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<div class="title">Tensor.cpp</div> </div>
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<a href="_tensor_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_tensor_8hpp.xhtml">armnn/Tensor.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_utils_8hpp.xhtml">armnn/Utils.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_exceptions_8hpp.xhtml">armnn/Exceptions.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_types_utils_8hpp.xhtml">armnn/TypesUtils.hpp</a>"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <boost/assert.hpp></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <boost/numeric/conversion/cast.hpp></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <sstream></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="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> {</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment">// ---</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment">// --- TensorShape</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment">// ---</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c"> 23</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>()</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  : m_NumDimensions(0)</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> {</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> }</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="classarmnn_1_1_tensor_shape.xhtml#a767390dbf62191471253b7541143bb04"> 28</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions)</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  : m_NumDimensions(numDimensions)</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> {</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keywordflow">if</span> (numDimensions < 1)</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  {</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Tensor numDimensions must be greater than 0"</span>);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  }</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keywordflow">if</span> (numDimensions > <a class="code" href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">MaxNumOfTensorDimensions</a>)</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Tensor numDimensions must be less than or equal to MaxNumOfTensorDimensions"</span>);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  }</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  std::fill(m_Dimensions.begin(), m_Dimensions.begin() + m_NumDimensions, 0);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> }</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a1c3de06b2e467f9663079dbb619e4732"> 44</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(<span class="keyword">const</span> <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>* <span class="keyword">const</span> dimensionSizes)</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  : m_NumDimensions(numDimensions)</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">if</span> (numDimensions < 1)</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Tensor numDimensions must be greater than 0"</span>);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  }</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">if</span> (numDimensions > <a class="code" href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">MaxNumOfTensorDimensions</a>)</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  {</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Tensor numDimensions must be less than or equal to MaxNumOfTensorDimensions"</span>);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keywordflow">if</span> (dimensionSizes == <span class="keyword">nullptr</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"> 59</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Tensor dimensionSizes must not be NULL"</span>);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  }</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  std::copy(dimensionSizes, dimensionSizes + numDimensions, m_Dimensions.begin());</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#ab18f5c64d49bbc1f7a97d031c5e79e3d"> 65</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(std::initializer_list<unsigned int> dimensionSizeList)</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(<a class="code" href="namespaceboost.xhtml">boost</a>::<a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">numeric_cast</a><unsigned int>(dimensionSizeList.size()), dimensionSizeList.begin())</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> }</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#abe2c91b98905750c515790c88f329670"> 70</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::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="l00071"></a><span class="lineno"> 71</span>  : m_NumDimensions(other.m_NumDimensions)</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  std::copy(other.m_Dimensions.cbegin(), other.m_Dimensions.cbegin() + other.m_NumDimensions, m_Dimensions.begin());</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> }</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31"> 76</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">TensorShape::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="l00077"></a><span class="lineno"> 77</span> {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  m_NumDimensions = other.m_NumDimensions;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  std::copy(other.m_Dimensions.cbegin(), other.m_Dimensions.cbegin() + other.m_NumDimensions, m_Dimensions.begin());</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</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> </div><div class="line"><a name="l00083"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52"> 83</a></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">TensorShape::operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="keyword"></span>{</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  CheckDimensionIndex(i);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordflow">return</span> m_Dimensions.at(i);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> }</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a0bd5fcf80a3838d0922354989762d7c8"> 89</a></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">TensorShape::operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> {</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  CheckDimensionIndex(i);</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keywordflow">return</span> m_Dimensions.at(i);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> }</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div><div class="line"><a name="l00095"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff"> 95</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">TensorShape::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="l00096"></a><span class="lineno"> 96</span> <span class="keyword"></span>{</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordflow">return</span> ((m_NumDimensions == other.m_NumDimensions) &&</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  std::equal(m_Dimensions.cbegin(), m_Dimensions.cbegin() + m_NumDimensions, other.m_Dimensions.cbegin()));</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> }</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349"> 101</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">TensorShape::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="l00102"></a><span class="lineno"> 102</span> <span class="keyword"></span>{</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordflow">return</span> !