceModelParams;</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a4fa312cf0d60fbd3988a7c76ab8e2980">m_ModelPath</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a44c7d128c41b2717fe425cf6fdc32936">m_ModelPath</a>;</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">m_IsModelBinary</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">m_IsModelBinary</a>;</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">m_ComputeDevices</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">m_ComputeDevices</a>;</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">m_DynamicBackendsPath</a> = params.<a class="code" href="struct_execute_network_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">m_DynamicBackendsPath</a>;</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#acde2af8cbbd224a9f94e509ca538a775">m_PrintIntermediateLayers</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a5acc5b4076604db15ee13ee19fa623c4">m_PrintIntermediate</a>;</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#aaae50a6c0f73e4c210c2e4331c439482">m_VisualizePostOptimizationModel</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a7efc68309e76bfefbfa16fe94501b060">m_EnableLayerDetails</a>;</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">m_ParseUnsupported</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">m_ParseUnsupported</a>;</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> </div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="keywordflow">for</span>(<span class="keyword">const</span> std::string& inputName: params.<a class="code" href="struct_execute_network_params.xhtml#a155de45be27135e4c9b6b7df277d0b8f">m_InputNames</a>)</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>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#aad2ac35d4cb83ee4da9fad5fbcb907e0">m_InputBindings</a>.push_back(inputName);</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  }</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>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>.size(); ++i)</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  {</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#ad69aa6b4967ce55ee4a915c52c71bf2e">m_InputShapes</a>.push_back(*params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>[i]);</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  }</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> </div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keywordflow">for</span>(<span class="keyword">const</span> std::string& outputName: params.<a class="code" href="struct_execute_network_params.xhtml#a1a08c6c34dd3ce290b4bc62a715bb810">m_OutputNames</a>)</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  {</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>.push_back(outputName);</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  }</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span> </div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a2d4582aa74998c397bd064ae73745b62">m_SubgraphId</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a2d4582aa74998c397bd064ae73745b62">m_SubgraphId</a>;</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a513151623e8d448951a0b94ad1946fbe">m_EnableFp16TurboMode</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a513151623e8d448951a0b94ad1946fbe">m_EnableFp16TurboMode</a>;</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> </div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <a class="code" href="class_inference_model.xhtml">InferenceModel<TParser, TDataType></a> model(inferenceModelParams,</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a26d42007440bb01a1a6d0ab3b5a657ee">m_EnableProfiling</a>,</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  params.<a class="code" href="struct_execute_network_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">m_DynamicBackendsPath</a>,</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  runtime);</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> </div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> numInputs = inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#aad2ac35d4cb83ee4da9fad5fbcb907e0">m_InputBindings</a>.size();</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputs; ++i)</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  {</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<QuantizationParams></a> qParams = params.<a class="code" href="struct_execute_network_params.xhtml#a077f6963fc555d9d42f98cf9ed3e7e03">m_QuantizeInput</a> ?</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  armnn::MakeOptional<QuantizationParams>(model.GetInputQuantizationParams()) :</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a>();</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span> </div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<std::string></a> dataFile = params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a> ?</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a>() :</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <a class="code" href="namespacearmnn.xhtml">armnn</a>::<a class="code" href="namespacearmnn.xhtml#a77780137c47f528921f6537447060f05">MakeOptional</a><<a class="code" href="namespacestd.xhtml">std</a>::string>(params.m_InputTensorDataFilePaths[i]);</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span> </div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numElements = model.GetInputSize(i);</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>.size() > i && params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>[i])</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>  <span class="comment">// If the user has provided a tensor shape for the current input,</span></div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <span class="comment">// override numElements</span></div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  numElements = params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>[i]->GetNumElements();</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  }</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> </div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <a class="code" href="_model_accuracy_checker_test_8cpp.xhtml#a9eb69ebdaf4ceb8014e7c8a540266100">TContainer</a> tensorData;</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  PopulateTensorWithData(tensorData,</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  numElements,</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a08c2e205fcf14f0caa44388f8314e7b5">m_InputTypes</a>[i],</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  qParams,</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  dataFile);</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span> </div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  inputDataContainers.push_back(tensorData);</div><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> </div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> numOutputs = inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>.size();</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  std::vector<TContainer> outputDataContainers;</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span> </div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numOutputs; ++i)</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  {</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a71c32d9b0334a1561bb6d2db677755d6">m_OutputTypes</a>[i].compare(<span class="stringliteral">"float"</span>) == 0)</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  {</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  outputDataContainers.push_back(std::vector<float>(model.GetOutputSize(i)));</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  }</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a71c32d9b0334a1561bb6d2db677755d6">m_OutputTypes</a>[i].compare(<span class="stringliteral">"int"</span>) == 0)</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  {</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  outputDataContainers.push_back(std::vector<int>(model.GetOutputSize(i)));</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  }</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a71c32d9b0334a1561bb6d2db677755d6">m_OutputTypes</a>[i].compare(<span class="stringliteral">"qasymm8"</span>) == 0)</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  {</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  outputDataContainers.push_back(std::vector<uint8_t>(model.GetOutputSize(i)));</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  }</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  {</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unsupported tensor data type \""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a71c32d9b0334a1561bb6d2db677755d6">m_OutputTypes</a>[i] << <span class="stringliteral">"\". "</span>;</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  }</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  }</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span> </div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <span class="comment">// model.Run returns the inference time elapsed in EnqueueWorkload (in milliseconds)</span></div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <span class="keyword">auto</span> inference_duration = model.Run(inputDataContainers, outputDataContainers);</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span> </div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a>)</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  {</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"The input data was generated, note that the output will not be useful"</span>;</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  }</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span> </div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="comment">// Print output tensors</span></div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& infosOut = model.GetOutputBindingInfos();</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < numOutputs; i++)</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  {</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& infoOut = infosOut[i].second;</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="keyword">auto</span> outputTensorFile = params.