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<div class="title">OnnxParser.hpp</div> </div>
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<a href="_onnx_parser_8hpp.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">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_i_onnx_parser_8hpp.xhtml">armnnOnnxParser/IOnnxParser.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "google/protobuf/repeated_field.h"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <unordered_map></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <onnx/onnx.pb.h></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> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</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">class </span>TensorInfo;</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">enum class</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">ActivationFunction</a>;</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> }</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn_onnx_parser.xhtml">armnnOnnxParser</a></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> </div><div class="line"><a name="l00023"></a><span class="lineno"><a class="line" href="namespacearmnn_onnx_parser.xhtml#a503ae4f55dae1486e53978657083b35d"> 23</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn_onnx_parser.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a> = std::unique_ptr<onnx::ModelProto>;</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"><a class="line" href="classarmnn_onnx_parser_1_1_onnx_parser.xhtml"> 25</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_onnx_parser_1_1_onnx_parser.xhtml">OnnxParser</a> : <span class="keyword">public</span> <a class="code" href="classarmnn_onnx_parser_1_1_i_onnx_parser.xhtml">IOnnxParser</a></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> {</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">using</span> OperationParsingFunction = void(<a class="code" href="classarmnn_onnx_parser_1_1_onnx_parser.xhtml">OnnxParser</a>::*)(<span class="keyword">const</span> onnx::NodeProto& NodeProto);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"><a class="line" href="classarmnn_onnx_parser_1_1_onnx_parser.xhtml#ac81510b21cb2b5719cce34474ad01675"> 32</a></span>  <span class="keyword">using</span> <a class="code" href="classarmnn_onnx_parser_1_1_onnx_parser.xhtml#ac81510b21cb2b5719cce34474ad01675">GraphPtr</a> = std::unique_ptr<onnx::GraphProto>;</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"></span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"> /// Create the network from a protobuf binary file on disk</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"></span> <span class="keyword">virtual</span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> CreateNetworkFromBinaryFile(<span class="keyword">const</span> <span class="keywordtype">char</span>* graphFile) <span class="keyword">override</span>;</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment"></span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> /// Create the network from a protobuf text file on disk</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="comment"></span> <span class="keyword">virtual</span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> CreateNetworkFromTextFile(<span class="keyword">const</span> <span class="keywordtype">char</span>* graphFile) <span class="keyword">override</span>;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"></span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"> /// Create the network directly from protobuf text in a string. Useful for debugging/testing</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"></span> <span class="keyword">virtual</span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> CreateNetworkFromString(<span class="keyword">const</span> std::string& protoText) <span class="keyword">override</span>;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="comment"></span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment"> /// Retrieve binding info (layer id and tensor info) for the network input identified by the given layer name</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"></span> <span class="keyword">virtual</span> <a class="code" href="namespacearmnn_onnx_parser.xhtml#a9084adbf804022c874039ad40d1939e9">BindingPointInfo</a> GetNetworkInputBindingInfo(<span class="keyword">const</span> std::string& name) <span class="keyword">const override</span>;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"></span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> /// Retrieve binding info (layer id and tensor info) for the network output identified by the given layer name</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"></span> <span class="keyword">virtual</span> <a class="code" href="namespacearmnn_onnx_parser.xhtml#a9084adbf804022c874039ad40d1939e9">BindingPointInfo</a> GetNetworkOutputBindingInfo(<span class="keyword">const</span> std::string& name) <span class="keyword">const override</span>;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="keyword">public</span>:</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>  <a class="code" href="classarmnn_onnx_parser_1_1_onnx_parser.xhtml">OnnxParser</a>();</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">static</span> <a class="code" href="namespacearmnn_onnx_parser.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a> LoadModelFromBinaryFile(<span class="keyword">const</span> <span class="keywordtype">char</span> * fileName);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keyword">static</span> <a class="code" href="namespacearmnn_onnx_parser.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a> LoadModelFromTextFile(<span class="keyword">const</span> <span class="keywordtype">char</span> * fileName);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keyword">static</span> <a class="code" href="namespacearmnn_onnx_parser.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a> LoadModelFromString(<span class="keyword">const</span> std::string& inputString);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"></span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> /// Retrieve inputs names</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"></span> <span class="keyword">static</span> std::vector<std::string> GetInputs(<a class="code" href="namespacearmnn_onnx_parser.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a>& model);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="comment"></span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="comment"> /// Retrieve outputs names</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="comment"></span> <span class="keyword">static</span> std::vector<std::string> GetOutputs(<a class="code" href="namespacearmnn_onnx_parser.