IVGCVSW-3726 Upload ArmNN Doxygen files
* Upload current ArmNN Doxygen files
Signed-off-by: Ryan OShea <Ryan.OShea2@arm.com>
Change-Id: I8989ed16ee40a99a4495b100bd009cf3e24a7285
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+<a href="_model_accuracy_tool-_armnn_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "../ImageTensorGenerator/ImageTensorGenerator.hpp"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "../InferenceTest.hpp"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_model_accuracy_checker_8hpp.html">ModelAccuracyChecker.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_i_deserializer_8hpp.html">armnnDeserializer/IDeserializer.hpp</a>"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <boost/algorithm/string.hpp></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <boost/filesystem.hpp></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <boost/program_options/variables_map.hpp></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <boost/range/iterator_range.hpp></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <map></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn_1_1test.html">armnn::test</a>;</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> map<std::string, std::string> <a class="code" href="_model_accuracy_tool-_armnn_8cpp.html#a6bf14e4292511ab535ca9c3df0870185">LoadValidationImageFilenamesAndLabels</a>(<span class="keyword">const</span> <span class="keywordtype">string</span>& validationLabelPath,</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keyword">const</span> <span class="keywordtype">string</span>& imageDirectoryPath,</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keywordtype">size_t</span> begIndex = 0,</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordtype">size_t</span> endIndex = 0,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keyword">const</span> <span class="keywordtype">string</span>& blacklistPath = <span class="stringliteral">""</span>);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> std::vector<armnnUtils::LabelCategoryNames> <a class="code" href="_model_accuracy_tool-_armnn_8cpp.html#a0860c525c02a295d28f4fe0a0c0747c6">LoadModelOutputLabels</a>(<span class="keyword">const</span> std::string& modelOutputLabelsPath);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="_model_accuracy_tool-_armnn_8cpp.html#a0ddf1224851353fc92bfbff6f499fa97"> 49</a></span> <span class="keywordtype">int</span> <a class="code" href="_model_accuracy_tool-_armnn_8cpp.html#a0ddf1224851353fc92bfbff6f499fa97">main</a>(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>* argv[])</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">using namespace </span>boost::filesystem;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="namespacearmnn.html#a93a3ba385cad27c4774e5fe64c025d3d">armnn::LogSeverity</a> level = <a class="code" href="namespacearmnn.html#a93a3ba385cad27c4774e5fe64c025d3daa603905470e2a5b8c13e96b579ef0dba">armnn::LogSeverity::Debug</a>;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="namespacearmnn.html#aa59f7a819c3e29d10ffc41e5c0616872">armnn::ConfigureLogging</a>(<span class="keyword">true</span>, <span class="keyword">true</span>, level);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// Set-up program Options</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">namespace </span>po = boost::program_options;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  std::vector<armnn::BackendId> computeDevice;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  std::vector<armnn::BackendId> <a class="code" href="_cl_end_to_end_tests_8cpp.html#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a> = {<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a>, <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>};</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  std::string modelPath;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  std::string modelFormat;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  std::string dataDir;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  std::string inputName;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  std::string inputLayout;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  std::string outputName;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  std::string modelOutputLabelsPath;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  std::string validationLabelPath;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  std::string validationRange;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  std::string blacklistPath;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">const</span> std::string backendsMessage = <span class="stringliteral">"Which device to run layers on by default. Possible choices: "</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  + <a class="code" href="namespacearmnn.html#ac2807505b850738bc8a1991ce669dd47">armnn::BackendRegistryInstance</a>().<a class="code" href="classarmnn_1_1_backend_registry.html#ae1de2f7ca1db17f45f97155e239b8b45">GetBackendIdsAsString</a>();</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  po::options_description desc(<span class="stringliteral">"Options"</span>);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  {</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="comment">// Adds generic options needed to run Accuracy Tool.</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  desc.add_options()</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  (<span class="stringliteral">"help,h"</span>, <span class="stringliteral">"Display help messages"</span>)</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  (<span class="stringliteral">"model-path,m"</span>, po::value<std::string>(&modelPath)->required(), <span class="stringliteral">"Path to armnn format model file"</span>)</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  (<span class="stringliteral">"model-format,f"</span>, po::value<std::string>(&modelFormat)->required(),</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="stringliteral">"The model format. Supported values: caffe, tensorflow, tflite"</span>)</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  (<span class="stringliteral">"input-name,i"</span>, po::value<std::string>(&inputName)->required(),</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="stringliteral">"Identifier of the input tensors in the network separated by comma."