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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>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_tensor_8hpp.xhtml">armnn/Tensor.hpp</a>&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_utils_8hpp.xhtml">armnn/Utils.hpp</a>&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_exceptions_8hpp.xhtml">armnn/Exceptions.hpp</a>&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_types_utils_8hpp.xhtml">armnn/TypesUtils.hpp</a>&quot;</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;</div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_assert_8hpp.xhtml">armnn/utility/Assert.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_numeric_cast_8hpp.xhtml">armnn/utility/NumericCast.hpp</a>&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;</div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &lt;iostream&gt;</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="preprocessor">#include &lt;sstream&gt;</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;{</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment">// ---</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment">// --- TensorShape</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment">// ---</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;</div><div class="line"><a name="l00025"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">   25</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>()</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160; : m_NumDimensions(0), m_Dimensionality(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a>::<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Specified</a>)</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;{</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;}</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a18cd85c032ed1d07bf07867e50ed143f">   30</a></span>&#160;<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, <span class="keywordtype">bool</span> initDimensionsSpecificity)</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160; : m_NumDimensions(numDimensions), m_Dimensionality(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a>::<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Specified</a>)</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;{</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;    CheckValidNumDimensions(numDimensions);</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    std::fill(m_Dimensions.begin(), m_Dimensions.begin() + m_NumDimensions, 0);</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    std::fill(m_DimensionsSpecificity.begin(), m_DimensionsSpecificity.begin() + m_NumDimensions,</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;              initDimensionsSpecificity);</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;}</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a1c3de06b2e467f9663079dbb619e4732">   40</a></span>&#160;<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="l00041"></a><span class="lineno">   41</span>&#160; : m_NumDimensions(numDimensions), m_Dimensionality(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a>::<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Specified</a>)</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;{</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    CheckValidNumDimensions(numDimensions);</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    <span class="keywordflow">if</span> (dimensionSizes == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    {</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;        <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">&quot;Tensor dimensionSizes must not be NULL&quot;</span>);</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;    }</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    std::copy(dimensionSizes, dimensionSizes + numDimensions, m_Dimensions.begin());</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    std::fill(m_DimensionsSpecificity.begin(), m_DimensionsSpecificity.begin() + m_NumDimensions, <span class="keyword">true</span>);</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;}</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;</div><div class="line"><a name="l00054"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#ab18f5c64d49bbc1f7a97d031c5e79e3d">   54</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(std::initializer_list&lt;unsigned int&gt; dimensionSizeList)</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160; : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(<a class="code" href="namespacearmnn.xhtml">armnn</a>::<a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">numeric_cast</a>&lt;unsigned int&gt;(dimensionSizeList.size()), dimensionSizeList.begin())</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;{</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;}</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#aa3f87e5fa5e657a8d1b792b7c43cffe3">   59</a></span>&#160;<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="l00060"></a><span class="lineno">   60</span>&#160;                         <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="l00061"></a><span class="lineno">   61</span>&#160;                         <span class="keyword">const</span> <span class="keywordtype">bool</span>* <span class="keyword">const</span> dimensionsSpecificity)</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;                       : m_NumDimensions(numDimensions), m_Dimensionality(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a>::<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Specified</a>)</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;{</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    CheckValidNumDimensions(numDimensions);</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="keywordflow">if</span> (dimensionSizes == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    {</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;        <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">&quot;Tensor dimensionSizes must not be NULL&quot;</span>);</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    }</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    <span class="keywordflow">if</span> (dimensionsSpecificity == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    {</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">&quot;Tensor dimensionsSpecificity must not be NULL&quot;</span>);</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;    }</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    std::copy(dimensionSizes, dimensionSizes + numDimensions, m_Dimensions.begin());</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    std::copy(dimensionsSpecificity, dimensionsSpecificity + numDimensions, m_DimensionsSpecificity.begin());</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;}</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;</div><div class="line"><a name="l00080"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a6624ad2ddc20bd7e3be162e0abea38fe">   80</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(std::initializer_list&lt;unsigned int&gt; dimensionSizeList,</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;                         std::initializer_list&lt;bool&gt; dimensionsSpecificityList)</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;{</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    <span class="keyword">auto</span> numDimensions = <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(dimensionSizeList.size());</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    <span class="keywordflow">if</span> (dimensionsSpecificityList.size() != numDimensions)</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    {</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;        <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">&quot;Tensors dimensionSizeList and dimensionsSpecificityList must be same size&quot;</span>);</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    }</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    *<span class="keyword">this</span> = <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(numDimensions, dimensionSizeList.begin(), dimensionsSpecificityList.begin());</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;}</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a81652660972380dfe493bf8572e68e39">   92</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> dimensionality)</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;: m_Dimensionality(dimensionality)</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;{</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    <span class="keywordflow">switch</span> (dimensionality)</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    {</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Dimensionality::Specified</a>:</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;            <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">&quot;Use other constructor to specify the rest of the values, this one is only &quot;</span></div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;                                           <span class="stringliteral">&quot;for tensors that have an unknown number of dimensions or that are scalar&quot;</span>);</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">Dimensionality::NotSpecified</a>:</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;            m_NumDimensions = 0;</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;            m_Dimensions = {0};</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;            m_DimensionsSpecificity = {<span class="keyword">false</span>};</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">Dimensionality::Scalar</a>:</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;            m_NumDimensions = 1;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;            m_Dimensions = {1};</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;            m_DimensionsSpecificity = {<span class="keyword">true</span>};</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;        <span class="keywordflow">default</span>:</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;            <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">&quot;Invalid Dimensionality value&quot;</span>);</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    }</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;}</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;</div><div class="line"><a name="l00116"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#abe2c91b98905750c515790c88f329670">  116</a></span>&#160;<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>&amp; other)</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160; : m_NumDimensions(other.m_NumDimensions), m_Dimensionality(other.m_Dimensionality)</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;{</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    std::copy(other.m_Dimensions.cbegin(), other.m_Dimensions.cbegin() + other.m_NumDimensions, m_Dimensions.begin());</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    std::copy(other.m_DimensionsSpecificity.cbegin(), other.m_DimensionsSpecificity.cbegin() + other.m_NumDimensions,</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;              m_DimensionsSpecificity.begin());</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;}</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;</div><div class="line"><a name="l00124"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">  124</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>&amp; <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>&amp; other)</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;{</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    m_NumDimensions = other.m_NumDimensions;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    m_Dimensionality = other.m_Dimensionality;</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    std::copy(other.m_Dimensions.cbegin(), other.m_Dimensions.cbegin() + other.m_NumDimensions, m_Dimensions.begin());</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    std::copy(other.m_DimensionsSpecificity.cbegin(), other.m_DimensionsSpecificity.cbegin() + other.m_NumDimensions,</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;              m_DimensionsSpecificity.begin());</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;}</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;<span class="comment">// read</span></div><div class="line"><a name="l00135"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">  135</a></span>&#160;<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="l00136"></a><span class="lineno">  136</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    CheckUnspecifiedNumDimensions();</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    CheckDimensionIndex(i);</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    CheckDimensionSpecified(i);</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    <span class="keywordflow">return</span> m_Dimensions.at(i);</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;}</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;<span class="comment">// read and write</span></div><div class="line"><a name="l00145"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a0bd5fcf80a3838d0922354989762d7c8">  145</a></span>&#160;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&amp; <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="l00146"></a><span class="lineno">  146</span>&#160;{</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">Dimensionality::Scalar</a> == m_Dimensionality)</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    {</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;        std::stringstream errorMessage;</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;        errorMessage &lt;&lt; <span class="stringliteral">&quot;TensorShape with Dimensionality::Scalar must be const to use operator[]&quot;</span>;</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;        <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="l00152"></a><span class="lineno">  152</span>&#160;    }</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    CheckUnspecifiedNumDimensions();</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    CheckDimensionIndex(i);</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    CheckDimensionSpecified(i);</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <span class="keywordflow">return</span> m_Dimensions.at(i);</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;}</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">  160</a></span>&#160;<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>&amp; other)<span class="keyword"> const</span></div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <span class="keywordflow">return</span> ((m_NumDimensions == other.m_NumDimensions) &amp;&amp;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;            (m_Dimensionality == other.m_Dimensionality) &amp;&amp;</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;             std::equal(m_Dimensions.cbegin(), m_Dimensions.cbegin() + m_NumDimensions, other.m_Dimensions.cbegin()) &amp;&amp;</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;             std::equal(m_DimensionsSpecificity.cbegin(), m_DimensionsSpecificity.cbegin() + m_NumDimensions,</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;                        other.m_DimensionsSpecificity.cbegin()));</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;}</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;</div><div class="line"><a name="l00169"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">  169</a></span>&#160;<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>&amp; other)<span class="keyword"> const</span></div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;    <span class="keywordflow">return</span> !