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| <a href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_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> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "../TfLiteParser.hpp"</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="keyword">using</span> <a class="code" href="classarmnn_tf_lite_parser_1_1_tf_lite_parser.xhtml">armnnTfLiteParser::TfLiteParser</a>;</div><div class="line"><a name="l00010"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d"> 10</a></span> <span class="keyword">using</span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a> = <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a>;</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> <a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(TensorflowLiteParser)</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> <span class="keyword">struct </span>GetInputsOutputsMainFixture : <span class="keyword">public</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></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>  <span class="keyword">explicit</span> GetInputsOutputsMainFixture(<span class="keyword">const</span> std::string& inputs, <span class="keyword">const</span> std::string& outputs)</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  {</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  m_JsonString = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="stringliteral"> "version": 3,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="stringliteral"> "operator_codes": [ { "builtin_code": "AVERAGE_POOL_2D" }, { "builtin_code": "CONV_2D" } ],</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="stringliteral"> "subgraphs": [</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="stringliteral"> "tensors": [</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"> "shape": [ 1, 1, 1, 1 ] ,</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="stringliteral"> "name": "OutputTensor",</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="stringliteral"> "zero_point": [ 0 ]</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"> },</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": [ 1, 2, 2, 1 ] ,</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="stringliteral"> "type": "UINT8",</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": "InputTensor",</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"> "min": [ -1.2 ],</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="stringliteral"> "max": [ 25.5 ],</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="stringliteral"> "scale": [ 0.25 ],</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="stringliteral"> "zero_point": [ 10 ]</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"> ],</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="stringliteral"> "inputs": [ 1 ],</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="stringliteral"> "outputs": [ 0 ],</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="stringliteral"> "operators": [ {</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="stringliteral"> "inputs": )"</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="stringliteral"> + inputs</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="stringliteral"> + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="stringliteral"> "outputs": )"</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="stringliteral"> + outputs</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="stringliteral"> + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="stringliteral"> "builtin_options_type": "Pool2DOptions",</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="stringliteral"> "builtin_options":</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"> "padding": "VALID",</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="stringliteral"> "stride_w": 2,</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="stringliteral"> "stride_h": 2,</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="stringliteral"> "filter_width": 2,</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="stringliteral"> "filter_height": 2,</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="stringliteral"> "fused_activation_function": "NONE"</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"> "custom_options_format": "FLEXBUFFERS"</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"> },</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"> "tensors": [</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="stringliteral"> "shape": [ 1, 3, 3, 1 ],</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="stringliteral"> "name": "ConvInputTensor",</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="stringliteral"> "zero_point": [ 0 ],</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"> "shape": [ 1, 1, 1, 1 ],</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="stringliteral"> "buffer": 1,</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="stringliteral"> "name": "ConvOutputTensor",</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="stringliteral"> "max": [ 511.0 ],</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="stringliteral"> "scale": [ 2.0 ],</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="stringliteral"> "zero_point": [ 0 ],</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"> "shape": [ 1, 3, 3, 1 ],</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="stringliteral"> "buffer": 2,</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="stringliteral"> "name": "filterTensor",</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="stringliteral"> "zero_point": [ 0 ],</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="stringliteral"> "inputs": [ 0 ],</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="stringliteral"> "outputs": [ 1 ],</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="stringliteral"> "operators": [</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="stringliteral"> "inputs": [ 0, 2 ],</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="stringliteral"> "outputs": [ 1 ],</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="stringliteral"> "builtin_options_type": "Conv2DOptions",</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="stringliteral"> "builtin_options": {</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="stringliteral"> "padding": "VALID",</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="stringliteral"> "stride_w": 