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<div class="title">ConversionUtils.hpp</div> </div>
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<a href="_conversion_utils_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 © 2022 Arm Ltd and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_canonical_utils_8hpp.xhtml">CanonicalUtils.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_arm_n_n_8hpp.xhtml">armnn/ArmNN.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_backend_helper_8hpp.xhtml">armnn/BackendHelper.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_assert_8hpp.xhtml">armnn/utility/Assert.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_ignore_unused_8hpp.xhtml">armnn/utility/IgnoreUnused.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</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="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_data_layout_indexed_8hpp.xhtml">armnnUtils/DataLayoutIndexed.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <<a class="code" href="_transpose_8hpp.xhtml">armnnUtils/Transpose.hpp</a>></span></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> <span class="preprocessor">#include <ActivationFunctor.h></span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <CpuExecutor.h></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include <OperationsUtils.h></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"> 23</span> <span class="preprocessor">#include <<a class="code" href="_floating_point_comparison_8hpp.xhtml">armnnUtils/FloatingPointComparison.hpp</a>></span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include <log/log.h></span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include <vector></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"><a class="line" href="_conversion_utils_8hpp.xhtml#abcb5019b10b89cbd2b96118885a026d4"> 28</a></span> <span class="keyword">inline</span> <span class="keyword">const</span> android::nn::Model::Subgraph& <a class="code" href="_conversion_utils_8hpp.xhtml#abcb5019b10b89cbd2b96118885a026d4">getMainModel</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">android::nn::Model</a>& model) { <span class="keywordflow">return</span> model.main; }</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">namespace </span><a class="code" href="namespacearmnn__driver.xhtml">armnn_driver</a></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> {</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"></span></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">/// Helper classes</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment">///</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="preprocessor">#include <nnapi/OperandTypes.h></span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include <nnapi/Result.h></span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include <nnapi/TypeUtils.h></span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="preprocessor">#include <nnapi/Types.h></span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor">#include <nnapi/Validation.h></span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798"> 43</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a> = <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">::android::nn::Model</a>;</div><div class="line"><a name="l00044"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac"> 44</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a> = <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">::android::nn::Operand</a>;</div><div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a275cd95635b854a80bb33f171d861ddc"> 45</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn__driver.xhtml#a275cd95635b854a80bb33f171d861ddc">OperandLifeTime</a> = ::android::nn::Operand::LifeTime;</div><div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a53bfb6eb38a90244ba166b641a6965d9"> 46</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn__driver.xhtml#a53bfb6eb38a90244ba166b641a6965d9">OperandType</a> = <a class="code" href="namespacearmnn__driver.xhtml#a53bfb6eb38a90244ba166b641a6965d9">::android::nn::OperandType</a>;</div><div class="line"><a name="l00047"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985"> 47</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a> = <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">::android::nn::Operation</a>;</div><div class="line"><a name="l00048"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#ace6b45d6363c32d1b93b7fce14bf6344"> 48</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn__driver.xhtml#ace6b45d6363c32d1b93b7fce14bf6344">OperationType</a> = <a class="code" href="namespacearmnn__driver.xhtml#ace6b45d6363c32d1b93b7fce14bf6344">::android::nn::OperationType</a>;</div><div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a1fa5070fa0d079873acaf7581de8a2ad"> 49</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn__driver.xhtml#a1fa5070fa0d079873acaf7581de8a2ad">ErrorStatus</a> = <a class="code" href="namespacearmnn__driver.xhtml#a1fa5070fa0d079873acaf7581de8a2ad">::android::nn::ErrorStatus</a>;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="structarmnn__driver_1_1_conversion_data.xhtml"> 51</a></span> <span class="keyword">struct </span><a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</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"><a class="line" href="structarmnn__driver_1_1_conversion_data.xhtml#a0b09b7d54e89b04521d9574a968be458"> 53</a></span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#a0b09b7d54e89b04521d9574a968be458">ConversionData</a>(<span class="keyword">const</span> std::vector<armnn::BackendId>& backends)</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  : <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#af3239731a47cf4c08a040c42ee855edc">m_Backends</a>(backends)</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  , <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#a2db3ae8d422f17d455e0ba0cb6291d2a">m_Network</a>(nullptr, nullptr)</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  , <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#a094e06eb84b3b80533c0f961f0f472de">m_DynamicInputsEncountered</a>(false)</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  {}</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="structarmnn__driver_1_1_conversion_data.xhtml#af3239731a47cf4c08a040c42ee855edc"> 59</a></span>  <span class="keyword">const</span> std::vector<armnn::BackendId> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#af3239731a47cf4c08a040c42ee855edc">m_Backends</a>;</div><div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="structarmnn__driver_1_1_conversion_data.xhtml#a2db3ae8d422f17d455e0ba0cb6291d2a"> 60</a></span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#a2db3ae8d422f17d455e0ba0cb6291d2a">m_Network</a>;</div><div class="line"><a name="l00061"></a><span class="lineno"><a class="line" href="structarmnn__driver_1_1_conversion_data.xhtml#a4df0c61eb897ecc9271a4a85604066ea"> 61</a></span>  std::vector<armnn::IOutputSlot*> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#a4df0c61eb897ecc9271a4a85604066ea">m_OutputSlotForOperand</a>;</div><div class="line"><a name="l00062"></a><span class="lineno"><a class="line" href="structarmnn__driver_1_1_conversion_data.xhtml#acb740de896710dbc576f5eaf7a9cfeaa"> 62</a></span>  std::vector<::android::nn::RunTimePoolInfo> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#acb740de896710dbc576f5eaf7a9cfeaa">m_MemPools</a>;</div><div class="line"><a name="l00063"></a><span class="lineno"><a class="line" href="structarmnn__driver_1_1_conversion_data.xhtml#a094e06eb84b3b80533c0f961f0f472de"> 63</a></span>  <span class="keywordtype">bool</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#a094e06eb84b3b80533c0f961f0f472de">m_DynamicInputsEncountered</a>;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> };</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div><div class="line"><a name="l00066"></a><span class="lineno"><a class="line" href="classarmnn__driver_1_1_layer_input_handle.xhtml"> 66</a></span> <span class="keyword">class </span><a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a></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">public</span>:</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a>();</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a>(<span class="keywordtype">bool</span> valid, <a class="code" href="classarmnn_1_1_i_output_slot.xhtml">armnn::IOutputSlot</a>* outputSlot, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo);</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>  <span class="keywordtype">bool</span> IsValid() <span class="keyword">const</span>;</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordtype">void</span> <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(<a class="code" href="classarmnn_1_1_i_input_slot.xhtml">armnn::IInputSlot</a>& inputSlot);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordtype">void</span> Disconnect(<a class="code" href="classarmnn_1_1_i_input_slot.xhtml">armnn::IInputSlot</a>& inputSlot);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& <a class="code" href="namespacearmnn_utils.xhtml#acee63cd08da47910fc166a1990988fa8">GetTensorInfo</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordtype">void</span> SanitizeQuantizationScale(<a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a>& weight, <a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a>& input);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="classarmnn_1_1_i_output_slot.xhtml">armnn::IOutputSlot</a>* GetOutputSlot() <span class="keyword">const</span>;</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">private</span>:</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="classarmnn_1_1_i_output_slot.xhtml">armnn::IOutputSlot</a>* m_OutputSlot;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordtype">bool</span> m_Valid;</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> m_TensorInfo;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> };</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"><a class="line" href="classarmnn__driver_1_1_const_tensor_pin.xhtml"> 90</a></span> <span class="keyword">class </span><a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a></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="keyword">public</span>:</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="comment">// Creates an invalid tensor pin (can be used to signal errors)</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="comment">// The optional flag can be set to indicate the tensor values were missing, but it was otherwise valid</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a>(<span class="keywordtype">bool</span> optional = <span class="keyword">false</span>);</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="comment">// @param tensorInfo TensorInfo associated with the tensor.</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="comment">// @param valueStart Start address of tensor data. Belongs to one of the memory pools associated with</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="comment">// the model being converted.</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="comment">// @param numBytes Number of bytes for the tensor data.</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& tensorInfo, <span class="keyword">const</span> <span class="keywordtype">void</span>* valueStart, uint32_t numBytes,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>& mappings);</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>  <a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a>(<span class="keyword">const</span> <a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a>& other) = <span class="keyword">delete</span>;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a>(<a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a>&& other) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordtype">bool</span> IsValid() <span class="keyword">const</span>;</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordtype">bool</span> IsOptional() <span class="keyword">const</span>;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>& GetConstTensor() <span class="keyword">const</span>;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>* GetConstTensorPtr() <span class="keyword">const</span>;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> m_ConstTensor;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> </div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="comment">// Owned memory for swizzled tensor data, only required if the tensor needed</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="comment">// swizzling. Otherwise, @ref m_ConstTensor will reference memory from one of</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="comment">// the pools associated with the model being converted.</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  std::vector<uint8_t> m_SwizzledTensorData;</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="comment">// optional flag to indicate that an invalid tensor pin is not an error, but the optional values were not given</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keywordtype">bool</span> m_Optional;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> };</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div><div class="line"><a name="l00125"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#afa2a6d5a1431289c92cea9cceeb174c9"> 125</a></span> <span class="keyword">enum class</span> <a class="code" href="namespacearmnn__driver.xhtml#afa2a6d5a1431289c92cea9cceeb174c9">ConversionResult</a></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> {</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <a class="code" href="namespacearmnn__driver.xhtml#afa2a6d5a1431289c92cea9cceeb174c9a505a83f220c02df2f85c3810cd9ceb38">Success</a>,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code" href="namespacearmnn__driver.xhtml#afa2a6d5a1431289c92cea9cceeb174c9ab7d6155514def6898ba4432a82efd28b">ErrorMappingPools</a>,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <a class="code" href="namespacearmnn__driver.xhtml#afa2a6d5a1431289c92cea9cceeb174c9a6dcca67f0df2a0038edf5a82b1399527">UnsupportedFeature</a></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> };</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> } <span class="comment">// namespace armnn_driver</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="comment"></span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="comment">///</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="comment">/// Utility functions</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="comment">///</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="comment"></span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="keyword">namespace</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">using namespace </span><a class="code" href="namespacearmnn__driver.xhtml">armnn_driver</a>;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> </div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment">// Convenience function to log the reason for failing to convert a model.</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment">// @return Always returns false (so that it can be used by callers as a quick way to signal an error and return)</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="keyword">template</span><<span class="keyword">class</span>... Args></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="keyword">static</span> <span class="keywordtype">bool</span> Fail(<span class="keyword">const</span> <span class="keywordtype">char</span>* formatStr, Args&&... args)</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>  ALOGD(formatStr, std::forward<Args>(args)...);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</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> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> <span class="comment">// Convenience macro to call an Is*Supported function and log caller name together with reason for lack of support.