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<div class="title">Tensor.hpp</div> </div>
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<a href="_tensor_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_tensor_fwd_8hpp.xhtml">TensorFwd.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_exceptions_8hpp.xhtml">Exceptions.hpp</a>"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include "<a class="code" href="_optional_8hpp.xhtml">Optional.hpp</a>"</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include "<a class="code" href="_types_8hpp.xhtml">Types.hpp</a>"</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <array></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <initializer_list></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> {</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml"> 20</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> {</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> /// Empty (invalid) constructor.</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>();</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="comment"></span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment"> /// @param initDimensionsSpecificity (optional) - value to initialize the specificity of each dimension size.</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"></span> <span class="keyword">explicit</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keywordtype">bool</span> initDimensionsSpecificity = <span class="keyword">true</span>);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment"></span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> /// @param dimensionSizes - Size of each of dimension.</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes);</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"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> /// @param dimensionSizeList - Size of each of dimension.</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(std::initializer_list<unsigned int> dimensionSizeList);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"></span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"> /// Copy Constructor for TensorShape</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"> /// @param other - TensorShape to copy from.</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment"></span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> /// @param dimensionSizes - Size of each of dimension.</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"> /// @param dimensionsSpecificity - Flags to indicate which dimension has its size specified.</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes, <span class="keyword">const</span> <span class="keywordtype">bool</span>* dimensionsSpecificity);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment"></span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> /// @param dimensionSizeList - Size of each of dimension.</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> /// @param dimensionsSpecificityList - Flags to indicate which dimension size is specified.</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(std::initializer_list<unsigned int> dimensionSizeList,</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  std::initializer_list<bool> dimensionsSpecificityList);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"></span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> /// @param dimensionality - Parameter to indicate if the Tensor is a Scalar, a Tensor of known dimensionality</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"> /// or a Tensor of unknown dimensionality.</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="comment"></span> <span class="keyword">explicit</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> dimensionality);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="comment"></span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="comment"> /// Assignation function</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="comment"> /// @param other - TensorShape to copy from.</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"></span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment"> /// Read only operator</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="comment"></span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="comment"> /// Read and write operator</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment"></span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="comment"> /// Equality comparison operator</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="comment"> /// @param other - TensorShape to compare with.</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">operator==</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="comment"></span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="comment"> /// Inequality comparison operator</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="comment"> /// @param other - TensorShape to compare with.</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">operator!=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="comment"></span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="comment"> /// Function that returns the tensor rank.</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="comment"> /// @return - Tensor rank.</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"></span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment"> /// Function that calculates the tensor elements by multiplying all dimension size which are Specified.</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="comment"> /// @return - Total number of elements in the tensor.</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="comment"></span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="comment"> /// Function that returns the tensor type.</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="comment"> /// @return - Parameter to indicate if the Tensor is a scalar, a Tensor of known dimensionality or</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="comment"> /// a Tensor of unknown dimensionality</span></div><div class="line"><a name="l00092"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a5a212540c00931bd2a4b4041beda33ae"> 92</a></span> <span class="comment"></span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a5a212540c00931bd2a4b4041beda33ae">GetDimensionality</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Dimensionality; }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="comment"></span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="comment"> /// Gets information about if the dimension size has been specified or not</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="comment"> /// @return - Flag to indicate if the dimension "i" has a specified size.</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a3919600d4aa8d5cd801a0e0740f62308">GetDimensionSpecificity</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="comment"></span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="comment"> /// Sets the tensor rank and therefore the Dimensionality is set to Specified if it was not.</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="comment"> /// @param initDimensionsSpecificity (optional) - value to initialize the specificity of each dimension size.