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<div class="title">LoadScopeDynamicTensor.cpp</div> </div>
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<a href="_load_scope_dynamic_tensor_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> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2020 Arm Ltd and Contributors. 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 "<a class="code" href="_i_tf_lite_parser_8hpp.xhtml">armnnTfLiteParser/ITfLiteParser.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <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> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="keyword">struct </span>LoadScopeDynamicTensorFixture : <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> {</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <span class="keyword">explicit</span> LoadScopeDynamicTensorFixture(<span class="keyword">const</span> std::string& shape0,</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keyword">const</span> std::string& shape1,</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keyword">const</span> std::string& shape2)</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  {</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a803c86dca3acef653c1cc481a27be7a9">m_JsonString</a> = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="stringliteral"> "version": 3,</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="stringliteral"> "operator_codes": [</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="stringliteral"> "builtin_code": "AVERAGE_POOL_2D",</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="stringliteral"> "version": 1</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="stringliteral"> "builtin_code": "SOFTMAX",</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="stringliteral"> "version": 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"> ],</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="stringliteral"> "subgraphs": [</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"> "tensors": [</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="stringliteral"> "shape": )" + shape0 + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="stringliteral"> "buffer": 1,</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="stringliteral"> "name": "input0",</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="stringliteral"> "details_type": 0,</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="stringliteral"> "quantized_dimension": 0</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"> "is_variable": false</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="stringliteral"> "shape": )" + shape1 + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="stringliteral"> "buffer": 3,</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="stringliteral"> "name": "output",</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="stringliteral"> "details_type": 0,</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="stringliteral"> "quantized_dimension": 0</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"> "is_variable": false</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"> {</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="stringliteral"> "shape": )" + shape2 + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="stringliteral"> "buffer": 2,</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="stringliteral"> "name": "model/average_pooling2d/AvgPool",</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="stringliteral"> "details_type": 0,</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="stringliteral"> "quantized_dimension": 0</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"> "is_variable": false</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"> "inputs": [</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="stringliteral"> 0</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="stringliteral"> "outputs": [</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="stringliteral"> 1</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="stringliteral"> "operators": [</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="stringliteral"> "opcode_index": 1,</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="stringliteral"> "inputs": [</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="stringliteral"> 2</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"> "outputs": [</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="stringliteral"> 1</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="stringliteral"> "builtin_options_type": "SoftmaxOptions",</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="stringliteral"> "builtin_options": {</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="stringliteral"> "beta": 1.0</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="stringliteral"> "custom_options_format": "FLEXBUFFERS"</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span 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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"> {</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="stringliteral"> {</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"> ]</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="stringliteral"> )";</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="stringliteral"> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a769404f2985a027a0d626fedfd4de1e9">Setup</a>();</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="stringliteral"> }</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"></span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="stringliteral"></span><span class="keyword">struct </span>LoadScopeDynamicTensor0Fixture : LoadScopeDynamicTensorFixture</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> {</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  LoadScopeDynamicTensor0Fixture() : LoadScopeDynamicTensorFixture(<span class="stringliteral">"[ 1, 2, 3, 2 ]"</span>, <span class="stringliteral">"[]"</span>, <span class="stringliteral">"[]"</span>) {}</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> };</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="keyword">struct </span>LoadScopeDynamicTensor1Fixture : LoadScopeDynamicTensorFixture</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> {</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  LoadScopeDynamicTensor1Fixture() : LoadScopeDynamicTensorFixture(<span class="stringliteral">"[ 1, 2, 4, 1 ]"</span>, <span class="stringliteral">"[ 1, 1, 2, 1 ]"</span>, <span class="stringliteral">"[]"</span>) {}</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> };</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> </div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="keyword">struct </span>LoadScopeDynamicTensor2Fixture : LoadScopeDynamicTensorFixture</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> {</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  LoadScopeDynamicTensor2Fixture() : LoadScopeDynamicTensorFixture(<span class="stringliteral">"[ 1, 3, 3, 2 ]"</span>, <span class="stringliteral">"[ ]"</span>, <span class="stringliteral">"[ 1, 1, 1, 2 ]"</span>) {}</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> };</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div><div class="line"><a name="l00147"></a><span class="lineno"><a class="line" href="_load_scope_dynamic_tensor_8cpp.xhtml#a81d319e7175cc67604497b0ba2c504e4"> 147</a></span> <a class="code" href="_load_scope_dynamic_tensor_8cpp.xhtml#a81d319e7175cc67604497b0ba2c504e4">BOOST_FIXTURE_TEST_CASE</a>(LoadScopeDynamicTensor0, LoadScopeDynamicTensor0Fixture)</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> {</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  RunTest<4, armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  0,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  { {<span class="stringliteral">"input0"</span>, { 0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f }} },</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  { {<span class="stringliteral">"output"</span>, { 0.26894143f, 0.7310586f }} },</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keyword">true</span>);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> }</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> </div><div class="line"><a name="l00156"></a><span class="lineno"><a class="line" href="_load_scope_dynamic_tensor_8cpp.xhtml#a7a239a1db31d362be7176a8fba27799c"> 156</a></span> <a class="code" href="_load_scope_dynamic_tensor_8cpp.xhtml#a81d319e7175cc67604497b0ba2c504e4">BOOST_FIXTURE_TEST_CASE</a>(LoadScopeDynamicTensor1, LoadScopeDynamicTensor1Fixture)</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> {</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  RunTest<4, armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  0,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  { {<span class="stringliteral">"input0"</span>, { 0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f }} },</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  { {<span class="stringliteral">"output"</span>, { 1.f, 1.f }} },</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">true</span>);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> }</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div><div class="line"><a name="l00165"></a><span class="lineno"><a class="line" href="_load_scope_dynamic_tensor_8cpp.xhtml#a7609ff6cabfed1c8f91a218add175f99"> 165</a></span> <a class="code" href="_load_scope_dynamic_tensor_8cpp.xhtml#a81d319e7175cc67604497b0ba2c504e4">BOOST_FIXTURE_TEST_CASE</a>(LoadScopeDynamicTensor2, LoadScopeDynamicTensor2Fixture)</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> {</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  RunTest<4, armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  0,</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  { {<span class="stringliteral">"input0"</span>, { 0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f }} },</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  { {<span class="stringliteral">"output"</span>, { 0.7772999f, 0.22270015f }} },</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keyword">true</span>);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</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> <span class="keyword">struct </span>LoadScopeDynamicTensorBroadcastingFixture : <span class="keyword">public</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></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">explicit</span> LoadScopeDynamicTensorBroadcastingFixture(<span class="keyword">const</span> std::string& inputShape0,</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keyword">const</span> std::string& inputShape1,</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keyword">const</span> std::string& inputShape2,</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keyword">const</span> std::string& addShape,</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keyword">const</span> std::string& outputShape)</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  {</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  m_JsonString = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> <span class="stringliteral"> "version": 3,</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> <span class="stringliteral"> "operator_codes": [</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> <span class="stringliteral"> "builtin_code": "ADD",</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="stringliteral"> "version": 1</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="stringliteral"> "builtin_code": "SUB",</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> <span class="stringliteral"> "version": 1</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> <span class="stringliteral"> "subgraphs": [</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"> "tensors": [</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> <span class="stringliteral"> "shape": )" + inputShape0 + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> <span class="stringliteral"> "buffer": 1,</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> <span class="stringliteral"> "name": "input0",</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> <span class="stringliteral"> "details_type": 0,</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> <span class="stringliteral"> "quantized_dimension": 0</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"> "is_variable": false</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"> "shape": )" + inputShape1 + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> <span class="stringliteral"> "buffer": 2,</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> <span class="stringliteral"> "name": "input1",</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> <span class="stringliteral"> "details_type": 0,</span></div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> <span class="stringliteral"> "quantized_dimension": 0</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> <span class="stringliteral"> "is_variable": false</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"> "shape": )" + outputShape + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="stringliteral"> "buffer": 