</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="comment">// Called as: FORWARD_LAYER_SUPPORT_FUNC(__func__, Is*Supported, backends, a, b, c, d, e)</span></div><div class="line"><a name="l00153"></a><span class="lineno"><a class="line" href="_conversion_utils_8hpp.xhtml#a6f98cfbf3171f950d1f0df30d60691a7"> 153</a></span> <span class="preprocessor">#define FORWARD_LAYER_SUPPORT_FUNC(funcName, func, backends, supported, ...) \</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="preprocessor">try \</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="preprocessor">{ \</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="preprocessor"> for (auto&& backendId : backends) \</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="preprocessor"> auto layerSupportObject = armnn::GetILayerSupportByBackendId(backendId); \</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="preprocessor"> if (layerSupportObject.IsBackendRegistered()) \</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="preprocessor"> std::string reasonIfUnsupported; \</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="preprocessor"> supported = \</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="preprocessor"> layerSupportObject.func(__VA_ARGS__, armnn::Optional<std::string&>(reasonIfUnsupported)); \</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> <span class="preprocessor"> if (supported) \</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> <span class="preprocessor"> break; \</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> <span class="preprocessor"> } \</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="preprocessor"> else \</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> <span class="preprocessor"> if (reasonIfUnsupported.size() > 0) \</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> <span class="preprocessor"> VLOG(DRIVER) << funcName << ": not supported by armnn: " << reasonIfUnsupported.c_str(); \</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> <span class="preprocessor"> } \</span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <span class="preprocessor"> else \</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="preprocessor"> VLOG(DRIVER) << funcName << ": not supported by armnn"; \</span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> <span class="preprocessor"> } \</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> <span class="preprocessor"> } \</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> <span class="preprocessor"> } \</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> <span class="preprocessor"> else \</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> <span class="preprocessor"> VLOG(DRIVER) << funcName << ": backend not registered: " << backendId.Get().c_str(); \</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> <span class="preprocessor"> } \</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> <span class="preprocessor"> } \</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> <span class="preprocessor"> if (!supported) \</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> <span class="preprocessor"> VLOG(DRIVER) << funcName << ": not supported by any specified backend"; \</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="preprocessor"> } \</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> <span class="preprocessor">} \</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> <span class="preprocessor">catch (const armnn::InvalidArgumentException &e) \</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="preprocessor">{ \</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> <span class="preprocessor"> throw armnn::InvalidArgumentException(e, "Failed to check layer support", CHECK_LOCATION()); \</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> <span class="preprocessor">}</span></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="keyword">inline</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> GetTensorShapeForOperand(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>& operand)</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">return</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>(operand.dimensions.size(), operand.dimensions.data());</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> }</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> <span class="comment">// Support within the 1.3 driver for specific tensor data types</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> IsOperandTypeSupportedForTensors(<a class="code" href="namespacearmnn__driver.xhtml#a53bfb6eb38a90244ba166b641a6965d9">OperandType</a> type)</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="keywordflow">return</span> type == OperandType::BOOL ||</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  type == OperandType::TENSOR_BOOL8 ||</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  type == OperandType::TENSOR_FLOAT16 ||</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  type == OperandType::TENSOR_FLOAT32 ||</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  type == OperandType::TENSOR_QUANT8_ASYMM ||</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  type == OperandType::TENSOR_QUANT8_ASYMM_SIGNED ||</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  type == OperandType::TENSOR_QUANT8_SYMM ||</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  type == OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL ||</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  type == OperandType::TENSOR_QUANT16_SYMM ||</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  type == OperandType::TENSOR_INT32;</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"> 215</span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> IsBool(<a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a> operand)</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>  <span class="keywordflow">return</span> operand.type == OperandType::BOOL;</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> }</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> <span class="keyword">inline</span> <span class="keywordtype">bool</span> Is12OrLaterOperand(<a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>)</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> {</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <span class="keywordflow">return</span> <span class="keyword">true</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> </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">template</span><<span class="keyword">typename</span> LayerHandleType></div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>& AddReshapeLayer(<a class="code" href="classarmnn_1_1_i_network.xhtml">armnn::INetwork</a>& network,</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  LayerHandleType& inputLayer,</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> reshapeInfo)</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>  <a class="code" href="structarmnn_1_1_reshape_descriptor.xhtml">armnn::ReshapeDescriptor</a> reshapeDescriptor;</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  reshapeDescriptor.<a class="code" href="structarmnn_1_1_reshape_descriptor.xhtml#a1178f4dafdda81f59c15145ec327f7d9">m_TargetShape</a> = reshapeInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</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>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* reshapeLayer = network.<a class="code" href="classarmnn_1_1_i_network.xhtml#a8a3380be13fba749fc4208214b049347">AddReshapeLayer</a>(reshapeDescriptor);</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(reshapeLayer != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="comment">// Attach the input layer to the reshape layer</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  inputLayer.Connect(reshapeLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  reshapeLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(reshapeInfo);</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keywordflow">return</span> *reshapeLayer;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> }</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"> 245</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> FlattenFullyConnectedInput(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& inputShape,</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& weightsShape)</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> {</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keywordflow">if</span> (inputShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() > 2U)</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> totalInputElements = inputShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>();</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = weightsShape[1];</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> </div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = totalInputElements / inputSize;</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> </div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keywordflow">if</span>(totalInputElements % batchSize != 0)</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  {</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">"Failed to deduce tensor shape"</span>);</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  }</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> </div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>({batchSize, inputSize});</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  }</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  {</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">return</span> inputShape;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  }</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> }</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> </div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> VerifyFullyConnectedShapes(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& inputShape,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& weightsShape,</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& outputShape,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <span class="keywordtype">bool</span> transposeWeightMatrix)</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> {</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimIdx = transposeWeightMatrix ? 0 : 1;</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keywordflow">return</span> (inputShape[0] == outputShape[0] && weightsShape[dimIdx] == outputShape[1]);</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> }</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> </div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="keywordtype">bool</span> BroadcastTensor(<a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a>& input0,</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a>& input1,</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* startLayer,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data)</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> {</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(startLayer != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> </div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& inputInfo0 = input0.<a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml#acbafd23115b06f0a82eab45bd1e3cff9">GetTensorInfo</a>();</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& inputInfo1 = input1.<a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml#acbafd23115b06f0a82eab45bd1e3cff9">GetTensorInfo</a>();</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputDimensions0 = inputInfo0.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputDimensions1 = inputInfo1.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> </div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keywordflow">if</span> (inputDimensions0 == inputDimensions1)</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  {</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="comment">// The inputs have the same number of dimensions, simply connect them to the given layer as they are</span></div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  input0.<a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml#a9b63bdf08709bc5302b3c1a9198d06a3">Connect</a>(startLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  input1.<a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml#a9b63bdf08709bc5302b3c1a9198d06a3">Connect</a>(startLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> </div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  }</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="comment">// Since the number of dimensions do not match then we need to add degenerate dimensions</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="comment">// to the "smaller" tensor using a reshape, while keeping the order of the inputs.</span></div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> </div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> maxInputDimensions = std::max(inputDimensions0, inputDimensions1);</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> sizeDifference = std::abs(armnn::numeric_cast<int>(inputDimensions0) -</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  armnn::numeric_cast<int>(inputDimensions1));</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> </div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordtype">bool</span> input0IsSmaller = inputDimensions0 < inputDimensions1;</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a>& smallInputHandle = input0IsSmaller ? input0 : input1;</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& smallInfo = smallInputHandle.<a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml#acbafd23115b06f0a82eab45bd1e3cff9">GetTensorInfo</a>();</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> </div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& smallShape = smallInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  std::vector<unsigned int> reshapedDimensions(maxInputDimensions, 1);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = sizeDifference; i < maxInputDimensions; i++)</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  {</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  reshapedDimensions[i] = smallShape[i - sizeDifference];</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  }</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> </div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> reshapedInfo = smallInfo;</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  reshapedInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>{ <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(reshapedDimensions.size()),</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  reshapedDimensions.data() });</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> </div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="comment">// RehsapeDescriptor that is ignored in the IsReshapeSupported function</span></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="structarmnn_1_1_reshape_descriptor.xhtml">armnn::ReshapeDescriptor</a> reshapeDescriptor;</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> </div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordtype">bool</span> isSupported = <span class="keyword">false</span>;</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <a class="code" href="_conversion_utils_8hpp.xhtml#a6f98cfbf3171f950d1f0df30d60691a7">FORWARD_LAYER_SUPPORT_FUNC</a>(__func__,</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <a class="code" href="namespacearmnn.xhtml#af5014cbc003abcf201d4372b0012734c">IsReshapeSupported</a>,</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  data.<a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#af3239731a47cf4c08a040c42ee855edc">m_Backends</a>,</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  isSupported,</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  smallInfo,</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  reshapedInfo,</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  reshapeDescriptor);</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordflow">if</span> (!isSupported)</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  {</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  }</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> </div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(data.<a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#a2db3ae8d422f17d455e0ba0cb6291d2a">m_Network</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>& reshapeLayer = AddReshapeLayer(*data.<a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#a2db3ae8d422f17d455e0ba0cb6291d2a">m_Network</a>, smallInputHandle, reshapedInfo);</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> </div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">if</span> (input0IsSmaller)</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  {</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="comment">// Input0 is the "smaller" tensor, connect the reshape layer as follows:</span></div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="comment">//</span></div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="comment">// Input0 Input1</span></div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="comment">// | |</span></div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="comment">// Reshape |</span></div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="comment">// \ /</span></div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="comment">// StartLayer</span></div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> </div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  reshapeLayer.