</span>)</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  (<span class="stringliteral">"output-name,o"</span>, po::value<std::string>(&outputName)->required(),</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="stringliteral">"Identifier of the output tensors in the network separated by comma."</span>)</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  (<span class="stringliteral">"data-dir,d"</span>, po::value<std::string>(&dataDir)->required(),</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="stringliteral">"Path to directory containing the ImageNet test data"</span>)</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  (<span class="stringliteral">"model-output-labels,p"</span>, po::value<std::string>(&modelOutputLabelsPath)->required(),</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="stringliteral">"Path to model output labels file."</span>)</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  (<span class="stringliteral">"validation-labels-path,v"</span>, po::value<std::string>(&validationLabelPath)->required(),</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="stringliteral">"Path to ImageNet Validation Label file"</span>)</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  (<span class="stringliteral">"data-layout,l"</span>, po::value<std::string>(&inputLayout)->default_value(<span class="stringliteral">"NHWC"</span>),</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="stringliteral">"Data layout. Supported value: NHWC, NCHW. Default: NHWC"</span>)</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  (<span class="stringliteral">"compute,c"</span>, po::value<std::vector<armnn::BackendId>>(&computeDevice)->default_value(defaultBackends),</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  backendsMessage.c_str())</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  (<span class="stringliteral">"validation-range,r"</span>, po::value<std::string>(&validationRange)->default_value(<span class="stringliteral">"1:0"</span>),</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="stringliteral">"The range of the images to be evaluated. Specified in the form <begin index>:<end index>."</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="stringliteral">"The index starts at 1 and the range is inclusive."</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="stringliteral">"By default the evaluation will be performed on all images."</span>)</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  (<span class="stringliteral">"blacklist-path,b"</span>, po::value<std::string>(&blacklistPath)->default_value(<span class="stringliteral">""</span>),</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="stringliteral">"Path to a blacklist file where each line denotes the index of an image to be "</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="stringliteral">"excluded from evaluation."</span>);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  }</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::exception& e)</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  {</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="comment">// Coverity points out that default_value(...) can throw a bad_lexical_cast,</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// and that desc.add_options() can throw boost::io::too_few_args.</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">// They really won't in any of these cases.</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Caught unexpected exception"</span>);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  std::cerr << <span class="stringliteral">"Fatal internal error: "</span> << e.what() << std::endl;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  }</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  po::variables_map vm;</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  po::store(po::parse_command_line(argc, argv, desc), vm);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keywordflow">if</span> (vm.count(<span class="stringliteral">"help"</span>))</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  {</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  std::cout << desc << std::endl;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  }</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  po::notify(vm);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  }</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">catch</span> (<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">po::error</a>& e)</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  std::cerr << e.what() << std::endl << std::endl;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  std::cerr << desc << std::endl;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  }</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="comment">// Check if the requested backend are all valid</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  std::string invalidBackends;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keywordflow">if</span> (!CheckRequestedBackendsAreValid(computeDevice, <a class="code" href="classarmnn_1_1_optional.html">armnn::Optional<std::string&></a>(invalidBackends)))</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  {</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"The list of preferred devices contains invalid backend IDs: "</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  << invalidBackends;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  }</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a> status;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="comment">// Create runtime</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.html">armnn::IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  std::ifstream file(modelPath);</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">// Create Parser</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keyword">using</span> IParser = <a class="code" href="classarmnn_deserializer_1_1_i_deserializer.html">armnnDeserializer::IDeserializer</a>;</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keyword">auto</span> armnnparser(IParser::Create());</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> </div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="comment">// Create a network</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = armnnparser->CreateNetworkFromBinary(file);</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">// Optimizes the network.