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+<div class="title">DepthwiseConvolution2D.cpp</div>  </div>
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+<a href="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_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 © 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;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &lt;boost/test/unit_test.hpp&gt;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a>&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &quot;../TfLiteParser.hpp&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &lt;string&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;iostream&gt;</span></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;<a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(TensorflowLiteParser)</div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;</div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="keyword">struct </span>DepthwiseConvolution2dFixture : <span class="keyword">public</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;{</div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;    <span class="keyword">explicit</span> DepthwiseConvolution2dFixture(<span class="keyword">const</span> std::string&amp; inputShape,</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;                                           <span class="keyword">const</span> std::string&amp; outputShape,</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;                                           <span class="keyword">const</span> std::string&amp; filterShape,</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;                                           <span class="keyword">const</span> std::string&amp; filterData,</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;                                           <span class="keyword">const</span> std::string&amp; strides,</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;                                           <span class="keyword">const</span> std::string&amp; paddingType,</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;                                           <span class="keyword">const</span> std::string biasShape = <span class="stringliteral">&quot;&quot;</span>,</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;                                           <span class="keyword">const</span> std::string biasData = <span class="stringliteral">&quot;&quot;</span>)</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;        std::string inputTensors = <span class="stringliteral">&quot;[ 0, 2 ]&quot;</span>;</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;        std::string biasTensor = <span class="stringliteral">&quot;&quot;</span>;</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;        std::string biasBuffer = <span class="stringliteral">&quot;&quot;</span>;</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;        <span class="keywordflow">if</span> (biasShape.size() &gt; 0 &amp;&amp; biasData.size() &gt; 0)</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;        {</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;            inputTensors = <span class="stringliteral">&quot;[ 0, 2, 3 ]&quot;</span>;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;            biasTensor = R<span class="stringliteral">&quot;(</span></div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="stringliteral">                        {</span></div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="stringliteral">                            &quot;shape&quot;: )&quot; + biasShape + R</span><span class="stringliteral">&quot;( ,</span></div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="stringliteral">                            &quot;type&quot;: &quot;INT32&quot;,</span></div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="stringliteral">                            &quot;buffer&quot;: 3,</span></div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="stringliteral">                            &quot;name&quot;: &quot;biasTensor&quot;,</span></div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="stringliteral">                            &quot;quantization&quot;: {</span></div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="stringliteral">                                &quot;min&quot;: [ 0.0 ],</span></div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="stringliteral">                                &quot;max&quot;: [ 255.0 ],</span></div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="stringliteral">                                &quot;scale&quot;: [ 1.0 ],</span></div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="stringliteral">                                &quot;zero_point&quot;: [ 0 ],</span></div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="stringliteral">                            }</span></div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="stringliteral">                        } )&quot;;</span></div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="stringliteral">            biasBuffer = R</span><span class="stringliteral">&quot;(</span></div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="stringliteral">                    { &quot;data&quot;: )&quot; + biasData + R</span><span class="stringliteral">&quot;(, }, )&quot;;</span></div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="stringliteral">        }</span></div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="stringliteral">        <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a803c86dca3acef653c1cc481a27be7a9">m_JsonString</a> = R</span><span class="stringliteral">&quot;(</span></div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;<span class="stringliteral">            {</span></div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;<span class="stringliteral">                &quot;version&quot;: 3,</span></div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;<span class="stringliteral">                &quot;operator_codes&quot;: [ { &quot;builtin_code&quot;: &quot;DEPTHWISE_CONV_2D&quot; } ],</span></div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;<span class="stringliteral">                &quot;subgraphs&quot;: [ {</span></div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;<span class="stringliteral">                    &quot;tensors&quot;: [</span></div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;<span class="stringliteral">                        {</span></div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;<span class="stringliteral">                            &quot;shape&quot;: )&quot; + inputShape + R</span><span class="stringliteral">&quot;(,</span></div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;<span class="stringliteral">                            &quot;type&quot;: &quot;UINT8&quot;,</span></div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;<span class="stringliteral">                            &quot;buffer&quot;: 