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a>& model);</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">private</span>:</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"></span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment"> /// Parses a ModelProto loaded into memory from one of the other CreateNetwork*</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment"></span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> CreateNetworkFromModel(onnx::ModelProto& model);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="comment"></span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="comment"> /// Parse every node and make the connection between the resulting tensors</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="comment"></span> <span class="keywordtype">void</span> LoadGraph();</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordtype">void</span> SetupInfo(<span class="keyword">const</span> google::protobuf::RepeatedPtrField<onnx::ValueInfoProto >* list);</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>  std::vector<armnn::TensorInfo> ComputeOutputInfo(std::vector<std::string> outNames,</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  std::vector<armnn::TensorShape> inputShapes);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keywordtype">void</span> DetectFullyConnected();</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Location></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordtype">void</span> GetInputAndParam(<span class="keyword">const</span> onnx::NodeProto& node,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  std::string* inputName,</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  std::string* constName,</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keyword">const</span> Location& location);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Location></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordtype">void</span> To1DTensor(<span class="keyword">const</span> std::string &name, <span class="keyword">const</span> Location& location);</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>  <span class="comment">//Broadcast Preparation functions</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  std::pair<std::string, std::string> AddPrepareBroadcast(<span class="keyword">const</span> std::string& input0, <span class="keyword">const</span> std::string& input1);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keywordtype">void</span> PrependForBroadcast(<span class="keyword">const</span> std::string& outputName, <span class="keyword">const</span> std::string& input0, <span class="keyword">const</span> std::string& input1);</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>  <span class="keywordtype">void</span> CreateConstantLayer(<span class="keyword">const</span> std::string& tensorName, <span class="keyword">const</span> std::string& layerName);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordtype">void</span> CreateReshapeLayer(<span class="keyword">const</span> std::string& inputName,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keyword">const</span> std::string& outputName,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keyword">const</span> std::string& layerName);</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordtype">void</span> ParseBatchNormalization(<span class="keyword">const</span> onnx::NodeProto& node);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordtype">void</span> ParseConstant(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</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="keywordtype">void</span> ParseMaxPool(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordtype">void</span> ParseAveragePool(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordtype">void</span> ParseGlobalAveragePool(<span class="keyword">const</span> onnx::NodeProto& node);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordtype">void</span> AddPoolingLayer(<span class="keyword">const</span> onnx::NodeProto& nodeProto, <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a>& desc);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordtype">void</span> ParseReshape(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordtype">void</span> ParseActivation(<span class="keyword">const</span> onnx::NodeProto& nodeProto, <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a> func);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordtype">void</span> ParseSigmoid(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordtype">void</span> ParseTanh(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordtype">void</span> ParseRelu(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordtype">void</span> ParseLeakyRelu(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordtype">void</span> AddConvLayerWithDepthwiseConv(<span class="keyword">const</span> onnx::NodeProto& node, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a>& convDesc);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keywordtype">void</span> ParseConv(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</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>  <span class="keywordtype">void</span> ParseAdd(<span class="keyword">const</span> onnx::NodeProto& nodeProto);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keywordtype">void</span> AddFullyConnected(<span class="keyword">const</span> onnx::NodeProto& matmulNode, <span class="keyword">const</span> onnx::NodeProto* addNode = <span class="keyword">nullptr</span>);</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>  <span class="keywordtype">void</span> RegisterInputSlots(<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer, <span class="keyword">const</span> std::vector<std::string>& tensorIndexes);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordtype">void</span> RegisterOutputSlots(<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer, <span class="keyword">const</span> std::vector<std::string>& tensorIndexes);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> </div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordtype">void</span> SetupInputLayers();</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keywordtype">void</span> SetupOutputLayers();</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keywordtype">void</span> ResetParser();</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordtype">void</span> Cleanup();</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  std::pair<armnn::ConstTensor, std::unique_ptr<float[]>> CreateConstTensor(<span class="keyword">const</span> std::string name);</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>  <span class="keyword">template</span> <<span class="keyword">typename</span> TypeList, <span class="keyword">typename</span> Location></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keywordtype">void</span> ValidateInputs(<span class="keyword">const</span> onnx::NodeProto& node,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  TypeList validInputs,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keyword">const</span> Location& location);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="comment"></span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="comment"> /// The network we're building. Gets cleared after it is passed to the user</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="comment"></span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> m_Network;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="comment"></span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="comment"> /// Ptr to the graph we're building the network from</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="comment"></span> <a