<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(startLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  input1.<a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml#a9b63bdf08709bc5302b3c1a9198d06a3">Connect</a>(startLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  }</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  {</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="comment">// Input1 is the "smaller" tensor, connect the reshape layer as follows:</span></div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="comment">//</span></div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="comment">// Input0 Input1</span></div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="comment">// | |</span></div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="comment">// | Reshape</span></div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="comment">// \ /</span></div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="comment">// StartLayer</span></div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span> </div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  input0.<a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml#a9b63bdf08709bc5302b3c1a9198d06a3">Connect</a>(startLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  reshapeLayer.<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(startLayer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  }</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> </div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> }</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> </div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> <span class="keywordtype">void</span> CalcPadding(uint32_t input,</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  uint32_t kernel,</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  uint32_t stride,</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  uint32_t& outPadHead,</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  uint32_t& outPadTail,</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  PaddingScheme scheme)</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> {</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  int32_t padHead;</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  int32_t padTail;</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  calculateExplicitPadding(input, stride, kernel, scheme, &padHead, &padTail);</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  outPadHead = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><uint32_t>(padHead);</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  outPadTail = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><uint32_t>(padTail);</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> }</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> </div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span> <span class="keywordtype">void</span> CalcPadding(uint32_t input, uint32_t kernel, uint32_t stride, uint32_t dilation, uint32_t& outPadHead,</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  uint32_t& outPadTail, ::android::nn::PaddingScheme scheme)</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span> {</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  int32_t padHead;</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  int32_t padTail;</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  calculateExplicitPadding(input, stride, dilation, kernel, scheme, &padHead, &padTail);</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  outPadHead = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><uint32_t>(padHead);</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  outPadTail = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><uint32_t>(padTail);</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span> }</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> </div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> CalcPaddingTransposeConv(uint32_t output, uint32_t kernel, int32_t stride, int32_t& outPadHead,</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  int32_t& outPadTail, ::android::nn::PaddingScheme scheme)</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span> {</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  calculateExplicitPaddingTransposeConv(output, stride, kernel, scheme, &outPadHead, &outPadTail);</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> }</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> </div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span> Shape GetOperandShape(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>& operand)</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> {</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  Shape shape;</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  shape.type = <a class="code" href="namespacearmnn__driver.xhtml#a53bfb6eb38a90244ba166b641a6965d9">OperandType</a>(operand.type);</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  shape.dimensions = operand.dimensions;</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  shape.scale = operand.scale;</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  shape.offset = operand.zeroPoint;</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="keywordflow">return</span> shape;</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span> }</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> </div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span> </div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> <span class="comment">// ArmNN requires the bias scale to be equal to the product of the weight and input scales, which is also</span></div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span> <span class="comment">// what AndroidNN requires. However for some of the AndroidNN tests the values don't exactly match so</span></div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span> <span class="comment">// we accept some tolerance. We don't want ArmNN itself to accept these inconsistencies as it is up to the</span></div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> <span class="comment">// user (us, in this case) to ensure they match.</span></div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> <span class="keywordtype">void</span> SanitizeBiasQuantizationScale(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& biasInfo,</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& weightInfo,</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& inputInfo)</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> {</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <span class="keywordflow">if</span> (weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48">HasPerAxisQuantization</a>())</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  {</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="comment">// NOTE: Bias scale is always set to 0 for per-axis quantization and</span></div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="comment">// it needs to be calculated: scale[i] = input_scale * weight_scale[i]</span></div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keyword">auto</span> UpdateBiasScaleValue = [&inputInfo](<span class="keywordtype">float</span> biasScale) -> <span class="keywordtype">float</span></div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  {</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  <span class="keywordflow">return</span> biasScale * inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>();</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  };</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> </div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  std::vector<float> biasScales(weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270">GetQuantizationScales</a>());</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  std::transform(biasScales.begin(), biasScales.end(), biasScales.begin(), UpdateBiasScaleValue);</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span> </div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  biasInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">SetQuantizationScales</a>(biasScales);</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <span class="comment">// bias is expected to be a 1d tensor, set qdim=0</span></div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  biasInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">SetQuantizationDim</a>(0);</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span> </div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  VLOG(DRIVER) << <span class="stringliteral">"Bias quantization params have been updated for per-axis quantization"</span>;</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  }</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  {</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> expectedBiasScale = weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>() * inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>();</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <span class="keywordflow">if</span> (biasInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>() != expectedBiasScale)</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  {</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn_utils.xhtml#a56b0e17341e000fa1d4561890294520c">armnnUtils::within_percentage_tolerance</a>(biasInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>(), expectedBiasScale, 1.0f))</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  {</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  VLOG(DRIVER) << <span class="stringliteral">"Bias quantization scale has been modified to match input * weights"</span>;</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  biasInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(expectedBiasScale);</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  }</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  }</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  }</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span> }</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span> </div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> <span class="comment">// 4D Tensor Permutations</span></div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> IdentityPermutation4D({ 0U, 1U, 2U, 3U });</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> IdentityPermutation3D({ 0U, 1U, 2U });</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> SwapDim1And2({ 0U, 2U, 1U, 3U });</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span> </div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> <span class="comment">// 3D Permutation Vectors</span></div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> RotateTensorLeft({ 1U, 2U, 0U });</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> RotateTensorRight({ 2U, 0U, 1U });</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span> </div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span> <span class="keyword">template</span><<span class="keyword">typename</span> OSlot></div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>& AddTransposeLayer(<a class="code" href="classarmnn_1_1_i_network.xhtml">armnn::INetwork</a>& network, OSlot& input,</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>& mappings)</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span> {</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <span class="comment">// Add swizzle layer</span></div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> layer = network.<a class="code" href="classarmnn_1_1_i_network.xhtml#ab067ba4ee9416d93abb8a52f3dc8feba">AddTransposeLayer</a>(mappings);</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span> </div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(layer != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> </div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="comment">// Connect input to swizzle layer</span></div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  input.Connect(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span> </div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <span class="comment">// Setup swizzled output</span></div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outInfo = <a class="code" href="namespacearmnn_utils.xhtml#a428a9a6ffdf0e8d723b50c038c56c336">armnnUtils::TransposeTensorShape</a>(input.GetTensorInfo(), mappings);</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outInfo);</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span> </div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  <span class="keywordflow">return</span> *layer;</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span> }</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span> </div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span> <span class="keywordtype">bool</span> ValidateConcatOutputShape(<span class="keyword">const</span> std::vector<armnn::TensorShape> & inputShapes,</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> & outputShape,</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  uint32_t concatDim)</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span> {</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="comment">// Validate the output shape is correct given the input shapes (which have just been validated)</span></div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions = inputShapes[0].GetNumDimensions();</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <span class="keywordflow">if</span> (outputShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() != numDimensions)</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  {</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <span class="keywordflow">return</span> Fail(<span class="stringliteral">"%s: Output shape has wrong number of dimensions"</span>, __func__);</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  }</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> </div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSizeAlongConcatenatedDimension = 0;</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < inputShapes.size(); i++)</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  {</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  outputSizeAlongConcatenatedDimension += inputShapes[i][concatDim];</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  }</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span> </div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numDimensions; ++i)</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  {</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keywordflow">if</span> (i == concatDim)</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  {</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keywordflow">if</span> (outputShape[i] != outputSizeAlongConcatenatedDimension)</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  {</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keywordflow">return</span> Fail(</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <span class="stringliteral">"%s: Invalid output shape for dimension %d (%d != %d)"</span>,</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  __func__,</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  i,</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  outputShape[i],</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  outputSizeAlongConcatenatedDimension);</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  }</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  }</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  {</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="keywordflow">if</span> (outputShape[i] != inputShapes[0][i])</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  {</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="keywordflow">return</span> Fail(<span class="stringliteral">"%s: Invalid output shape"</span>, __func__);</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  }</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  }</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  }</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span> </div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span> }</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span> </div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> RequiresReshape(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> & inputShape)</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span> {</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  <span class="keywordflow">return</span> inputShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() < 3;</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span> }</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span> </div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> SwizzleInputs(<a class="code" href="classarmnn_1_1_i_network.xhtml">armnn::INetwork</a>& network,</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  std::vector<LayerInputHandle>& inputs,</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  std::vector<armnn::TensorShape>& inputShapes,</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>& mapping)</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span> {</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <span class="keywordflow">if</span> (!mapping.