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<a href="_unsupported_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 © 2019 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 "<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="preprocessor">#include <<a class="code" href="_layer_visitor_base_8hpp.xhtml">armnn/LayerVisitorBase.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_assert_8hpp.xhtml">armnn/utility/Assert.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_numeric_cast_8hpp.xhtml">armnn/utility/NumericCast.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_polymorphic_downcast_8hpp.xhtml">armnn/utility/PolymorphicDowncast.hpp</a>></span></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="preprocessor">#include <<a class="code" href="_stand_in_layer_8hpp.xhtml">layers/StandInLayer.hpp</a>></span></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="preprocessor">#include <boost/test/unit_test.hpp></span></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> <span class="preprocessor">#include <sstream></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(TensorflowLiteParser)</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> </div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="keyword">class </span>StandInLayerVerifier : <span class="keyword">public</span> <a class="code" href="classarmnn_1_1_layer_visitor_base.xhtml">LayerVisitorBase</a><VisitorThrowingPolicy></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> {</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  StandInLayerVerifier(<span class="keyword">const</span> std::vector<TensorInfo>& inputInfos,</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keyword">const</span> std::vector<TensorInfo>& outputInfos)</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  : <a class="code" href="classarmnn_1_1_layer_visitor_base.xhtml">LayerVisitorBase</a><<a class="code" href="structarmnn_1_1_visitor_throwing_policy.xhtml">VisitorThrowingPolicy</a>>()</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  , m_InputInfos(inputInfos)</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  , m_OutputInfos(outputInfos) {}</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordtype">void</span> VisitInputLayer(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>*, <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a>, <span class="keyword">const</span> <span class="keywordtype">char</span>*)<span class="keyword"> override </span>{}</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordtype">void</span> VisitOutputLayer(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>*, <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a>, <span class="keyword">const</span> <span class="keywordtype">char</span>*)<span class="keyword"> override </span>{}</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordtype">void</span> VisitStandInLayer(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer,</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml">StandInDescriptor</a>& descriptor,</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>*)<span class="keyword"> override</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(m_InputInfos.size());</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  BOOST_CHECK(descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">m_NumInputs</a> == numInputs);</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>() == numInputs);</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(m_OutputInfos.size());</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  BOOST_CHECK(descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a> == numOutputs);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>() == numOutputs);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_stand_in_layer.xhtml">StandInLayer</a>* standInLayer = PolymorphicDowncast<const StandInLayer*>(layer);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < numInputs; ++i)</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  {</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>* connectedSlot = standInLayer->GetInputSlot(i).GetConnectedOutputSlot();</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  BOOST_CHECK(connectedSlot != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputInfo = connectedSlot-><a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  BOOST_CHECK(inputInfo == m_InputInfos[i]);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  }</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < numOutputs; ++i)</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  {</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputInfo = layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(i).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  BOOST_CHECK(outputInfo == m_OutputInfos[i]);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  }</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  }</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  std::vector<TensorInfo> m_InputInfos;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  std::vector<TensorInfo> m_OutputInfos;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> };</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="keyword">class </span>DummyCustomFixture : <span class="keyword">public</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keyword">explicit</span> DummyCustomFixture(<span class="keyword">const</span> std::vector<TensorInfo>& inputInfos,</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">const</span> std::vector<TensorInfo>& outputInfos)</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  : <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a>()</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  , m_StandInLayerVerifier(inputInfos, outputInfos)</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  {</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(inputInfos.size());</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(numInputs > 0);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(outputInfos.size());</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(numOutputs > 0);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  