</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2">SetNumDimensions</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keywordtype">bool</span> initDimensionsSpecificity = <span class="keyword">false</span>);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="comment"></span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="comment"> /// Sets the size of the indicated dimension and Specificity for that dimension is set to true.</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="comment"> /// @param dimensionSize - size of one dimension.</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90">SetDimensionSize</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimensionSize);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="comment"></span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment"> /// Checks if there is at least one dimension not specified. AND of all array elements.</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="comment"> /// @return - True when all dimension sizes are specified. False when at least one dimension size is not specified.</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1">AreAllDimensionsSpecified</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="comment"></span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="comment"> /// Checks if there is at least one dimension specified. OR of all array elements.</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"> /// @return - True at least one dimension sizes is specified. False when all dimension sizes are not specified.</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b">IsAtLeastOneDimensionSpecified</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="keyword">private</span>:<span class="comment"></span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="comment"> /// Array of the dimension sizes.</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="comment"></span> std::array<unsigned int, MaxNumOfTensorDimensions> m_Dimensions{};</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="comment"></span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="comment"> /// Array of flags to indicate if the size of each of the dimensions is specified or not</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="comment"></span> std::array<bool, MaxNumOfTensorDimensions> m_DimensionsSpecificity = { {<span class="keyword">true</span>} };</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="comment"></span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="comment"> /// Tensor rank</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m_NumDimensions{};</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="comment"></span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="comment"> /// Tensor type: Specified, NotSpecified or Scalar.</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="comment"></span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> m_Dimensionality = <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Dimensionality::Specified</a>;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="comment"></span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="comment"> /// Checks if the dimension index given is within range.</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckDimensionIndex(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</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"> /// Checks if the tensor rank given is within range.</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="comment"></span> <span class="keyword">static</span> <span class="keywordtype">void</span> CheckValidNumDimensions(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions) ;</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="comment"> /// Checks if the size of the dimension index given is specified.</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckDimensionSpecified(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="comment"></span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment"> /// Checks if this is a scalar.</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckScalar() <span class="keyword">const</span>;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment"></span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="comment"> /// Checks if the number of dimensions is unknown, i.e. rank is unspecified.</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckUnspecifiedNumDimensions() <span class="keyword">const</span>;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="comment"></span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="comment"> /// Checks if the number of dimensions is known, i.e. rank is specified.</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckSpecifiedNumDimensions() <span class="keyword">const</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> </div><div class="line"><a name="l00152"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml"> 152</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> {</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="comment"> /// Empty (invalid) constructor.</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>();</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& shape,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordtype">float</span> quantizationScale = 0.0f,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  int32_t quantizationOffset = 0);</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keywordtype">float</span> quantizationScale = 0.0f,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  int32_t quantizationOffset = 0);</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& shape,</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim);</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> </div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> </div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">operator==</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">operator!=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div><div class="line"><a name="l00187"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8"> 187</a></span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Shape; }</div><div class="line"><a name="l00188"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a350bcc7d86f7d9333340a0a04be078f6"> 188</a></span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a350bcc7d86f7d9333340a0a04be078f6">GetShape</a>() { <span class="keywordflow">return</span> m_Shape; }</div><div class="line"><a name="l00189"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298"> 189</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& newShape) { m_Shape = newShape; }</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24"> 191</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Shape.GetNumDimensions(); }</div><div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7"> 192</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Shape.GetNumElements(); }</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> </div><div class="line"><a name="l00194"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3"> 194</a></span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_DataType; }</div><div class="line"><a name="l00195"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd"> 195</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd">SetDataType</a>(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> type) { m_DataType = type; }</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7"> 197</a></span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">HasMultipleQuantizationScales</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Quantization.m_Scales.size() > 1; }</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>  <span class="keywordtype">bool</span> HasPerAxisQuantization() <span class="keyword">const</span>;</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  std::vector<float> GetQuantizationScales() <span class="keyword">const</span>;</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordtype">void</span> SetQuantizationScales(<span class="keyword">const</span> std::vector<float>& scales);</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> </div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keywordtype">float</span> GetQuantizationScale() <span class="keyword">const</span>;</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordtype">void</span> <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a522a440dc1e26bed45fd3f68be8484e9">SetQuantizationScale</a>(<span class="keywordtype">float</span> scale);</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  int32_t GetQuantizationOffset() <span class="keyword">const</span>;</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordtype">void</span> <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#aec48a5a5ab6ecf86c8db0f6d0859fe2f">SetQuantizationOffset</a>(int32_t offset);</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span> </div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a> GetQuantizationDim() <span class="keyword">const</span>;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keywordtype">void</span> SetQuantizationDim(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a>& quantizationDim);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="keywordtype">bool</span> IsQuantized() <span class="keyword">const</span>;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> <span class="comment"></span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> <span class="comment"> /// Check that the types are the same and, if quantize, that the quantization parameters are the same.</span></div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> <span class="comment"></span> <span class="keywordtype">bool</span> IsTypeSpaceMatch(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> </div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> GetNumBytes() <span class="keyword">const</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">private</span>:</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> m_Shape;</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> m_DataType;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="comment"></span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="comment"> /// Vectors of scale and offset are used for per-axis quantization.</span></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> <span class="comment"></span> <span class="keyword">struct </span>Quantization</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  {</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  Quantization()</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  : m_Scales{}</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  , m_Offset(<a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>())</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  , m_QuantizationDim(<a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>()) {}</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  Quantization(<span class="keyword">const</span> Quantization& other)</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  : m_Scales(other.m_Scales)</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  , m_Offset(other.m_Offset)</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  , m_QuantizationDim(other.m_QuantizationDim) {}</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="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">operator==</a>(<span class="keyword">const</span> Quantization& other)<span class="keyword"> const</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keywordflow">return</span> ((m_Scales == other.m_Scales) && (m_Offset == other.m_Offset) &&</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  (m_QuantizationDim == other.m_QuantizationDim));</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  }</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> </div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  Quantization& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">operator=</a>(<span class="keyword">const</span> Quantization& other)</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>  <span class="keywordflow">if</span>(<span class="keyword">this</span> != &other)</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  {</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  m_Scales = other.m_Scales;</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  m_Offset = other.m_Offset;</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  m_QuantizationDim = other.m_QuantizationDim;</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  }</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  }</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> </div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  std::vector<float> m_Scales;</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<int32_t></a> m_Offset;</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a> m_QuantizationDim;</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> </div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  } m_Quantization;</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> </div><div class="line"><a name="l00261"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44"> 261</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">BindingPointInfo</a> = std::pair<armnn::LayerBindingId, armnn::TensorInfo>;</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> </div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00264"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml"> 264</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a></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> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> <span class="comment"> /// Empty (invalid) constructor.</span></div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>();</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> <span class="comment"></span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> <span class="comment"> /// Constructor from a raw memory pointer.</span></div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> <span class="comment"> /// @param memoryArea - Region of CPU-addressable memory where tensor data will be stored. Must be valid while</span></div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> <span class="comment"> /// workloads are on the fly. Tensor instances do not claim ownership of referenced memory regions, that is,</span></div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> <span class="comment"> /// no attempt will be made by ArmNN to free these memory regions automatically.