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+<a href="_tf_lite_mobile_net_quantized_softmax-_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>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="preprocessor">#include &quot;../InferenceTest.hpp&quot;</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &quot;../ImagePreprocessor.hpp&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_i_tf_lite_parser_8hpp.html">armnnTfLiteParser/ITfLiteParser.hpp</a>&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;</div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn_tf_lite_parser.html">armnnTfLiteParser</a>;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;</div><div class="line"><a name="l00011"></a><span class="lineno"><a class="line" href="_tf_lite_mobile_net_quantized_softmax-_armnn_8cpp.html#a0ddf1224851353fc92bfbff6f499fa97">   11</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="_tf_lite_mobile_net_quantized_softmax-_armnn_8cpp.html#a0ddf1224851353fc92bfbff6f499fa97">main</a>(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>* argv[])</div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;{</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;    <span class="keywordtype">int</span> retVal = EXIT_FAILURE;</div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;    <span class="keywordflow">try</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;    {</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;        <span class="comment">// Coverity fix: The following code may throw an exception of type std::length_error.</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;        <span class="comment">// The model we are using incorrectly classifies the images</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;        <span class="comment">// But can still be used for benchmarking the layers.</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;        std::vector&lt;ImageSet&gt; imageSet =</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;                {</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;                        {<span class="stringliteral">&quot;Dog.jpg&quot;</span>, 789},</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;                        {<span class="stringliteral">&quot;Cat.jpg&quot;</span>, 592},</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;                        {<span class="stringliteral">&quot;shark.jpg&quot;</span>, 755},</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;                };</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;        <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputTensorShape({ 1, 128, 128, 3 });</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;        <span class="keyword">using</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> = uint8_t;</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;        <span class="keyword">using</span> DatabaseType = <a class="code" href="class_image_preprocessor.html">ImagePreprocessor&lt;DataType&gt;</a>;</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;        <span class="keyword">using</span> ParserType = <a class="code" href="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser.html">armnnTfLiteParser::ITfLiteParser</a>;</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;        <span class="keyword">using</span> ModelType = <a class="code" href="class_inference_model.html">InferenceModel&lt;ParserType, DataType&gt;</a>;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;        <span class="comment">// Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.</span></div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;        retVal = <a class="code" href="namespacearmnn_1_1test.html#a47dfae02e22fcca1b6b784873b0328d9">armnn::test::ClassifierInferenceTestMain</a>&lt;DatabaseType,</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;                ParserType&gt;(</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;                argc, argv,</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;                <span class="stringliteral">&quot;mobilenet_v1_0.25_128_quant.tflite&quot;</span>, <span class="comment">// model name</span></div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;                <span class="keyword">true</span>,                      <span class="comment">// model is binary</span></div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;                <span class="stringliteral">&quot;input&quot;</span>,      <span class="comment">// input tensor name</span></div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;                <span class="stringliteral">&quot;MobilenetV1/Predictions/Reshape_1&quot;</span>,        <span class="comment">// output tensor name</span></div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;                { 0, 1, 2 },               <span class="comment">// test images to test with as above</span></div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;                [&amp;imageSet](<span class="keyword">const</span> <span class="keywordtype">char</span>* dataDir, <span class="keyword">const</span> ModelType &amp;) {</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;                    <span class="comment">// we need to get the input quantization parameters from</span></div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;                    <span class="comment">// the parsed model</span></div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;                    <span class="keywordflow">return</span> DatabaseType(</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;                            dataDir,</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;                            128,</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;                            128,</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;                            imageSet,</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;                            1,</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;                            {{0, 0, 0}},</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;                            {{1, 1, 1}},</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;                            DatabaseType::DataFormat::NCHW,</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;                            1);</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;                },</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;                &amp;inputTensorShape);</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    }</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::exception&amp; e)</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    {</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;        <span class="comment">// Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an</span></div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;        <span class="comment">// exception of type std::length_error.</span></div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;        <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="l00063"></a><span class="lineno">   63</span>&#160;        std::cerr &lt;&lt; <span class="stringliteral">&quot;WARNING: &quot;</span> &lt;&lt; *argv &lt;&lt; <span class="stringliteral">&quot;: An error has occurred when running &quot;</span></div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;                                             <span class="stringliteral">&quot;the classifier inference tests: &quot;</span> &lt;&lt; e.what() &lt;&lt; std::endl;</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    }</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="keywordflow">return</span> retVal;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;}</div><div class="ttc" id="namespacearmnn_tf_lite_parser_html"><div class="ttname"><a href="namespacearmnn_tf_lite_parser.html">armnnTfLiteParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_tf_lite_parser_8hpp_source.html#l00017">ITfLiteParser.hpp:17</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="namespacearmnn_1_1test_html_a47dfae02e22fcca1b6b784873b0328d9"><div class="ttname"><a href="namespacearmnn_1_1test.html#a47dfae02e22fcca1b6b784873b0328d9">armnn::test::ClassifierInferenceTestMain</a></div><div class="ttdeci">int ClassifierInferenceTestMain(int argc, char *argv[], const char *modelFilename, bool isModelBinary, const char *inputBindingName, const char *outputBindingName, const std::vector&lt; unsigned int &gt; &amp;defaultTestCaseIds, TConstructDatabaseCallable constructDatabase, const armnn::TensorShape *inputTensorShape=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_inference_test_8inl_source.html#l00352">InferenceTest.inl:352</a></div></div>
+<div class="ttc" id="_tf_lite_mobile_net_quantized_softmax-_armnn_8cpp_html_a0ddf1224851353fc92bfbff6f499fa97"><div class="ttname"><a href="_tf_lite_mobile_net_quantized_softmax-_armnn_8cpp.html#a0ddf1224851353fc92bfbff6f499fa97">main</a></div><div class="ttdeci">int main(int argc, char *argv[])</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_mobile_net_quantized_softmax-_armnn_8cpp_source.html#l00011">TfLiteMobileNetQuantizedSoftmax-Armnn.cpp:11</a></div></div>
+<div class="ttc" id="_i_tf_lite_parser_8hpp_html"><div class="ttname"><a href="_i_tf_lite_parser_8hpp.html">ITfLiteParser.hpp</a></div></div>
+<div class="ttc" id="class_image_preprocessor_html"><div class="ttname"><a href="class_image_preprocessor.html">ImagePreprocessor</a></div><div class="ttdef"><b>Definition:</b> <a href="_image_preprocessor_8hpp_source.html#l00020">ImagePreprocessor.hpp:20</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00032">Types.hpp:32</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser_html"><div class="ttname"><a href="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser.html">armnnTfLiteParser::ITfLiteParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_tf_lite_parser_8hpp_source.html#l00025">ITfLiteParser.hpp:25</a></div></div>
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