</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optimizedNet(<span class="keyword">nullptr</span>, <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  {</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  optimizedNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(*network, computeDevice, runtime->GetDeviceSpec());</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  }</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">catch</span> (<a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>& e)</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  {</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  std::stringstream message;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  message << <span class="stringliteral">"armnn::Exception ("</span> << e.<a class="code" href="classarmnn_1_1_exception.html#abf843cbb29dec939d0731e491bab6f70">what</a>() << <span class="stringliteral">") caught from optimize."</span>;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << message.str();</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  }</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> </div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="comment">// Loads the network into the runtime.</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <a class="code" href="namespacearmnn.html#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a> networkId;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  status = runtime->LoadNetwork(networkId, std::move(optimizedNet));</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keywordflow">if</span> (status == <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">armnn::Status::Failure</a>)</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  {</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"armnn::IRuntime: Failed to load network"</span>;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  }</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="comment">// Set up Network</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keyword">using</span> <a class="code" href="namespacearmnn.html#a280670a263dc4fd40491f6d0a2737f44">BindingPointInfo</a> = <a class="code" href="namespace_inference_model_internal.html#a9084adbf804022c874039ad40d1939e9">InferenceModelInternal::BindingPointInfo</a>;</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html">armnnDeserializer::BindingPointInfo</a>&</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  inputBindingInfo = armnnparser->GetNetworkInputBindingInfo(0, inputName);</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  std::pair<armnn::LayerBindingId, armnn::TensorInfo></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  m_InputBindingInfo(inputBindingInfo.<a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html#a663b3104ec65e4e08b5e37fb42942087">m_BindingId</a>, inputBindingInfo.<a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html#aa308d10e76e29f09e44a933a2d091a79">m_TensorInfo</a>);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  std::vector<BindingPointInfo> inputBindings = { m_InputBindingInfo };</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html">armnnDeserializer::BindingPointInfo</a>&</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  outputBindingInfo = armnnparser->GetNetworkOutputBindingInfo(0, outputName);</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> </div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  std::pair<armnn::LayerBindingId, armnn::TensorInfo></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  m_OutputBindingInfo(outputBindingInfo.<a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html#a663b3104ec65e4e08b5e37fb42942087">m_BindingId</a>, outputBindingInfo.<a class="code" href="structarmnn_deserializer_1_1_binding_point_info.html#aa308d10e76e29f09e44a933a2d091a79">m_TensorInfo</a>);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  std::vector<BindingPointInfo> outputBindings = { m_OutputBindingInfo };</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="comment">// Load model output labels</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keywordflow">if</span> (modelOutputLabelsPath.empty() || !boost::filesystem::exists(modelOutputLabelsPath) ||</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  !boost::filesystem::is_regular_file(modelOutputLabelsPath))</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  {</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Invalid model output labels path at "</span> << modelOutputLabelsPath;</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  }</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keyword">const</span> std::vector<armnnUtils::LabelCategoryNames> modelOutputLabels =</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <a class="code" href="_model_accuracy_tool-_armnn_8cpp.html#a0860c525c02a295d28f4fe0a0c0747c6">LoadModelOutputLabels</a>(modelOutputLabelsPath);</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="comment">// Parse begin and end image indices</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  std::vector<std::string> imageIndexStrs = <a