m_JsonString = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="stringliteral"> "version": 3,</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="stringliteral"> "operator_codes": [{</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="stringliteral"> "builtin_code": "CUSTOM",</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="stringliteral"> "custom_code": "DummyCustomOperator"</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="stringliteral"> }],</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="stringliteral"> "subgraphs": [ {</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="stringliteral"> "tensors": [)";</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><span class="comment">// Add input tensors</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < numInputs; ++i)</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  {</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputInfo = inputInfos[i];</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  m_JsonString += R<span class="stringliteral">"(</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="stringliteral"> "shape": )" + GetTensorShapeAsString(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()) + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="stringliteral"> "type": )" + GetDataTypeAsString(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()) + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="stringliteral"> "name": "inputTensor)" + std::to_string(i) + R</span><span class="stringliteral">"(",</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="stringliteral"> "scale": [ )" + std::to_string(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>()) + R</span><span class="stringliteral">"( ],</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="stringliteral"> "zero_point": [ )" + std::to_string(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>()) + R</span><span class="stringliteral">"( ],</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="stringliteral"> },)";</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="stringliteral"></span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="stringliteral"> </span><span class="comment">// Add output tensors</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < numOutputs; ++i)</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  {</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputInfo = outputInfos[i];</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  m_JsonString += R<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"> "shape": )" + GetTensorShapeAsString(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()) + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="stringliteral"> "type": )" + GetDataTypeAsString(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()) + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="stringliteral"> "name": "outputTensor)" + std::to_string(i) + R</span><span class="stringliteral">"(",</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="stringliteral"> "scale": [ )" + std::to_string(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>()) + R</span><span class="stringliteral">"( ],</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="stringliteral"> "zero_point": [ )" + std::to_string(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>()) + R</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></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="stringliteral"></span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="stringliteral"> </span><span class="keywordflow">if</span> (i + 1 < numOutputs)</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>  m_JsonString += <span class="stringliteral">","</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"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keyword">const</span> std::string inputIndices = GetIndicesAsString(0u, numInputs - 1u);</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">const</span> std::string outputIndices = GetIndicesAsString(numInputs, numInputs + numOutputs - 1u);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// Add dummy custom operator</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  m_JsonString += R<span class="stringliteral">"(],</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="stringliteral"> "inputs": )" + inputIndices + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="stringliteral"> "outputs": )" + outputIndices + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="stringliteral"> "operators": [</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> <span class="stringliteral"> "inputs": )" + inputIndices + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> <span class="stringliteral"> "outputs": )" + outputIndices + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="stringliteral"> "builtin_options_type": 0,</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> <span class="stringliteral"> "custom_options": [ ],</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="stringliteral"> "custom_options_format": "FLEXBUFFERS"</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="stringliteral"> } ],</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="stringliteral"> "buffers" : [</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="stringliteral"> { },</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> <span class="stringliteral"> { }</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="stringliteral"> ]</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="stringliteral"> )";</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> <span class="stringliteral"></span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> <span class="stringliteral"> ReadStringToBinary();</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> <span class="stringliteral"></span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="stringliteral"> </span><span class="keywordtype">void</span> RunTest()</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  {</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = m_Parser->CreateNetworkFromBinary(m_GraphBinary);</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  