<a class="code" href="struct_execute_network_params.xhtml#a64c0a99d553c42d215c4b2f1a2f1c7d4">m_OutputTensorFiles</a>.empty() ? <span class="stringliteral">""</span> : params.<a class="code" href="struct_execute_network_params.xhtml#a64c0a99d553c42d215c4b2f1a2f1c7d4">m_OutputTensorFiles</a>[i];</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span> </div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  TensorPrinter printer(inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>[i],</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  infoOut,</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  outputTensorFile,</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a85929a48c5e7b16af8f5bc637e45a37f">m_DequantizeOutput</a>);</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  boost::apply_visitor(printer, outputDataContainers[i]);</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  }</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="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"\nInference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  << std::fixed << inference_duration.count() << <span class="stringliteral">" ms"</span>;</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>  <span class="comment">// If thresholdTime == 0.0 (default), then it hasn't been supplied at command line</span></div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> != 0.0)</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="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Threshold time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  << std::fixed << params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> << <span class="stringliteral">" ms"</span>;</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <span class="keyword">auto</span> thresholdMinusInference = params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> - inference_duration.count();</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Threshold time - Inference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  << std::fixed << thresholdMinusInference << <span class="stringliteral">" ms"</span> << <span class="stringliteral">"\n"</span>;</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span> </div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <span class="keywordflow">if</span> (thresholdMinusInference < 0)</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  {</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  std::string errorMessage = <span class="stringliteral">"Elapsed inference time is greater than provided threshold time."</span>;</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << errorMessage;</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  }</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  }</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>  <span class="keywordflow">catch</span> (<a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a> <span class="keyword">const</span>& e)</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  {</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Armnn Error: "</span> << e.<a class="code" href="classarmnn_1_1_exception.xhtml#abf843cbb29dec939d0731e491bab6f70">what</a>();</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><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> </div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keywordflow">return</span> EXIT_SUCCESS;</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span> }</div><div class="ttc" id="struct_execute_network_params_xhtml_a85929a48c5e7b16af8f5bc637e45a37f"><div class="ttname"><a href="struct_execute_network_params.xhtml#a85929a48c5e7b16af8f5bc637e45a37f">ExecuteNetworkParams::m_DequantizeOutput</a></div><div class="ttdeci">bool m_DequantizeOutput</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00379">NetworkExecutionUtils.hpp:379</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a71c32d9b0334a1561bb6d2db677755d6"><div class="ttname"><a href="struct_execute_network_params.xhtml#a71c32d9b0334a1561bb6d2db677755d6">ExecuteNetworkParams::m_OutputTypes</a></div><div class="ttdeci">std::vector< string > m_OutputTypes</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00376">NetworkExecutionUtils.hpp:376</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a64c0a99d553c42d215c4b2f1a2f1c7d4"><div class="ttname"><a href="struct_execute_network_params.xhtml#a64c0a99d553c42d215c4b2f1a2f1c7d4">ExecuteNetworkParams::m_OutputTensorFiles</a></div><div class="ttdeci">std::vector< string > m_OutputTensorFiles</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00378">NetworkExecutionUtils.hpp:378</a></div></div>
<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00270">Optional.hpp:270</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a091cda9098c6f03f91f477a22327892d"><div class="ttname"><a href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">ExecuteNetworkParams::m_InputTensorShapes</a></div><div class="ttdeci">std::vector< TensorShapePtr > m_InputTensorShapes</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00372">NetworkExecutionUtils.hpp:372</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a513151623e8d448951a0b94ad1946fbe"><div class="ttname"><a href="struct_execute_network_params.xhtml#a513151623e8d448951a0b94ad1946fbe">ExecuteNetworkParams::m_EnableFp16TurboMode</a></div><div class="ttdeci">bool m_EnableFp16TurboMode</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00381">NetworkExecutionUtils.hpp:381</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_ae43cf4b5df0068ee6a9151c98947248b"><div class="ttname"><a href="struct_execute_network_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">ExecuteNetworkParams::m_DynamicBackendsPath</a></div><div class="ttdeci">std::string m_DynamicBackendsPath</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00370">NetworkExecutionUtils.hpp:370</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_ae43cf4b5df0068ee6a9151c98947248b"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">InferenceModelInternal::Params::m_DynamicBackendsPath</a></div><div class="ttdeci">std::string m_DynamicBackendsPath</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00089">InferenceModel.hpp:89</a></div></div>
<div class="ttc" id="class_inference_model_xhtml"><div class="ttname"><a href="class_inference_model.xhtml">InferenceModel</a></div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00316">InferenceModel.hpp:316</a></div></div>
<div class="ttc" id="classarmnn_1_1_exception_xhtml_abf843cbb29dec939d0731e491bab6f70"><div class="ttname"><a href="classarmnn_1_1_exception.xhtml#abf843cbb29dec939d0731e491bab6f70">armnn::Exception::what</a></div><div class="ttdeci">virtual const char * what() const noexcept override</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8cpp_source.xhtml#l00032">Exceptions.cpp:32</a></div></div>
<div class="ttc" id="_logging_8hpp_xhtml_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.xhtml#l00163">Logging.hpp:163</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a513151623e8d448951a0b94ad1946fbe"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a513151623e8d448951a0b94ad1946fbe">InferenceModelInternal::Params::m_EnableFp16TurboMode</a></div><div class="ttdeci">bool m_EnableFp16TurboMode</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00093">InferenceModel.hpp:93</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a5acc5b4076604db15ee13ee19fa623c4"><div class="ttname"><a href="struct_execute_network_params.xhtml#a5acc5b4076604db15ee13ee19fa623c4">ExecuteNetworkParams::m_PrintIntermediate</a></div><div class="ttdeci">bool m_PrintIntermediate</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00383">NetworkExecutionUtils.hpp:383</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a5c7f0c083da98e7b6e9ba79d2fcd985d"><div class="ttname"><a href="struct_execute_network_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">ExecuteNetworkParams::m_ParseUnsupported</a></div><div class="ttdeci">bool m_ParseUnsupported</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00387">NetworkExecutionUtils.hpp:387</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_aaae50a6c0f73e4c210c2e4331c439482"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#aaae50a6c0f73e4c210c2e4331c439482">InferenceModelInternal::Params::m_VisualizePostOptimizationModel</a></div><div class="ttdeci">bool m_VisualizePostOptimizationModel</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00092">InferenceModel.hpp:92</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a2d4582aa74998c397bd064ae73745b62"><div class="ttname"><a href="struct_execute_network_params.xhtml#a2d4582aa74998c397bd064ae73745b62">ExecuteNetworkParams::m_SubgraphId</a></div><div class="ttdeci">size_t m_SubgraphId</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00384">NetworkExecutionUtils.hpp:384</a></div></div>
