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<a href="graph__squeezenet_8cpp.xhtml">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 (c) 2017-2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="graph_8h.xhtml">arm_compute/graph.h</a>&quot;</span></div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_toolchain_support_8h.xhtml">support/ToolchainSupport.h</a>&quot;</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_graph_utils_8h.xhtml">utils/GraphUtils.h</a>&quot;</span></div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="utils_2_utils_8h.xhtml">utils/Utils.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="preprocessor">#include &lt;cstdlib&gt;</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="preprocessor">#include &lt;tuple&gt;</span></div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearm__compute_1_1utils.xhtml">arm_compute::utils</a>;</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearm__compute_1_1graph_1_1frontend.xhtml">arm_compute::graph::frontend</a>;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearm__compute_1_1graph__utils.xhtml">arm_compute::graph_utils</a>;</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearm__compute_1_1logging.xhtml">arm_compute::logging</a>;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="keyword">class </span>GraphSqueezenetExample : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1utils_1_1_example.xhtml">Example</a></div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;{</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    <span class="keywordtype">void</span> do_setup(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span> **argv)<span class="keyword"> override</span></div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="keyword">    </span>{</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;        std::string data_path; <span class="comment">/* Path to the trainable data */</span></div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;        std::string image;     <span class="comment">/* Image data */</span></div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;        std::string label;     <span class="comment">/* Label data */</span></div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;        <span class="comment">// Create a preprocessor object</span></div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;        <span class="keyword">const</span> std::array&lt;float, 3&gt; mean_rgb{ { 122.68f, 116.67f, 104.01f } };</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;        std::unique_ptr&lt;IPreprocessor&gt; preprocessor = arm_compute::support::cpp14::make_unique&lt;CaffePreproccessor&gt;(mean_rgb);</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;        <span class="comment">// Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON</span></div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">int</span>    target         = argc &gt; 1 ? std::strtol(argv[1], <span class="keyword">nullptr</span>, 10) : 0;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;        <a class="code" href="namespacearm__compute_1_1graph.xhtml#a31488d29805a596498c0234ae392d35d">Target</a>       target_hint    = <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#ab6dc388200717b5fae17342af13f5e41">set_target_hint</a>(target);</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;        <a class="code" href="namespacearm__compute_1_1graph.xhtml#ac85a46f3ebd3ab09f576a994ac2dce11">FastMathHint</a> fast_math_hint = FastMathHint::DISABLED;</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">// Parse arguments</span></div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;        <span class="keywordflow">if</span>(argc &lt; 2)</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;        {</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;            <span class="comment">// Print help</span></div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;Usage: &quot;</span> &lt;&lt; argv[0] &lt;&lt; <span class="stringliteral">&quot; [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n&quot;</span>;</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;No data folder provided: using random values\n\n&quot;</span>;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;        }</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span>(argc == 2)</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;        {</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;Usage: &quot;</span> &lt;&lt; argv[0] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[1] &lt;&lt; <span class="stringliteral">&quot; [path_to_data] [image] [labels] [fast_math_hint]\n\n&quot;</span>;</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;No data folder provided: using random values\n\n&quot;</span>;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        }</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span>(argc == 3)</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        {</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;            data_path = argv[2];</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;Usage: &quot;</span> &lt;&lt; argv[0] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[1] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[2] &lt;&lt; <span class="stringliteral">&quot; [image] [labels] [fast_math_hint]\n\n&quot;</span>;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;No image provided: using random values\n\n&quot;</span>;</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;        }</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span>(argc == 4)</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;        {</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;            data_path = argv[2];</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;            