| 101 | <a href="armnn_tf_lite_parser_2test_2_minimum_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 © 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="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "../TfLiteParser.hpp"</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> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <iostream></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>MinimumFixture : <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> MinimumFixture(<span class="keyword">const</span> std::string & inputShape1,</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keyword">const</span> std::string & inputShape2,</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keyword">const</span> std::string & outputShape)</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": [ { "builtin_code": "MINIMUM" } ],</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="stringliteral"> "subgraphs": [ {</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="stringliteral"> "tensors": [</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="stringliteral"> "shape": )" + inputShape1 + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="stringliteral"> "name": "inputTensor1",</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="stringliteral"> "zero_point": [ 0 ],</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"> },</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="stringliteral"> "shape": )" + inputShape2 + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="stringliteral"> "buffer": 1,</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="stringliteral"> "name": "inputTensor2",</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="stringliteral"> "zero_point": [ 0 ],</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="stringliteral"> "shape": )" + outputShape + R</span><span class="stringliteral">"( ,</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="stringliteral"> "buffer": 2,</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="stringliteral"> "name": "outputTensor",</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="stringliteral"> "zero_point": [ 0 ],</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="stringliteral"> "inputs": [ 0, 1 ],</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="stringliteral"> "outputs": [ 2 ],</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="stringliteral"> "operators": [</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"> "opcode_index": 0,</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="stringliteral"> "inputs": [ 0, 1 ],</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="stringliteral"> "outputs": [ 2 ],</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="stringliteral"> "custom_options_format": "FLEXBUFFERS"</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="stringliteral"> }</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"> } ],</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="stringliteral"> "buffers" : [</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"> { }</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"> }</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"> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a769404f2985a027a0d626fedfd4de1e9">Setup</a>();</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"></span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="stringliteral"></span><span class="keyword">struct </span>MinimumFixture4D : MinimumFixture</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> {</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  MinimumFixture4D() : MinimumFixture(<span class="stringliteral">"[ 1, 2, 2, 3 ]"</span>,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="stringliteral">"[ 1, 2, 2, 3 ]"</span>,</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="stringliteral">"[ 1, 2, 2, 3 ]"</span>) {}</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> };</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#a22beb506dae13f30efcd16bf90e0df7b"> 93</a></span> <a class="code" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#a22beb506dae13f30efcd16bf90e0df7b">BOOST_FIXTURE_TEST_CASE</a>(ParseMinimum4D, MinimumFixture4D)</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  RunTest<4, armnn::DataType::Float32>(</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  0,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  {{<span class="stringliteral">"inputTensor1"</span>, { 0.0f, 1.0f, 2.0f,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  6.0f, 7.0f, 8.0f,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  9.0f, 10.0f, 11.0f }},</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  {<span class="stringliteral">"inputTensor2"</span>, { 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  5.0f, 5.0f, 5.0f,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  7.0f, 7.0f, 7.0f,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  9.0f, 9.0f, 9.0f }}},</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  {{<span class="stringliteral">"outputTensor"</span>, { 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  6.0f, 7.0f, 7.0f,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  9.0f, 9.0f, 9.0f }}});</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> }</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="keyword">struct </span>MinimumBroadcastFixture4D : MinimumFixture</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  MinimumBroadcastFixture4D() : MinimumFixture(<span class="stringliteral">"[ 1, 1, 2, 1 ]"</span>,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="stringliteral">"[ 1, 2, 1, 3 ]"</span>,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="stringliteral">"[ 1, 2, 2, 3 ]"</span>) {}</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> };</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#a987870bce143386b1a18e2fd3dd10bfe"> 118</a></span> <a class="code" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#a22beb506dae13f30efcd16bf90e0df7b">BOOST_FIXTURE_TEST_CASE</a>(ParseMinimumBroadcast4D, MinimumBroadcastFixture4D)</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  RunTest<4, armnn::DataType::Float32>(</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  0,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {{<span class="stringliteral">"inputTensor1"</span>, { 2.0f,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  4.0f }},</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {<span class="stringliteral">"inputTensor2"</span>, { 1.0f, 2.0f, 3.0f,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  4.0f, 5.0f, 6.0f }}},</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  {{<span class="stringliteral">"outputTensor"</span>, { 1.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  1.0f, 2.0f, 3.0f,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  2.