(*<span class="keyword">this</span> == other);</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;}</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;</div><div class="line"><a name="l00174"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">  174</a></span>&#160;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">TensorShape::GetNumDimensions</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    CheckUnspecifiedNumDimensions();</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    <span class="keywordflow">return</span> m_NumDimensions;</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;}</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;</div><div class="line"><a name="l00181"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">  181</a></span>&#160;<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="l00182"></a><span class="lineno">  182</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    CheckUnspecifiedNumDimensions();</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    <span class="keywordflow">if</span> (m_NumDimensions == 0)</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    {</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;        <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;    }</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> count = 1;</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;    <span class="keywordtype">bool</span> atLeastOneDimensionSpecified = <span class="keyword">false</span>;</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; m_NumDimensions; ++i)</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;    {</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;        <span class="keywordflow">if</span> (m_DimensionsSpecificity[i])</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;        {</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;            atLeastOneDimensionSpecified = <span class="keyword">true</span>;</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;            count *= m_Dimensions[i];</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;        }</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    }</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    <span class="keywordflow">if</span> (atLeastOneDimensionSpecified)</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;    {</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;        <span class="keywordflow">return</span> count;</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;    } </div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    <span class="keywordflow">else</span> </div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    {</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;        <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    }</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;}</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;</div><div class="line"><a name="l00211"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a3919600d4aa8d5cd801a0e0740f62308">  211</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a3919600d4aa8d5cd801a0e0740f62308">TensorShape:: GetDimensionSpecificity</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;    CheckUnspecifiedNumDimensions();</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;    CheckDimensionIndex(i);</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;    <span class="keywordflow">return</span> m_DimensionsSpecificity[i];</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;}</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;</div><div class="line"><a name="l00219"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2">  219</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2">TensorShape::SetNumDimensions</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keywordtype">bool</span> initDimensionsSpecificity)</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;{</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;    CheckScalar();</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    CheckSpecifiedNumDimensions();</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;    CheckValidNumDimensions(numDimensions);</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;    m_NumDimensions = numDimensions;</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    m_Dimensionality = <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Dimensionality::Specified</a>;</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;    std::fill(m_Dimensions.begin(), m_Dimensions.begin() + m_NumDimensions, 0);</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;    std::fill(m_DimensionsSpecificity.begin(), m_DimensionsSpecificity.begin() + m_NumDimensions,</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;              initDimensionsSpecificity);</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;}</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;</div><div class="line"><a name="l00232"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90">  232</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90">TensorShape::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="l00233"></a><span class="lineno">  233</span>&#160;{</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;    CheckScalar();</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    CheckDimensionIndex(i);</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;    m_Dimensions[i] = dimensionSize;</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    m_DimensionsSpecificity[i] = <span class="keyword">true</span>;</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;}</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;</div><div class="line"><a name="l00241"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1">  241</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1">TensorShape::AreAllDimensionsSpecified</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    CheckUnspecifiedNumDimensions();</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;    <span class="keywordtype">bool</span> areAllDimensionsSpecified = <span class="keyword">true</span>;</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; m_NumDimensions; ++i)</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    {</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;        <span class="keywordflow">if</span> (!m_DimensionsSpecificity[i])</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;        {</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;            areAllDimensionsSpecified = <span class="keyword">false</span>;</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;        }</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    }</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    <span class="keywordflow">return</span> areAllDimensionsSpecified;</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;}</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;</div><div class="line"><a name="l00257"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b">  257</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b">TensorShape::IsAtLeastOneDimensionSpecified</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;    CheckUnspecifiedNumDimensions();</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    <span