class="code" href="namespacearmnn_utils.html#a71164960978af8b3820717bc92b9a322">armnnUtils::SplitBy</a>(validationRange, <span class="stringliteral">":"</span>);</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordtype">size_t</span> imageBegIndex;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordtype">size_t</span> imageEndIndex;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keywordflow">if</span> (imageIndexStrs.size() != 2)</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  {</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Invalid validation range specification: Invalid format "</span> << validationRange;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  }</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  {</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  imageBegIndex = std::stoul(imageIndexStrs[0]);</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  imageEndIndex = std::stoul(imageIndexStrs[1]);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  }</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::exception& e)</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  {</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Invalid validation range specification: "</span> << validationRange;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  }</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="comment">// Validate blacklist file if it's specified</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="keywordflow">if</span> (!blacklistPath.empty() &&</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  !(boost::filesystem::exists(blacklistPath) && boost::filesystem::is_regular_file(blacklistPath)))</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  {</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Invalid path to blacklist file at "</span> << blacklistPath;</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  }</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> </div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  path pathToDataDir(dataDir);</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keyword">const</span> map<std::string, std::string> imageNameToLabel = <a class="code" href="_model_accuracy_tool-_armnn_8cpp.html#a6bf14e4292511ab535ca9c3df0870185">LoadValidationImageFilenamesAndLabels</a>(</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  validationLabelPath, pathToDataDir.string(), imageBegIndex, imageEndIndex, blacklistPath);</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <a class="code" href="classarmnn_utils_1_1_model_accuracy_checker.html">armnnUtils::ModelAccuracyChecker</a> checker(imageNameToLabel, modelOutputLabels);</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keyword">using</span> <a class="code" href="_model_accuracy_checker_test_8cpp.html#a9eb69ebdaf4ceb8014e7c8a540266100">TContainer</a> = boost::variant<std::vector<float>, std::vector<int>, std::vector<uint8_t>>;</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn_1_1test.html#a8a678fb3a8864e31aeb77f857ae6fc43">ValidateDirectory</a>(dataDir))</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  {</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <a class="code" href="struct_inference_model_internal_1_1_params.html">InferenceModel<armnnDeserializer::IDeserializer, float>::Params</a> params;</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  params.<a class="code" href="struct_inference_model_internal_1_1_params.html#a4fa312cf0d60fbd3988a7c76ab8e2980">m_ModelPath</a> = modelPath;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  params.<a class="code" href="struct_inference_model_internal_1_1_params.html#a6bf2f586c403977d31c7d32d371918cf">m_IsModelBinary</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  params.<a class="code" href="struct_inference_model_internal_1_1_params.html#a2d54e6252c1c9a0e29f7706ba03b2b74">m_ComputeDevices</a> = computeDevice;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  params.<a class="code" href="struct_inference_model_internal_1_1_params.html#aad2ac35d4cb83ee4da9fad5fbcb907e0">m_InputBindings</a>.push_back(inputName);</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  params.<a class="code" href="struct_inference_model_internal_1_1_params.html#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>.push_back(outputName);</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keyword">using</span> TParser = <a class="code" href="classarmnn_deserializer_1_1_i_deserializer.html">armnnDeserializer::IDeserializer</a>;</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <a class="code" href="class_inference_model.html">InferenceModel<TParser, float></a> model(params, <span class="keyword">false</span>);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="comment">// Get input tensor information</span></div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& inputTensorInfo = model.<a class="code" href="class_inference_model.html#a9a28e0c17604e5a945409f994c020212">GetInputBindingInfo</a>().second;</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a>& inputTensorShape = inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a>& inputTensorDataType = inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>();</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> inputTensorDataLayout;</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keywordflow">if</span> (inputLayout == <span class="stringliteral">"NCHW"</span>)</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  {</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  inputTensorDataLayout = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  }</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (inputLayout == <span class="stringliteral">"NHWC"</span>)</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  {</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  inputTensorDataLayout = <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  }</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  {</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Invalid Data layout: "</span> << inputLayout;</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  }</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputTensorWidth =</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  inputTensorDataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a> ? inputTensorShape[3] : inputTensorShape[2];</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputTensorHeight =</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  inputTensorDataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a> ? inputTensorShape[2] : inputTensorShape[1];</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="comment">// Get output tensor info</span></div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputNumElements = model.