1,</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="stringliteral"> "stride_h": 1,</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="stringliteral"> "fused_activation_function": "NONE"</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"> "custom_options_format": "FLEXBUFFERS"</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"> ],</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="stringliteral"> "description": "Test Subgraph Inputs Outputs",</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="stringliteral"> "buffers" : [</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></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="stringliteral"> { "data": [ 2,1,0, 6,2,1, 4,1,2 ], },</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="stringliteral"> { },</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="stringliteral"> ]</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"></span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="stringliteral"> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a69fc8e7f42386fa67732cb8c98d8b024">ReadStringToBinary</a>();</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="stringliteral"></span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="stringliteral">};</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="stringliteral"></span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="stringliteral"></span><span class="keyword">struct </span>GetEmptyInputsOutputsFixture : GetInputsOutputsMainFixture</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> {</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  GetEmptyInputsOutputsFixture() : GetInputsOutputsMainFixture(<span class="stringliteral">"[ ]"</span>, <span class="stringliteral">"[ ]"</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"> 147</span> </div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="keyword">struct </span>GetInputsOutputsFixture : GetInputsOutputsMainFixture</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> {</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  GetInputsOutputsFixture() : GetInputsOutputsMainFixture(<span class="stringliteral">"[ 1 ]"</span>, <span class="stringliteral">"[ 0 ]"</span>) {}</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> };</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div><div class="line"><a name="l00153"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a335c7484ecd7511ded76bacd7a5ae10e"> 153</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetEmptyInputs, GetEmptyInputsOutputsFixture)</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>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  TfLiteParser::TensorRawPtrVector tensors = TfLiteParser::GetInputs(model, 0, 0);</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  BOOST_CHECK_EQUAL(0, tensors.size());</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</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"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ab5a78eaf3349aa3d92b8e52573702bbc"> 160</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetEmptyOutputs, GetEmptyInputsOutputsFixture)</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> {</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  TfLiteParser::TensorRawPtrVector tensors = TfLiteParser::GetOutputs(model, 0, 0);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  BOOST_CHECK_EQUAL(0, tensors.size());</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> }</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a098c20531aa4520e3d89e302b4699cb7"> 167</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetInputs, GetInputsOutputsFixture)</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> {</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  TfLiteParser::TensorRawPtrVector tensors = TfLiteParser::GetInputs(model, 0, 0);</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  BOOST_CHECK_EQUAL(1, tensors.size());</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  CheckTensors(tensors[0], 4, { 1, 2, 2, 1 }, tflite::TensorType::TensorType_UINT8, 1,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="stringliteral">"InputTensor"</span>, { -1.2f }, { 25.5f }, { 0.25f }, { 10 });</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"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a1e76c0b0b048ec93fc449a3dce7a8200"> 176</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetOutputs, GetInputsOutputsFixture)</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>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  TfLiteParser::TensorRawPtrVector tensors = TfLiteParser::GetOutputs(model, 0, 0);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  BOOST_CHECK_EQUAL(1, tensors.size());</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  CheckTensors(tensors[0], 4, { 1, 1, 1, 1 }, tflite::TensorType::TensorType_UINT8, 0,</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="stringliteral">"OutputTensor"</span>, { 0.0f }, { 255.0f }, { 1.0f }, { 0 });</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> }</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a1c501913b832b10ff30b12053c586c46"> 185</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetInputsMultipleInputs, GetInputsOutputsFixture)</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> {</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  TfLiteParser::TensorRawPtrVector tensors = TfLiteParser::GetInputs(model, 1, 0);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  BOOST_CHECK_EQUAL(2, tensors.size());</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  CheckTensors(tensors[0], 4, { 1, 3, 3, 1 }, tflite::TensorType::TensorType_UINT8, 0,</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="stringliteral">"ConvInputTensor"</span>, { }, { }, { 1.0f }, { 0 });</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  CheckTensors(tensors[1], 4, { 1, 3, 3, 1 }, tflite::TensorType::TensorType_UINT8, 2,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="stringliteral">"filterTensor"</span>, { 0.0f }, { 255.0f }, { 1.0f }, { 0 });</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> }</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div><div class="line"><a name="l00196"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#acc9175ff0d037236039f6de903412153"> 196</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetOutputs2, GetInputsOutputsFixture)</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> {</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  