network->Accept(m_StandInLayerVerifier);</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">private</span>:</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keyword">static</span> std::string GetTensorShapeAsString(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& tensorShape)</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  {</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  std::stringstream stream;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  stream << <span class="stringliteral">"[ "</span>;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  {</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  stream << tensorShape[i];</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordflow">if</span> (i + 1 < tensorShape.GetNumDimensions())</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>  stream << <span class="stringliteral">","</span>;</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  }</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  stream << <span class="stringliteral">" "</span>;</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  }</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  stream << <span class="stringliteral">"]"</span>;</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="keywordflow">return</span> stream.str();</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  }</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keyword">static</span> std::string GetDataTypeAsString(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType)</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>  <span class="keywordflow">switch</span> (dataType)</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  {</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>: <span class="keywordflow">return</span> <span class="stringliteral">"FLOAT32"</span>;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>: <span class="keywordflow">return</span> <span class="stringliteral">"UINT8"</span>;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keywordflow">default</span>: <span class="keywordflow">return</span> <span class="stringliteral">"UNKNOWN"</span>;</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  }</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  }</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keyword">static</span> std::string GetIndicesAsString(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> first, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> last)</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  {</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  std::stringstream stream;</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  stream << <span class="stringliteral">"[ "</span>;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = first; i <= last ; ++i)</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>  stream << i;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">if</span> (i + 1 <= last)</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>  stream << <span class="stringliteral">","</span>;</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>  stream << <span class="stringliteral">" "</span>;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  }</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  stream << <span class="stringliteral">"]"</span>;</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> </div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keywordflow">return</span> stream.str();</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"> 221</span>  StandInLayerVerifier m_StandInLayerVerifier;</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> </div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="keyword">class </span>DummyCustom1Input1OutputFixture : <span class="keyword">public</span> DummyCustomFixture</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> <span class="keyword">public</span>:</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  DummyCustom1Input1OutputFixture()</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  : DummyCustomFixture({ <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>) },</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  { <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>) }) {}</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> };</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> <span class="keyword">class </span>DummyCustom2Inputs1OutputFixture : <span class="keyword">public</span> DummyCustomFixture</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> {</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  DummyCustom2Inputs1OutputFixture()</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  : DummyCustomFixture({ <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>) },</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  { <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 3, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>) }) {}</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> </div><div class="line"><a name="l00240"></a><span class="lineno"><a class="line" href="_unsupported_8cpp.xhtml#aae7fa857598a8590c2efe13832774dc9"> 240</a></span> <a class="code" href="_unsupported_8cpp.xhtml#aae7fa857598a8590c2efe13832774dc9">BOOST_FIXTURE_TEST_CASE</a>(UnsupportedCustomOperator1Input1Output, DummyCustom1Input1OutputFixture)</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> {</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  RunTest();</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> }</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> </div><div class="line"><a name="l00245"></a><span class="lineno"><a class="line" href="_unsupported_8cpp.xhtml#aa79dc79c1094831a55a21fbb8d4c12f5"> 245</a></span> <a class="code" href="_unsupported_8cpp.xhtml#aae7fa857598a8590c2efe13832774dc9">BOOST_FIXTURE_TEST_CASE</a>(UnsupportedCustomOperator2Inputs1Output, DummyCustom2Inputs1OutputFixture)</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> {</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  