image     = argv[3];</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;Usage: &quot;</span> &lt;&lt; argv[0] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[1] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[2] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[3] &lt;&lt; <span class="stringliteral">&quot; [labels] [fast_math_hint]\n\n&quot;</span>;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;No text file with labels provided: skipping output accessor\n\n&quot;</span>;</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;        }</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span>(argc == 5)</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;        {</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;            data_path = argv[2];</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;            image     = argv[3];</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;            label     = argv[4];</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;Usage: &quot;</span> &lt;&lt; argv[0] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[1] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[2] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[3] &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; argv[4] &lt;&lt; <span class="stringliteral">&quot; [fast_math_hint]\n\n&quot;</span>;</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ssarm__compute_1_1graph_1_1frontend_1_1_activation_layer.xhtml">ActivationLayer</a>(ActivationLayerInfo(<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaad346bb4679d29be241279f15d7795c1c">ActivationLayerInfo::ActivationFunction::RELU</a>));</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        graph &lt;&lt; get_expand_fire_node(data_path, <span class="stringliteral">&quot;fire7&quot;</span>, 192U, 192U);</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;        graph &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_convolution_layer.xhtml">ConvolutionLayer</a>(</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;                  1U, 1U, 64U,</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;                  <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, <span class="stringliteral">&quot;/cnn_data/squeezenet_v1.0_model/fire8_squeeze1x1_w.npy&quot;</span>),</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;                  <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, <span class="stringliteral">&quot;/cnn_data/squeezenet_v1.0_model/fire8_squeeze1x1_b.npy&quot;</span>),</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;                  PadStrideInfo(1, 1, 0, 0))</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;              &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_activation_layer.xhtml">ActivationLayer</a>(ActivationLayerInfo(<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaad346bb4679d29be241279f15d7795c1c">ActivationLayerInfo::ActivationFunction::RELU</a>));</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;        graph &lt;&lt; get_expand_fire_node(data_path, <span class="stringliteral">&quot;fire8&quot;</span>, 256U, 256U);</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;        graph &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_pooling_layer.xhtml">PoolingLayer</a>(PoolingLayerInfo(<a class="code" href="namespacearm__compute.xhtml#adf2ced65e536375a1c96425d9fced858a26a4b44a837bf97b972628509912b4a5">PoolingType::MAX</a>, 3, PadStrideInfo(2, 2, 0, 0, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa5bdce8e6d9dc3efbbd31e90a8a181dff">DimensionRoundingType::CEIL</a>)))</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;              &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_convolution_layer.xhtml">ConvolutionLayer</a>(</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;                  1U, 1U, 64U,</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;                  <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, <span class="stringliteral">&quot;/cnn_data/squeezenet_v1.0_model/fire9_squeeze1x1_w.npy&quot;</span>),</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;                  <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, <span class="stringliteral">&quot;/cnn_data/squeezenet_v1.0_model/fire9_squeeze1x1_b.npy&quot;</span>),</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;                  PadStrideInfo(1, 1, 0, 0))</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;              &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_activation_layer.xhtml">ActivationLayer</a>(ActivationLayerInfo(<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaad346bb4679d29be241279f15d7795c1c">ActivationLayerInfo::ActivationFunction::RELU</a>));</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;        graph &lt;&lt; get_expand_fire_node(data_path, <span class="stringliteral">&quot;fire9&quot;</span>, 256U, 256U);</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;        graph &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_convolution_layer.xhtml">ConvolutionLayer</a>(</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;                  1U, 1U, 1000U,</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;                  <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, <span class="stringliteral">&quot;/cnn_data/squeezenet_v1.0_model/conv10_w.npy&quot;</span>),</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;                  <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, <span class="stringliteral">&quot;/cnn_data/squeezenet_v1.0_model/conv10_b.npy&quot;</span>),</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;                  PadStrideInfo(1, 1, 0, 0))</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;              &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_activation_layer.xhtml">ActivationLayer</a>(ActivationLayerInfo(<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaad346bb4679d29be241279f15d7795c1c">ActivationLayerInfo::ActivationFunction::RELU</a>))</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;              &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_pooling_layer.xhtml">PoolingLayer</a>(PoolingLayerInfo(<a class="code" href="namespacearm__compute.xhtml#a9172da722f0a434e5cc07c0a3c115d93afcefd647d6a866603c627b11347c707a">PoolingType::AVG</a>))</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;              &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_flatten_layer.xhtml">FlattenLayer</a>()</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;              &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_softmax_layer.xhtml">SoftmaxLayer</a>()</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;              &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_output_layer.xhtml">OutputLayer</a>(<a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#aaf0c8eff756108c8bb23aecf51d44f79">get_output_accessor</a>(label, 5));</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;        <span class="comment">// Finalize graph</span></div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;        GraphConfig config;</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;        config.use_tuner = (target == 2);</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;        graph.finalize(target_hint, config);</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    }</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    <span class="keywordtype">void</span> do_run()<span class="keyword"> override</span></div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;<span class="keyword">    </span>{</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;        <span class="comment">// Run graph</span></div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;        graph.run();</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    }</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;    <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_stream.xhtml">Stream</a> graph{ 0, <span class="stringliteral">&quot;SqueezeNetV1&quot;</span> };</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;    <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_branch_layer.xhtml">BranchLayer</a> get_expand_fire_node(<span class="keyword">const</span> std::string &amp;data_path, std::string &amp;&amp;param_path, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> expand1_filt, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> expand3_filt)</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;    {</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;        std::string total_path = <span class="stringliteral">&quot;/cnn_data/squeezenet_v1.0_model/&quot;</span> + param_path + <span class="stringliteral">&quot;_&quot;</span>;</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;        <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_sub_stream.xhtml">SubStream</a>   i_a(graph);</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;        i_a &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_convolution_layer.xhtml">ConvolutionLayer</a>(</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;                1U, 1U, expand1_filt,</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;                <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, total_path + <span class="stringliteral">&quot;expand1x1_w.npy&quot;</span>),</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;                <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, total_path + <span class="stringliteral">&quot;expand1x1_b.npy&quot;</span>),</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;                PadStrideInfo(1, 1, 0, 0))</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;            &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_activation_layer.xhtml">ActivationLayer</a>(ActivationLayerInfo(<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaad346bb4679d29be241279f15d7795c1c">ActivationLayerInfo::ActivationFunction::RELU</a>));</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;        <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_sub_stream.xhtml">SubStream</a> i_b(graph);</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;        i_b &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_convolution_layer.xhtml">ConvolutionLayer</a>(</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;                3U, 3U, expand3_filt,</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;                <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, total_path + <span class="stringliteral">&quot;expand3x3_w.npy&quot;</span>),</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;                <a class="code" href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">get_weights_accessor</a>(data_path, total_path + <span class="stringliteral">&quot;expand3x3_b.npy&quot;</span>),</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;                PadStrideInfo(1, 1, 1, 1))</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;            &lt;&lt; <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_activation_layer.xhtml">ActivationLayer</a>(ActivationLayerInfo(<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaad346bb4679d29be241279f15d7795c1c">ActivationLayerInfo::ActivationFunction::RELU</a>));</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;        <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1graph_1_1frontend_1_1_branch_layer.xhtml">BranchLayer</a>(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b));</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    }</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;};</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;</div><div class="line"><a name="l00223"></a><span class="lineno"><a class="line" href="graph__squeezenet_8cpp.xhtml#a3c04138a5bfe5d72780bb7e82a18e627">  223</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="graph__squeezenet_8cpp.xhtml#a3c04138a5bfe5d72780bb7e82a18e627">main</a>(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span> **argv)</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;{</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;    <span class="keywordflow">return</span> arm_compute::utils::run_example&lt;GraphSqueezenetExample&gt;(argc, argv);</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_branch_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_branch_layer.xhtml">arm_compute::graph::frontend::BranchLayer</a></div><div class="ttdoc">Branch Layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layers_8h_source.xhtml#l00435">Layers.h:435</a></div></div>
 121 <div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_pooling_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_pooling_layer.xhtml">arm_compute::graph::frontend::PoolingLayer</a></div><div class="ttdoc">Pooling Layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layers_8h_source.xhtml#l00336">Layers.h:336</a></div></div>
 122 <div class="ttc" id="namespacearm__compute_1_1graph__utils_xhtml_ab6dc388200717b5fae17342af13f5e41"><div class="ttname"><a href="namespacearm__compute_1_1graph__utils.xhtml#ab6dc388200717b5fae17342af13f5e41">arm_compute::graph_utils::set_target_hint</a></div><div class="ttdeci">graph::Target set_target_hint(int target)</div><div class="ttdoc">Utility function to return the TargetHint. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8h_source.xhtml#l00370">GraphUtils.h:370</a></div></div>
 123 <div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_sub_stream_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_sub_stream.xhtml">arm_compute::graph::frontend::SubStream</a></div><div class="ttdoc">Sub stream class. </div><div class="ttdef"><b>Definition:</b> <a href="_sub_stream_8h_source.xhtml#l00047">SubStream.h:47</a></div></div>
 124 <div class="ttc" id="_toolchain_support_8h_xhtml"><div class="ttname"><a href="_toolchain_support_8h.xhtml">ToolchainSupport.h</a></div></div>
 125 <div class="ttc" id="namespacearm__compute_xhtml_a1fece1bd804e64f39f602d1c3969849aa5bdce8e6d9dc3efbbd31e90a8a181dff"><div class="ttname"><a href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa5bdce8e6d9dc3efbbd31e90a8a181dff">arm_compute::DimensionRoundingType::CEIL</a></div><div class="ttdoc">Ceil rounding. </div></div>
 126 <div class="ttc" id="graph__squeezenet_8cpp_xhtml_a3c04138a5bfe5d72780bb7e82a18e627"><div class="ttname"><a href="graph__squeezenet_8cpp.xhtml#a3c04138a5bfe5d72780bb7e82a18e627">main</a></div><div class="ttdeci">int main(int argc, char **argv)</div><div class="ttdoc">Main program for Squeezenet v1.0. </div><div class="ttdef"><b>Definition:</b> <a href="graph__squeezenet_8cpp_source.xhtml#l00223">graph_squeezenet.cpp:223</a></div></div>
 127 <div class="ttc" id="classarm__compute_1_1_activation_layer_info_xhtml_a56297e0f7b215eea46c818cb7528d9eaad346bb4679d29be241279f15d7795c1c"><div class="ttname"><a href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaad346bb4679d29be241279f15d7795c1c">arm_compute::ActivationLayerInfo::ActivationFunction::RELU</a></div><div class="ttdoc">Rectifier (  ) </div></div>
 128 <div class="ttc" id="namespacearm__compute_1_1graph__utils_xhtml_aaf0c8eff756108c8bb23aecf51d44f79"><div class="ttname"><a href="namespacearm__compute_1_1graph__utils.xhtml#aaf0c8eff756108c8bb23aecf51d44f79">arm_compute::graph_utils::get_output_accessor</a></div><div class="ttdeci">std::unique_ptr&lt; graph::ITensorAccessor &gt; get_output_accessor(const std::string &amp;labels_path, size_t top_n=5, std::ostream &amp;output_stream=std::cout)</div><div class="ttdoc">Generates appropriate output accessor according to the specified labels_path. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8h_source.xhtml#l00330">GraphUtils.h:330</a></div></div>
 129 <div class="ttc" id="utils_2_utils_8h_xhtml"><div class="ttname"><a href="utils_2_utils_8h.xhtml">Utils.h</a></div></div>
 130 <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel </div></div>
 131 <div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_input_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_input_layer.xhtml">arm_compute::graph::frontend::InputLayer</a></div><div class="ttdoc">Input Layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layers_8h_source.xhtml#l00045">Layers.h:45</a></div></div>
 132 <div class="ttc" id="_graph_utils_8h_xhtml"><div class="ttname"><a href="_graph_utils_8h.xhtml">GraphUtils.h</a></div></div>
 133 <div class="ttc" id="graph_8h_xhtml"><div class="ttname"><a href="graph_8h.xhtml">graph.h</a></div></div>
 134 <div class="ttc" id="classarm__compute_1_1utils_1_1_example_xhtml"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_example.xhtml">arm_compute::utils::Example</a></div><div class="ttdoc">Abstract Example class. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00062">Utils.h:62</a></div></div>
 135 <div class="ttc" id="namespacearm__compute_1_1graph__utils_xhtml_a9984cc47279cdb732b7b83caf0627de6"><div class="ttname"><a href="namespacearm__compute_1_1graph__utils.xhtml#a9984cc47279cdb732b7b83caf0627de6">arm_compute::graph_utils::get_input_accessor</a></div><div class="ttdeci">std::unique_ptr&lt; graph::ITensorAccessor &gt; get_input_accessor(const std::string &amp;ppm_path, std::unique_ptr&lt; IPreprocessor &gt; preprocessor=nullptr, bool bgr=true)</div><div class="ttdoc">Generates appropriate input accessor according to the specified ppm_path. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8h_source.xhtml#l00299">GraphUtils.h:299</a></div></div>
