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| 87 | <a href="_batch_norm_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 <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_i_onnx_parser_8hpp.html">armnnOnnxParser/IOnnxParser.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_parser_prototxt_fixture_8hpp.html">ParserPrototxtFixture.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <a class="code" href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(OnnxParser)</div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="keyword">struct </span>BatchNormalizationMainFixture : <span class="keyword">public</span> <a class="code" href="structarmnn_utils_1_1_parser_prototxt_fixture.html">armnnUtils::ParserPrototxtFixture</a><armnnOnnxParser::IOnnxParser></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> {</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>  BatchNormalizationMainFixture()</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>  {</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>  <a class="code" href="structarmnn_utils_1_1_parser_prototxt_fixture.html#a5ca0f757171382fbf7fa5b05b447b024">m_Prototext</a> = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="stringliteral"> ir_version: 3</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="stringliteral"> producer_name: "CNTK"</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="stringliteral"> producer_version: "2.5.1"</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="stringliteral"> domain: "ai.cntk"</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="stringliteral"> model_version: 1</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="stringliteral"> graph {</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="stringliteral"> name: "CNTKGraph"</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="stringliteral"> name: "Input"</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="stringliteral"> dim_value: 3</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="stringliteral"> dim_value: 3</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="stringliteral"> name: "mean"</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="stringliteral"> name: "var"</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="stringliteral"> name: "scale"</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="stringliteral"> name: "bias"</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="stringliteral"> node {</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="stringliteral"> input: "Input"</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="stringliteral"> input: "scale"</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="stringliteral"> input: "bias"</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="stringliteral"> input: "mean"</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="stringliteral"> input: "var"</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="stringliteral"> output: "Output"</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="stringliteral"> name: "batchNorm"</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="stringliteral"> op_type: "BatchNormalization"</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="stringliteral"> attribute {</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="stringliteral"> name: "epsilon"</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="stringliteral"> f: 0.0010000000475</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="stringliteral"> type: 1</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="stringliteral"> initializer {</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="stringliteral"> dims: 1</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="stringliteral"> data_type: 1</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="stringliteral"> float_data: 5.0</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="stringliteral"> name: "mean"</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="stringliteral"> initializer {</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="stringliteral"> dims: 1</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="stringliteral"> data_type: 1</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="stringliteral"> float_data: 2.0</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="stringliteral"> name: "var"</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="stringliteral"> initializer {</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="stringliteral"> dims: 1</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="stringliteral"> data_type: 1</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="stringliteral"> float_data: 0.0</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="stringliteral"> name: "bias"</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="stringliteral"> initializer {</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="stringliteral"> dims: 1</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="stringliteral"> data_type: 1</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="stringliteral"> float_data: 1.0</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="stringliteral"> name: "scale"</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="stringliteral"> output {</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="stringliteral"> name: "Output"</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> <span class="stringliteral"> dim_value: 3</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> <span class="stringliteral"> dim_value: 3</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> <span class="stringliteral"> opset_import {</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="stringliteral"> version: 7</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="stringliteral"> })";</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="stringliteral"> <a class="code" href="structarmnn_utils_1_1_parser_prototxt_fixture.html#a769404f2985a027a0d626fedfd4de1e9">Setup</a>();</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> <span class="stringliteral">};</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> <span class="stringliteral"></span></div><div class="line"><a name="l00167"></a><span class="lineno"><a class="line" href="_batch_norm_8cpp.html#ad4b6f0108bb45ef24add6ea0532c055b"> 167</a></span> <span class="stringliteral"><a class="code" href="_batch_norm_8cpp.html#ad4b6f0108bb45ef24add6ea0532c055b">BOOST_FIXTURE_TEST_CASE</a>(ValidBatchNormalizationTest, BatchNormalizationMainFixture)</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="stringliteral">{</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="stringliteral"> RunTest<4>({{</span><span class="stringliteral">"Input"</span>, {1, 2, 3, 4, 5, 6, 7, 8, 9}}}, <span class="comment">// Input data.