<a class="code" href="classarmnn_1_1_permutation_vector.xhtml#aae44e4154aa80fba7616747450ff69d5">IsEqual</a>(IdentityPermutation4D))</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  {</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <span class="keywordtype">size_t</span> nInputs = inputs.size();</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i=0; i<nInputs; ++i)</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  {</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  <span class="comment">// add swizzle layer</span></div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>& swizzleLayer = AddTransposeLayer(network, inputs[i], mapping);</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  <span class="keyword">auto</span>& outputSlot = swizzleLayer.<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0);</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="keyword">auto</span>& outputInfo = outputSlot.<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <span class="comment">// replace inputs with the swizzled ones</span></div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  inputs[i] = <a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a>(<span class="keyword">true</span>, &outputSlot, outputInfo);</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  inputShapes[i] = inputs[i].GetTensorInfo().GetShape();</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  }</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  }</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span> }</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span> </div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span> <span class="keywordtype">bool</span> TransposeInputTensors(<a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  std::vector<LayerInputHandle>& inputs,</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  std::vector<armnn::TensorShape>& inputShapes,</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>& mapping)</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span> {</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <span class="comment">// If we have a IdentityPermutation4D or IdentityPermutation3D then we are not permuting</span></div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <span class="keywordflow">if</span> (!mapping.<a class="code" href="classarmnn_1_1_permutation_vector.xhtml#aae44e4154aa80fba7616747450ff69d5">IsEqual</a>(IdentityPermutation4D) && !mapping.<a class="code" href="classarmnn_1_1_permutation_vector.xhtml#aae44e4154aa80fba7616747450ff69d5">IsEqual</a>(IdentityPermutation3D))</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  {</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTransposeInfo;</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="keywordtype">size_t</span> nInputs = inputs.size();</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i=0; i<nInputs; ++i)</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  {</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <span class="comment">// check permute layer</span></div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  <a class="code" href="structarmnn_1_1_transpose_descriptor.xhtml">armnn::TransposeDescriptor</a> transposeDesc;</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  transposeDesc.<a class="code" href="structarmnn_1_1_transpose_descriptor.xhtml#a14433af2b223695b40d8c8f8ba2ebb8f">m_DimMappings</a> = mapping;</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  outputTransposeInfo = <a class="code" href="namespacearmnn_utils.xhtml#a428a9a6ffdf0e8d723b50c038c56c336">armnnUtils::TransposeTensorShape</a>(inputs[i].<a class="code" href="namespacearmnn_utils.xhtml#acee63cd08da47910fc166a1990988fa8">GetTensorInfo</a>(), mapping);</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span> </div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <span class="keywordtype">bool</span> isSupported = <span class="keyword">false</span>;</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <a class="code" href="_conversion_utils_8hpp.xhtml#a6f98cfbf3171f950d1f0df30d60691a7">FORWARD_LAYER_SUPPORT_FUNC</a>(__func__,</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  IsTransposeSupported,</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  data.<a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#af3239731a47cf4c08a040c42ee855edc">m_Backends</a>,</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  isSupported,</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  inputs[i].GetTensorInfo(),</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  outputTransposeInfo,</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  transposeDesc);</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="keywordflow">if</span> (!isSupported)</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  {</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  }</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span> </div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  }</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  SwizzleInputs(*data.<a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml#a2db3ae8d422f17d455e0ba0cb6291d2a">m_Network</a>, inputs, inputShapes, mapping);</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  }</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span> }</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span> </div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span> <span class="keywordtype">bool</span> CreateConcatPermutationParameters(<span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfDimensions,</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  int32_t & concatDimension,</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  std::pair<armnn::PermutationVector, armnn::PermutationVector> & permutationPair)</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span> {</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  <span class="keywordtype">bool</span> needPermute = <span class="keyword">false</span>;</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(numberOfDimensions >= 3);</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span> </div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <span class="comment">// ArmNN uses Compute Library subtensors to perform concatenation</span></div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="comment">// This only works when concatenating along dimension 0, 1 or 3 for a 4-D tensor,</span></div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <span class="comment">// or along dimension 0 or 2 for a 3-D tensor.</span></div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <span class="keywordflow">if</span> (numberOfDimensions == 4 && concatDimension == 2)</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  {</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  concatDimension = 1;</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  permutationPair = std::make_pair(SwapDim1And2, SwapDim1And2);</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  needPermute = <span class="keyword">true</span>;</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  }</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (numberOfDimensions == 3 && concatDimension == 1)</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  {</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  concatDimension = 0;</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  permutationPair = std::make_pair(RotateTensorLeft, RotateTensorRight);</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  needPermute = <span class="keyword">true</span>;</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  }</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="comment">// If the tensor is 3-D and the concat dimension is 2 then we don't need to permute but we do need to change the</span></div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="comment">// permutation identity to only have 3 dimensions</span></div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (numberOfDimensions == 3 && concatDimension == 2)</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  {</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  permutationPair = std::make_pair(IdentityPermutation3D, IdentityPermutation3D);</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  }</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keywordflow">return</span> needPermute;</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span> }</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span> </div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span> } <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span> </div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn__driver.xhtml">armnn_driver</a></div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span> {</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span> <span class="keyword">using namespace </span><a class="code" href="namespaceandroid_1_1nn.xhtml">android::nn</a>;</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span> <span class="comment"></span></div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span> <span class="comment">//// Creates an ArmNN activation layer and connects it to the given layer, if the</span></div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span> <span class="comment">//// passed in AndroidNN activation function requires so.</span></div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span> <span class="comment">//// @return The end layer of the sequence of layers built for the given AndroidNN</span></div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span> <span class="comment">//// activation function or nullptr if an error occurred (e.g. unsupported activation).</span></div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span> <span class="comment">//// Note that the end layer matches the input layer if no activation is required</span></div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span> <span class="comment">//// (the sequence of layers has length 1).</span></div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span> <span class="comment"></span><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <a class="code" href="namespacearmnn__driver.xhtml#aac972ee73e8bd2374bc40ab844a7d894">ProcessActivation</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& tensorInfo,</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  ActivationFn activation,</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* prevLayer,</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data);</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span> </div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span> </div><div class="line"><a name="l00633"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a14977f94479f2f7e13bdf915ac8ce8d0"> 633</a></span> <span class="keyword">inline</span> <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>* <a class="code" href="namespacearmnn__driver.xhtml#a14977f94479f2f7e13bdf915ac8ce8d0">GetInputOperand</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  uint32_t inputIndex,</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  <span class="keywordtype">bool</span> failOnIndexOutOfBounds = <span class="keyword">true</span>)</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span> {</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <span class="keywordflow">if</span> (inputIndex >= operation.inputs.size())</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  {</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <span class="keywordflow">if</span> (failOnIndexOutOfBounds)</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  {</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  Fail(<span class="stringliteral">"%s: invalid input index: %i out of %i"</span>, __func__, inputIndex, operation.inputs.size());</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  }</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  }</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span> </div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  <span class="comment">// Model should have been validated beforehand</span></div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(operation.inputs[inputIndex] < <a class="code" href="_conversion_utils_8hpp.xhtml#abcb5019b10b89cbd2b96118885a026d4">getMainModel</a>(model).operands.size());</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  <span class="keywordflow">return</span> &<a class="code" href="_conversion_utils_8hpp.xhtml#abcb5019b10b89cbd2b96118885a026d4">getMainModel</a>(model).operands[operation.inputs[inputIndex]];</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span> }</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span> </div><div class="line"><a name="l00652"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a5890dee5ebd8c09d4b3787136d8170d8"> 652</a></span> <span class="keyword">inline</span> <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>* <a class="code" href="namespacearmnn__driver.xhtml#a5890dee5ebd8c09d4b3787136d8170d8">GetOutputOperand</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  uint32_t outputIndex,</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model)</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span> {</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <span class="keywordflow">if</span> (outputIndex >= operation.outputs.size())</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  {</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  Fail(<span class="stringliteral">"%s: invalid output index: %i out of %i"</span>, __func__, outputIndex, operation.outputs.size());</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  }</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span> </div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <span class="comment">// Model should have been validated beforehand</span></div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(operation.outputs[outputIndex] < <a class="code" href="_conversion_utils_8hpp.xhtml#abcb5019b10b89cbd2b96118885a026d4">getMainModel</a>(model).operands.size());</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span> </div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  <span class="keywordflow">return</span> &<a class="code" href="_conversion_utils_8hpp.xhtml#abcb5019b10b89cbd2b96118885a026d4">getMainModel</a>(model).operands[operation.outputs[outputIndex]];</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span> }</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span> </div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span> <span class="keyword">const</span> <span class="keywordtype">void</span>* <a class="code" href="namespacearmnn__driver.xhtml#a8d20245b5ca3cbb0b132064ab44f2682">GetOperandValueReadOnlyAddress</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>& operand,</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  <span class="keywordtype">bool</span> optional = <span class="keyword">false</span>);</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span> </div><div class="line"><a name="l00673"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#adfc2c5b834fdb89e5458ddb1d9aa7830"> 673</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#adfc2c5b834fdb89e5458ddb1d9aa7830">GetOperandType</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  uint32_t inputIndex,</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  <a class="code" href="namespacearmnn__driver.xhtml#a53bfb6eb38a90244ba166b641a6965d9">OperandType</a>& type)</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span> {</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>* operand = <a class="code" href="namespacearmnn__driver.xhtml#a14977f94479f2f7e13bdf915ac8ce8d0">GetInputOperand</a>(operation, inputIndex, model);</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  <span class="keywordflow">if</span> (!operand)</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  {</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  <span class="keywordflow">return</span> Fail(<span class="stringliteral">"%s: invalid input operand at index %i"</span>, __func__, inputIndex);</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  }</div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span> </div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  type = operand->type;</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span> }</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span> </div><div