(*<span class="keyword">this</span> == other);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> }</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7"> 106</a></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">TensorShape::GetNumElements</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="keyword"></span>{</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">if</span> (m_NumDimensions == 0)</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="keywordflow">return</span> 0;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> count = 1;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < m_NumDimensions; i++)</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>  count *= m_Dimensions[i];</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  }</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keywordflow">return</span> count;</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> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="keywordtype">void</span> TensorShape::CheckDimensionIndex(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="keyword"></span>{</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keywordflow">if</span> (i >= m_NumDimensions)</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  {</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  std::stringstream errorMessage;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  errorMessage << <span class="stringliteral">"Invalid dimension index: "</span> << i << <span class="stringliteral">" (number of dimensions is "</span> << m_NumDimensions << <span class="stringliteral">")"</span>;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(errorMessage.str(), <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  }</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">// ---</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="comment">// --- TensorInfo</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> </div><div class="line"><a name="l00136"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c"> 136</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>()</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> : m_DataType(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>::<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">Float32</a>)</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> {</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> }</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ae0f1e7addec3daacb5e656e3031e84b2"> 141</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::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="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keywordtype">float</span> quantizationScale,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  int32_t quantizationOffset)</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  : m_Shape(shape)</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  , m_DataType(dataType)</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> {</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(quantizationScale);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(quantizationOffset);</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#ac478f429b6f31e62bc72bdfc9c9ad242"> 152</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordtype">float</span> quantizationScale,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  int32_t quantizationOffset)</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  : m_Shape(numDimensions, dimensionSizes)</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  , m_DataType(dataType)</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> {</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(quantizationScale);</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(quantizationOffset);</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> </div><div class="line"><a name="l00164"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ac58c3467c7a7998120249cd0b940d221"> 164</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::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="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="keyword">const</span> std::vector<float>& quantizationScales,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim)</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  : m_Shape(shape)</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  , m_DataType(dataType)</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> {</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">SetQuantizationScales</a>(quantizationScales);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">SetQuantizationDim</a>(MakeOptional<unsigned int>(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> </div><div class="line"><a name="l00175"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a1e546b0233ac93ef3ef0e9ee96117c76"> 175</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim)</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  : m_Shape(numDimensions, dimensionSizes)</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  , m_DataType(dataType)</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> {</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">SetQuantizationScales</a>(quantizationScales);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">SetQuantizationDim</a>(MakeOptional<unsigned int>(quantizationDim));</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> }</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div><div class="line"><a name="l00187"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#aef0989e23ab5fc862df9981d3b371f63"> 187</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::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="l00188"></a><span class="lineno"> 188</span> : m_Shape(other.m_Shape)</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> , m_DataType(other.m_DataType)</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> , m_Quantization(other.m_Quantization)</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> {}</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div><div class="line"><a name="l00193"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ac45c8c0052476cd66ef732de76dd9bc8"> 193</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#ac45c8c0052476cd66ef732de76dd9bc8">TensorInfo::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="l00194"></a><span class="lineno"> 194</span> {</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  m_Shape = other.m_Shape;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  m_DataType = other.m_DataType;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  m_Quantization = other.m_Quantization;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keywordflow">return</span> *<span class="keyword">this</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> </div><div class="line"><a name="l00201"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a586e1eec08e847abfeb3de3a4038c5ce"> 201</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a586e1eec08e847abfeb3de3a4038c5ce">TensorInfo::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="l00202"></a><span class="lineno"> 202</span> <span class="keyword"></span>{</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordflow">return</span> ((m_Shape == other.m_Shape) &&</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  (m_DataType == other.m_DataType) &&</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  (m_Quantization == other.m_Quantization));</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> </div><div class="line"><a name="l00208"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a2a944e616dc6fdde5287b17f2265307d"> 208</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a2a944e616dc6fdde5287b17f2265307d">TensorInfo::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="l00209"></a><span class="lineno"> 209</span> <span class="keyword"></span>{</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">return</span> !(*<span class="keyword">this</span> == other);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> }</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0"> 213</a></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">TensorInfo::GetNumBytes</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> <span class="keyword"></span>{</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aa02b9e06fb20fa3c13da0427e6ee5ab2">GetDataTypeSize</a>(m_DataType) * <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>();</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> </div><div class="line"><a name="l00218"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a22f377fc4e10dc1773a3f979061e85f1"> 218</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a22f377fc4e10dc1773a3f979061e85f1">TensorInfo::IsTypeSpaceMatch</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="l00219"></a><span class="lineno"> 219</span> <span class="keyword"></span>{</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keywordtype">bool</span> match = <span class="keyword">true</span>;</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>  match &= m_DataType == other.m_DataType;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> </div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd">IsQuantized</a>() && !