5,</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="stringliteral"> "name": "output",</span></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> <span class="stringliteral"> "details_type": 0,</span></div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> <span class="stringliteral"> "quantized_dimension": 0</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="stringliteral"> "is_variable": false</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="stringliteral"> },</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"> "shape": )" + addShape + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> <span class="stringliteral"> "buffer": 4,</span></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> <span class="stringliteral"> "name": "model/add/add",</span></div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="stringliteral"> "details_type": 0,</span></div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> <span class="stringliteral"> "quantized_dimension": 0</span></div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> <span class="stringliteral"> "is_variable": false</span></div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> <span class="stringliteral"> "shape": )" + inputShape2 + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <span class="stringliteral"> "buffer": 3,</span></div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> <span class="stringliteral"> "name": "input2",</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <span class="stringliteral"> "details_type": 0,</span></div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> <span class="stringliteral"> "quantized_dimension": 0</span></div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> <span class="stringliteral"> "is_variable": false</span></div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> <span class="stringliteral"> "inputs": [</span></div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> <span class="stringliteral"> 0,</span></div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> <span class="stringliteral"> 1,</span></div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> <span class="stringliteral"> 4</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"> "outputs": [</span></div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> <span class="stringliteral"> 2</span></div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <span class="stringliteral"> "operators": [</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> <span class="stringliteral"> "inputs": [</span></div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> <span class="stringliteral"> 0,</span></div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> <span class="stringliteral"> 1</span></div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> <span class="stringliteral"> "outputs": [</span></div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> <span class="stringliteral"> 3</span></div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> <span class="stringliteral"> "builtin_options_type": "AddOptions",</span></div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> <span class="stringliteral"> "builtin_options": {</span></div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> <span class="stringliteral"> "fused_activation_function": "NONE"</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"> "custom_options_format": "FLEXBUFFERS"</span></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="stringliteral"> "opcode_index": 1,</span></div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="stringliteral"> "inputs": [</span></div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> <span class="stringliteral"> 3,</span></div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="stringliteral"> 4</span></div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> <span class="stringliteral"> "outputs": [</span></div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> <span class="stringliteral"> 2</span></div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> <span class="stringliteral"> "builtin_options_type": "SubOptions",</span></div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="stringliteral"> "builtin_options": {</span></div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> <span class="stringliteral"> "fused_activation_function": "NONE"</span></div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> <span class="stringliteral"> "custom_options_format": "FLEXBUFFERS"</span></div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> <span class="stringliteral"> "name": "main"</span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> <span class="stringliteral"> }</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"> "buffers": [</span></div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span> <span class="stringliteral"> {</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"> {</span></div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> <span class="stringliteral"> ]</span></div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="stringliteral"> }</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"> Setup();</span></div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> <span class="stringliteral"> }</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"></span></div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="stringliteral"></span><span class="keyword">struct </span>LoadScopeDynamicTensorBroadcasting3DFixture : LoadScopeDynamicTensorBroadcastingFixture</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> {</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  LoadScopeDynamicTensorBroadcasting3DFixture() : LoadScopeDynamicTensorBroadcastingFixture(<span class="stringliteral">"[ 1, 2, 3, 2 ]"</span>,</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="stringliteral">"[ 2, 3, 2 ]"</span>,</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="stringliteral">"[ 2, 3, 2 ]"</span>,</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="stringliteral">"[ 1, 2, 3, 2 ]"</span>, <span class="stringliteral">"[]"</span>) {}</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> };</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> </div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> <span class="keyword">struct </span>LoadScopeDynamicTensorBroadcasting2DFixture : LoadScopeDynamicTensorBroadcastingFixture</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> {</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  LoadScopeDynamicTensorBroadcasting2DFixture() : LoadScopeDynamicTensorBroadcastingFixture(<span class="stringliteral">"[ 1, 2, 3, 2 ]"</span>,</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="stringliteral">"[ 3, 2 ]"</span>,</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="stringliteral">"[ 3, 2 ]"</span>,</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="stringliteral">"[]"</span>, <span class="stringliteral">"[]"</span>) {}</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> };</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> </div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> <span class="keyword">struct </span>LoadScopeDynamicTensorBroadcasting1DFixture : LoadScopeDynamicTensorBroadcastingFixture</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> {</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  LoadScopeDynamicTensorBroadcasting1DFixture() : LoadScopeDynamicTensorBroadcastingFixture(<span class="stringliteral">"[ 1, 2, 3, 2 ]"</span>,</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="stringliteral">"[ 1 ]"</span>,</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="stringliteral">"[ 1 ]"</span>,</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="stringliteral">"[]"</span>,</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="stringliteral">"[ 1, 2, 3, 2 ]"</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> </div><div class="line"><a name="l00343"></a><span class="lineno"><a class="line" href="_load_scope_dynamic_tensor_8cpp.xhtml#a9c8ec0e8a7130531f10ec0bfca18a459"> 343</a></span> <a class="code" href="_load_scope_dynamic_tensor_8cpp.xhtml#a81d319e7175cc67604497b0ba2c504e4">BOOST_FIXTURE_TEST_CASE</a>(LoadScopeDynamicTensorBroadcasting3D, LoadScopeDynamicTensorBroadcasting3DFixture)</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span> {</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  RunTest<4, armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  0,</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  { {<span class="stringliteral">"input0"</span>, { 0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f }},</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  {<span class="stringliteral">"input1"</span>, { 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f, 12.f, 13.f, 14.f }},</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  {<span class="stringliteral">"input2"</span>, { 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f, 12.f }}</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  },</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  { {<span class="stringliteral">"output"</span>, { 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f, 12.f, 13.f }} },</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keyword">true</span>);</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> }</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> </div><div class="line"><a name="l00355"></a><span class="lineno"><a class="line" href="_load_scope_dynamic_tensor_8cpp.xhtml#ad04c861a3e72984269dee5f16c1f3a98"> 355</a></span> <a class="code" href="_load_scope_dynamic_tensor_8cpp.xhtml#a81d319e7175cc67604497b0ba2c504e4">BOOST_FIXTURE_TEST_CASE</a>(LoadScopeDynamicTensorBroadcasting2D, LoadScopeDynamicTensorBroadcasting2DFixture)</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> {</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  RunTest<4, armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  0,</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  { {<span class="stringliteral">"input0"</span>, { 0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f }},</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  {<span class="stringliteral">"input1"</span>, { 3.f, 4.f, 5.f, 6.f, 7.f, 8.f }},</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  {<span class="stringliteral">"input2"</span>, { -1.f, -2.f, 3.f, 4.f, 5.f, 6.f }}</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  },</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  { {<span class="stringliteral">"output"</span>, { 4.f, 7.f, 4.f, 5.f, 6.f, 7.f, 10.f, 13.f, 10.f, 11.f, 12.f, 13.f }} },</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keyword">true</span>);</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> }</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> </div><div class="line"><a name="l00367"></a><span class="lineno"><a class="line" href="_load_scope_dynamic_tensor_8cpp.xhtml#a159a57c6f69622044567858f08910117"> 367</a></span> <a class="code" href="_load_scope_dynamic_tensor_8cpp.xhtml#a81d319e7175cc67604497b0ba2c504e4">BOOST_FIXTURE_TEST_CASE</a>(LoadScopeDynamicTensorBroadcasting1D, LoadScopeDynamicTensorBroadcasting1DFixture)</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> {</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  RunTest<4, armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  0,</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  { {<span class="stringliteral">"input0"</span>, { 0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f }},</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  {<span class="stringliteral">"input1"</span>, { 5.f }},</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  {<span class="stringliteral">"input2"</span>, { 1.f }}</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  },</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  { {<span class="stringliteral">"output"</span>, { 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f, 12.f, 13.f, 14.f, 15.f }} },</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keyword">true</span>);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> }</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> </div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> <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_a769404f2985a027a0d626fedfd4de1e9"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a769404f2985a027a0d626fedfd4de1e9">ParserFlatbuffersFixture::Setup</a></div><div class="ttdeci">void Setup()</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00061">ParserFlatbuffersFixture.hpp:61</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#l00036">ParserFlatbuffersFixture.hpp:36</a></div></div>
<div class="ttc" id="_i_tf_lite_parser_8hpp_xhtml"><div class="ttname"><a href="_i_tf_lite_parser_8hpp.xhtml">ITfLiteParser.hpp</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="_load_scope_dynamic_tensor_8cpp_xhtml_a81d319e7175cc67604497b0ba2c504e4"><div class="ttname"><a href="_load_scope_dynamic_tensor_8cpp.xhtml#a81d319e7175cc67604497b0ba2c504e4">BOOST_FIXTURE_TEST_CASE</a></div><div class="ttdeci">BOOST_FIXTURE_TEST_CASE(LoadScopeDynamicTensor0, LoadScopeDynamicTensor0Fixture)</div><div class="ttdef"><b>Definition:</b> <a href="_load_scope_dynamic_tensor_8cpp_source.xhtml#l00147">LoadScopeDynamicTensor.cpp:147</a></div></div>
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