class="line"><a name="l00688"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a9ddfceb499ef7b3d01053399bc79b852"> 688</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a9ddfceb499ef7b3d01053399bc79b852">IsOperandConstant</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>& operand)</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span> {</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <a class="code" href="namespacearmnn__driver.xhtml#a275cd95635b854a80bb33f171d861ddc">OperandLifeTime</a> lifetime = operand.lifetime;</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span> </div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <span class="keywordflow">return</span> lifetime == OperandLifeTime::CONSTANT_COPY ||</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  lifetime == OperandLifeTime::CONSTANT_REFERENCE ||</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  lifetime == OperandLifeTime::POINTER ||</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  lifetime == OperandLifeTime::NO_VALUE;</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span> }</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span> </div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a56e87ad879b142327b822beff44ca171">IsWeightsValid</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation, uint32_t inputIndex, <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model);</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span> </div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span> <a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a> <a class="code" href="namespacearmnn__driver.xhtml#a82e85436d5f7cbfa90e8ab521bddae31">ConvertOperandToConstTensorPin</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>& operand,</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>& dimensionMappings = <a class="code" href="namespacearmnn__driver.xhtml#ae059aea66ee0867a204aa2f2d9abb42c">g_DontPermute</a>,</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>* overrideTensorShape = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <span class="keywordtype">bool</span> optional = <span class="keyword">false</span>,</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a>* overrideDataType = <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span> </div><div class="line"><a name="l00708"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a8c749c18e62c59a5c1254aac342c995a"> 708</a></span> <span class="keyword">inline</span> <a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a> <a class="code" href="namespacearmnn__driver.xhtml#a8c749c18e62c59a5c1254aac342c995a">ConvertOperationInputToConstTensorPin</a>(</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  uint32_t inputIndex,</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>& dimensionMappings = <a class="code" href="namespacearmnn__driver.xhtml#ae059aea66ee0867a204aa2f2d9abb42c">g_DontPermute</a>,</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>* overrideTensorShape = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <span class="keywordtype">bool</span> optional = <span class="keyword">false</span>)</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span> {</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>* operand = <a class="code" href="namespacearmnn__driver.xhtml#a14977f94479f2f7e13bdf915ac8ce8d0">GetInputOperand</a>(operation, inputIndex, model);</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  <span class="keywordflow">if</span> (!operand)</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  {</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  Fail(<span class="stringliteral">"%s: failed to get input operand: index=%u"</span>, __func__, inputIndex);</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a>();</div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  }</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn__driver.xhtml#a82e85436d5f7cbfa90e8ab521bddae31">ConvertOperandToConstTensorPin</a>(*operand,</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  model,</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  data,</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  dimensionMappings,</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  overrideTensorShape,</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  optional);</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span> }</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span> </div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span> <span class="keyword">template</span> <<span class="keyword">typename</span> OutputType></div><div class="line"><a name="l00732"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#abf92490dc588f48af86fc12184841fd5"> 732</a></span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#abf92490dc588f48af86fc12184841fd5">GetInputScalar</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  uint32_t inputIndex,</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  <a class="code" href="namespacearmnn__driver.xhtml#a53bfb6eb38a90244ba166b641a6965d9">OperandType</a> type,</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  OutputType& outValue,</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  <span class="keywordtype">bool</span> optional = <span class="keyword">false</span>)</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span> {</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>* operand = <a class="code" href="namespacearmnn__driver.xhtml#a14977f94479f2f7e13bdf915ac8ce8d0">GetInputOperand</a>(operation, inputIndex, model);</div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <span class="keywordflow">if</span> (!optional && !operand)</div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  {</div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  <span class="keywordflow">return</span> Fail(<span class="stringliteral">"%s: invalid input operand at index %i"</span>, __func__, inputIndex);</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  }</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span> </div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <span class="keywordflow">if</span> (!optional && operand->type != type)</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  {</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  VLOG(DRIVER) << __func__ << <span class="stringliteral">": unexpected operand type: "</span> << operand->type << <span class="stringliteral">" should be: "</span> << type;</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  }</div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span> </div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <span class="keywordflow">if</span> (!optional && operand->location.length != <span class="keyword">sizeof</span>(OutputType))</div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  {</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  <span class="keywordflow">return</span> Fail(<span class="stringliteral">"%s: incorrect operand location length: %i (should be %i)"</span>,</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  __func__, operand->location.length, <span class="keyword">sizeof</span>(OutputType));</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  }</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span> </div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  <span class="keyword">const</span> <span class="keywordtype">void</span>* valueAddress = <a class="code" href="namespacearmnn__driver.xhtml#a8d20245b5ca3cbb0b132064ab44f2682">GetOperandValueReadOnlyAddress</a>(*operand, model, data);</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  <span class="keywordflow">if</span> (!optional && !valueAddress)</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  {</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  <span class="keywordflow">return</span> Fail(<span class="stringliteral">"%s: failed to get address for operand"</span>, __func__);</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  }</div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span> </div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  <span class="keywordflow">if</span>(!optional)</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  {</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  outValue = *(<span class="keyword">static_cast<</span><span class="keyword">const </span>OutputType*<span class="keyword">></span>(valueAddress));</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  }</div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span> </div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span> }</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span> </div><div class="line"><a name="l00772"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#aa43f9c81f830559c15e5af86f8e11482"> 772</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#aa43f9c81f830559c15e5af86f8e11482">GetInputInt32</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  uint32_t inputIndex,</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  int32_t& outValue,</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data)</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span> {</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn__driver.xhtml#abf92490dc588f48af86fc12184841fd5">GetInputScalar</a>(operation, inputIndex, OperandType::INT32, outValue, model, data);</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span> }</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span> </div><div class="line"><a name="l00781"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a560530462631e354561c1763f695351c"> 781</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a560530462631e354561c1763f695351c">GetInputFloat32</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  uint32_t inputIndex,</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  <span class="keywordtype">float</span>& outValue,</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data)</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span> {</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn__driver.xhtml#abf92490dc588f48af86fc12184841fd5">GetInputScalar</a>(operation, inputIndex, OperandType::FLOAT32, outValue, model, data);</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span> }</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span> </div><div class="line"><a name="l00790"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a3ac499dc54900adc7f2613944b583e10"> 790</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a3ac499dc54900adc7f2613944b583e10">GetInputActivationFunctionImpl</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  uint32_t inputIndex,</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <a class="code" href="namespacearmnn__driver.xhtml#a53bfb6eb38a90244ba166b641a6965d9">OperandType</a> type,</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  ActivationFn& outActivationFunction,</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data)</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span> {</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  <span class="keywordflow">if</span> (type != OperandType::INT32 && type != OperandType::TENSOR_INT32)</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  {</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  VLOG(DRIVER) << __func__ << <span class="stringliteral">": unexpected operand type: "</span> << type</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  << <span class="stringliteral">" should be OperandType::INT32 or OperandType::TENSOR_INT32"</span>;</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  }</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span> </div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  int32_t activationFunctionAsInt;</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn__driver.xhtml#abf92490dc588f48af86fc12184841fd5">GetInputScalar</a>(operation, inputIndex, type, activationFunctionAsInt, model, data))</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  {</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  <span class="keywordflow">return</span> Fail(<span class="stringliteral">"%s: failed to get activation input value"</span>, __func__);</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  }</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  outActivationFunction = <span class="keyword">static_cast<</span>ActivationFn<span class="keyword">></span>(activationFunctionAsInt);</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span> }</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span> </div><div class="line"><a name="l00813"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#ac092fff5c81f7938eea9a2479f014c66"> 813</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#ac092fff5c81f7938eea9a2479f014c66">GetInputActivationFunction</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  uint32_t inputIndex,</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  ActivationFn& outActivationFunction,</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data)</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span> {</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn__driver.xhtml#a3ac499dc54900adc7f2613944b583e10">GetInputActivationFunctionImpl</a>(operation,</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  inputIndex,</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  OperandType::INT32,</div><div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  outActivationFunction,</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  model,</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  data);</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span> }</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span> </div><div class="line"><a name="l00827"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a4c6b55ca5080b58c2cc6d7c6c7347d96"> 827</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a4c6b55ca5080b58c2cc6d7c6c7347d96">GetInputActivationFunctionFromTensor</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  uint32_t inputIndex,</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  ActivationFn& outActivationFunction,</div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data)</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span> {</div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span>  <span class="comment">// This only accepts a 1-D tensor of size 1</span></div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn__driver.xhtml#a3ac499dc54900adc7f2613944b583e10">GetInputActivationFunctionImpl</a>(operation,</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  inputIndex,</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  OperandType::INT32,</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  outActivationFunction,</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  model,</div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  data);</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span> }</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span> </div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span> </div><div class="line"><a name="l00843"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#acd62ec697055015572a6ba61eaba4f1a"> 843</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#acd62ec697055015572a6ba61eaba4f1a">GetOptionalInputActivation</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  uint32_t inputIndex,</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  ActivationFn& activationFunction,</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data)</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span> {</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  <span class="keywordflow">if</span> (operation.inputs.size() <= inputIndex)</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  {</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  activationFunction = ActivationFn::kActivationNone;</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  }</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  {</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn__driver.xhtml#ac092fff5c81f7938eea9a2479f014c66">GetInputActivationFunction</a>(operation, inputIndex, activationFunction, model, data))</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  {</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <span class="keywordflow">return</span> Fail(<span class="stringliteral">"%s: Operation has invalid inputs"</span>, __func__);</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  }</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  }</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span> }</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span> </div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span> <span class="keyword">template</span><<span class="keyword">typename</span> ConvolutionDescriptor></div><div