<a class="code" href="class_inference_model.html#a8282dddf88e0deb3c414235e20a6cb2c">GetOutputSize</a>();</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="comment">// Check output tensor shape is valid</span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="keywordflow">if</span> (modelOutputLabels.size() != outputNumElements)</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  {</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Number of output elements: "</span> << outputNumElements</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  << <span class="stringliteral">" , mismatches the number of output labels: "</span> << modelOutputLabels.size();</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  }</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> </div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 1;</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="comment">// Get normalisation parameters</span></div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <a class="code" href="_image_tensor_generator_8hpp.html#a7599848540a5f43e977119c054b3563e">SupportedFrontend</a> modelFrontend;</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordflow">if</span> (modelFormat == <span class="stringliteral">"caffe"</span>)</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  {</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  modelFrontend = <a class="code" href="_image_tensor_generator_8hpp.html#a7599848540a5f43e977119c054b3563ea4df6064eb76f848def300474b7aef0da">SupportedFrontend::Caffe</a>;</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  }</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (modelFormat == <span class="stringliteral">"tensorflow"</span>)</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  {</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  modelFrontend = <a class="code" href="_image_tensor_generator_8hpp.html#a7599848540a5f43e977119c054b3563ea074dd699710da0ec1eb45f13b31788e3">SupportedFrontend::TensorFlow</a>;</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  }</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (modelFormat == <span class="stringliteral">"tflite"</span>)</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  {</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  modelFrontend = <a class="code" href="_image_tensor_generator_8hpp.html#a7599848540a5f43e977119c054b3563ea35120628a2097980f88fd49246124cae">SupportedFrontend::TFLite</a>;</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  }</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  {</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unsupported frontend: "</span> << modelFormat;</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  }</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keyword">const</span> <a class="code" href="struct_normalization_parameters.html">NormalizationParameters</a>& normParams = <a class="code" href="_image_tensor_generator_8hpp.html#a572494250ece8d94b68ea490d0bf46e4">GetNormalizationParameters</a>(modelFrontend, inputTensorDataType);</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& imageEntry : imageNameToLabel)</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  {</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keyword">const</span> std::string imageName = imageEntry.first;</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  std::cout << <span class="stringliteral">"Processing image: "</span> << imageName << <span class="stringliteral">"\n"</span>;</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> </div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  vector<TContainer> inputDataContainers;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  vector<TContainer> outputDataContainers;</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keyword">auto</span> imagePath = pathToDataDir / boost::filesystem::path(imageName);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordflow">switch</span> (inputTensorDataType)</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  {</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>:</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  inputDataContainers.push_back(</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <a class="code" href="_image_tensor_generator_8hpp.html#ac1e8e68c74e5d1c8fd19a91a68de3cb7">PrepareImageTensor<int></a>(imagePath.string(),</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  inputTensorWidth, inputTensorHeight,</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  normParams,</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  batchSize,</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  inputTensorDataLayout));</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  outputDataContainers = { vector<int>(outputNumElements) };</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>:</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  inputDataContainers.push_back(</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <a class="code" href="_image_tensor_generator_8hpp.html#ac372cd2b257f33f29999217e1d2d8a37">PrepareImageTensor<uint8_t></a>(imagePath.string(),</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  