<div class="ttc" id="_model_accuracy_checker_test_8cpp_xhtml_a9eb69ebdaf4ceb8014e7c8a540266100"><div class="ttname"><a href="_model_accuracy_checker_test_8cpp.xhtml#a9eb69ebdaf4ceb8014e7c8a540266100">TContainer</a></div><div class="ttdeci">boost::variant< std::vector< float >, std::vector< int >, std::vector< unsigned char > > TContainer</div><div class="ttdef"><b>Definition:</b> <a href="_model_accuracy_checker_test_8cpp_source.xhtml#l00059">ModelAccuracyCheckerTest.cpp:59</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_aad2ac35d4cb83ee4da9fad5fbcb907e0"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#aad2ac35d4cb83ee4da9fad5fbcb907e0">InferenceModelInternal::Params::m_InputBindings</a></div><div class="ttdeci">std::vector< std::string > m_InputBindings</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00085">InferenceModel.hpp:85</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a2d54e6252c1c9a0e29f7706ba03b2b74"><div class="ttname"><a href="struct_execute_network_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">ExecuteNetworkParams::m_ComputeDevices</a></div><div class="ttdeci">std::vector< armnn::BackendId > m_ComputeDevices</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00369">NetworkExecutionUtils.hpp:369</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a155de45be27135e4c9b6b7df277d0b8f"><div class="ttname"><a href="struct_execute_network_params.xhtml#a155de45be27135e4c9b6b7df277d0b8f">ExecuteNetworkParams::m_InputNames</a></div><div class="ttdeci">std::vector< string > m_InputNames</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00371">NetworkExecutionUtils.hpp:371</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a6bf2f586c403977d31c7d32d371918cf"><div class="ttname"><a href="struct_execute_network_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">ExecuteNetworkParams::m_IsModelBinary</a></div><div class="ttdeci">bool m_IsModelBinary</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00368">NetworkExecutionUtils.hpp:368</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_ad69aa6b4967ce55ee4a915c52c71bf2e"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#ad69aa6b4967ce55ee4a915c52c71bf2e">InferenceModelInternal::Params::m_InputShapes</a></div><div class="ttdeci">std::vector< armnn::TensorShape > m_InputShapes</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00086">InferenceModel.hpp:86</a></div></div>
<div class="ttc" id="namespacestd_xhtml"><div class="ttname"><a href="namespacestd.xhtml">std</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.xhtml#l00147">BackendId.hpp:147</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a99c7360a4d4b248b3f10607bc5d2fe7b"><div class="ttname"><a href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">ExecuteNetworkParams::m_GenerateTensorData</a></div><div class="ttdeci">bool m_GenerateTensorData</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00386">NetworkExecutionUtils.hpp:386</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_abeacb4ed1ca9256ee0e8aea73185a0cc"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">InferenceModelInternal::Params::m_OutputBindings</a></div><div class="ttdeci">std::vector< std::string > m_OutputBindings</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00087">InferenceModel.hpp:87</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a2d54e6252c1c9a0e29f7706ba03b2b74"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">InferenceModelInternal::Params::m_ComputeDevices</a></div><div class="ttdeci">std::vector< armnn::BackendId > m_ComputeDevices</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00088">InferenceModel.hpp:88</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a318999172ae5197f56326b12d29104b7"><div class="ttname"><a href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">ExecuteNetworkParams::m_ThresholdTime</a></div><div class="ttdeci">double m_ThresholdTime</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00382">NetworkExecutionUtils.hpp:382</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a44c7d128c41b2717fe425cf6fdc32936"><div class="ttname"><a href="struct_execute_network_params.xhtml#a44c7d128c41b2717fe425cf6fdc32936">ExecuteNetworkParams::m_ModelPath</a></div><div class="ttdeci">const char * m_ModelPath</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00367">NetworkExecutionUtils.hpp:367</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a1a08c6c34dd3ce290b4bc62a715bb810"><div class="ttname"><a href="struct_execute_network_params.xhtml#a1a08c6c34dd3ce290b4bc62a715bb810">ExecuteNetworkParams::m_OutputNames</a></div><div class="ttdeci">std::vector< string > m_OutputNames</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00377">NetworkExecutionUtils.hpp:377</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a5c7f0c083da98e7b6e9ba79d2fcd985d"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">InferenceModelInternal::Params::m_ParseUnsupported</a></div><div class="ttdeci">bool m_ParseUnsupported</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00095">InferenceModel.hpp:95</a></div></div>
<div class="ttc" id="structarmnn_1_1_empty_optional_xhtml"><div class="ttname"><a href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a></div><div class="ttdoc">EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00032">Optional.hpp:32</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_acde2af8cbbd224a9f94e509ca538a775"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#acde2af8cbbd224a9f94e509ca538a775">InferenceModelInternal::Params::m_PrintIntermediateLayers</a></div><div class="ttdeci">bool m_PrintIntermediateLayers</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00094">InferenceModel.hpp:94</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a7efc68309e76bfefbfa16fe94501b060"><div class="ttname"><a href="struct_execute_network_params.xhtml#a7efc68309e76bfefbfa16fe94501b060">ExecuteNetworkParams::m_EnableLayerDetails</a></div><div class="ttdeci">bool m_EnableLayerDetails</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00385">NetworkExecutionUtils.hpp:385</a></div></div>
<div class="ttc" id="classarmnn_1_1_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_exception.xhtml">armnn::Exception</a></div><div class="ttdoc">Base class for all ArmNN exceptions so that users can filter to just those. </div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00046">Exceptions.hpp:46</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a08c2e205fcf14f0caa44388f8314e7b5"><div class="ttname"><a href="struct_execute_network_params.xhtml#a08c2e205fcf14f0caa44388f8314e7b5">ExecuteNetworkParams::m_InputTypes</a></div><div class="ttdeci">std::vector< string > m_InputTypes</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00374">NetworkExecutionUtils.hpp:374</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a77780137c47f528921f6537447060f05"><div class="ttname"><a href="namespacearmnn.xhtml#a77780137c47f528921f6537447060f05">armnn::MakeOptional</a></div><div class="ttdeci">Optional< T > MakeOptional(Args &&... args)</div><div class="ttdoc">Utility template that constructs an object of type T in-place and wraps it inside an Optional<T> obje...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00304">Optional.hpp:304</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a4fa312cf0d60fbd3988a7c76ab8e2980"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a4fa312cf0d60fbd3988a7c76ab8e2980">InferenceModelInternal::Params::m_ModelPath</a></div><div class="ttdeci">std::string m_ModelPath</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00084">InferenceModel.hpp:84</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a6bf2f586c403977d31c7d32d371918cf"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">InferenceModelInternal::Params::m_IsModelBinary</a></div><div class="ttdeci">bool m_IsModelBinary</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00091">InferenceModel.hpp:91</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a2d4582aa74998c397bd064ae73745b62"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a2d4582aa74998c397bd064ae73745b62">InferenceModelInternal::Params::m_SubgraphId</a></div><div class="ttdeci">size_t m_SubgraphId</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00090">InferenceModel.hpp:90</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a077f6963fc555d9d42f98cf9ed3e7e03"><div class="ttname"><a href="struct_execute_network_params.xhtml#a077f6963fc555d9d42f98cf9ed3e7e03">ExecuteNetworkParams::m_QuantizeInput</a></div><div class="ttdeci">bool m_QuantizeInput</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00375">NetworkExecutionUtils.hpp:375</a></div></div>
<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml">InferenceModelInternal::Params</a></div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00082">InferenceModel.hpp:82</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a26d42007440bb01a1a6d0ab3b5a657ee"><div class="ttname"><a href="struct_execute_network_params.xhtml#a26d42007440bb01a1a6d0ab3b5a657ee">ExecuteNetworkParams::m_EnableProfiling</a></div><div class="ttdeci">bool m_EnableProfiling</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00380">NetworkExecutionUtils.hpp:380</a></div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a31556a7bc4fe615f51dd68af510a9947">◆ </a></span>RunCsvTest()</h2>
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<td class="memname">int RunCsvTest </td>
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<td class="paramtype">const <a class="el" href="structarmnn_utils_1_1_csv_row.xhtml">armnnUtils::CsvRow</a> & </td>
<td class="paramname"><em>csvRow</em>, </td>
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<td class="paramtype">const std::shared_ptr< <a class="el" href="classarmnn_1_1_i_runtime.xhtml">armnn::IRuntime</a> > & </td>
<td class="paramname"><em>runtime</em>, </td>
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<td class="paramtype">const bool </td>
<td class="paramname"><em>enableProfiling</em>, </td>
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<td class="paramtype">const bool </td>
<td class="paramname"><em>enableFp16TurboMode</em>, </td>
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<td class="paramtype">const double & </td>
<td class="paramname"><em>thresholdTime</em>, </td>
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<td class="paramtype">const bool </td>
<td class="paramname"><em>printIntermediate</em>, </td>
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<td class="paramtype">bool </td>
<td class="paramname"><em>enableLayerDetails</em> = <code><a class="el" href="_ref_layer_tests_8cpp.xhtml#af3b727ae5a13ff472892ab8bda2eb1b5">false</a></code>, </td>
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<td class="paramname"><em>parseUnuspported</em> = <code><a class="el" href="_ref_layer_tests_8cpp.xhtml#af3b727ae5a13ff472892ab8bda2eb1b5">false</a></code> </td>
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<p class="definition">Definition at line <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00750">750</a> of file <a class="el" href="_network_execution_utils_8hpp_source.xhtml">NetworkExecutionUtils.hpp</a>.</p>