class="line"><a name="l00864"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#acfe37581bc8296b5d4cdb311b1e3f142"> 864</a></span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#acfe37581bc8296b5d4cdb311b1e3f142">GetOptionalConvolutionDilationParams</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  uint32_t dilationXIndex,</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  ConvolutionDescriptor& descriptor,</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data)</div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span> {</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  <span class="keywordtype">bool</span> success = <span class="keyword">true</span>;</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  <span class="keywordflow">if</span> (operation.inputs.size() >= dilationXIndex + 2)</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  {</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  success &= <a class="code" href="namespacearmnn__driver.xhtml#abf92490dc588f48af86fc12184841fd5">GetInputScalar</a>(operation,</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  dilationXIndex,</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  OperandType::INT32,</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  descriptor.m_DilationX,</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  model,</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  data);</div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  success &= <a class="code" href="namespacearmnn__driver.xhtml#abf92490dc588f48af86fc12184841fd5">GetInputScalar</a>(operation,</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  dilationXIndex + 1,</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  OperandType::INT32,</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  descriptor.m_DilationY,</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  model,</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  data);</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  }</div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span> </div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <span class="keywordflow">return</span> success;</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span> }</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span> </div><div class="line"><a name="l00890"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#ae28f9841f6cb1775849b7921b54da32e"> 890</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#ae28f9841f6cb1775849b7921b54da32e">GetOptionalBool</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  uint32_t inputIndex,</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data)</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span> {</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>* operand = <a class="code" href="namespacearmnn__driver.xhtml#a14977f94479f2f7e13bdf915ac8ce8d0">GetInputOperand</a>(operation, inputIndex, model);</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  <span class="keywordflow">if</span> (!operand)</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  {</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  }</div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span> </div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  <span class="keywordflow">if</span> (!IsBool(*operand))</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  {</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  }</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span> </div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  <span class="keyword">const</span> <span class="keywordtype">void</span>* valueAddress = <a class="code" href="namespacearmnn__driver.xhtml#a8d20245b5ca3cbb0b132064ab44f2682">GetOperandValueReadOnlyAddress</a>(*operand, model, data);</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  <span class="keywordflow">if</span> (!valueAddress)</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  {</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  }</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span> </div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  <span class="keywordflow">return</span> *(<span class="keyword">static_cast<</span><span class="keyword">const </span><span class="keywordtype">bool</span>*<span class="keyword">></span>(valueAddress));</div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span> }</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span> </div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#ac8643aaee3eafc54336c5462b51bd53f">GetTensorInt32Values</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>& operand,</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  std::vector<int32_t>& outValues,</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data);</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span> </div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9ef723ace8562b9636e8387a120fbde">GetInputPaddingScheme</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  uint32_t inputIndex,</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  PaddingScheme& outPaddingScheme,</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data);</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span> </div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span> <a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a> <a class="code" href="namespacearmnn__driver.xhtml#a1f6b85ab26d684241babcde2d659116b">ConvertToLayerInputHandle</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  uint32_t inputIndex,</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>& dimensionMappings = <a class="code" href="namespacearmnn__driver.xhtml#ae059aea66ee0867a204aa2f2d9abb42c">g_DontPermute</a>,</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  <span class="keyword">const</span> <a class="code" href="classarmnn__driver_1_1_layer_input_handle.xhtml">LayerInputHandle</a>* inputHandle = <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span> </div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a5378da53b59c1c826e6320383ca0257e">SetupAndTrackLayerOutputSlot</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  uint32_t operationOutputIndex,</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>& layer,</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  uint32_t layerOutputIndex,</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>* overrideOutputInfo = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="keyword">const</span> std::function <<span class="keywordtype">void</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&, <span class="keywordtype">bool</span>&)>& validateFunc = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  <span class="keyword">const</span> ActivationFn& activationFunction = ActivationFn::kActivationNone,</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  <span class="keywordtype">bool</span> inferOutputShapes = <span class="keyword">false</span>);</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span> </div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> <a class="code" href="namespacearmnn__driver.xhtml#a3f3a756df9dee4b33566cddd786b83c9">OptionalDataLayout</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  uint32_t inputIndex,</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data);</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span> </div><div class="line"><a name="l00949"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#ad8f11d121a42a43f14c18bdb10f14b9e"> 949</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a5378da53b59c1c826e6320383ca0257e">SetupAndTrackLayerOutputSlot</a>(</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  uint32_t outputIndex,</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>& layer,</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>* overrideOutputInfo = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  <span class="keyword">const</span> std::function <<span class="keywordtype">void</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&, <span class="keywordtype">bool</span>&)>& validateFunc = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  <span class="keyword">const</span> ActivationFn& activationFunction = ActivationFn::kActivationNone)</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span> {</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn__driver.xhtml#a5378da53b59c1c826e6320383ca0257e">SetupAndTrackLayerOutputSlot</a>(operation,</div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  outputIndex,</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  layer,</div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  outputIndex,</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  model,</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  data,</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  overrideOutputInfo,</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  validateFunc,</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  activationFunction);</div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span> }</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span> </div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a28243ca97e12ccb50e01f03d313ecc86">ConvertToActivation</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* operationName,</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a>& activationDesc,</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data);</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span> </div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a8d4f662a4fb5b9272724bdaeacbd370a">ConvertPaddings</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> rank,</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  <a class="code" href="structarmnn_1_1_pad_descriptor.xhtml">armnn::PadDescriptor</a>& padDescriptor);</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a3f6b313fd199d1552844f3f95fd25cd2">ConvertReduce</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  <a class="code" href="namespacearmnn.xhtml#abc05539fc6e7907f32ef0fb242e3b3b0">armnn::ReduceOperation</a> reduceOperation);</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span> </div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a2eb75cb48464cf87c290503d7bea79a4">ConvertPooling2d</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* operationName,</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a> poolType,</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data);</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span> </div><div class="line"><a name="l00992"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a267f6b68937e2126b6ca890a6b11ea9c"> 992</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a267f6b68937e2126b6ca890a6b11ea9c">IsQSymm8</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">Operand</a>& operand)</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span> {</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  <span class="keywordflow">return</span> operand.type == OperandType::TENSOR_QUANT8_SYMM;</div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span> }</div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span> </div><div class="line"><a name="l00997"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5c"> 997</a></span> <span class="keyword">enum class</span> <a class="code" href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5c">DequantizeStatus</a></div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span> {</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  <a class="code" href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5cad0749aaba8b833466dfcbb0428e4f89c">SUCCESS</a>,</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  <a class="code" href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5caaf655f85da1fc9b6a348b9893ee6aef7">NOT_REQUIRED</a>,</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  <a class="code" href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5ca6bf179afa8f7fba18cf39bc0ca6fe043">INVALID_OPERAND</a></div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span> };</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span> </div><div class="line"><a name="l01004"></a><span class="lineno"><a class="line" href="namespacearmnn__driver.xhtml#a8932639a884a3dc698f29d4e8395ba49"> 1004</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn__driver.xhtml#a8932639a884a3dc698f29d4e8395ba49">DequantizeResult</a> = std::tuple<std::unique_ptr<float[]>, size_t, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>, <a class="code" href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5c">DequantizeStatus</a>>;</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span> </div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span> <a class="code" href="namespacearmnn__driver.xhtml#a8932639a884a3dc698f29d4e8395ba49">DequantizeResult</a> <a class="code" href="namespacearmnn__driver.xhtml#a78a9a9f196810df6bc4795568f275c75">DequantizeIfRequired</a>(<span class="keywordtype">size_t</span> operand_index,</div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data);</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span> </div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span> <a class="code" href="classarmnn__driver_1_1_const_tensor_pin.xhtml">ConstTensorPin</a> <a class="code" href="namespacearmnn__driver.xhtml#a37ca67c646393225921543233a873803">DequantizeAndMakeConstTensorPin</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">Operation</a>& operation,</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">Model</a>& model,</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  <span class="keyword">const</span> <a class="code" href="structarmnn__driver_1_1_conversion_data.xhtml">ConversionData</a>& data,</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  <span class="keywordtype">size_t</span> operandIndex,</div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  <span class="keywordtype">bool</span> optional = <span class="keyword">false</span>);</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span> </div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn__driver.xhtml#a7bf2bd59bc8ca21e0dd906044bfc2faf">IsConnectedToDequantize</a>(<a class="code" href="classarmnn_1_1_i_output_slot.xhtml">armnn::IOutputSlot</a>* ioutputSlot);</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span> </div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span> } <span class="comment">// namespace armnn_driver</span></div><div class="ttc" id="structarmnn__driver_1_1_conversion_data_xhtml"><div class="ttname"><a href="structarmnn__driver_1_1_conversion_data.xhtml">armnn_driver::ConversionData</a></div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00051">ConversionUtils.hpp:51</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorShape::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdoc">Function that calculates the tensor elements by multiplying all dimension size which are Specified...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00181">Tensor.cpp:181</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a5890dee5ebd8c09d4b3787136d8170d8"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a5890dee5ebd8c09d4b3787136d8170d8">armnn_driver::GetOutputOperand</a></div><div class="ttdeci">const Operand * GetOutputOperand(const Operation &operation, uint32_t outputIndex, const Model &model)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00652">ConversionUtils.hpp:652</a></div></div>
<div class="ttc" id="structarmnn__driver_1_1_conversion_data_xhtml_acb740de896710dbc576f5eaf7a9cfeaa"><div class="ttname"><a href="structarmnn__driver_1_1_conversion_data.xhtml#acb740de896710dbc576f5eaf7a9cfeaa">armnn_driver::ConversionData::m_MemPools</a></div><div class="ttdeci">std::vector<::android::nn::RunTimePoolInfo > m_MemPools</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00062">ConversionUtils.hpp:62</a></div></div>
<div class="ttc" id="_canonical_utils_8hpp_xhtml"><div class="ttname"><a href="_canonical_utils_8hpp.xhtml">CanonicalUtils.hpp</a></div></div>
<div class="ttc" id="_ignore_unused_8hpp_xhtml"><div class="ttname"><a href="_ignore_unused_8hpp.xhtml">IgnoreUnused.hpp</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_afa2a6d5a1431289c92cea9cceeb174c9ab7d6155514def6898ba4432a82efd28b"><div class="ttname"><a href="namespacearmnn__driver.xhtml#afa2a6d5a1431289c92cea9cceeb174c9ab7d6155514def6898ba4432a82efd28b">armnn_driver::ConversionResult::ErrorMappingPools</a></div></div>
<div class="ttc" id="_data_layout_indexed_8hpp_xhtml"><div class="ttname"><a href="_data_layout_indexed_8hpp.xhtml">DataLayoutIndexed.hpp</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#l00068">INetwork.hpp:68</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a267f6b68937e2126b6ca890a6b11ea9c"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a267f6b68937e2126b6ca890a6b11ea9c">armnn_driver::IsQSymm8</a></div><div class="ttdeci">bool IsQSymm8(const Operand &operand)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00992">ConversionUtils.hpp:992</a></div></div>