inputTensorWidth, inputTensorHeight,</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  normParams,</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  batchSize,</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  inputTensorDataLayout));</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  outputDataContainers = { vector<uint8_t>(outputNumElements) };</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>:</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  inputDataContainers.push_back(</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <a class="code" href="_image_tensor_generator_8hpp.html#affacfe95f011fce3b897b2745880f82a">PrepareImageTensor<float></a>(imagePath.string(),</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  inputTensorWidth, inputTensorHeight,</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  normParams,</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  batchSize,</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  inputTensorDataLayout));</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  outputDataContainers = { vector<float>(outputNumElements) };</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  }</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  status = runtime->EnqueueWorkload(networkId,</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="namespacearmnn_utils.html#ad5310a199d4969927169ed084b1f6c28">armnnUtils::MakeInputTensors</a>(inputBindings, inputDataContainers),</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <a class="code" href="namespacearmnn_utils.html#ad4efd5a7fa660df5246466d83517220d">armnnUtils::MakeOutputTensors</a>(outputBindings, outputDataContainers));</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> </div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">if</span> (status == <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">armnn::Status::Failure</a>)</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  {</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"armnn::IRuntime: Failed to enqueue workload for image: "</span> << imageName;</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  }</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> </div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  checker.AddImageResult<<a class="code" href="_model_accuracy_checker_test_8cpp.html#a9eb69ebdaf4ceb8014e7c8a540266100">TContainer</a>>(imageName, outputDataContainers);</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  }</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  }</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  {</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  }</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span> </div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 1; i <= 5; ++i)</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  {</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  std::cout << <span class="stringliteral">"Top "</span> << i << <span class="stringliteral">" Accuracy: "</span> << checker.GetAccuracy(i) << <span class="stringliteral">"%"</span> << <span class="stringliteral">"\n"</span>;</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  }</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span> </div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Accuracy Tool ran successfully!"</span>;</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  }</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordflow">catch</span> (<a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a> <span class="keyword">const</span> & e)</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  {</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="comment">// Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an</span></div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="comment">// exception of type std::length_error.</span></div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="comment">// Using stderr instead in this context as there is no point in nesting try-catch blocks here.</span></div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  std::cerr << <span class="stringliteral">"Armnn Error: "</span> << e.<a class="code" href="classarmnn_1_1_exception.html#abf843cbb29dec939d0731e491bab6f70">what</a>() << std::endl;</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  }</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::exception & e)</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  {</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="comment">// Coverity fix: various boost exceptions can be thrown by methods called by this test.</span></div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  std::cerr << <span class="stringliteral">"WARNING: ModelAccuracyTool-Armnn: An error has occurred when running the "</span></div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="stringliteral">"Accuracy Tool: "</span> << e.what() << std::endl;</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  }</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span> }</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> </div><div class="line"><a name="l00388"></a><span class="lineno"><a class="line" href="_model_accuracy_tool-_armnn_8cpp.html#a6bf14e4292511ab535ca9c3df0870185"> 388</a></span> map<std::string, std::string> <a class="code" href="_model_accuracy_tool-_armnn_8cpp.html#a6bf14e4292511ab535ca9c3df0870185">LoadValidationImageFilenamesAndLabels</a>(<span class="keyword">const</span> <span class="keywordtype">string</span>& validationLabelPath,</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keyword">const</span> <span class="keywordtype">string</span>& imageDirectoryPath,</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keywordtype">size_t</span> begIndex,</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="keywordtype">size_t</span> endIndex,</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="keyword">const</span> <span