</span></div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, MemoryType memoryArea);</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> <span class="comment"></span></div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> <span class="comment"> /// Tensors are copyable.</span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>& other);</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> <span class="comment"></span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="comment"> /// Tensors are copyable.</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>&);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div><div class="line"><a name="l00282"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678"> 282</a></span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info; }</div><div class="line"><a name="l00283"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#ab2e02564acd2ce6db36de310702a75de"> 283</a></span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#ab2e02564acd2ce6db36de310702a75de">GetInfo</a>() { <span class="keywordflow">return</span> m_Info; }</div><div class="line"><a name="l00284"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8"> 284</a></span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetShape(); }</div><div class="line"><a name="l00285"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a350bcc7d86f7d9333340a0a04be078f6"> 285</a></span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a350bcc7d86f7d9333340a0a04be078f6">GetShape</a>() { <span class="keywordflow">return</span> m_Info.GetShape(); }</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3"> 287</a></span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetDataType(); }</div><div class="line"><a name="l00288"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24"> 288</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetNumDimensions(); }</div><div class="line"><a name="l00289"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0"> 289</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetNumBytes(); }</div><div class="line"><a name="l00290"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a8846406ac37fbd2204f0be16ee05d5b7"> 290</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetNumElements(); }</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996"> 292</a></span>  MemoryType <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996">GetMemoryArea</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_MemoryArea; }</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> </div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> <span class="keyword">protected</span>:<span class="comment"></span></div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> <span class="comment"> /// Protected destructor to stop users from making these</span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> <span class="comment"> /// (could still new one on the heap and then leak it...)</span></div><div class="line"><a name="l00297"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#abac025efeffc6e099a365bdb17b5ca3e"> 297</a></span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#abac025efeffc6e099a365bdb17b5ca3e">~BaseTensor</a>() {}</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49"> 299</a></span>  MemoryType <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>;</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> </div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> m_Info;</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span> };</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> <span class="comment"></span></div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> <span class="comment">/// A tensor defined by a TensorInfo (shape and data type) and a mutable backing store.</span></div><div class="line"><a name="l00306"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor.xhtml"> 306</a></span> <span class="comment"></span><span class="keyword">class </span><a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a> : <span class="keyword">public</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><void*></div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> {</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="comment"> /// Brings in the constructors and assignment operator.</span></div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> <span class="comment"></span> <span class="keyword">using</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<void*>::BaseTensor</a>;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> };</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="comment"></span></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> <span class="comment">/// A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.</span></div><div class="line"><a name="l00314"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml"> 314</a></span> <span class="comment"></span><span class="keyword">class </span><a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> : <span class="keyword">public</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*></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> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <span class="comment"> /// Brings in the constructors and assignment operator.</span></div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="comment"></span> <span class="keyword">using</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<const void*>::BaseTensor</a>;</div><div class="line"><a name="l00319"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#a6b6561873c02b1bd9b7a7ae8dd4a339c"> 319</a></span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml#a6b6561873c02b1bd9b7a7ae8dd4a339c">ConstTensor</a>() : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>() {} <span class="comment">// This needs to be redefined explicitly??</span></div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> <span class="comment"></span></div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> <span class="comment"> /// Can be implicitly constructed from non-const Tensor.</span></div><div class="line"><a name="l00322"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#a42aec46c635aa2e38932ca103d2064ed"> 322</a></span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml#a42aec46c635aa2e38932ca103d2064ed">ConstTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a>& other) : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>(other.GetInfo(), other.GetMemoryArea()) {}</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> <span class="comment"></span></div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> <span class="comment"> /// Constructor from a backing container.</span></div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> <span class="comment"> /// @param container - An stl-like container type which implements data() and size() methods.</span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> <span class="comment"> /// Presence of data() and size() is a strong indicator of the continuous memory layout of the container,</span></div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> <span class="comment"> /// which is a requirement for Tensor data. Tensor instances do not claim ownership of referenced memory regions,</span></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> <span class="comment"> /// that is, no attempt will be made by ArmNN to free these memory regions automatically.