<p class="reference">References <a class="el" href="_logging_8hpp_source.xhtml#l00163">ARMNN_LOG</a>, <a class="el" href="_backend_registry_8cpp_source.xhtml#l00013">armnn::BackendRegistryInstance()</a>, <a class="el" href="_backend_registry_8cpp_source.xhtml#l00076">BackendRegistry::GetBackendIdsAsString()</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00537">RunTest()</a>, and <a class="el" href="_csv_reader_8hpp_source.xhtml#l00015">CsvRow::values</a>.</p>
<p class="reference">Referenced by <a class="el" href="_execute_network_8cpp_source.xhtml#l00009">main()</a>.</p>
<div class="fragment"><div class="line"><a name="l00753"></a><span class="lineno"> 753</span> {</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(runtime);</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  std::string modelFormat;</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  std::string modelPath;</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  std::string inputNames;</div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  std::string inputTensorShapes;</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  std::string inputTensorDataFilePaths;</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  std::string outputNames;</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  std::string inputTypes;</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  std::string outputTypes;</div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  std::string dynamicBackendsPath;</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  std::string outputTensorFiles;</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span> </div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  <span class="keywordtype">size_t</span> subgraphId = 0;</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span> </div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  <span class="keyword">const</span> std::string backendsMessage = std::string(<span class="stringliteral">"The preferred order of devices to run layers on by default. "</span>)</div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  + std::string(<span class="stringliteral">"Possible choices: "</span>)</div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  + <a class="code" href="namespacearmnn.xhtml#ac2807505b850738bc8a1991ce669dd47">armnn::BackendRegistryInstance</a>().<a class="code" href="classarmnn_1_1_backend_registry.xhtml#ae1de2f7ca1db17f45f97155e239b8b45">GetBackendIdsAsString</a>();</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span> </div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  po::options_description desc(<span class="stringliteral">"Options"</span>);</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  {</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  desc.add_options()</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  (<span class="stringliteral">"model-format,f"</span>, po::value(&modelFormat),</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <span class="stringliteral">"armnn-binary, caffe-binary, caffe-text, tflite-binary, onnx-binary, onnx-text, tensorflow-binary or "</span></div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  <span class="stringliteral">"tensorflow-text."</span>)</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  (<span class="stringliteral">"model-path,m"</span>, po::value(&modelPath), <span class="stringliteral">"Path to model file, e.g. .armnn, .caffemodel, .prototxt, "</span></div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  <span class="stringliteral">".tflite, .onnx"</span>)</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  (<span class="stringliteral">"compute,c"</span>, po::value<std::vector<armnn::BackendId>>()->multitoken(),</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  backendsMessage.c_str())</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  (<span class="stringliteral">"dynamic-backends-path,b"</span>, po::value(&dynamicBackendsPath),</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <span class="stringliteral">"Path where to load any available dynamic backend from. "</span></div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  <span class="stringliteral">"If left empty (the default), dynamic backends will not be used."</span>)</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  (<span class="stringliteral">"input-name,i"</span>, po::value(&inputNames), <span class="stringliteral">"Identifier of the input tensors in the network separated by comma."</span>)</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  (<span class="stringliteral">"subgraph-number,n"</span>, po::value<size_t>(&subgraphId)->default_value(0), <span class="stringliteral">"Id of the subgraph to be "</span></div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <span class="stringliteral">"executed. Defaults to 0."</span>)</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  (<span class="stringliteral">"input-tensor-shape,s"</span>, po::value(&inputTensorShapes),</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <span class="stringliteral">"The shape of the input tensors in the network as a flat array of integers separated by comma. "</span></div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  <span class="stringliteral">"Several shapes can be passed separating them by semicolon. "</span></div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <span class="stringliteral">"This parameter is optional, depending on the network."</span>)</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  (<span class="stringliteral">"input-tensor-data,d"</span>, po::value(&inputTensorDataFilePaths)->default_value(<span class="stringliteral">""</span>),</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <span class="stringliteral">"Path to files containing the input data as a flat array separated by whitespace. "</span></div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <span class="stringliteral">"Several paths can be passed separating them by comma. If not specified, the network will be run with dummy "</span></div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <span class="stringliteral">"data (useful for profiling)."</span>)</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  (<span class="stringliteral">"input-type,y"</span>,po::value(&inputTypes), <span class="stringliteral">"The type of the input tensors in the network separated by comma. "</span></div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <span class="stringliteral">"If unset, defaults to \"float\" for all defined inputs. "</span></div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  <span class="stringliteral">"Accepted values (float, int or qasymm8)."</span>)</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  (<span class="stringliteral">"quantize-input,q"</span>,po::bool_switch()->default_value(<span class="keyword">false</span>),</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  <span class="stringliteral">"If this option is enabled, all float inputs will be quantized to qasymm8. "</span></div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <span class="stringliteral">"If unset, default to not quantized. "</span></div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <span class="stringliteral">"Accepted values (true or false)"</span>)</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  (<span class="stringliteral">"output-type,z"</span>,po::value(&outputTypes), <span class="stringliteral">"The type of the output tensors in the network separated by comma. "</span></div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <span class="stringliteral">"If unset, defaults to \"float\" for all defined outputs. "</span></div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <span class="stringliteral">"Accepted values (float, int or qasymm8)."</span>)</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  (<span class="stringliteral">"output-name,o"</span>, po::value(&outputNames),</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <span class="stringliteral">"Identifier of the output tensors in the network separated by comma."</span>)</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  (<span class="stringliteral">"dequantize-output,l"</span>,po::bool_switch()->default_value(<span class="keyword">false</span>),</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <span class="stringliteral">"If this option is enabled, all quantized outputs will be dequantized to float. "</span></div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <span class="stringliteral">"If unset, default to not get dequantized. "</span></div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  <span class="stringliteral">"Accepted values (true or false)"</span>)</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  (<span class="stringliteral">"write-outputs-to-file,w"</span>, po::value(&outputTensorFiles),</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <span class="stringliteral">"Comma-separated list of output file paths keyed with the binding-id of the output slot. "</span></div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  <span class="stringliteral">"If left empty (the default), the output tensors will not be written to a file."</span>);</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  }</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::exception& e)</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  {</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  <span class="comment">// Coverity points out that default_value(...) can throw a bad_lexical_cast,</span></div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  <span class="comment">// and that desc.add_options() can throw boost::io::too_few_args.</span></div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  <span class="comment">// They really won't in any of these cases.