<div class="ttc" id="_transpose_8hpp_xhtml"><div class="ttname"><a href="_transpose_8hpp.xhtml">Transpose.hpp</a></div></div>
<div class="ttc" id="structarmnn__driver_1_1_conversion_data_xhtml_a4df0c61eb897ecc9271a4a85604066ea"><div class="ttname"><a href="structarmnn__driver_1_1_conversion_data.xhtml#a4df0c61eb897ecc9271a4a85604066ea">armnn_driver::ConversionData::m_OutputSlotForOperand</a></div><div class="ttdeci">std::vector< armnn::IOutputSlot * > m_OutputSlotForOperand</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00061">ConversionUtils.hpp:61</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00062">Types.hpp:62</a></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#l00191">Tensor.hpp:191</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a10c64daf22426af432d0a9ada03eee5caaf655f85da1fc9b6a348b9893ee6aef7"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5caaf655f85da1fc9b6a348b9893ee6aef7">armnn_driver::DequantizeStatus::NOT_REQUIRED</a></div></div>
<div class="ttc" id="structarmnn_1_1_reshape_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.xhtml">armnn::ReshapeDescriptor</a></div><div class="ttdoc">A ReshapeDescriptor for the ReshapeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00963">Descriptors.hpp:963</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a1fa5070fa0d079873acaf7581de8a2ad"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a1fa5070fa0d079873acaf7581de8a2ad">armnn_driver::ErrorStatus</a></div><div class="ttdeci">::android::nn::ErrorStatus ErrorStatus</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00049">ConversionUtils.hpp:49</a></div></div>
<div class="ttc" id="structarmnn__driver_1_1_conversion_data_xhtml_af3239731a47cf4c08a040c42ee855edc"><div class="ttname"><a href="structarmnn__driver_1_1_conversion_data.xhtml#af3239731a47cf4c08a040c42ee855edc">armnn_driver::ConversionData::m_Backends</a></div><div class="ttdeci">const std::vector< armnn::BackendId > m_Backends</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00059">ConversionUtils.hpp:59</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="namespacearmnn__driver_xhtml_ac092fff5c81f7938eea9a2479f014c66"><div class="ttname"><a href="namespacearmnn__driver.xhtml#ac092fff5c81f7938eea9a2479f014c66">armnn_driver::GetInputActivationFunction</a></div><div class="ttdeci">bool GetInputActivationFunction(const Operation &operation, uint32_t inputIndex, ActivationFn &outActivationFunction, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00813">ConversionUtils.hpp:813</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_ab85cd8cc10c96a7c99c14042c251fc48"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48">armnn::TensorInfo::HasPerAxisQuantization</a></div><div class="ttdeci">bool HasPerAxisQuantization() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00446">Tensor.cpp:446</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a3f6b313fd199d1552844f3f95fd25cd2"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a3f6b313fd199d1552844f3f95fd25cd2">armnn_driver::ConvertReduce</a></div><div class="ttdeci">bool ConvertReduce(const Operation &operation, const Model &model, ConversionData &data, armnn::ReduceOperation reduceOperation)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00502">ConversionUtils.cpp:502</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_ad3a9c1424b37970a54624f514196b985"><div class="ttname"><a href="namespacearmnn__driver.xhtml#ad3a9c1424b37970a54624f514196b985">armnn_driver::Operation</a></div><div class="ttdeci">::android::nn::Operation Operation</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00047">ConversionUtils.hpp:47</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_ae28f9841f6cb1775849b7921b54da32e"><div class="ttname"><a href="namespacearmnn__driver.xhtml#ae28f9841f6cb1775849b7921b54da32e">armnn_driver::GetOptionalBool</a></div><div class="ttdeci">bool GetOptionalBool(const Operation &operation, uint32_t inputIndex, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00890">ConversionUtils.hpp:890</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a82e85436d5f7cbfa90e8ab521bddae31"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a82e85436d5f7cbfa90e8ab521bddae31">armnn_driver::ConvertOperandToConstTensorPin</a></div><div class="ttdeci">ConstTensorPin ConvertOperandToConstTensorPin(const Operand &operand, const Model &model, const ConversionData &data, const armnn::PermutationVector &dimensionMappings, const armnn::TensorShape *overrideTensorShape, bool optional, const armnn::DataType *overrideDataType)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00154">ConversionUtils.cpp:154</a></div></div>
<div class="ttc" id="_floating_point_comparison_8hpp_xhtml"><div class="ttname"><a href="_floating_point_comparison_8hpp.xhtml">FloatingPointComparison.hpp</a></div></div>
<div class="ttc" id="_arm_n_n_8hpp_xhtml"><div class="ttname"><a href="_arm_n_n_8hpp.xhtml">ArmNN.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml">armnn::INetwork</a></div><div class="ttdoc">Main network class which provides the interface for building up a neural network. ...</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00261">INetwork.hpp:261</a></div></div>
<div class="ttc" id="classarmnn__driver_1_1_layer_input_handle_xhtml_a9b63bdf08709bc5302b3c1a9198d06a3"><div class="ttname"><a href="classarmnn__driver_1_1_layer_input_handle.xhtml#a9b63bdf08709bc5302b3c1a9198d06a3">armnn_driver::LayerInputHandle::Connect</a></div><div class="ttdeci">void Connect(armnn::IInputSlot &inputSlot)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00032">ConversionUtils.cpp:32</a></div></div>
<div class="ttc" id="classarmnn__driver_1_1_const_tensor_pin_xhtml"><div class="ttname"><a href="classarmnn__driver_1_1_const_tensor_pin.xhtml">armnn_driver::ConstTensorPin</a></div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00090">ConversionUtils.hpp:90</a></div></div>
<div class="ttc" id="_backend_helper_8hpp_xhtml"><div class="ttname"><a href="_backend_helper_8hpp.xhtml">BackendHelper.hpp</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_adfc2c5b834fdb89e5458ddb1d9aa7830"><div class="ttname"><a href="namespacearmnn__driver.xhtml#adfc2c5b834fdb89e5458ddb1d9aa7830">armnn_driver::GetOperandType</a></div><div class="ttdeci">bool GetOperandType(const Operation &operation, uint32_t inputIndex, const Model &model, OperandType &type)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00673">ConversionUtils.hpp:673</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_a961bbfe1db71a848eff5a1f0ab775718"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a></div><div class="ttdeci">PoolingAlgorithm</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00136">Types.hpp:136</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_acd62ec697055015572a6ba61eaba4f1a"><div class="ttname"><a href="namespacearmnn__driver.xhtml#acd62ec697055015572a6ba61eaba4f1a">armnn_driver::GetOptionalInputActivation</a></div><div class="ttdeci">bool GetOptionalInputActivation(const Operation &operation, uint32_t inputIndex, ActivationFn &activationFunction, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00843">ConversionUtils.hpp:843</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8bc11f1fa23ef42532f9fdd04d355270"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270">armnn::TensorInfo::GetQuantizationScales</a></div><div class="ttdeci">std::vector< float > GetQuantizationScales() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00451">Tensor.cpp:451</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a53bfb6eb38a90244ba166b641a6965d9"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a53bfb6eb38a90244ba166b641a6965d9">armnn_driver::OperandType</a></div><div class="ttdeci">::android::nn::OperandType OperandType</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00046">ConversionUtils.hpp:46</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a10c64daf22426af432d0a9ada03eee5cad0749aaba8b833466dfcbb0428e4f89c"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5cad0749aaba8b833466dfcbb0428e4f89c">armnn_driver::DequantizeStatus::SUCCESS</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a3ac499dc54900adc7f2613944b583e10"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a3ac499dc54900adc7f2613944b583e10">armnn_driver::GetInputActivationFunctionImpl</a></div><div class="ttdeci">bool GetInputActivationFunctionImpl(const Operation &operation, uint32_t inputIndex, OperandType type, ActivationFn &outActivationFunction, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00790">ConversionUtils.hpp:790</a></div></div>
<div class="ttc" id="structarmnn__driver_1_1_conversion_data_xhtml_a094e06eb84b3b80533c0f961f0f472de"><div class="ttname"><a href="structarmnn__driver_1_1_conversion_data.xhtml#a094e06eb84b3b80533c0f961f0f472de">armnn_driver::ConversionData::m_DynamicInputsEncountered</a></div><div class="ttdeci">bool m_DynamicInputsEncountered</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00063">ConversionUtils.hpp:63</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</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="classarmnn_1_1_tensor_info_xhtml_abe8889e8150beef5fd204b2d87b49298"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">armnn::TensorInfo::SetShape</a></div><div class="ttdeci">void SetShape(const TensorShape &newShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00193">Tensor.hpp:193</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_ae059aea66ee0867a204aa2f2d9abb42c"><div class="ttname"><a href="namespacearmnn__driver.xhtml#ae059aea66ee0867a204aa2f2d9abb42c">armnn_driver::g_DontPermute</a></div><div class="ttdeci">const armnn::PermutationVector g_DontPermute</div><div class="ttdef"><b>Definition:</b> <a href="_canonical_utils_8cpp_source.xhtml#l00038">CanonicalUtils.cpp:38</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a14977f94479f2f7e13bdf915ac8ce8d0"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a14977f94479f2f7e13bdf915ac8ce8d0">armnn_driver::GetInputOperand</a></div><div class="ttdeci">const Operand * GetInputOperand(const Operation &operation, uint32_t inputIndex, const Model &model, bool failOnIndexOutOfBounds=true)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00633">ConversionUtils.hpp:633</a></div></div>
<div class="ttc" id="structarmnn_1_1_reshape_descriptor_xhtml_a1178f4dafdda81f59c15145ec327f7d9"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.xhtml#a1178f4dafdda81f59c15145ec327f7d9">armnn::ReshapeDescriptor::m_TargetShape</a></div><div class="ttdeci">TensorShape m_TargetShape</div><div class="ttdoc">Target shape value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00979">Descriptors.hpp:979</a></div></div>
<div class="ttc" id="structarmnn_1_1_pad_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pad_descriptor.xhtml">armnn::PadDescriptor</a></div><div class="ttdoc">A PadDescriptor for the PadLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01136">Descriptors.hpp:1136</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a10c64daf22426af432d0a9ada03eee5ca6bf179afa8f7fba18cf39bc0ca6fe043"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5ca6bf179afa8f7fba18cf39bc0ca6fe043">armnn_driver::DequantizeStatus::INVALID_OPERAND</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a2eb75cb48464cf87c290503d7bea79a4"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a2eb75cb48464cf87c290503d7bea79a4">armnn_driver::ConvertPooling2d</a></div><div class="ttdeci">bool ConvertPooling2d(const Operation &operation, const char *operationName, armnn::PoolingAlgorithm poolType, const Model &model, ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00376">ConversionUtils.cpp:376</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a8c749c18e62c59a5c1254aac342c995a"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a8c749c18e62c59a5c1254aac342c995a">armnn_driver::ConvertOperationInputToConstTensorPin</a></div><div class="ttdeci">ConstTensorPin ConvertOperationInputToConstTensorPin(const Operation &operation, uint32_t inputIndex, const Model &model, const ConversionData &data, const armnn::PermutationVector &dimensionMappings=g_DontPermute, const armnn::TensorShape *overrideTensorShape=nullptr, bool optional=false)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00708">ConversionUtils.hpp:708</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_abc05539fc6e7907f32ef0fb242e3b3b0"><div class="ttname"><a href="namespacearmnn.xhtml#abc05539fc6e7907f32ef0fb242e3b3b0">armnn::ReduceOperation</a></div><div class="ttdeci">ReduceOperation</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00143">Types.hpp:143</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a923b39ec5f83672f50289cbaf5de6798"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a923b39ec5f83672f50289cbaf5de6798">armnn_driver::Model</a></div><div class="ttdeci">::android::nn::Model Model</div><div class="ttdoc">Helper classes. </div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00043">ConversionUtils.hpp:43</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#l00048">Types.hpp:48</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_abf92490dc588f48af86fc12184841fd5"><div class="ttname"><a href="namespacearmnn__driver.xhtml#abf92490dc588f48af86fc12184841fd5">armnn_driver::GetInputScalar</a></div><div class="ttdeci">bool GetInputScalar(const Operation &operation, uint32_t inputIndex, OperandType type, OutputType &outValue, const Model &model, const ConversionData &data, bool optional=false)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00732">ConversionUtils.hpp:732</a></div></div>
<div class="ttc" id="structarmnn__driver_1_1_conversion_data_xhtml_a2db3ae8d422f17d455e0ba0cb6291d2a"><div class="ttname"><a href="structarmnn__driver_1_1_conversion_data.xhtml#a2db3ae8d422f17d455e0ba0cb6291d2a">armnn_driver::ConversionData::m_Network</a></div><div class="ttdeci">armnn::INetworkPtr m_Network</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00060">ConversionUtils.hpp:60</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#l00041">INetwork.hpp:41</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_afa2a6d5a1431289c92cea9cceeb174c9a6dcca67f0df2a0038edf5a82b1399527"><div class="ttname"><a href="namespacearmnn__driver.xhtml#afa2a6d5a1431289c92cea9cceeb174c9a6dcca67f0df2a0038edf5a82b1399527">armnn_driver::ConversionResult::UnsupportedFeature</a></div></div>
<div class="ttc" id="classarmnn__driver_1_1_layer_input_handle_xhtml_acbafd23115b06f0a82eab45bd1e3cff9"><div class="ttname"><a href="classarmnn__driver_1_1_layer_input_handle.xhtml#acbafd23115b06f0a82eab45bd1e3cff9">armnn_driver::LayerInputHandle::GetTensorInfo</a></div><div class="ttdeci">const armnn::TensorInfo & GetTensorInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00050">ConversionUtils.cpp:50</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a3f3a756df9dee4b33566cddd786b83c9"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a3f3a756df9dee4b33566cddd786b83c9">armnn_driver::OptionalDataLayout</a></div><div class="ttdeci">armnn::DataLayout OptionalDataLayout(const Operation &operation, uint32_t inputIndex, const Model &model, ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00842">ConversionUtils.cpp:842</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#l00461">Tensor.cpp:461</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00327">Tensor.hpp:327</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a8d4f662a4fb5b9272724bdaeacbd370a"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a8d4f662a4fb5b9272724bdaeacbd370a">armnn_driver::ConvertPaddings</a></div><div class="ttdeci">bool ConvertPaddings(const Operation &operation, const Model &model, ConversionData &data, unsigned int rank, armnn::PadDescriptor &padDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00334">ConversionUtils.cpp:334</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a10c64daf22426af432d0a9ada03eee5c"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a10c64daf22426af432d0a9ada03eee5c">armnn_driver::DequantizeStatus</a></div><div class="ttdeci">DequantizeStatus</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00997">ConversionUtils.hpp:997</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a8d20245b5ca3cbb0b132064ab44f2682"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a8d20245b5ca3cbb0b132064ab44f2682">armnn_driver::GetOperandValueReadOnlyAddress</a></div><div class="ttdeci">const void * GetOperandValueReadOnlyAddress(const Operand &operand, const Model &model, const ConversionData &data, bool optional)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00766">ConversionUtils.cpp:766</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00473">Tensor.cpp:473</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="namespaceandroid_1_1nn_xhtml"><div class="ttname"><a href="namespaceandroid_1_1nn.xhtml">android::nn</a></div><div class="ttdef"><b>Definition:</b> <a href="support__library__service_8cpp_source.xhtml#l00010">support_library_service.cpp:10</a></div></div>