0,</span></div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;<span class="stringliteral">                            &quot;name&quot;: &quot;inputTensor&quot;,</span></div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;<span class="stringliteral">                            &quot;quantization&quot;: {</span></div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;<span class="stringliteral">                                &quot;min&quot;: [ 0.0 ],</span></div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;<span class="stringliteral">                                &quot;max&quot;: [ 255.0 ],</span></div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;<span class="stringliteral">                                &quot;scale&quot;: [ 1.0 ],</span></div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;<span class="stringliteral">                                &quot;zero_point&quot;: [ 0 ],</span></div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<span class="stringliteral">                            }</span></div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;<span class="stringliteral">                        },</span></div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;<span class="stringliteral">                        {</span></div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;<span class="stringliteral">                            &quot;shape&quot;: )&quot; + outputShape + R</span><span class="stringliteral">&quot;(,</span></div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;<span class="stringliteral">                            &quot;type&quot;: &quot;UINT8&quot;,</span></div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;<span class="stringliteral">                            &quot;buffer&quot;: 1,</span></div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;<span class="stringliteral">                            &quot;name&quot;: &quot;outputTensor&quot;,</span></div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;<span class="stringliteral">                            &quot;quantization&quot;: {</span></div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;<span class="stringliteral">                                &quot;min&quot;: [ 0.0 ],</span></div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;<span class="stringliteral">                                &quot;max&quot;: [ 511.0 ],</span></div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;<span class="stringliteral">                                &quot;scale&quot;: [ 2.0 ],</span></div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;<span class="stringliteral">                                &quot;zero_point&quot;: [ 0 ],</span></div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;<span class="stringliteral">                            }</span></div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;<span class="stringliteral">                        },</span></div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;<span class="stringliteral">                        {</span></div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;<span class="stringliteral">                            &quot;shape&quot;: )&quot; + filterShape + R</span><span class="stringliteral">&quot;(,</span></div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;<span class="stringliteral">                            &quot;type&quot;: &quot;UINT8&quot;,</span></div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;<span class="stringliteral">                            &quot;buffer&quot;: 2,</span></div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;<span class="stringliteral">                            &quot;name&quot;: &quot;filterTensor&quot;,</span></div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;<span class="stringliteral">                            &quot;quantization&quot;: {</span></div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;<span class="stringliteral">                                &quot;min&quot;: [ 0.0 ],</span></div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;<span class="stringliteral">                                &quot;max&quot;: [ 255.0 ],</span></div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;<span class="stringliteral">                                &quot;scale&quot;: [ 1.0 ],</span></div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;<span class="stringliteral">                                &quot;zero_point&quot;: [ 0 ],</span></div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;<span class="stringliteral">                            }</span></div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;<span class="stringliteral">                        }, )&quot; + biasTensor + R</span><span class="stringliteral">&quot;(</span></div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;<span class="stringliteral">                    ],</span></div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;<span class="stringliteral">                    &quot;inputs&quot;: [ 0 ],</span></div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;<span class="stringliteral">                    &quot;outputs&quot;: [ 1 ],</span></div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;<span class="stringliteral">                    &quot;operators&quot;: [</span></div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;<span class="stringliteral">                        {</span></div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;<span class="stringliteral">                            &quot;opcode_index&quot;: 0,</span></div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;<span class="stringliteral">                            &quot;inputs&quot;: )&quot; + inputTensors + R</span><span class="stringliteral">&quot;(,</span></div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;<span class="stringliteral">                            &quot;outputs&quot;: [ 1 ],</span></div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;<span class="stringliteral">                            &quot;builtin_options_type&quot;: &quot;DepthwiseConv2DOptions&quot;,</span></div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;<span class="stringliteral">                            &quot;builtin_options&quot;: {</span></div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;<span class="stringliteral">                                &quot;padding&quot;: &quot;)&quot; + paddingType + R</span><span class="stringliteral">&quot;(&quot;,</span></div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;<span class="stringliteral">                                &quot;stride_w&quot;: )&quot; + strides+ R</span><span class="stringliteral">&quot;(,</span></div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;<span class="stringliteral">                                &quot;stride_h&quot;: )&quot; + strides+ R</span><span class="stringliteral">&quot;(,</span></div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;<span