class="keywordtype">string</span>& blacklistPath)</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> {</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="comment">// Populate imageFilenames with names of all .JPEG, .PNG images</span></div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  std::vector<std::string> imageFilenames;</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& imageEntry :</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  boost::make_iterator_range(boost::filesystem::directory_iterator(boost::filesystem::path(imageDirectoryPath))))</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  {</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  boost::filesystem::path imagePath = imageEntry.path();</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  std::string imageExtension = boost::to_upper_copy<std::string>(imagePath.extension().string());</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keywordflow">if</span> (boost::filesystem::is_regular_file(imagePath) && (imageExtension == <span class="stringliteral">".JPEG"</span> || imageExtension == <span class="stringliteral">".PNG"</span>))</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  {</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  imageFilenames.push_back(imagePath.filename().string());</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  }</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  }</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  <span class="keywordflow">if</span> (imageFilenames.empty())</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  {</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"No image file (JPEG, PNG) found at "</span> + imageDirectoryPath);</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> </div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <span class="comment">// Sort the image filenames lexicographically</span></div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  std::sort(imageFilenames.begin(), imageFilenames.end());</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>  std::cout << imageFilenames.size() << <span class="stringliteral">" images found at "</span> << imageDirectoryPath << std::endl;</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> </div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="comment">// Get default end index</span></div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keywordflow">if</span> (begIndex < 1 || endIndex > imageFilenames.size())</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>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"Invalid image index range"</span>);</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  }</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  endIndex = endIndex == 0 ? imageFilenames.size() : endIndex;</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keywordflow">if</span> (begIndex > endIndex)</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>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"Invalid image index range"</span>);</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  }</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> </div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <span class="comment">// Load blacklist if there is one</span></div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  std::vector<unsigned int> blacklist;</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="keywordflow">if</span> (!blacklistPath.empty())</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  {</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  std::ifstream blacklistFile(blacklistPath);</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index;</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keywordflow">while</span> (blacklistFile >> index)</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  {</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  blacklist.push_back(index);</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  }</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  }</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> </div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="comment">// Load ground truth labels and pair them with corresponding image names</span></div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  std::string classification;</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  map<std::string, std::string> imageNameToLabel;</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  ifstream infile(validationLabelPath);</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="keywordtype">size_t</span> imageIndex = begIndex;</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="keywordtype">size_t</span> blacklistIndexCount = 0;</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="keywordflow">while</span> (std::getline(infile, classification))</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="keywordflow">if</span> (imageIndex > endIndex)</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  {</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <span class="keywordflow">break</span>;</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>  <span class="comment">// If current imageIndex is included in blacklist, skip the current image</span></div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="keywordflow">if</span> (blacklistIndexCount < blacklist.size() && imageIndex == blacklist[blacklistIndexCount])</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  {</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  ++imageIndex;</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  ++blacklistIndexCount;</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  }</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  imageNameToLabel.insert(std::pair<std::string, std::string>(imageFilenames[imageIndex - 1], classification));</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  ++imageIndex;</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>  std::cout << blacklistIndexCount << <span