<a class="code" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">HasMultipleQuantizationScales</a>())</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  {</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  match &= <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>() == other.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>() &&</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>() == other.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>();</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  }</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keywordflow">return</span> match;</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> }</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div><div class="line"><a name="l00232"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48"> 232</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48">TensorInfo::HasPerAxisQuantization</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> <span class="keyword"></span>{</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">HasMultipleQuantizationScales</a>() || m_Quantization.m_QuantizationDim.has_value();</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</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"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270"> 237</a></span> std::vector<float> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270">TensorInfo::GetQuantizationScales</a>()<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_Quantization.m_Scales;</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> </div><div class="line"><a name="l00242"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332"> 242</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">TensorInfo::SetQuantizationScales</a>(<span class="keyword">const</span> std::vector<float>& scales)</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>  m_Quantization.m_Scales = scales;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> }</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> </div><div class="line"><a name="l00247"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0"> 247</a></span> <span class="keywordtype">float</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">TensorInfo::GetQuantizationScale</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="keyword"></span>{</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordflow">if</span> (m_Quantization.m_Scales.empty())</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="comment">// NOTE: old default for backward compatibility</span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">return</span> 1.0f;</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> </div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  BOOST_ASSERT(!<a class="code" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">HasMultipleQuantizationScales</a>());</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <span class="keywordflow">return</span> m_Quantization.m_Scales[0];</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> </div><div class="line"><a name="l00259"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6"> 259</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">TensorInfo::SetQuantizationScale</a>(<span class="keywordtype">float</span> scale)</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> {</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  m_Quantization.m_Scales = { scale };</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> </div><div class="line"><a name="l00264"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5"> 264</a></span> int32_t <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">TensorInfo::GetQuantizationOffset</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> <span class="keyword"></span>{</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keywordflow">if</span> (!m_Quantization.m_Offset.has_value())</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="comment">// NOTE: old default for backward compatibility</span></div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  }</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keywordflow">return</span> m_Quantization.m_Offset.value();</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> }</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> </div><div class="line"><a name="l00275"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c"> 275</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">TensorInfo::SetQuantizationOffset</a>(int32_t offset)</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>  m_Quantization.m_Offset = MakeOptional<int32_t>(offset);</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> }</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> </div><div class="line"><a name="l00280"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8b8fc85ce966c035d789cf22db5088a1"> 280</a></span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b8fc85ce966c035d789cf22db5088a1">TensorInfo::GetQuantizationDim</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="keyword"></span>{</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="keywordflow">return</span> m_Quantization.m_QuantizationDim;</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> </div><div class="line"><a name="l00285"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e"> 285</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">TensorInfo::SetQuantizationDim</a>(<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="l00286"></a><span class="lineno"> 286</span> {</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  m_Quantization.m_QuantizationDim = quantizationDim;</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> }</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> </div><div class="line"><a name="l00290"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd"> 290</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd">TensorInfo::IsQuantized</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> <span class="keyword"></span>{</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ad44c007f21af2d0375e3ef9400a1b275">IsQuantizedType</a>(m_DataType);</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> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> <span class="comment">// ---</span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> <span class="comment">// --- BaseTensor</span></div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> <span class="comment">// ---</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="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed"> 300</a></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">BaseTensor<MemoryType>::BaseTensor</a>()</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  : m_MemoryArea(nullptr)</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> {</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> </div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00306"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aa84008eafa57252bcb4cc4b2d779a6f4"> 306</a></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType>::BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& info, MemoryType memoryArea)</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  : m_MemoryArea(memoryArea)</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  , m_Info(info)</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> }</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="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType>::BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType></a>& other)</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  : m_MemoryArea(other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>)</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  , m_Info(other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>())</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> }</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> </div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00320"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a844fc6ba8f5435b5a200072a3ec163af"> 320</a></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType></a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType>::operator =</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType></a>& other)</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> {</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  m_Info = other.m_Info;</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  m_MemoryArea = other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>;</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> }</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> </div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> <span class="comment">// Explicit instantiations.