</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  {{<span class="stringliteral">"Output"</span>, {-2.8277204f, -2.12079024f, -1.4138602f,</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  -0.7069301f, 0.0f, 0.7069301f,</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  1.4138602f, 2.12079024f, 2.8277204f}}}); <span class="comment">// Expected output data.</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> }</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="keyword">struct </span>BatchNormalizationBisFixture : <span class="keyword">public</span> <a class="code" href="structarmnn_utils_1_1_parser_prototxt_fixture.html">armnnUtils::ParserPrototxtFixture</a><armnnOnnxParser::IOnnxParser></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> {</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  BatchNormalizationBisFixture()</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>  m_Prototext = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> <span class="stringliteral"> ir_version: 3</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> <span class="stringliteral"> producer_name: "CNTK"</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> <span class="stringliteral"> producer_version: "2.5.1"</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> <span class="stringliteral"> domain: "ai.cntk"</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> <span class="stringliteral"> model_version: 1</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> <span class="stringliteral"> graph {</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> <span class="stringliteral"> name: "CNTKGraph"</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> <span class="stringliteral"> name: "Input"</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> <span class="stringliteral"> dim_value: 2</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> <span class="stringliteral"> dim_value: 3</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> <span class="stringliteral"> name: "mean"</span></div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> <span class="stringliteral"> dim_value: 2</span></div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="stringliteral"> name: "var"</span></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="stringliteral"> dim_value: 2</span></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> <span class="stringliteral"> name: "scale"</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> <span class="stringliteral"> dim_value: 2</span></div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <span class="stringliteral"> input {</span></div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> <span class="stringliteral"> name: "bias"</span></div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> <span class="stringliteral"> dim_value: 2</span></div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> <span class="stringliteral"> node {</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <span class="stringliteral"> input: "Input"</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> <span class="stringliteral"> input: "scale"</span></div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> <span class="stringliteral"> input: "bias"</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> <span class="stringliteral"> input: "mean"</span></div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> <span class="stringliteral"> input: "var"</span></div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> <span class="stringliteral"> output: "Output"</span></div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> <span class="stringliteral"> name: "batchNorm"</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> <span class="stringliteral"> op_type: "BatchNormalization"</span></div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> <span class="stringliteral"> attribute {</span></div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> <span class="stringliteral"> name: "epsilon"</span></div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> <span class="stringliteral"> f: 0.00001</span></div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> <span class="stringliteral"> type: 1</span></div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="stringliteral"> initializer {</span></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> <span class="stringliteral"> dims: 2</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="stringliteral"> data_type: 1</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="stringliteral"> float_data: 0.0</span></div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="stringliteral"> float_data: 3.0</span></div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> <span class="stringliteral"> name: "mean"</span></div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> <span class="stringliteral"> initializer {</span></div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> <span class="stringliteral"> dims: 2</span></div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> <span class="stringliteral"> data_type: 1</span></div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="stringliteral"> float_data: 1.0</span></div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> <span class="stringliteral"> float_data: 1.5</span></div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="stringliteral"> name: "var"</span></div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> <span class="stringliteral"> initializer {</span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> <span class="stringliteral"> dims: 2</span></div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> <span class="stringliteral"> data_type: 1</span></div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> <span class="stringliteral"> float_data: 0.0</span></div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> <span