</span></div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> <span class="comment"></span> <span class="keyword">template</span> < <span class="keyword">template</span><<span class="keyword">typename</span>, <span class="keyword">typename</span>...> <span class="keyword">class </span>ContainerType, <span class="keyword">typename</span> T, <span class="keyword">typename</span>...ContainerArgs ></div><div class="line"><a name="l00330"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#aa04de06d072895b6df9125338d55c205"> 330</a></span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml#aa04de06d072895b6df9125338d55c205">ConstTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, <span class="keyword">const</span> ContainerType<T, ContainerArgs...>& container)</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>(info, container.data())</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  {</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordflow">if</span> (container.size() * <span class="keyword">sizeof</span>(T) != info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>())</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  {</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Container size is not correct"</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>  }</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> };</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> </div><div class="line"><a name="l00340"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527"> 340</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> = std::vector<std::pair<LayerBindingId, class ConstTensor>>;</div><div class="line"><a name="l00341"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea"> 341</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> = std::vector<std::pair<LayerBindingId, class Tensor>>;</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span> </div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> } <span class="comment">// namespace armnn</span></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="classarmnn_1_1_tensor_shape_xhtml_a77d202fcd47612eb5a4d6d23a7d4b349"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">armnn::TensorShape::operator!=</a></div><div class="ttdeci">bool operator!=(const TensorShape &other) const</div><div class="ttdoc">Inequality comparison operator. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00169">Tensor.cpp:169</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a6e6dab22049a4432e8306a301dceff52"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">armnn::TensorShape::operator[]</a></div><div class="ttdeci">unsigned int operator[](unsigned int i) const</div><div class="ttdoc">Read only operator. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00135">Tensor.cpp:135</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">armnn::Dimensionality</a></div><div class="ttdeci">Dimensionality</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00125">Types.hpp:125</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#l00187">Tensor.hpp:187</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a0ca6f42172d27e9799da3e3f7840ac31"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">armnn::TensorShape::operator=</a></div><div class="ttdeci">TensorShape & operator=(const TensorShape &other)</div><div class="ttdoc">Assignation function. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00124">Tensor.cpp:124</a></div></div>
<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional< unsigned int ></a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_acccb75bd1d68a81f6ddd61687f51c5a1"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1">armnn::TensorShape::AreAllDimensionsSpecified</a></div><div class="ttdeci">bool AreAllDimensionsSpecified() const</div><div class="ttdoc">Checks if there is at least one dimension not specified. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00241">Tensor.cpp:241</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="classarmnn_1_1_tensor_shape_xhtml_a5a212540c00931bd2a4b4041beda33ae"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a5a212540c00931bd2a4b4041beda33ae">armnn::TensorShape::GetDimensionality</a></div><div class="ttdeci">Dimensionality GetDimensionality() const</div><div class="ttdoc">Function that returns the tensor type. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00092">Tensor.hpp:92</a></div></div>
<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_aec48a5a5ab6ecf86c8db0f6d0859fe2f"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#aec48a5a5ab6ecf86c8db0f6d0859fe2f">SetQuantizationOffset</a></div><div class="ttdeci">boxEncodingsInfo SetQuantizationOffset(1)</div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::BaseTensor::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00284">Tensor.hpp:284</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_abcbdfb544ece4c31d0b37715ad0f3be0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">armnn::TensorInfo::GetNumBytes</a></div><div class="ttdeci">unsigned int GetNumBytes() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00418">Tensor.cpp:418</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::BaseTensor::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00290">Tensor.hpp:290</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_aa81f67ac64f0c249e26499600c45d996"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996">armnn::BaseTensor::GetMemoryArea</a></div><div class="ttdeci">MemoryType GetMemoryArea() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00292">Tensor.hpp:292</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">armnn::Dimensionality::Specified</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="classarmnn_1_1_tensor_info_xhtml_af672d1c9e2a120a18926cb645981fbb7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">armnn::TensorInfo::HasMultipleQuantizationScales</a></div><div class="ttdeci">bool HasMultipleQuantizationScales() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00197">Tensor.hpp:197</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a3919600d4aa8d5cd801a0e0740f62308"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a3919600d4aa8d5cd801a0e0740f62308">armnn::TensorShape::GetDimensionSpecificity</a></div><div class="ttdeci">bool GetDimensionSpecificity(unsigned int i) const</div><div class="ttdoc">Gets information about if the dimension size has been specified or not. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00211">Tensor.cpp:211</a></div></div>
<div class="ttc" id="_tensor_fwd_8hpp_xhtml"><div class="ttname"><a href="_tensor_fwd_8hpp.xhtml">TensorFwd.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#l00189">Tensor.hpp:189</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml_a6b6561873c02b1bd9b7a7ae8dd4a339c"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#a6b6561873c02b1bd9b7a7ae8dd4a339c">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00319">Tensor.hpp:319</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a07e348fae6036aecdaf41e738d1ae9ff"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">armnn::TensorShape::operator==</a></div><div class="ttdeci">bool operator==(const TensorShape &other) const</div><div class="ttdoc">Equality comparison operator. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00160">Tensor.cpp:160</a></div></div>