class="stringliteral">                                &quot;depth_multiplier&quot;: 1,</span></div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;<span class="stringliteral">                                &quot;fused_activation_function&quot;: &quot;NONE&quot;</span></div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;<span class="stringliteral">                            },</span></div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;<span class="stringliteral">                            &quot;custom_options_format&quot;: &quot;FLEXBUFFERS&quot;</span></div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;<span class="stringliteral">                        }</span></div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;<span class="stringliteral">                    ],</span></div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;<span class="stringliteral">                } ],</span></div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;<span class="stringliteral">                &quot;buffers&quot; : [</span></div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;<span class="stringliteral">                    { },</span></div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;<span class="stringliteral">                    { },</span></div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;<span class="stringliteral">                    { &quot;data&quot;: )&quot; + filterData + R</span><span class="stringliteral">&quot;(, }, )&quot;</span></div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;<span class="stringliteral">                    + biasBuffer + R</span><span class="stringliteral">&quot;(</span></div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;<span class="stringliteral">                ]</span></div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;<span class="stringliteral">            }</span></div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;<span class="stringliteral">        )&quot;;</span></div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;<span class="stringliteral">        <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a2bb4ea256fbbf6d53068ca93bb4bc95c">SetupSingleInputSingleOutput</a>(</span><span class="stringliteral">&quot;inputTensor&quot;</span>, <span class="stringliteral">&quot;outputTensor&quot;</span>);</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    }</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;};</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;<span class="keyword">struct </span>DepthwiseConvolution2dSameFixture : DepthwiseConvolution2dFixture</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;{</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;    DepthwiseConvolution2dSameFixture()</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    : DepthwiseConvolution2dFixture(<span class="stringliteral">&quot;[ 1, 3, 3, 1 ]&quot;</span>,           <span class="comment">// inputShape</span></div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;                                    <span class="stringliteral">&quot;[ 1, 3, 3, 1 ]&quot;</span>,           <span class="comment">// outputShape</span></div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;                                    <span class="stringliteral">&quot;[ 1, 3, 3, 1 ]&quot;</span>,           <span class="comment">// filterShape</span></div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;                                    <span class="stringliteral">&quot;[ 9,8,7, 6,5,4, 3,2,1 ]&quot;</span>,  <span class="comment">// filterData</span></div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;                                    <span class="stringliteral">&quot;1&quot;</span>,                        <span class="comment">// stride w and h</span></div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;                                    <span class="stringliteral">&quot;SAME&quot;</span>)                     <span class="comment">// padding type</span></div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    {}</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;};</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;</div><div class="line"><a name="l00134"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_8cpp.xhtml#af53fa33ced6d7398ff45034555f163aa">  134</a></span>&#160;<a class="code" href="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_8cpp.xhtml#af53fa33ced6d7398ff45034555f163aa">BOOST_FIXTURE_TEST_CASE</a>(ParseDepthwiseConv2DSame, DepthwiseConvolution2dSameFixture)</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;{</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    RunTest&lt;4, armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;        0,</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        { 0, 1, 2,</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;          3, 4, 5,</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;          6, 7, 8 },</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;        <span class="comment">// the expected values were generated using the example python implementation at</span></div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;        <span class="comment">// https://eli.thegreenplace.net/2018/depthwise-separable-convolutions-for-machine-learning/</span></div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;        <span class="comment">// divide the expected values by the output scale, as it is not 1.0</span></div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;        {  14/2,  35/2,  38/2,</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;           57/2, 120/2, 111/2,</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;          110/2, 197/2, 158/2 });</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;}</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;<span class="keyword">struct </span>DepthwiseConvolution2dValidFixture : DepthwiseConvolution2dFixture</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;{</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    DepthwiseConvolution2dValidFixture ()</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    : DepthwiseConvolution2dFixture(<span class="stringliteral">&quot;[ 1, 3, 3, 1 ]&quot;</span>,           <span class="comment">// inputShape</span></div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;                                    <span class="stringliteral">&quot;[ 1, 1, 1, 1 ]&quot;</span>,           <span class="comment">// outputShape</span></div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;                                    <span class="stringliteral">&quot;[ 1, 3, 3, 1 ]&quot;</span>,           <span class="comment">// filterShape</span></div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;                                    <span class="stringliteral">&quot;[ 9,8,7, 6,5,4, 3,2,1 ]&quot;</span>,  <span class="comment">// filterData</span></div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;                                    <span class="stringliteral">&quot;1&quot;</span>,                        <span class="comment">// stride w and h</span></div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;                                    <span class="stringliteral">&quot;VALID&quot;</span>)                    <span class="comment">// padding type</span></div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    {}</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;};</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;</div><div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_8cpp.xhtml#a6e7cc099f8ebc8db20852ca41f9600e0">  161</a></span>&#160;<a class="code" href="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_8cpp.xhtml#af53fa33ced6d7398ff45034555f163aa">BOOST_FIXTURE_TEST_CASE</a>(ParseDepthwiseConv2DValid, DepthwiseConvolution2dValidFixture)</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;{</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    RunTest&lt;4, armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        0,</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;        { 0, 1, 2,</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;          3, 4, 5,</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;          6, 7, 8 },</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;        <span class="comment">// divide the expected values by the output scale, as it is not 1.0</span></div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;        { 120/2 });</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;}</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;<span class="keyword">struct </span>DepthwiseConvolution2dSameBiasFixture : DepthwiseConvolution2dFixture</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;{</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    DepthwiseConvolution2dSameBiasFixture()</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    : DepthwiseConvolution2dFixture(<span class="stringliteral">&quot;[ 1, 3, 3, 1 ]&quot;</span>,           <span class="comment">// inputShape</span></div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;                                    <span class="stringliteral">&quot;[ 1, 3, 3, 1 ]&quot;</span>,           <span class="comment">// outputShape</span></div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                                    <span class="stringliteral">&quot;[ 1, 3, 3, 1 ]&quot;</span>,           <span class="comment">// filterShape</span></div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;                                    <span class="stringliteral">&quot;[ 9,8,7, 6,5,4, 3,2,1 ]&quot;</span>,  <span class="comment">// filterData</span></div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;                                    <span class="stringliteral">&quot;1&quot;</span>,                        <span class="comment">// stride w and h</span></div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;                                    <span class="stringliteral">&quot;SAME&quot;</span>,                     <span class="comment">// padding type</span></div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;                                    <span class="stringliteral">&quot;[ 1 ]&quot;</span>,                    <span class="comment">// biasShape</span></div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;                                    <span class="stringliteral">&quot;[ 10, 0, 0, 0 ]&quot;</span>)          <span class="comment">// biasData</span></div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    {}</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;};</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"><a class="line" href="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_8cpp.xhtml#afc6740eb06761e5194dda25370e5b85e">  186</a></span>&#160;<a class="code" href="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_8cpp.xhtml#af53fa33ced6d7398ff45034555f163aa">BOOST_FIXTURE_TEST_CASE</a>(ParseDepthwiseConv2DSameBias, DepthwiseConvolution2dSameBiasFixture)</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;{</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;    RunTest&lt;4, armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;        0,</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;        { 0, 1, 2,</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;          3, 4, 5,</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;          6, 7, 8 },</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;        <span class="comment">// divide the expected values by the output scale, as it is not 1.0</span></div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;        { ( 14+10)/2, ( 35+10)/2, ( 38+10)/2,</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;          ( 57+10)/2, (120+10)/2, (111+10)/2,</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;          (110+10)/2, (197+10)/2, (158+10)/2 });</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;}</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;<a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="_output_shape_of_squeeze_8cpp_xhtml_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div>
+<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a803c86dca3acef653c1cc481a27be7a9"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a803c86dca3acef653c1cc481a27be7a9">ParserFlatbuffersFixture::m_JsonString</a></div><div class="ttdeci">std::string m_JsonString</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00051">ParserFlatbuffersFixture.hpp:51</a></div></div>
+<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00037">ParserFlatbuffersFixture.hpp:37</a></div></div>
+<div class="ttc" id="_parser_flatbuffers_fixture_8hpp_xhtml"><div class="ttname"><a href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a></div></div>
+<div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div>
+<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a2bb4ea256fbbf6d53068ca93bb4bc95c"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a2bb4ea256fbbf6d53068ca93bb4bc95c">ParserFlatbuffersFixture::SetupSingleInputSingleOutput</a></div><div class="ttdeci">void SetupSingleInputSingleOutput(const std::string &amp;inputName, const std::string &amp;outputName)</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00094">ParserFlatbuffersFixture.hpp:94</a></div></div>
+<div class="ttc" id="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_8cpp_xhtml_af53fa33ced6d7398ff45034555f163aa"><div class="ttname"><a href="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_8cpp.xhtml#af53fa33ced6d7398ff45034555f163aa">BOOST_FIXTURE_TEST_CASE</a></div><div class="ttdeci">BOOST_FIXTURE_TEST_CASE(ParseDepthwiseConv2DSame, DepthwiseConvolution2dSameFixture)</div><div class="ttdef"><b>Definition:</b> <a href="armnn_tf_lite_parser_2test_2_depthwise_convolution2_d_8cpp_source.xhtml#l00134">DepthwiseConvolution2D.cpp:134</a></div></div>
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