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  4.0f, 4.0f, 4.0f }}});</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> }</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="keyword">struct </span>MinimumBroadcastFixture4D1D : MinimumFixture</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>  MinimumBroadcastFixture4D1D() : MinimumFixture(<span class="stringliteral">"[ 1, 2, 2, 3 ]"</span>,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="stringliteral">"[ 1 ]"</span>,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="stringliteral">"[ 1, 2, 2, 3 ]"</span>) {}</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> };</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#a397f9751e9b2b537044ad50df7956199"> 139</a></span> <a class="code" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#a22beb506dae13f30efcd16bf90e0df7b">BOOST_FIXTURE_TEST_CASE</a>(ParseMinimumBroadcast4D1D, MinimumBroadcastFixture4D1D)</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>  RunTest<4, armnn::DataType::Float32>(</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  0,</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  {{<span class="stringliteral">"inputTensor1"</span>, { 0.0f, 1.0f, 2.0f,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  6.0f, 7.0f, 8.0f,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  9.0f, 10.0f, 11.0f }},</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  {<span class="stringliteral">"inputTensor2"</span>, { 5.0f }}},</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  {{<span class="stringliteral">"outputTensor"</span>, { 0.0f, 1.0f, 2.0f,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  5.0f, 5.0f, 5.0f,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  5.0f, 5.0f, 5.0f }}});</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> }</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="keyword">struct </span>MinimumBroadcastFixture1D4D : MinimumFixture</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> {</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  MinimumBroadcastFixture1D4D() : MinimumFixture(<span class="stringliteral">"[ 3 ]"</span>,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="stringliteral">"[ 1, 2, 2, 3 ]"</span>,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="stringliteral">"[ 1, 2, 2, 3 ]"</span>) {}</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> };</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#ac8219e832c3c5988459a8f482c30e1ae"> 161</a></span> <a class="code" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#a22beb506dae13f30efcd16bf90e0df7b">BOOST_FIXTURE_TEST_CASE</a>(ParseMinimumBroadcast1D4D, MinimumBroadcastFixture1D4D)</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> {</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  RunTest<4, armnn::DataType::Float32>(</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  0,</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  {{<span class="stringliteral">"inputTensor1"</span>, { 5.0f, 6.0f, 7.0f }},</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  {<span class="stringliteral">"inputTensor2"</span>, { 0.0f, 1.0f, 2.0f,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  6.0f, 7.0f, 8.0f,</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  9.0f, 10.0f, 11.0f }}},</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  {{<span class="stringliteral">"outputTensor"</span>, { 0.0f, 1.0f, 2.0f,</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  5.0f, 6.0f, 7.0f,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  5.0f, 6.0f, 7.0f }}});</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>MinimumBroadcastFixture2D0D : <span class="keyword">public</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></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>  <span class="keyword">explicit</span> MinimumBroadcastFixture2D0D()</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_JsonString = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> <span class="stringliteral"> "version": 3,</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> <span class="stringliteral"> "operator_codes": [ { "builtin_code": "MINIMUM" } ],</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> <span class="stringliteral"> "subgraphs": [ {</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> <span class="stringliteral"> "tensors": [</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"> "shape": [ 1, 2 ],</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> <span class="stringliteral"> "name": "input0",</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> <span class="stringliteral"> "zero_point": [ 0 ],</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"> },</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": [ ],</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": 2,</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> <span class="stringliteral"> "name": "input1",</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"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> <span class="stringliteral"> "zero_point": [ 0 ],</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"> {</span></div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> <span class="stringliteral"> "shape": [ 1, 2 ] ,</span></div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> <span class="stringliteral"> "buffer": 1,</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> <span class="stringliteral"> "name": "output",</span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> <span class="stringliteral"> "zero_point": [ 0 ],</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"> "inputs": [ 0 ],</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="stringliteral"> "outputs": [ 2 ],</span></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> <span class="stringliteral"> "operators": [</span></div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> <span class="stringliteral"> "inputs": [ 0, 1 ],</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="stringliteral"> "outputs": [ 2 ],</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="stringliteral"> "custom_options_format": "FLEXBUFFERS"</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"> "buffers" : [</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"> { },</span></div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> <span class="stringliteral"> { "data": [ 0, 0, 0, 64 ] }</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="stringliteral"> ]</span></div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> <span class="stringliteral"> }</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"> Setup();</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"></span></div><div class="line"><a name="l00245"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#ab3b1e63909cccbc071a476e7ba28d412"> 245</a></span> <span class="stringliteral"><a class="code" href="armnn_tf_lite_parser_2test_2_minimum_8cpp.xhtml#a22beb506dae13f30efcd16bf90e0df7b">BOOST_FIXTURE_TEST_CASE</a>(ParseMinimumBroadcast2D0D, MinimumBroadcastFixture2D0D)</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"> RunTest<2, armnn::DataType::Float32>(</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="stringliteral"> 0,</span></div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <span class="stringliteral"> {{</span><span class="stringliteral">"input0"</span>, { 1.0f, 5.0f }}},</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  {{<span class="stringliteral">"output"</span>, { 1.0f, 2.0f }}});</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> }</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> </div><div class="line"><a name="l00253"></a><span class="lineno"> 253</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> |