</span></div><div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Caught unexpected exception"</span>);</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Fatal internal error: "</span> << e.what();</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  }</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span> </div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  std::vector<const char*> clOptions;</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  clOptions.reserve(csvRow.<a class="code" href="structarmnn_utils_1_1_csv_row.xhtml#af80d24ad6806a497ec21dc835c28b7ce">values</a>.size());</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> std::string& value : csvRow.<a class="code" href="structarmnn_utils_1_1_csv_row.xhtml#af80d24ad6806a497ec21dc835c28b7ce">values</a>)</div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  {</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  clOptions.push_back(value.c_str());</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span>  }</div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span> </div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  po::variables_map vm;</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  {</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  po::store(po::parse_command_line(static_cast<int>(clOptions.size()), clOptions.data(), desc), vm);</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span> </div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  po::notify(vm);</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span> </div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  CheckOptionDependencies(vm);</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  }</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> po::error& e)</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  {</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  std::cerr << e.what() << std::endl << std::endl;</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  std::cerr << desc << std::endl;</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  }</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span> </div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="comment">// Get the value of the switch arguments.</span></div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <span class="keywordtype">bool</span> quantizeInput = vm[<span class="stringliteral">"quantize-input"</span>].as<<span class="keywordtype">bool</span>>();</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  <span class="keywordtype">bool</span> dequantizeOutput = vm[<span class="stringliteral">"dequantize-output"</span>].as<<span class="keywordtype">bool</span>>();</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span> </div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  <span class="comment">// Get the preferred order of compute devices.</span></div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  std::vector<armnn::BackendId> computeDevices = vm[<span class="stringliteral">"compute"</span>].as<std::vector<armnn::BackendId>>();</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span> </div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <span class="comment">// Remove duplicates from the list of compute devices.</span></div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  RemoveDuplicateDevices(computeDevices);</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span> </div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  <span class="comment">// Check that the specified compute devices are valid.</span></div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  std::string invalidBackends;</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <span class="keywordflow">if</span> (!CheckRequestedBackendsAreValid(computeDevices, <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<std::string&></a>(invalidBackends)))</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  {</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"The list of preferred devices contains invalid backend IDs: "</span></div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  << invalidBackends;</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  }</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span> </div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  <span class="keywordflow">return</span> <a class="code" href="_network_execution_utils_8hpp.xhtml#ab182729acbd2161a0358d85906d30703">RunTest</a>(modelFormat, inputTensorShapes, computeDevices, dynamicBackendsPath, modelPath, inputNames,</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  inputTensorDataFilePaths, inputTypes, quantizeInput, outputTypes, outputNames, outputTensorFiles,</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  dequantizeOutput, enableProfiling, enableFp16TurboMode, thresholdTime, printIntermediate, subgraphId,</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  enableLayerDetails, parseUnuspported);</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span> }</div><div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00270">Optional.hpp:270</a></div></div>
<div class="ttc" id="_network_execution_utils_8hpp_xhtml_ab182729acbd2161a0358d85906d30703"><div class="ttname"><a href="_network_execution_utils_8hpp.xhtml#ab182729acbd2161a0358d85906d30703">RunTest</a></div><div class="ttdeci">int RunTest(const std::string &format, const std::string &inputTensorShapesStr, const vector< armnn::BackendId > &computeDevices, const std::string &dynamicBackendsPath, const std::string &path, const std::string &inputNames, const std::string &inputTensorDataFilePaths, const std::string &inputTypes, bool quantizeInput, const std::string &outputTypes, const std::string &outputNames, const std::string &outputTensorFiles, bool dequantizeOuput, bool enableProfiling, bool enableFp16TurboMode, const double &thresholdTime, bool printIntermediate, const size_t subgraphId, bool enableLayerDetails=false, bool parseUnsupported=false, const std::shared_ptr< armnn::IRuntime > &runtime=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00537">NetworkExecutionUtils.hpp:537</a></div></div>
<div class="ttc" id="structarmnn_utils_1_1_csv_row_xhtml_af80d24ad6806a497ec21dc835c28b7ce"><div class="ttname"><a href="structarmnn_utils_1_1_csv_row.xhtml#af80d24ad6806a497ec21dc835c28b7ce">armnnUtils::CsvRow::values</a></div><div class="ttdeci">std::vector< std::string > values</div><div class="ttdef"><b>Definition:</b> <a href="_csv_reader_8hpp_source.xhtml#l00015">CsvReader.hpp:15</a></div></div>
<div class="ttc" id="_logging_8hpp_xhtml_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.xhtml#l00163">Logging.hpp:163</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ac2807505b850738bc8a1991ce669dd47"><div class="ttname"><a href="namespacearmnn.xhtml#ac2807505b850738bc8a1991ce669dd47">armnn::BackendRegistryInstance</a></div><div class="ttdeci">BackendRegistry & BackendRegistryInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.xhtml#l00013">BackendRegistry.cpp:13</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div>
<div class="ttc" id="classarmnn_1_1_backend_registry_xhtml_ae1de2f7ca1db17f45f97155e239b8b45"><div class="ttname"><a href="classarmnn_1_1_backend_registry.xhtml#ae1de2f7ca1db17f45f97155e239b8b45">armnn::BackendRegistry::GetBackendIdsAsString</a></div><div class="ttdeci">std::string GetBackendIdsAsString() const</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.xhtml#l00076">BackendRegistry.cpp:76</a></div></div>
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<a id="ab182729acbd2161a0358d85906d30703"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ab182729acbd2161a0358d85906d30703">◆ </a></span>RunTest()</h2>
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<td class="memname">int RunTest </td>
<td>(</td>
<td class="paramtype">const std::string & </td>
<td class="paramname"><em>format</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const std::string & </td>
<td class="paramname"><em>inputTensorShapesStr</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const vector< <a class="el" href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a> > & </td>
<td class="paramname"><em>computeDevices</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const std::string & </td>
<td class="paramname"><em>dynamicBackendsPath</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const std::string & </td>
<td class="paramname"><em>path</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const std::string & </td>
<td class="paramname"><em>inputNames</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const std::string & </td>
<td class="paramname"><em>inputTensorDataFilePaths</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const std::string & </td>
<td class="paramname"><em>inputTypes</em>, </td>
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<td class="paramtype">bool </td>
<td class="paramname"><em>quantizeInput</em>, </td>
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<td class="paramtype">const std::string & </td>
<td class="paramname"><em>outputTypes</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const std::string & </td>
<td class="paramname"><em>outputNames</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const std::string & </td>
<td class="paramname"><em>outputTensorFiles</em>, </td>
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<td class="paramtype">bool </td>
<td class="paramname"><em>dequantizeOuput</em>, </td>
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<td class="paramtype">bool </td>
<td class="paramname"><em>enableProfiling</em>, </td>
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<td class="paramtype">bool </td>
<td class="paramname"><em>enableFp16TurboMode</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const double & </td>
<td class="paramname"><em>thresholdTime</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">bool </td>
<td class="paramname"><em>printIntermediate</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const size_t </td>
<td class="paramname"><em>subgraphId</em>, </td>
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<td class="paramtype">bool </td>