class="stringliteral"> float_data: 1.0</span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> <span class="stringliteral"> name: "bias"</span></div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> <span class="stringliteral"> initializer {</span></div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> <span class="stringliteral"> dims: 2</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> <span class="stringliteral"> data_type: 1</span></div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> <span class="stringliteral"> float_data: 1.0</span></div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> <span class="stringliteral"> float_data: 1.5</span></div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span> <span class="stringliteral"> name: "scale"</span></div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> <span class="stringliteral"> output {</span></div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> <span class="stringliteral"> name: "Output"</span></div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="stringliteral"> type {</span></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="stringliteral"> tensor_type {</span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="stringliteral"> elem_type: 1</span></div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> <span class="stringliteral"> shape {</span></div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> <span class="stringliteral"> dim_value: 2</span></div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="stringliteral"> dim_value: 1</span></div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> <span class="stringliteral"> dim {</span></div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> <span class="stringliteral"> dim_value: 3</span></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> <span class="stringliteral"> opset_import {</span></div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> <span class="stringliteral"> version: 7</span></div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span> <span class="stringliteral"> })";</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> <span class="stringliteral"> Setup();</span></div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> <span class="stringliteral">};</span></div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> <span class="stringliteral"></span></div><div class="line"><a name="l00335"></a><span class="lineno"><a class="line" href="_batch_norm_8cpp.html#a02ce5312697a7baf4a85348bdb771b41"> 335</a></span> <span class="stringliteral"><a class="code" href="_batch_norm_8cpp.html#ad4b6f0108bb45ef24add6ea0532c055b">BOOST_FIXTURE_TEST_CASE</a>(ValidBatchNormalizationBisTest, BatchNormalizationBisFixture)</span></div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> <span class="stringliteral">{</span></div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> <span class="stringliteral"> RunTest<4>({{</span><span class="stringliteral">"Input"</span>, {-1, 0.0, 1, 2, 3.0, 4.0}}}, <span class="comment">// Input data.</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  {{<span class="stringliteral">"Output"</span>, {-0.999995f, 0.0, 0.999995f,</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  -0.22474074f, 1.0f, 2.2247407f}}}); <span class="comment">// Expected output data.</span></div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> }</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span> <a class="code" href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="_i_onnx_parser_8hpp_html"><div class="ttname"><a href="_i_onnx_parser_8hpp.html">IOnnxParser.hpp</a></div></div> |
| 88 | <div class="ttc" id="structarmnn_utils_1_1_parser_prototxt_fixture_html_a5ca0f757171382fbf7fa5b05b447b024"><div class="ttname"><a href="structarmnn_utils_1_1_parser_prototxt_fixture.html#a5ca0f757171382fbf7fa5b05b447b024">armnnUtils::ParserPrototxtFixture< armnnOnnxParser::IOnnxParser >::m_Prototext</a></div><div class="ttdeci">std::string m_Prototext</div><div class="ttdef"><b>Definition:</b> <a href="_parser_prototxt_fixture_8hpp_source.html#l00068">ParserPrototxtFixture.hpp:68</a></div></div> |
| 89 | <div class="ttc" id="_batch_norm_8cpp_html_ad4b6f0108bb45ef24add6ea0532c055b"><div class="ttname"><a href="_batch_norm_8cpp.html#ad4b6f0108bb45ef24add6ea0532c055b">BOOST_FIXTURE_TEST_CASE</a></div><div class="ttdeci">BOOST_FIXTURE_TEST_CASE(ValidBatchNormalizationTest, BatchNormalizationMainFixture)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_norm_8cpp_source.html#l00167">BatchNorm.cpp:167</a></div></div> |
| 90 | <div class="ttc" id="_profiler_tests_8cpp_html_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div> |
| 91 | <div class="ttc" id="structarmnn_utils_1_1_parser_prototxt_fixture_html"><div class="ttname"><a href="structarmnn_utils_1_1_parser_prototxt_fixture.html">armnnUtils::ParserPrototxtFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_parser_prototxt_fixture_8hpp_source.html#l00024">ParserPrototxtFixture.hpp:24</a></div></div> |
| 92 | <div class="ttc" id="_output_shape_of_squeeze_8cpp_html_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div> |
| 93 | <div class="ttc" id="_parser_prototxt_fixture_8hpp_html"><div class="ttname"><a href="_parser_prototxt_fixture_8hpp.html">ParserPrototxtFixture.hpp</a></div></div> |
| 94 | <div class="ttc" id="structarmnn_utils_1_1_parser_prototxt_fixture_html_a769404f2985a027a0d626fedfd4de1e9"><div class="ttname"><a href="structarmnn_utils_1_1_parser_prototxt_fixture.html#a769404f2985a027a0d626fedfd4de1e9">armnnUtils::ParserPrototxtFixture::Setup</a></div><div class="ttdeci">void Setup()</div><div class="ttdef"><b>Definition:</b> <a href="_parser_prototxt_fixture_8hpp_source.html#l00140">ParserPrototxtFixture.hpp:140</a></div></div> |
| 95 | </div><!-- fragment --></div><!-- contents --> |
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| 100 | <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.html">src</a></li><li class="navelem"><a class="el" href="dir_29e3193d5087607956cb928081b12830.html">armnnOnnxParser</a></li><li class="navelem"><a class="el" href="dir_14b0222e5488316bb30ce89add6c280e.html">test</a></li><li class="navelem"><a class="el" href="_batch_norm_8cpp.html">BatchNorm.cpp</a></li> |
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