class="stringliteral">" images blacklisted"</span> << std::endl;</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  std::cout << imageIndex - begIndex - blacklistIndexCount << <span class="stringliteral">" images to be loaded"</span> << std::endl;</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keywordflow">return</span> imageNameToLabel;</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> </div><div class="line"><a name="l00466"></a><span class="lineno"><a class="line" href="_model_accuracy_tool-_armnn_8cpp.html#a0860c525c02a295d28f4fe0a0c0747c6"> 466</a></span> std::vector<armnnUtils::LabelCategoryNames> <a class="code" href="_model_accuracy_tool-_armnn_8cpp.html#a0860c525c02a295d28f4fe0a0c0747c6">LoadModelOutputLabels</a>(<span class="keyword">const</span> std::string& modelOutputLabelsPath)</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span> {</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  std::vector<armnnUtils::LabelCategoryNames> modelOutputLabels;</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  ifstream modelOutputLablesFile(modelOutputLabelsPath);</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  std::string line;</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keywordflow">while</span> (std::getline(modelOutputLablesFile, line))</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  {</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <a class="code" href="namespacearmnn_utils.html#ab175d8bf2482d5a39c2331d1f0ddcece">armnnUtils::LabelCategoryNames</a> tokens = <a class="code" href="namespacearmnn_utils.html#a71164960978af8b3820717bc92b9a322">armnnUtils::SplitBy</a>(line, <span class="stringliteral">":"</span>);</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <a class="code" href="namespacearmnn_utils.html#ab175d8bf2482d5a39c2331d1f0ddcece">armnnUtils::LabelCategoryNames</a> predictionCategoryNames = <a class="code" href="namespacearmnn_utils.html#a71164960978af8b3820717bc92b9a322">armnnUtils::SplitBy</a>(tokens.back(), <span class="stringliteral">","</span>);</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  std::transform(predictionCategoryNames.begin(), predictionCategoryNames.end(), predictionCategoryNames.begin(),</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  [](<span class="keyword">const</span> std::string& category) { <span class="keywordflow">return</span> <a class="code" href="namespacearmnn_utils.html#a24f7c8ffa12c4c91bc2cecd4d329add4">armnnUtils::Strip</a>(category); });</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  modelOutputLabels.push_back(predictionCategoryNames);</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">return</span> modelOutputLabels;</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span> }</div><div class="ttc" id="namespacearmnn_utils_html_ad4efd5a7fa660df5246466d83517220d"><div class="ttname"><a href="namespacearmnn_utils.html#ad4efd5a7fa660df5246466d83517220d">armnnUtils::MakeOutputTensors</a></div><div class="ttdeci">armnn::OutputTensors MakeOutputTensors(const std::vector< armnn::BindingPointInfo > &outputBindings, std::vector< TContainer > &outputDataContainers)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_i_o_utils_8hpp_source.html#l00056">TensorIOUtils.hpp:56</a></div></div>
+<div class="ttc" id="namespacearmnn_utils_html_a71164960978af8b3820717bc92b9a322"><div class="ttname"><a href="namespacearmnn_utils.html#a71164960978af8b3820717bc92b9a322">armnnUtils::SplitBy</a></div><div class="ttdeci">std::vector< std::string > SplitBy(const std::string &originalString, const std::string &delimiter, bool includeEmptyToken)</div><div class="ttdef"><b>Definition:</b> <a href="_model_accuracy_checker_8cpp_source.html#l00041">ModelAccuracyChecker.cpp:41</a></div></div>
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+<div class="ttc" id="classarmnn_1_1_backend_registry_html_ae1de2f7ca1db17f45f97155e239b8b45"><div class="ttname"><a href="classarmnn_1_1_backend_registry.html#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.html#l00076">BackendRegistry.cpp:76</a></div></div>
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+<div class="ttc" id="namespacearmnn_html_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.html#l00807">Network.cpp:807</a></div></div>
+<div class="ttc" id="class_inference_model_html"><div class="ttname"><a href="class_inference_model.html">InferenceModel</a></div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.html#l00316">InferenceModel.hpp:316</a></div></div>
+<div class="ttc" id="classarmnn_1_1_optional_html"><div class="ttname"><a href="classarmnn_1_1_optional.html">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00270">Optional.hpp:270</a></div></div>
+<div class="ttc" id="namespace_inference_model_internal_html_a9084adbf804022c874039ad40d1939e9"><div class="ttname"><a href="namespace_inference_model_internal.html#a9084adbf804022c874039ad40d1939e9">InferenceModelInternal::BindingPointInfo</a></div><div class="ttdeci">armnn::BindingPointInfo BindingPointInfo</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.html#l00078">InferenceModel.hpp:78</a></div></div>
+<div class="ttc" id="_image_tensor_generator_8hpp_html_ac372cd2b257f33f29999217e1d2d8a37"><div class="ttname"><a href="_image_tensor_generator_8hpp.html#ac372cd2b257f33f29999217e1d2d8a37">PrepareImageTensor< uint8_t ></a></div><div class="ttdeci">std::vector< uint8_t > PrepareImageTensor< uint8_t >(const std::string &imagePath, unsigned int newWidth, unsigned int newHeight, const NormalizationParameters &normParams, unsigned int batchSize, const armnn::DataLayout &outputLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_image_tensor_generator_8hpp_source.html#l00148">ImageTensorGenerator.hpp:148</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
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+<div class="ttc" id="_i_deserializer_8hpp_html"><div class="ttname"><a href="_i_deserializer_8hpp.html">IDeserializer.hpp</a></div></div>
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