<td class="paramname"><em>enableLayerDetails</em> = <code><a class="el" href="_ref_layer_tests_8cpp.xhtml#af3b727ae5a13ff472892ab8bda2eb1b5">false</a></code>, </td>
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<td class="paramtype">bool </td>
<td class="paramname"><em>parseUnsupported</em> = <code><a class="el" href="_ref_layer_tests_8cpp.xhtml#af3b727ae5a13ff472892ab8bda2eb1b5">false</a></code>, </td>
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<td></td>
<td class="paramtype">const std::shared_ptr< <a class="el" href="classarmnn_1_1_i_runtime.xhtml">armnn::IRuntime</a> > & </td>
<td class="paramname"><em>runtime</em> = <code>nullptr</code> </td>
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<td>)</td>
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<p class="definition">Definition at line <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00537">537</a> of file <a class="el" href="_network_execution_utils_8hpp_source.xhtml">NetworkExecutionUtils.hpp</a>.</p>
<p class="reference">References <a class="el" href="_logging_8hpp_source.xhtml#l00163">ARMNN_LOG</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00369">ExecuteNetworkParams::m_ComputeDevices</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00379">ExecuteNetworkParams::m_DequantizeOutput</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00370">ExecuteNetworkParams::m_DynamicBackendsPath</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00381">ExecuteNetworkParams::m_EnableFp16TurboMode</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00385">ExecuteNetworkParams::m_EnableLayerDetails</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00380">ExecuteNetworkParams::m_EnableProfiling</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00386">ExecuteNetworkParams::m_GenerateTensorData</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00371">ExecuteNetworkParams::m_InputNames</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00373">ExecuteNetworkParams::m_InputTensorDataFilePaths</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00372">ExecuteNetworkParams::m_InputTensorShapes</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00374">ExecuteNetworkParams::m_InputTypes</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00368">ExecuteNetworkParams::m_IsModelBinary</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00367">ExecuteNetworkParams::m_ModelPath</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00377">ExecuteNetworkParams::m_OutputNames</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00378">ExecuteNetworkParams::m_OutputTensorFiles</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00376">ExecuteNetworkParams::m_OutputTypes</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00387">ExecuteNetworkParams::m_ParseUnsupported</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00383">ExecuteNetworkParams::m_PrintIntermediate</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00375">ExecuteNetworkParams::m_QuantizeInput</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00384">ExecuteNetworkParams::m_SubgraphId</a>, <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00382">ExecuteNetworkParams::m_ThresholdTime</a>, and <a class="el" href="_exceptions_8cpp_source.xhtml#l00032">Exception::what()</a>.</p>
<p class="reference">Referenced by <a class="el" href="_unsupported_8cpp_source.xhtml#l00239">BOOST_FIXTURE_TEST_CASE()</a>, <a class="el" href="_execute_network_8cpp_source.xhtml#l00009">main()</a>, and <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00750">RunCsvTest()</a>.</p>
<div class="fragment"><div class="line"><a name="l00558"></a><span class="lineno"> 558</span> {</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  std::string modelFormat = boost::trim_copy(format);</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  std::string modelPath = boost::trim_copy(path);</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  std::vector<std::string> inputNamesVector = ParseStringList(inputNames, <span class="stringliteral">","</span>);</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  std::vector<std::string> inputTensorShapesVector = ParseStringList(inputTensorShapesStr, <span class="stringliteral">":"</span>);</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  std::vector<std::string> inputTensorDataFilePathsVector = ParseStringList(</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  inputTensorDataFilePaths, <span class="stringliteral">","</span>);</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  std::vector<std::string> outputNamesVector = ParseStringList(outputNames, <span class="stringliteral">","</span>);</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  std::vector<std::string> inputTypesVector = ParseStringList(inputTypes, <span class="stringliteral">","</span>);</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  std::vector<std::string> outputTypesVector = ParseStringList(outputTypes, <span class="stringliteral">","</span>);</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  std::vector<std::string> outputTensorFilesVector = ParseStringList(outputTensorFiles, <span class="stringliteral">","</span>);</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span> </div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <span class="comment">// Parse model binary flag from the model-format string we got from the command-line</span></div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <span class="keywordtype">bool</span> isModelBinary;</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <span class="keywordflow">if</span> (modelFormat.find(<span class="stringliteral">"bin"</span>) != std::string::npos)</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  {</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  isModelBinary = <span class="keyword">true</span>;</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  }</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (modelFormat.find(<span class="stringliteral">"txt"</span>) != std::string::npos || modelFormat.find(<span class="stringliteral">"text"</span>) != std::string::npos)</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  {</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  isModelBinary = <span class="keyword">false</span>;</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  }</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  {</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unknown model format: '"</span> << modelFormat << <span class="stringliteral">"'. Please include 'binary' or 'text'"</span>;</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  }</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>  <span class="keywordflow">if</span> ((inputTensorShapesVector.size() != 0) && (inputTensorShapesVector.size() != inputNamesVector.size()))</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  {</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"input-name and input-tensor-shape must have the same amount of elements."</span>;</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  }</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span> </div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="keywordflow">if</span> ((inputTensorDataFilePathsVector.size() != 0) &&</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  (inputTensorDataFilePathsVector.size() != inputNamesVector.size()))</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  {</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"input-name and input-tensor-data must have the same amount of elements."</span>;</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</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> </div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <span class="keywordflow">if</span> ((outputTensorFilesVector.size() != 0) &&</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  (outputTensorFilesVector.size() != outputNamesVector.size()))</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  {</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"output-name and write-outputs-to-file must have the same amount of elements."</span>;</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  }</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span> </div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keywordflow">if</span> (inputTypesVector.size() == 0)</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  {</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="comment">//Defaults the value of all inputs to "float"</span></div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  inputTypesVector.assign(inputNamesVector.size(), <span class="stringliteral">"float"</span>);</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>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> ((inputTypesVector.size() != 0) && (inputTypesVector.size() != inputNamesVector.size()))</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  {</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"input-name and input-type must have the same amount of elements."</span>;</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  }</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span> </div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <span class="keywordflow">if</span> (outputTypesVector.size() == 0)</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  {</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <span class="comment">//Defaults the value of all outputs to "float"</span></div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  outputTypesVector.assign(outputNamesVector.size(), <span class="stringliteral">"float"</span>);</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  }</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> ((outputTypesVector.size() != 0) && (outputTypesVector.size() != outputNamesVector.size()))</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  {</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"output-name and output-type must have the same amount of elements."