 136 <div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_activation_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_activation_layer.xhtml">arm_compute::graph::frontend::ActivationLayer</a></div><div class="ttdoc">Activation Layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layers_8h_source.xhtml#l00094">Layers.h:94</a></div></div>
 137 <div class="ttc" id="namespacearm__compute_1_1graph_xhtml_a31488d29805a596498c0234ae392d35d"><div class="ttname"><a href="namespacearm__compute_1_1graph.xhtml#a31488d29805a596498c0234ae392d35d">arm_compute::graph::Target</a></div><div class="ttdeci">Target</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2graph_2_types_8h_source.xhtml#l00084">Types.h:84</a></div></div>
 138 <div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_convolution_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_convolution_layer.xhtml">arm_compute::graph::frontend::ConvolutionLayer</a></div><div class="ttdoc">Convolution Layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layers_8h_source.xhtml#l00158">Layers.h:158</a></div></div>
 139 <div class="ttc" id="namespacearm__compute_1_1graph_xhtml_ac85a46f3ebd3ab09f576a994ac2dce11"><div class="ttname"><a href="namespacearm__compute_1_1graph.xhtml#ac85a46f3ebd3ab09f576a994ac2dce11">arm_compute::graph::FastMathHint</a></div><div class="ttdeci">FastMathHint</div><div class="ttdoc">Enable or disable fast math for Convolution layer. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2graph_2_types_8h_source.xhtml#l00118">Types.h:118</a></div></div>
 140 <div class="ttc" id="namespacearm__compute_1_1utils_xhtml"><div class="ttname"><a href="namespacearm__compute_1_1utils.xhtml">arm_compute::utils</a></div><div class="ttdef"><b>Definition:</b> <a href="_cast_8h_source.xhtml#l00031">Cast.h:31</a></div></div>
 141 <div class="ttc" id="namespacearm__compute_1_1graph__utils_xhtml"><div class="ttname"><a href="namespacearm__compute_1_1graph__utils.xhtml">arm_compute::graph_utils</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8h_source.xhtml#l00041">GraphUtils.h:41</a></div></div>
 142 <div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_softmax_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_softmax_layer.xhtml">arm_compute::graph::frontend::SoftmaxLayer</a></div><div class="ttdoc">Softmax Layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layers_8h_source.xhtml#l00411">Layers.h:411</a></div></div>
 143 <div class="ttc" id="namespacearm__compute_xhtml_a9172da722f0a434e5cc07c0a3c115d93afcefd647d6a866603c627b11347c707a"><div class="ttname"><a href="namespacearm__compute.xhtml#a9172da722f0a434e5cc07c0a3c115d93afcefd647d6a866603c627b11347c707a">arm_compute::PoolingType::AVG</a></div><div class="ttdoc">Average Pooling. </div></div>
 144 <div class="ttc" id="namespacearm__compute_1_1logging_xhtml"><div class="ttname"><a href="namespacearm__compute_1_1logging.xhtml">arm_compute::logging</a></div><div class="ttdef"><b>Definition:</b> <a href="_file_printer_8h_source.xhtml#l00033">FilePrinter.h:33</a></div></div>
 145 <div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_output_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_output_layer.xhtml">arm_compute::graph::frontend::OutputLayer</a></div><div class="ttdoc">Output Layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layers_8h_source.xhtml#l00070">Layers.h:70</a></div></div>
 146 <div class="ttc" id="namespacearm__compute_1_1graph__utils_xhtml_a30bee0b52a919bbcb1dc48b1b6546a16"><div class="ttname"><a href="namespacearm__compute_1_1graph__utils.xhtml#a30bee0b52a919bbcb1dc48b1b6546a16">arm_compute::graph_utils::get_weights_accessor</a></div><div class="ttdeci">std::unique_ptr&lt; graph::ITensorAccessor &gt; get_weights_accessor(const std::string &amp;path, const std::string &amp;data_file, DataLayout file_layout=DataLayout::NCHW)</div><div class="ttdoc">Generates appropriate weights accessor according to the specified path. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8h_source.xhtml#l00275">GraphUtils.h:275</a></div></div>
 147 <div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_stream_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_stream.xhtml">arm_compute::graph::frontend::Stream</a></div><div class="ttdoc">Stream frontend class to construct simple graphs in a stream fashion. </div><div class="ttdef"><b>Definition:</b> <a href="_stream_8h_source.xhtml#l00045">Stream.h:45</a></div></div>
 148 <div class="ttc" id="namespacearm__compute_1_1graph_1_1frontend_xhtml"><div class="ttname"><a href="namespacearm__compute_1_1graph_1_1frontend.xhtml">arm_compute::graph::frontend</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_layer_8h_source.xhtml#l00031">ILayer.h:31</a></div></div>
 149 <div class="ttc" id="namespacearm__compute_xhtml_adf2ced65e536375a1c96425d9fced858a26a4b44a837bf97b972628509912b4a5"><div class="ttname"><a href="namespacearm__compute.xhtml#adf2ced65e536375a1c96425d9fced858a26a4b44a837bf97b972628509912b4a5">arm_compute::NonLinearFilterFunction::MAX</a></div><div class="ttdoc">Non linear dilate. </div></div>
 150 <div class="ttc" id="classarm__compute_1_1graph_1_1frontend_1_1_flatten_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1frontend_1_1_flatten_layer.xhtml">arm_compute::graph::frontend::FlattenLayer</a></div><div class="ttdoc">Flatten Layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layers_8h_source.xhtml#l00264">Layers.h:264</a></div></div>
 151 </div><!-- fragment --></div><!-- contents -->
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 155   <ul>
 156     <li class="navelem"><a class="el" href="dir_d28a4824dc47e487b107a5db32ef43c4.xhtml">examples</a></li><li class="navelem"><a class="el" href="graph__squeezenet_8cpp.xhtml">graph_squeezenet.cpp</a></li>
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