</span></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> <span class="keyword">template</span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<const void*></a>;</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> <span class="keyword">template</span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<void*></a>;</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span> </div><div class="line"><a name="l00331"></a><span class="lineno"> 331</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="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00106">Tensor.cpp:106</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="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00101">Tensor.cpp:101</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="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00083">Tensor.cpp:83</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a22f377fc4e10dc1773a3f979061e85f1"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a22f377fc4e10dc1773a3f979061e85f1">armnn::TensorInfo::IsTypeSpaceMatch</a></div><div class="ttdeci">bool IsTypeSpaceMatch(const TensorInfo &other) const</div><div class="ttdoc">Check that the types are the same and, if quantize, that the quantization parameters are the same...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00218">Tensor.cpp:218</a></div></div>
<div class="ttc" id="_tensor_8hpp_xhtml"><div class="ttname"><a href="_tensor_8hpp.xhtml">Tensor.hpp</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="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00076">Tensor.cpp:76</a></div></div>
<div class="ttc" id="_utils_8hpp_xhtml"><div class="ttname"><a href="_utils_8hpp.xhtml">Utils.hpp</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="namespacearmnn_xhtml_ad44c007f21af2d0375e3ef9400a1b275"><div class="ttname"><a href="namespacearmnn.xhtml#ad44c007f21af2d0375e3ef9400a1b275">armnn::IsQuantizedType</a></div><div class="ttdeci">constexpr bool IsQuantizedType()</div><div class="ttdef"><b>Definition:</b> <a href="_types_utils_8hpp_source.xhtml#l00236">TypesUtils.hpp:236</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#l00053">Tensor.hpp:53</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#l00232">Tensor.cpp:232</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b8fc85ce966c035d789cf22db5088a1"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b8fc85ce966c035d789cf22db5088a1">armnn::TensorInfo::GetQuantizationDim</a></div><div class="ttdeci">Optional< unsigned int > GetQuantizationDim() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00280">Tensor.cpp:280</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#l00213">Tensor.cpp:213</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
<div class="ttc" id="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_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#l00237">Tensor.cpp:237</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#l00098">Tensor.hpp:98</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="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00095">Tensor.cpp:95</a></div></div>
<div class="ttc" id="_types_utils_8hpp_xhtml"><div class="ttname"><a href="_types_utils_8hpp.xhtml">TypesUtils.hpp</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#l00023">Tensor.cpp:23</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a21c2ae9fa438faf42669dadda628080c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">armnn::TensorInfo::TensorInfo</a></div><div class="ttdeci">TensorInfo()</div><div class="ttdoc">Empty (invalid) constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00136">Tensor.cpp:136</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">armnn::TensorInfo::GetQuantizationOffset</a></div><div class="ttdeci">int32_t GetQuantizationOffset() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00264">Tensor.cpp:264</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#l00247">Tensor.cpp:247</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#l00259">Tensor.cpp:259</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a37fa39012e90d568df7f774cd6d1e956"><div class="ttname"><a href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">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#l00033">NumericCast.hpp:33</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#l00184">Tensor.hpp:184</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#l00167">Tensor.hpp:167</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="_exceptions_8hpp_xhtml_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00192">Exceptions.hpp:192</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_ac45c8c0052476cd66ef732de76dd9bc8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#ac45c8c0052476cd66ef732de76dd9bc8">armnn::TensorInfo::operator=</a></div><div class="ttdeci">TensorInfo & operator=(const TensorInfo &other)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00193">Tensor.cpp:193</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#l00285">Tensor.cpp:285</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a586e1eec08e847abfeb3de3a4038c5ce"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a586e1eec08e847abfeb3de3a4038c5ce">armnn::TensorInfo::operator==</a></div><div class="ttdeci">bool operator==(const TensorInfo &other) const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00201">Tensor.cpp:201</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a2a944e616dc6fdde5287b17f2265307d"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a2a944e616dc6fdde5287b17f2265307d">armnn::TensorInfo::operator!=</a></div><div class="ttdeci">bool operator!=(const TensorInfo &other) const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00208">Tensor.cpp:208</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_aca0044508ebeb3b236a777db828910ed"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">armnn::BaseTensor::BaseTensor</a></div><div class="ttdeci">BaseTensor()</div><div class="ttdoc">Empty (invalid) constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00300">Tensor.cpp:300</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_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#l00149">Tensor.hpp:149</a></div></div>
<div class="ttc" id="namespaceboost_xhtml"><div class="ttname"><a href="namespaceboost.xhtml">boost</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00275">Tensor.cpp:275</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#l00242">Tensor.cpp:242</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a7c00efeb540198b33b8558c76e5cc2dd"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd">armnn::TensorInfo::IsQuantized</a></div><div class="ttdeci">bool IsQuantized() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00290">Tensor.cpp:290</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_abdcd184ed3bd648bb31d385040cafd5d"><div class="ttname"><a href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">armnn::MaxNumOfTensorDimensions</a></div><div class="ttdeci">constexpr unsigned int MaxNumOfTensorDimensions</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00018">Types.hpp:18</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#l00093">Tensor.hpp:93</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aa02b9e06fb20fa3c13da0427e6ee5ab2"><div class="ttname"><a href="namespacearmnn.xhtml#aa02b9e06fb20fa3c13da0427e6ee5ab2">armnn::GetDataTypeSize</a></div><div class="ttdeci">constexpr unsigned int GetDataTypeSize(DataType dataType)</div><div class="ttdef"><b>Definition:</b> <a href="_types_utils_8hpp_source.xhtml#l00115">TypesUtils.hpp:115</a></div></div>
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