</span>;</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  }</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span> </div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  <span class="comment">// Parse input tensor shape from the string we got from the command-line.</span></div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  std::vector<std::unique_ptr<armnn::TensorShape>> inputTensorShapes;</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span> </div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  <span class="keywordflow">if</span> (!inputTensorShapesVector.empty())</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  {</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  inputTensorShapes.reserve(inputTensorShapesVector.size());</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span> </div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <span class="keywordflow">for</span>(<span class="keyword">const</span> std::string& shape : inputTensorShapesVector)</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  {</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  std::stringstream ss(shape);</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  std::vector<unsigned int> dims = ParseArray(ss);</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span> </div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  {</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  <span class="comment">// Coverity fix: An exception of type armnn::InvalidArgumentException is thrown and never caught.</span></div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  inputTensorShapes.push_back(std::make_unique<armnn::TensorShape>(dims.size(), dims.data()));</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  }</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>& e)</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  {</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Cannot create tensor shape: "</span> << e.<a class="code" href="classarmnn_1_1_exception.xhtml#abf843cbb29dec939d0731e491bab6f70">what</a>();</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  }</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  }</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  }</div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span> </div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  <span class="comment">// Check that threshold time is not less than zero</span></div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  <span class="keywordflow">if</span> (thresholdTime < 0)</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  {</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Threshold time supplied as a command line argument is less than zero."</span>;</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  }</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span> </div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <a class="code" href="struct_execute_network_params.xhtml">ExecuteNetworkParams</a> params;</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a44c7d128c41b2717fe425cf6fdc32936">m_ModelPath</a> = modelPath.c_str();</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">m_IsModelBinary</a> = isModelBinary;</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">m_ComputeDevices</a> = computeDevices;</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  params.<a class="code" href="struct_execute_network_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">m_DynamicBackendsPath</a> = dynamicBackendsPath;</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a155de45be27135e4c9b6b7df277d0b8f">m_InputNames</a> = inputNamesVector;</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a> = std::move(inputTensorShapes);</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a924e9ee22f0bf39f05e0c1b45e5c637b">m_InputTensorDataFilePaths</a> = inputTensorDataFilePathsVector;</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a08c2e205fcf14f0caa44388f8314e7b5">m_InputTypes</a> = inputTypesVector;</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a077f6963fc555d9d42f98cf9ed3e7e03">m_QuantizeInput</a> = quantizeInput;</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a71c32d9b0334a1561bb6d2db677755d6">m_OutputTypes</a> = outputTypesVector;</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a1a08c6c34dd3ce290b4bc62a715bb810">m_OutputNames</a> = outputNamesVector;</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a64c0a99d553c42d215c4b2f1a2f1c7d4">m_OutputTensorFiles</a> = outputTensorFilesVector;</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a85929a48c5e7b16af8f5bc637e45a37f">m_DequantizeOutput</a> = dequantizeOuput;</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a26d42007440bb01a1a6d0ab3b5a657ee">m_EnableProfiling</a> = enableProfiling;</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a513151623e8d448951a0b94ad1946fbe">m_EnableFp16TurboMode</a> = enableFp16TurboMode;</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> = thresholdTime;</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a5acc5b4076604db15ee13ee19fa623c4">m_PrintIntermediate</a> = printIntermediate;</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a2d4582aa74998c397bd064ae73745b62">m_SubgraphId</a> = subgraphId;</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a7efc68309e76bfefbfa16fe94501b060">m_EnableLayerDetails</a> = enableLayerDetails;</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a> = inputTensorDataFilePathsVector.empty();</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">m_ParseUnsupported</a> = parseUnsupported;</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span> </div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  <span class="comment">// Warn if ExecuteNetwork will generate dummy input data</span></div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a>)</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  {</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"No input files provided, input tensors will be filled with 0s."</span>;</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  }</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span> </div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  <span class="comment">// Forward to implementation based on the parser type</span></div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <span class="keywordflow">if</span> (modelFormat.find(<span class="stringliteral">"armnn"</span>) != std::string::npos)</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  {</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span> <span class="preprocessor">#if defined(ARMNN_SERIALIZER)</span></div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  <span class="keywordflow">return</span> MainImpl<armnnDeserializer::IDeserializer, float>(params, runtime);</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Not built with serialization support."</span>;</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  }</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (modelFormat.find(<span class="stringliteral">"caffe"</span>) != std::string::npos)</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  {</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span> <span class="preprocessor">#if defined(ARMNN_CAFFE_PARSER)</span></div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keywordflow">return</span> MainImpl<armnnCaffeParser::ICaffeParser, float>(params, runtime);</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Not built with Caffe parser support."</span>;</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  }</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (modelFormat.find(<span class="stringliteral">"onnx"</span>) != std::string::npos)</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span> {</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span> <span class="preprocessor">#if defined(ARMNN_ONNX_PARSER)</span></div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  <span class="keywordflow">return</span> MainImpl<armnnOnnxParser::IOnnxParser, float>(params, runtime);</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Not built with Onnx parser support."</span>;</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  }</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (modelFormat.find(<span class="stringliteral">"tensorflow"</span>) != std::string::npos)</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  {</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span> <span class="preprocessor">#if defined(ARMNN_TF_PARSER)</span></div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <span class="keywordflow">return</span> MainImpl<armnnTfParser::ITfParser, float>(params, runtime);</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Not built with Tensorflow parser support."