<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00036">Descriptors.hpp:36</a></div></div>
<div class="ttc" id="classarmnn__driver_1_1_layer_input_handle_xhtml"><div class="ttname"><a href="classarmnn__driver_1_1_layer_input_handle.xhtml">armnn_driver::LayerInputHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00066">ConversionUtils.hpp:66</a></div></div>
<div class="ttc" id="classarmnn_1_1_permutation_vector_xhtml"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00295">Types.hpp:295</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_ac8643aaee3eafc54336c5462b51bd53f"><div class="ttname"><a href="namespacearmnn__driver.xhtml#ac8643aaee3eafc54336c5462b51bd53f">armnn_driver::GetTensorInt32Values</a></div><div class="ttdeci">bool GetTensorInt32Values(const Operand &operand, std::vector< int32_t > &outValues, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00811">ConversionUtils.cpp:811</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a4c6b55ca5080b58c2cc6d7c6c7347d96"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a4c6b55ca5080b58c2cc6d7c6c7347d96">armnn_driver::GetInputActivationFunctionFromTensor</a></div><div class="ttdeci">bool GetInputActivationFunctionFromTensor(const Operation &operation, uint32_t inputIndex, ActivationFn &outActivationFunction, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00827">ConversionUtils.hpp:827</a></div></div>
<div class="ttc" id="structarmnn__driver_1_1_conversion_data_xhtml_a0b09b7d54e89b04521d9574a968be458"><div class="ttname"><a href="structarmnn__driver_1_1_conversion_data.xhtml#a0b09b7d54e89b04521d9574a968be458">armnn_driver::ConversionData::ConversionData</a></div><div class="ttdeci">ConversionData(const std::vector< armnn::BackendId > &backends)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00053">ConversionUtils.hpp:53</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a519efe8ff6dc3aacdfe8a999415e3e4e"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">armnn::TensorInfo::SetQuantizationDim</a></div><div class="ttdeci">void SetQuantizationDim(const Optional< unsigned int > &quantizationDim)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00499">Tensor.cpp:499</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a56e87ad879b142327b822beff44ca171"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a56e87ad879b142327b822beff44ca171">armnn_driver::IsWeightsValid</a></div><div class="ttdeci">bool IsWeightsValid(const Operation &operation, uint32_t inputIndex, const Model &model)</div><div class="ttdoc">Utility functions. </div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00134">ConversionUtils.cpp:134</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a8932639a884a3dc698f29d4e8395ba49"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a8932639a884a3dc698f29d4e8395ba49">armnn_driver::DequantizeResult</a></div><div class="ttdeci">std::tuple< std::unique_ptr< float[]>, size_t, armnn::TensorInfo, DequantizeStatus > DequantizeResult</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l01004">ConversionUtils.hpp:1004</a></div></div>
<div class="ttc" id="classarmnn_1_1_permutation_vector_xhtml_aae44e4154aa80fba7616747450ff69d5"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml#aae44e4154aa80fba7616747450ff69d5">armnn::PermutationVector::IsEqual</a></div><div class="ttdeci">bool IsEqual(const PermutationVector &other) const</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00347">Types.hpp:347</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="namespacearmnn__driver_xhtml_a1f6b85ab26d684241babcde2d659116b"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a1f6b85ab26d684241babcde2d659116b">armnn_driver::ConvertToLayerInputHandle</a></div><div class="ttdeci">LayerInputHandle ConvertToLayerInputHandle(const Operation &operation, uint32_t inputIndex, const Model &model, ConversionData &data, const armnn::PermutationVector &dimensionMappings, const LayerInputHandle *inputHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00204">ConversionUtils.cpp:204</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_aa9b4bc8d4cfb04be14771dbb1bc1a1ac"><div class="ttname"><a href="namespacearmnn__driver.xhtml#aa9b4bc8d4cfb04be14771dbb1bc1a1ac">armnn_driver::Operand</a></div><div class="ttdeci">::android::nn::Operand Operand</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00044">ConversionUtils.hpp:44</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a8a3380be13fba749fc4208214b049347"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a8a3380be13fba749fc4208214b049347">armnn::INetwork::AddReshapeLayer</a></div><div class="ttdeci">IConnectableLayer * AddReshapeLayer(const ReshapeDescriptor &reshapeDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a reshape layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00274">Network.cpp:274</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a5378da53b59c1c826e6320383ca0257e"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a5378da53b59c1c826e6320383ca0257e">armnn_driver::SetupAndTrackLayerOutputSlot</a></div><div class="ttdeci">bool SetupAndTrackLayerOutputSlot(const Operation &operation, uint32_t operationOutputIndex, armnn::IConnectableLayer &layer, uint32_t layerOutputIndex, const Model &model, ConversionData &data, const armnn::TensorInfo *overrideOutputInfo, const std::function< void(const armnn::TensorInfo &, bool &)> &validateFunc, const ActivationFn &activationFunction, bool inferOutputShapes)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00949">ConversionUtils.cpp:949</a></div></div>
<div class="ttc" id="_conversion_utils_8hpp_xhtml_abcb5019b10b89cbd2b96118885a026d4"><div class="ttname"><a href="_conversion_utils_8hpp.xhtml#abcb5019b10b89cbd2b96118885a026d4">getMainModel</a></div><div class="ttdeci">const android::nn::Model::Subgraph & getMainModel(const android::nn::Model &model)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00028">ConversionUtils.hpp:28</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_aa9ef723ace8562b9636e8387a120fbde"><div class="ttname"><a href="namespacearmnn__driver.xhtml#aa9ef723ace8562b9636e8387a120fbde">armnn_driver::GetInputPaddingScheme</a></div><div class="ttdeci">bool GetInputPaddingScheme(const Operation &operation, uint32_t inputIndex, PaddingScheme &outPaddingScheme, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00750">ConversionUtils.cpp:750</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a28243ca97e12ccb50e01f03d313ecc86"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a28243ca97e12ccb50e01f03d313ecc86">armnn_driver::ConvertToActivation</a></div><div class="ttdeci">bool ConvertToActivation(const Operation &operation, const char *operationName, const armnn::ActivationDescriptor &activationDesc, const Model &model, ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00583">ConversionUtils.cpp:583</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a37ca67c646393225921543233a873803"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a37ca67c646393225921543233a873803">armnn_driver::DequantizeAndMakeConstTensorPin</a></div><div class="ttdeci">ConstTensorPin DequantizeAndMakeConstTensorPin(const Operation &operation, const Model &model, const ConversionData &data, size_t operandIndex, bool optional)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00720">ConversionUtils.cpp:720</a></div></div>
<div class="ttc" id="_conversion_utils_8hpp_xhtml_a6f98cfbf3171f950d1f0df30d60691a7"><div class="ttname"><a href="_conversion_utils_8hpp.xhtml#a6f98cfbf3171f950d1f0df30d60691a7">FORWARD_LAYER_SUPPORT_FUNC</a></div><div class="ttdeci">#define FORWARD_LAYER_SUPPORT_FUNC(funcName, func, backends, supported,...)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00153">ConversionUtils.hpp:153</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_aa43f9c81f830559c15e5af86f8e11482"><div class="ttname"><a href="namespacearmnn__driver.xhtml#aa43f9c81f830559c15e5af86f8e11482">armnn_driver::GetInputInt32</a></div><div class="ttdeci">bool GetInputInt32(const Operation &operation, uint32_t inputIndex, int32_t &outValue, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00772">ConversionUtils.hpp:772</a></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="namespacearmnn__driver_xhtml_a7bf2bd59bc8ca21e0dd906044bfc2faf"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a7bf2bd59bc8ca21e0dd906044bfc2faf">armnn_driver::IsConnectedToDequantize</a></div><div class="ttdeci">bool IsConnectedToDequantize(armnn::IOutputSlot *ioutputSlot)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l01026">ConversionUtils.cpp:1026</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a275cd95635b854a80bb33f171d861ddc"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a275cd95635b854a80bb33f171d861ddc">armnn_driver::OperandLifeTime</a></div><div class="ttdeci">::android::nn::Operand::LifeTime OperandLifeTime</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00045">ConversionUtils.hpp:45</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_afa2a6d5a1431289c92cea9cceeb174c9a505a83f220c02df2f85c3810cd9ceb38"><div class="ttname"><a href="namespacearmnn__driver.xhtml#afa2a6d5a1431289c92cea9cceeb174c9a505a83f220c02df2f85c3810cd9ceb38">armnn_driver::ConversionResult::Success</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_aac972ee73e8bd2374bc40ab844a7d894"><div class="ttname"><a href="namespacearmnn__driver.xhtml#aac972ee73e8bd2374bc40ab844a7d894">armnn_driver::ProcessActivation</a></div><div class="ttdeci">armnn::IConnectableLayer * ProcessActivation(const armnn::TensorInfo &tensorInfo, ActivationFn activation, armnn::IConnectableLayer *prevLayer, ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00874">ConversionUtils.cpp:874</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_utils_xhtml_acee63cd08da47910fc166a1990988fa8"><div class="ttname"><a href="namespacearmnn_utils.xhtml#acee63cd08da47910fc166a1990988fa8">armnnUtils::GetTensorInfo</a></div><div class="ttdeci">armnn::TensorInfo GetTensorInfo(unsigned int numberOfBatches, unsigned int numberOfChannels, unsigned int height, unsigned int width, const armnn::DataLayout dataLayout, const armnn::DataType dataType)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.xhtml#l00038">TensorUtils.cpp:38</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a9ddfceb499ef7b3d01053399bc79b852"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a9ddfceb499ef7b3d01053399bc79b852">armnn_driver::IsOperandConstant</a></div><div class="ttdeci">bool IsOperandConstant(const Operand &operand)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00688">ConversionUtils.hpp:688</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_descriptor.xhtml">armnn::TransposeDescriptor</a></div><div class="ttdoc">A TransposeDescriptor for the TransposeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01430">Descriptors.hpp:1430</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="namespacearmnn__driver_xhtml_ace6b45d6363c32d1b93b7fce14bf6344"><div class="ttname"><a href="namespacearmnn__driver.xhtml#ace6b45d6363c32d1b93b7fce14bf6344">armnn_driver::OperationType</a></div><div class="ttdeci">::android::nn::OperationType OperationType</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00048">ConversionUtils.hpp:48</a></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="namespacearmnn__driver_xhtml_a78a9a9f196810df6bc4795568f275c75"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a78a9a9f196810df6bc4795568f275c75">armnn_driver::DequantizeIfRequired</a></div><div class="ttdeci">DequantizeResult DequantizeIfRequired(size_t operand_index, const Operation &operation, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8cpp_source.xhtml#l00637">ConversionUtils.cpp:637</a></div></div>
<div class="ttc" id="_test_utils_8cpp_xhtml_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00014">TestUtils.cpp: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#l00253">INetwork.hpp:253</a></div></div>
<div class="ttc" id="namespacearmnn_utils_xhtml_a428a9a6ffdf0e8d723b50c038c56c336"><div class="ttname"><a href="namespacearmnn_utils.xhtml#a428a9a6ffdf0e8d723b50c038c56c336">armnnUtils::TransposeTensorShape</a></div><div class="ttdeci">armnn::TensorShape TransposeTensorShape(const armnn::TensorShape &srcShape, const armnn::PermutationVector &mappings)</div><div class="ttdef"><b>Definition:</b> <a href="_transpose_8cpp_source.xhtml#l00098">Transpose.cpp:98</a></div></div>
<div class="ttc" id="namespacearmnn_utils_xhtml_a56b0e17341e000fa1d4561890294520c"><div class="ttname"><a href="namespacearmnn_utils.xhtml#a56b0e17341e000fa1d4561890294520c">armnnUtils::within_percentage_tolerance</a></div><div class="ttdeci">bool within_percentage_tolerance(float a, float b, float tolerancePercent=1.0f)</div><div class="ttdoc">Compare two floats and return true if their values are within a specified tolerance of each other...</div><div class="ttdef"><b>Definition:</b> <a href="_floating_point_comparison_8hpp_source.xhtml#l00020">FloatingPointComparison.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_acfe37581bc8296b5d4cdb311b1e3f142"><div class="ttname"><a href="namespacearmnn__driver.xhtml#acfe37581bc8296b5d4cdb311b1e3f142">armnn_driver::GetOptionalConvolutionDilationParams</a></div><div class="ttdeci">bool GetOptionalConvolutionDilationParams(const Operation &operation, uint32_t dilationXIndex, ConvolutionDescriptor &descriptor, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00864">ConversionUtils.hpp:864</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_afa2a6d5a1431289c92cea9cceeb174c9"><div class="ttname"><a href="namespacearmnn__driver.xhtml#afa2a6d5a1431289c92cea9cceeb174c9">armnn_driver::ConversionResult</a></div><div class="ttdeci">ConversionResult</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00125">ConversionUtils.hpp:125</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a1a8675f9d64c3fb59e6af15362bb6332"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">armnn::TensorInfo::SetQuantizationScales</a></div><div class="ttdeci">void SetQuantizationScales(const std::vector< float > &scales)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00456">Tensor.cpp:456</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00195">Tensor.hpp:195</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml"><div class="ttname"><a href="namespacearmnn__driver.xhtml">armnn_driver</a></div><div class="ttdoc">Helper classes. </div><div class="ttdef"><b>Definition:</b> <a href="_armnn_device_8cpp_source.xhtml#l00037">ArmnnDevice.cpp:37</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_descriptor_xhtml_a14433af2b223695b40d8c8f8ba2ebb8f"><div class="ttname"><a href="structarmnn_1_1_transpose_descriptor.xhtml#a14433af2b223695b40d8c8f8ba2ebb8f">armnn::TransposeDescriptor::m_DimMappings</a></div><div class="ttdeci">PermutationVector m_DimMappings</div><div class="ttdoc">Indicates how to translate tensor elements from a given source into the target destination, when source and target potentially have different memory layouts e.g. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01447">Descriptors.hpp:1447</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_input_slot_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_input_slot.xhtml">armnn::IInputSlot</a></div><div class="ttdoc">An input connection slot for a layer. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00025">INetwork.hpp:25</a></div></div>
<div class="ttc" id="namespacearmnn__driver_xhtml_a560530462631e354561c1763f695351c"><div class="ttname"><a href="namespacearmnn__driver.xhtml#a560530462631e354561c1763f695351c">armnn_driver::GetInputFloat32</a></div><div class="ttdeci">bool GetInputFloat32(const Operation &operation, uint32_t inputIndex, float &outValue, const Model &model, const ConversionData &data)</div><div class="ttdef"><b>Definition:</b> <a href="_conversion_utils_8hpp_source.xhtml#l00781">ConversionUtils.hpp:781</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_xhtml_ab067ba4ee9416d93abb8a52f3dc8feba"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ab067ba4ee9416d93abb8a52f3dc8feba">armnn::INetwork::AddTransposeLayer</a></div><div class="ttdeci">IConnectableLayer * AddTransposeLayer(const TransposeDescriptor &transposeDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a transpose layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00379">Network.cpp:379</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_af5014cbc003abcf201d4372b0012734c"><div class="ttname"><a href="namespacearmnn.xhtml#af5014cbc003abcf201d4372b0012734c">armnn::IsReshapeSupported</a></div><div class="ttdeci">bool IsReshapeSupported(const BackendId &backend, const TensorInfo &input, const ReshapeDescriptor &descriptor, char *reasonIfUnsupported=nullptr, size_t reasonIfUnsupportedMaxLength=1024)</div><div class="ttdoc">Deprecated in favor of IBackend and ILayerSupport interfaces. </div></div>
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