RunTest();</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> }</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</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="classarmnn_1_1_i_connectable_layer_xhtml_ac2dac3b61c94de52093616be4ab17f8d"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#ac2dac3b61c94de52093616be4ab17f8d">armnn::IConnectableLayer::GetNumOutputSlots</a></div><div class="ttdeci">virtual unsigned int GetNumOutputSlots() const =0</div><div class="ttdoc">Returns the number of connectable output slots. </div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00062">INetwork.hpp:62</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a9c2cba04b6d7ace4fc2a2436b82a5a63"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a9c2cba04b6d7ace4fc2a2436b82a5a63">armnn::IConnectableLayer::GetNumInputSlots</a></div><div class="ttdeci">virtual unsigned int GetNumInputSlots() const =0</div><div class="ttdoc">Returns the number of connectable input slots. </div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00187">Tensor.hpp:187</a></div></div>
<div class="ttc" id="_unsupported_8cpp_xhtml_aae7fa857598a8590c2efe13832774dc9"><div class="ttname"><a href="_unsupported_8cpp.xhtml#aae7fa857598a8590c2efe13832774dc9">BOOST_FIXTURE_TEST_CASE</a></div><div class="ttdeci">BOOST_FIXTURE_TEST_CASE(UnsupportedCustomOperator1Input1Output, DummyCustom1Input1OutputFixture)</div><div class="ttdef"><b>Definition:</b> <a href="_unsupported_8cpp_source.xhtml#l00240">Unsupported.cpp:240</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="structarmnn_1_1_visitor_throwing_policy_xhtml"><div class="ttname"><a href="structarmnn_1_1_visitor_throwing_policy.xhtml">armnn::VisitorThrowingPolicy</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_visitor_base_8hpp_source.xhtml#l00013">LayerVisitorBase.hpp:13</a></div></div>
<div class="ttc" id="_stand_in_layer_8hpp_xhtml"><div class="ttname"><a href="_stand_in_layer_8hpp.xhtml">StandInLayer.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_stand_in_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_stand_in_layer.xhtml">armnn::StandInLayer</a></div><div class="ttdoc">This layer represents an unknown operation in the input graph. </div><div class="ttdef"><b>Definition:</b> <a href="_stand_in_layer_8hpp_source.xhtml#l00014">StandInLayer.hpp:14</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</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="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a></div><div class="ttdeci">int LayerBindingId</div><div class="ttdoc">Type of identifiers for bindable layers (inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00210">Types.hpp:210</a></div></div>
<div class="ttc" id="_numeric_cast_8hpp_xhtml"><div class="ttname"><a href="_numeric_cast_8hpp.xhtml">NumericCast.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_stand_in_descriptor_xhtml_abb8a2d2bb8cc594c26aaa70c820ac5cc"><div class="ttname"><a href="structarmnn_1_1_stand_in_descriptor.xhtml#abb8a2d2bb8cc594c26aaa70c820ac5cc">armnn::StandInDescriptor::m_NumOutputs</a></div><div class="ttdeci">uint32_t m_NumOutputs</div><div class="ttdoc">Number of output tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01072">Descriptors.hpp:1072</a></div></div>
<div class="ttc" id="_polymorphic_downcast_8hpp_xhtml"><div class="ttname"><a href="_polymorphic_downcast_8hpp.xhtml">PolymorphicDowncast.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">armnn::TensorInfo::GetQuantizationOffset</a></div><div class="ttdeci">int32_t GetQuantizationOffset() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00469">Tensor.cpp:469</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00452">Tensor.cpp:452</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00194">Tensor.hpp:194</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml">armnn::OutputSlot</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00083">Layer.hpp:83</a></div></div>
<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div>
<div class="ttc" id="structarmnn_1_1_stand_in_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stand_in_descriptor.xhtml">armnn::StandInDescriptor</a></div><div class="ttdoc">A StandInDescriptor for the StandIn layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01054">Descriptors.hpp:1054</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_visitor_base_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer_visitor_base.xhtml">armnn::LayerVisitorBase</a></div><div class="ttdoc">Visitor base class with empty implementations. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_visitor_base_8hpp_source.xhtml#l00025">LayerVisitorBase.hpp:25</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="_assert_8hpp_xhtml"><div class="ttname"><a href="_assert_8hpp.xhtml">Assert.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_tensor_shape_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdoc">Function that returns the tensor rank. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00174">Tensor.cpp:174</a></div></div>
<div class="ttc" id="structarmnn_1_1_stand_in_descriptor_xhtml_aed6086070440ceb94129bef06f70173f"><div class="ttname"><a href="structarmnn_1_1_stand_in_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">armnn::StandInDescriptor::m_NumInputs</a></div><div class="ttdeci">uint32_t m_NumInputs</div><div class="ttdoc">Number of input tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01070">Descriptors.hpp:1070</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a375ca3cff9f1b005d1412dc5f3cf5b6e"><div class="ttname"><a href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00035">NumericCast.hpp:35</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a9943775a364fc4ab53b85ac88f311886"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">armnn::IOutputSlot::GetTensorInfo</a></div><div class="ttdeci">virtual const TensorInfo & GetTensorInfo() const =0</div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0</div><div class="ttdoc">Get the const output slot handle by slot index. </div></div>
<div class="ttc" id="_layer_visitor_base_8hpp_xhtml"><div class="ttname"><a href="_layer_visitor_base_8hpp.xhtml">LayerVisitorBase.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00063">Layer.cpp:63</a></div></div>
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