</span>;</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  }</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(modelFormat.find(<span class="stringliteral">"tflite"</span>) != std::string::npos)</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  {</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span> <span class="preprocessor">#if defined(ARMNN_TF_LITE_PARSER)</span></div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  <span class="keywordflow">if</span> (! isModelBinary)</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  {</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unknown model format: '"</span> << modelFormat << <span class="stringliteral">"'. Only 'binary' format supported \</span></div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span> <span class="stringliteral"> for tflite files"</span>;</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  }</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  <span class="keywordflow">return</span> MainImpl<armnnTfLiteParser::ITfLiteParser, float>(params, runtime);</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unknown model format: '"</span> << modelFormat <<</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  <span class="stringliteral">"'. Please include 'caffe', 'tensorflow', 'tflite' or 'onnx'"</span>;</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  }</div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  {</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unknown model format: '"</span> << modelFormat <<</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  <span class="stringliteral">"'. Please include 'caffe', 'tensorflow', 'tflite' or 'onnx'"</span>;</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  }</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span> }</div><div class="ttc" id="struct_execute_network_params_xhtml_a85929a48c5e7b16af8f5bc637e45a37f"><div class="ttname"><a href="struct_execute_network_params.xhtml#a85929a48c5e7b16af8f5bc637e45a37f">ExecuteNetworkParams::m_DequantizeOutput</a></div><div class="ttdeci">bool m_DequantizeOutput</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00379">NetworkExecutionUtils.hpp:379</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a71c32d9b0334a1561bb6d2db677755d6"><div class="ttname"><a href="struct_execute_network_params.xhtml#a71c32d9b0334a1561bb6d2db677755d6">ExecuteNetworkParams::m_OutputTypes</a></div><div class="ttdeci">std::vector< string > m_OutputTypes</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00376">NetworkExecutionUtils.hpp:376</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a64c0a99d553c42d215c4b2f1a2f1c7d4"><div class="ttname"><a href="struct_execute_network_params.xhtml#a64c0a99d553c42d215c4b2f1a2f1c7d4">ExecuteNetworkParams::m_OutputTensorFiles</a></div><div class="ttdeci">std::vector< string > m_OutputTensorFiles</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00378">NetworkExecutionUtils.hpp:378</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a091cda9098c6f03f91f477a22327892d"><div class="ttname"><a href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">ExecuteNetworkParams::m_InputTensorShapes</a></div><div class="ttdeci">std::vector< TensorShapePtr > m_InputTensorShapes</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00372">NetworkExecutionUtils.hpp:372</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a513151623e8d448951a0b94ad1946fbe"><div class="ttname"><a href="struct_execute_network_params.xhtml#a513151623e8d448951a0b94ad1946fbe">ExecuteNetworkParams::m_EnableFp16TurboMode</a></div><div class="ttdeci">bool m_EnableFp16TurboMode</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00381">NetworkExecutionUtils.hpp:381</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_ae43cf4b5df0068ee6a9151c98947248b"><div class="ttname"><a href="struct_execute_network_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">ExecuteNetworkParams::m_DynamicBackendsPath</a></div><div class="ttdeci">std::string m_DynamicBackendsPath</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00370">NetworkExecutionUtils.hpp:370</a></div></div>
<div class="ttc" id="classarmnn_1_1_exception_xhtml_abf843cbb29dec939d0731e491bab6f70"><div class="ttname"><a href="classarmnn_1_1_exception.xhtml#abf843cbb29dec939d0731e491bab6f70">armnn::Exception::what</a></div><div class="ttdeci">virtual const char * what() const noexcept override</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8cpp_source.xhtml#l00032">Exceptions.cpp:32</a></div></div>
<div class="ttc" id="_logging_8hpp_xhtml_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.xhtml#l00163">Logging.hpp:163</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a5acc5b4076604db15ee13ee19fa623c4"><div class="ttname"><a href="struct_execute_network_params.xhtml#a5acc5b4076604db15ee13ee19fa623c4">ExecuteNetworkParams::m_PrintIntermediate</a></div><div class="ttdeci">bool m_PrintIntermediate</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00383">NetworkExecutionUtils.hpp:383</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a5c7f0c083da98e7b6e9ba79d2fcd985d"><div class="ttname"><a href="struct_execute_network_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">ExecuteNetworkParams::m_ParseUnsupported</a></div><div class="ttdeci">bool m_ParseUnsupported</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00387">NetworkExecutionUtils.hpp:387</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a2d4582aa74998c397bd064ae73745b62"><div class="ttname"><a href="struct_execute_network_params.xhtml#a2d4582aa74998c397bd064ae73745b62">ExecuteNetworkParams::m_SubgraphId</a></div><div class="ttdeci">size_t m_SubgraphId</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00384">NetworkExecutionUtils.hpp:384</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a2d54e6252c1c9a0e29f7706ba03b2b74"><div class="ttname"><a href="struct_execute_network_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">ExecuteNetworkParams::m_ComputeDevices</a></div><div class="ttdeci">std::vector< armnn::BackendId > m_ComputeDevices</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00369">NetworkExecutionUtils.hpp:369</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a155de45be27135e4c9b6b7df277d0b8f"><div class="ttname"><a href="struct_execute_network_params.xhtml#a155de45be27135e4c9b6b7df277d0b8f">ExecuteNetworkParams::m_InputNames</a></div><div class="ttdeci">std::vector< string > m_InputNames</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00371">NetworkExecutionUtils.hpp:371</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a6bf2f586c403977d31c7d32d371918cf"><div class="ttname"><a href="struct_execute_network_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">ExecuteNetworkParams::m_IsModelBinary</a></div><div class="ttdeci">bool m_IsModelBinary</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00368">NetworkExecutionUtils.hpp:368</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a99c7360a4d4b248b3f10607bc5d2fe7b"><div class="ttname"><a href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">ExecuteNetworkParams::m_GenerateTensorData</a></div><div class="ttdeci">bool m_GenerateTensorData</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00386">NetworkExecutionUtils.hpp:386</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml"><div class="ttname"><a href="struct_execute_network_params.xhtml">ExecuteNetworkParams</a></div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00363">NetworkExecutionUtils.hpp:363</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a318999172ae5197f56326b12d29104b7"><div class="ttname"><a href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">ExecuteNetworkParams::m_ThresholdTime</a></div><div class="ttdeci">double m_ThresholdTime</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00382">NetworkExecutionUtils.hpp:382</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a44c7d128c41b2717fe425cf6fdc32936"><div class="ttname"><a href="struct_execute_network_params.xhtml#a44c7d128c41b2717fe425cf6fdc32936">ExecuteNetworkParams::m_ModelPath</a></div><div class="ttdeci">const char * m_ModelPath</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00367">NetworkExecutionUtils.hpp:367</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a1a08c6c34dd3ce290b4bc62a715bb810"><div class="ttname"><a href="struct_execute_network_params.xhtml#a1a08c6c34dd3ce290b4bc62a715bb810">ExecuteNetworkParams::m_OutputNames</a></div><div class="ttdeci">std::vector< string > m_OutputNames</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00377">NetworkExecutionUtils.hpp:377</a></div></div>
<div class="ttc" id="classarmnn_1_1_invalid_argument_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00080">Exceptions.hpp:80</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a924e9ee22f0bf39f05e0c1b45e5c637b"><div class="ttname"><a href="struct_execute_network_params.xhtml#a924e9ee22f0bf39f05e0c1b45e5c637b">ExecuteNetworkParams::m_InputTensorDataFilePaths</a></div><div class="ttdeci">std::vector< string > m_InputTensorDataFilePaths</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00373">NetworkExecutionUtils.hpp:373</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a7efc68309e76bfefbfa16fe94501b060"><div class="ttname"><a href="struct_execute_network_params.xhtml#a7efc68309e76bfefbfa16fe94501b060">ExecuteNetworkParams::m_EnableLayerDetails</a></div><div class="ttdeci">bool m_EnableLayerDetails</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00385">NetworkExecutionUtils.hpp:385</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a08c2e205fcf14f0caa44388f8314e7b5"><div class="ttname"><a href="struct_execute_network_params.xhtml#a08c2e205fcf14f0caa44388f8314e7b5">ExecuteNetworkParams::m_InputTypes</a></div><div class="ttdeci">std::vector< string > m_InputTypes</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00374">NetworkExecutionUtils.hpp:374</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a077f6963fc555d9d42f98cf9ed3e7e03"><div class="ttname"><a href="struct_execute_network_params.xhtml#a077f6963fc555d9d42f98cf9ed3e7e03">ExecuteNetworkParams::m_QuantizeInput</a></div><div class="ttdeci">bool m_QuantizeInput</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00375">NetworkExecutionUtils.hpp:375</a></div></div>
<div class="ttc" id="struct_execute_network_params_xhtml_a26d42007440bb01a1a6d0ab3b5a657ee"><div class="ttname"><a href="struct_execute_network_params.xhtml#a26d42007440bb01a1a6d0ab3b5a657ee">ExecuteNetworkParams::m_EnableProfiling</a></div><div class="ttdeci">bool m_EnableProfiling</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00380">NetworkExecutionUtils.hpp:380</a></div></div>
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<h2 class="groupheader">Variable Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#ad7abdfb6c0cc99eb356c1eefdc6ff696">◆ </a></span>generateTensorData</h2>
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<td class="memname">bool generateTensorData = <a class="el" href="_ref_layer_tests_8cpp.xhtml#a37f1c3ccc9fc906be85185350dd83d48">true</a></td>
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<p class="definition">Definition at line <a class="el" href="_network_execution_utils_8hpp_source.xhtml#l00361">361</a> of file <a class="el" href="_network_execution_utils_8hpp_source.xhtml">NetworkExecutionUtils.hpp</a>.</p>
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