class="code" href="classarmnn_onnx_parser_1_1_onnx_parser.xhtml#ac81510b21cb2b5719cce34474ad01675">GraphPtr</a> m_Graph;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="comment"></span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment"> /// Map of the information for every tensor</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment"></span> <span class="keyword">struct </span>OnnxTensor</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>  std::unique_ptr<armnn::TensorInfo> m_info;</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  std::unique_ptr<const onnx::TensorProto> m_tensor;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">onnx::TensorProto::DataType</a> m_dtype;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  OnnxTensor() : m_info(nullptr), m_tensor(nullptr), m_dtype(onnx::TensorProto::FLOAT) { }</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keywordtype">bool</span> isConstant() { <span class="keywordflow">return</span> m_tensor != <span class="keyword">nullptr</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"> 153</span>  std::unordered_map<std::string, OnnxTensor> m_TensorsInfo;</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="comment"></span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="comment"> /// map of onnx operation names to parsing member functions</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="comment"></span> <span class="keyword">static</span> <span class="keyword">const</span> std::map<std::string, OperationParsingFunction> m_ParserFunctions;</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="comment"></span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="comment"> /// A mapping of an output slot to each of the input slots it should be connected to</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="comment"> /// The outputSlot is from the layer that creates this tensor as one of its ouputs</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> <span class="comment"> /// The inputSlots are from the layers that use this tensor as one of their inputs</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="comment"></span> <span class="keyword">struct </span>TensorSlots</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>  <a class="code" href="classarmnn_1_1_i_output_slot.xhtml">armnn::IOutputSlot</a>* outputSlot;</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  std::vector<armnn::IInputSlot*> inputSlots;</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>  TensorSlots() : outputSlot(nullptr) { }</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  };<span class="comment"></span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="comment"> /// Map of the tensor names to their connections for the connections of the layers of the graph</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="comment"></span> std::unordered_map<std::string, TensorSlots> m_TensorConnections;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> <span class="comment"></span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> <span class="comment"> /// Map of the tensor names to their node and index in graph.node()</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> <span class="comment"></span> std::unordered_map<std::string, std::pair<const onnx::NodeProto*, int>> m_OutputsMap;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> <span class="comment"></span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <span class="comment"> /// Number of times a specific node (identified by his index number) was used as input</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> <span class="comment"> /// and list of the nodes it was fused with</span></div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="comment"></span> <span class="keyword">struct </span>UsageSummary</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>  std::vector<size_t> fusedWithNodes;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keywordtype">size_t</span> inputForNodes;</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>  UsageSummary() : fusedWithNodes({}), inputForNodes(0) { }</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </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"> 185</span>  std::vector<UsageSummary> m_OutputsFusedAndUsed;</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> }</div><div class="ttc" id="classarmnn_onnx_parser_1_1_onnx_parser_xhtml"><div class="ttname"><a href="classarmnn_onnx_parser_1_1_onnx_parser.xhtml">armnnOnnxParser::OnnxParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_onnx_parser_8hpp_source.xhtml#l00025">OnnxParser.hpp:25</a></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#l00061">INetwork.hpp:61</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00392">Descriptors.hpp:392</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
<div class="ttc" id="namespacearmnn_onnx_parser_xhtml_a503ae4f55dae1486e53978657083b35d"><div class="ttname"><a href="namespacearmnn_onnx_parser.xhtml#a503ae4f55dae1486e53978657083b35d">armnnOnnxParser::ModelPtr</a></div><div class="ttdeci">std::unique_ptr< onnx::ModelProto > ModelPtr</div><div class="ttdef"><b>Definition:</b> <a href="_onnx_parser_8hpp_source.xhtml#l00023">OnnxParser.hpp:23</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_onnx_parser_1_1_onnx_parser_xhtml_ac81510b21cb2b5719cce34474ad01675"><div class="ttname"><a href="classarmnn_onnx_parser_1_1_onnx_parser.xhtml#ac81510b21cb2b5719cce34474ad01675">armnnOnnxParser::OnnxParser::GraphPtr</a></div><div class="ttdeci">std::unique_ptr< onnx::GraphProto > GraphPtr</div><div class="ttdef"><b>Definition:</b> <a href="_onnx_parser_8hpp_source.xhtml#l00032">OnnxParser.hpp:32</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml">armnn::IOutputSlot</a></div><div class="ttdoc">An output connection slot for a layer. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00037">INetwork.hpp:37</a></div></div>
<div class="ttc" id="classarmnn_onnx_parser_1_1_i_onnx_parser_xhtml"><div class="ttname"><a href="classarmnn_onnx_parser_1_1_i_onnx_parser.xhtml">armnnOnnxParser::IOnnxParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_onnx_parser_8hpp_source.xhtml#l00022">IOnnxParser.hpp:22</a></div></div>
<div class="ttc" id="_i_onnx_parser_8hpp_xhtml"><div class="ttname"><a href="_i_onnx_parser_8hpp.xhtml">IOnnxParser.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_onnx_parser_xhtml"><div class="ttname"><a href="namespacearmnn_onnx_parser.xhtml">armnnOnnxParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_onnx_parser_8hpp_source.xhtml#l00014">IOnnxParser.hpp:14</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#l00101">INetwork.hpp:101</a></div></div>
<div class="ttc" id="namespacearmnn_onnx_parser_xhtml_a9084adbf804022c874039ad40d1939e9"><div class="ttname"><a href="namespacearmnn_onnx_parser.xhtml#a9084adbf804022c874039ad40d1939e9">armnnOnnxParser::BindingPointInfo</a></div><div class="ttdeci">armnn::BindingPointInfo BindingPointInfo</div><div class="ttdef"><b>Definition:</b> <a href="_i_onnx_parser_8hpp_source.xhtml#l00017">IOnnxParser.hpp:17</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00313">Descriptors.hpp:313</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9ea"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a></div><div class="ttdeci">ActivationFunction</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00055">Types.hpp:55</a></div></div>
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