TfLiteParser::TensorRawPtrVector tensors = TfLiteParser::GetOutputs(model, 1, 0);</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  BOOST_CHECK_EQUAL(1, tensors.size());</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  CheckTensors(tensors[0], 4, { 1, 1, 1, 1 }, tflite::TensorType::TensorType_UINT8, 1,</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="stringliteral">"ConvOutputTensor"</span>, { 0.0f }, { 511.0f }, { 2.0f }, { 0 });</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> }</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#afef83a0459066ae76b0cd1ec5ae29687"> 205</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#afef83a0459066ae76b0cd1ec5ae29687">BOOST_AUTO_TEST_CASE</a>(GetInputsNullModel)</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> {</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  BOOST_CHECK_THROW(TfLiteParser::GetInputs(<span class="keyword">nullptr</span>, 0, 0), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> }</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span> </div><div class="line"><a name="l00210"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ace561296442c03f91bc6ddea34e4265a"> 210</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#afef83a0459066ae76b0cd1ec5ae29687">BOOST_AUTO_TEST_CASE</a>(GetOutputsNullModel)</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> {</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  BOOST_CHECK_THROW(TfLiteParser::GetOutputs(<span class="keyword">nullptr</span>, 0, 0), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> }</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> </div><div class="line"><a name="l00215"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a5efb75e14733af13b8db287c346cbbb3"> 215</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetInputsInvalidSubgraph, GetInputsOutputsFixture)</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> {</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  BOOST_CHECK_THROW(TfLiteParser::GetInputs(model, 2, 0), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> }</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> </div><div class="line"><a name="l00221"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a702114bf6f59f0b397a5dc26383b6f6d"> 221</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetOutputsInvalidSubgraph, GetInputsOutputsFixture)</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> {</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  BOOST_CHECK_THROW(TfLiteParser::GetOutputs(model, 2, 0), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> }</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div><div class="line"><a name="l00227"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#afe09776bdc4df4e737426d904f4559bb"> 227</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetInputsInvalidOperator, GetInputsOutputsFixture)</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> {</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  BOOST_CHECK_THROW(TfLiteParser::GetInputs(model, 0, 1), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> }</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> </div><div class="line"><a name="l00233"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a5f5ca0db2c69d69ace0a82fb6210d2e0"> 233</a></span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a>(GetOutputsInvalidOperator, GetInputsOutputsFixture)</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> {</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  BOOST_CHECK_THROW(TfLiteParser::GetOutputs(model, 0, 1), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> }</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</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="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp_xhtml_afef83a0459066ae76b0cd1ec5ae29687"><div class="ttname"><a href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#afef83a0459066ae76b0cd1ec5ae29687">BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(GetInputsNullModel)</div><div class="ttdef"><b>Definition:</b> <a href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp_source.xhtml#l00147">GetInputsOutputs.cpp:147</a></div></div> |
| <div class="ttc" id="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp_xhtml_ae636b47986a5a3f38e00a366c1c0060e"><div class="ttname"><a href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#ae636b47986a5a3f38e00a366c1c0060e">BOOST_FIXTURE_TEST_CASE</a></div><div class="ttdeci">BOOST_FIXTURE_TEST_CASE(GetInput, GetInputsOutputsMainFixture)</div><div class="ttdef"><b>Definition:</b> <a href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp_source.xhtml#l00069">GetInputsOutputs.cpp:69</a></div></div> |
| <div class="ttc" id="classarmnn_tf_lite_parser_1_1_tf_lite_parser_xhtml"><div class="ttname"><a href="classarmnn_tf_lite_parser_1_1_tf_lite_parser.xhtml">armnnTfLiteParser::TfLiteParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_parser_8hpp_source.xhtml#l00019">TfLiteParser.hpp:19</a></div></div> |
| <div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a69fc8e7f42386fa67732cb8c98d8b024"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a69fc8e7f42386fa67732cb8c98d8b024">ParserFlatbuffersFixture::ReadStringToBinary</a></div><div class="ttdeci">bool ReadStringToBinary()</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00102">ParserFlatbuffersFixture.hpp:102</a></div></div> |
| <div class="ttc" id="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp_xhtml_a503ae4f55dae1486e53978657083b35d"><div class="ttname"><a href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a></div><div class="ttdeci">std::unique_ptr< onnx::ModelProto > ModelPtr</div><div class="ttdef"><b>Definition:</b> <a href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp_source.xhtml#l00012">GetInputsOutputs.cpp:12</a></div></div> |
| <div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00037">ParserFlatbuffersFixture.hpp:37</a></div></div> |
| <div class="ttc" id="_parser_flatbuffers_fixture_8hpp_xhtml"><div class="ttname"><a href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a></div></div> |
| <div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div> |
| <div class="ttc" id="classarmnn_1_1_parse_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00092">Exceptions.hpp:92</a></div></div> |
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