<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_a522a440dc1e26bed45fd3f68be8484e9"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#a522a440dc1e26bed45fd3f68be8484e9">SetQuantizationScale</a></div><div class="ttdeci">boxEncodingsInfo SetQuantizationScale(1.0f)</div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a350bcc7d86f7d9333340a0a04be078f6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a350bcc7d86f7d9333340a0a04be078f6">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">TensorShape & GetShape()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00188">Tensor.hpp:188</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a76d053cd9b4373d90682ad646dad334c"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">armnn::TensorShape::TensorShape</a></div><div class="ttdeci">TensorShape()</div><div class="ttdoc">Empty (invalid) constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00025">Tensor.cpp:25</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div>
<div class="ttc" id="_optional_8hpp_xhtml"><div class="ttname"><a href="_optional_8hpp.xhtml">Optional.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00194">Tensor.hpp:194</a></div></div>
<div class="ttc" id="_types_8hpp_xhtml"><div class="ttname"><a href="_types_8hpp.xhtml">Types.hpp</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#l00314">Tensor.hpp:314</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a82c7d5a6e675b1a876daa9983cd125d2"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2">armnn::TensorShape::SetNumDimensions</a></div><div class="ttdeci">void SetNumDimensions(unsigned int numDimensions, bool initDimensionsSpecificity=false)</div><div class="ttdoc">Sets the tensor rank and therefore the Dimensionality is set to Specified if it was not...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00219">Tensor.cpp:219</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a350bcc7d86f7d9333340a0a04be078f6"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a350bcc7d86f7d9333340a0a04be078f6">armnn::BaseTensor::GetShape</a></div><div class="ttdeci">TensorShape & GetShape()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00285">Tensor.hpp:285</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_aba26e5decca8be8786d8a5faf2e06a49"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">armnn::BaseTensor::m_MemoryArea</a></div><div class="ttdeci">MemoryType m_MemoryArea</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00299">Tensor.hpp:299</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_ab2e02564acd2ce6db36de310702a75de"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#ab2e02564acd2ce6db36de310702a75de">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">TensorInfo & GetInfo()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00283">Tensor.hpp:283</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a8aeddebdcf02e1832b22203c08a6b678"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">const TensorInfo & GetInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00282">Tensor.hpp:282</a></div></div>
<div class="ttc" id="classarmnn_1_1_invalid_argument_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00080">Exceptions.hpp:80</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a71975fcec1464d639f1a78f73164d1bd"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd">armnn::TensorInfo::SetDataType</a></div><div class="ttdeci">void SetDataType(DataType type)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00195">Tensor.hpp:195</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml_aa04de06d072895b6df9125338d55c205"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#aa04de06d072895b6df9125338d55c205">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor(const TensorInfo &info, const ContainerType< T, ContainerArgs... > &container)</div><div class="ttdoc">Constructor from a backing container. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00330">Tensor.hpp:330</a></div></div>
<div class="ttc" id="structarmnn_1_1_empty_optional_xhtml"><div class="ttname"><a href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a></div><div class="ttdoc">EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00032">Optional.hpp:32</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a280670a263dc4fd40491f6d0a2737f44"><div class="ttname"><a href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">armnn::BindingPointInfo</a></div><div class="ttdeci">std::pair< armnn::LayerBindingId, armnn::TensorInfo > BindingPointInfo</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00261">Tensor.hpp:261</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml_a42aec46c635aa2e38932ca103d2064ed"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#a42aec46c635aa2e38932ca103d2064ed">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor(const Tensor &other)</div><div class="ttdoc">Can be implicitly constructed from non-const Tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00322">Tensor.hpp:322</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::BaseTensor::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00288">Tensor.hpp:288</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="_exceptions_8hpp_xhtml"><div class="ttname"><a href="_exceptions_8hpp.xhtml">Exceptions.hpp</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="classarmnn_1_1_tensor_shape_xhtml_ad82b782a8e1a05b6a3756e73c66d5f90"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90">armnn::TensorShape::SetDimensionSize</a></div><div class="ttdeci">void SetDimensionSize(unsigned int i, unsigned int dimensionSize)</div><div class="ttdoc">Sets the size of the indicated dimension and Specificity for that dimension is set to true...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00232">Tensor.cpp:232</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml">armnn::BaseTensor</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00264">Tensor.hpp:264</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_abac025efeffc6e099a365bdb17b5ca3e"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#abac025efeffc6e099a365bdb17b5ca3e">armnn::BaseTensor::~BaseTensor</a></div><div class="ttdeci">~BaseTensor()</div><div class="ttdoc">Protected destructor to stop users from making these (could still new one on the heap and then leak i...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00297">Tensor.hpp:297</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3">armnn::BaseTensor::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00287">Tensor.hpp:287</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#l00191">Tensor.hpp:191</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a34e12ab75d9073354565c2039f92112b"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b">armnn::TensorShape::IsAtLeastOneDimensionSpecified</a></div><div class="ttdeci">bool IsAtLeastOneDimensionSpecified() const</div><div class="ttdoc">Checks if there is at least one dimension specified. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00257">Tensor.cpp:257</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00192">Tensor.hpp:192</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_abcbdfb544ece4c31d0b37715ad0f3be0"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">armnn::BaseTensor::GetNumBytes</a></div><div class="ttdeci">unsigned int GetNumBytes() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00289">Tensor.hpp:289</a></div></div>
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