class="keywordtype">bool</span> isAtLeastOneDimensionSpecified = <span class="keyword">false</span>;</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; m_NumDimensions; ++i)</div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;    {</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;        <span class="keywordflow">if</span> (m_DimensionsSpecificity[i])</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;        {</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;            isAtLeastOneDimensionSpecified = <span class="keyword">true</span>;</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;        }</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;    }</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    <span class="keywordflow">return</span> isAtLeastOneDimensionSpecified;</div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;}</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;<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="l00274"></a><span class="lineno">  274</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;    <span class="keywordflow">if</span> (i &gt;= m_NumDimensions)</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;    {</div><div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;        std::stringstream errorMessage;</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;        errorMessage &lt;&lt; <span class="stringliteral">&quot;Invalid dimension index: &quot;</span> &lt;&lt; i &lt;&lt; <span class="stringliteral">&quot; (number of dimensions is &quot;</span> &lt;&lt; m_NumDimensions &lt;&lt; <span class="stringliteral">&quot;)&quot;</span>;</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;        <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="l00280"></a><span class="lineno">  280</span>&#160;    }</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;}</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;<span class="keywordtype">void</span> TensorShape::CheckValidNumDimensions(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions)</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;{</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;    <span class="keywordflow">if</span> (numDimensions &lt; 1)</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;    {</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;        <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">&quot;Tensor numDimensions must be greater than 0&quot;</span>, <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;    }</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;    <span class="keywordflow">if</span> (numDimensions &gt; <a class="code" href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">MaxNumOfTensorDimensions</a>)</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;    {</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;        <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">&quot;Tensor numDimensions must be less than or equal to MaxNumOfTensorDimensions&quot;</span></div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;                , <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div><div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;    }</div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;}</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;<span class="keywordtype">void</span> TensorShape::CheckDimensionSpecified(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div><div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;    <span class="keywordflow">if</span> (!m_DimensionsSpecificity[i])</div><div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;    {</div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;        std::stringstream errorMessage;</div><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;        errorMessage &lt;&lt; <span class="stringliteral">&quot;Dimension index: &quot;</span> &lt;&lt; i &lt;&lt; <span class="stringliteral">&quot; not specified. Tensor shape not inferred yet.&quot;</span>;</div><div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;        <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="l00304"></a><span class="lineno">  304</span>&#160;    }</div><div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;}</div><div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;</div><div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;<span class="keywordtype">void</span> TensorShape::CheckScalar()<span class="keyword"> const</span></div><div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">Dimensionality::Scalar</a> == m_Dimensionality)</div><div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;    {</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;        std::stringstream errorMessage;</div><div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;        errorMessage &lt;&lt; <span class="stringliteral">&quot;Invalid action on a tensor shape that holds a scalar value.&quot;</span>;</div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;        <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="l00314"></a><span class="lineno">  314</span>&#160;    }</div><div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;}</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;<span class="keywordtype">void</span> TensorShape::CheckUnspecifiedNumDimensions()<span class="keyword"> const</span></div><div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">Dimensionality::NotSpecified</a> == m_Dimensionality)</div><div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;    {</div><div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;        std::stringstream errorMessage;</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;        errorMessage &lt;&lt; <span class="stringliteral">&quot;Invalid action on a tensor shape that has unknown number of dimensions.&quot;</span>;</div><div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;        <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="l00324"></a><span class="lineno">  324</span>&#160;    }</div><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;}</div><div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;</div><div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;<span class="keywordtype">void</span> TensorShape::CheckSpecifiedNumDimensions()<span class="keyword"> const</span></div><div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Dimensionality::Specified</a> == m_Dimensionality)</div><div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    {</div><div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;        std::stringstream errorMessage;</div><div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;        errorMessage &lt;&lt; <span class="stringliteral">&quot;Invalid action on a tensor shape that has known number of dimensions.&quot;</span>;</div><div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;        <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="l00334"></a><span class="lineno">  334</span>&#160;    }</div><div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;}</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;</div><div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;<span class="comment">// ---</span></div><div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;<span class="comment">// --- TensorInfo</span></div><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;<span class="comment">// ---</span></div><div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;</div><div class="line"><a name="l00341"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">  341</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>()</div><div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;: 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="l00343"></a><span class="lineno">  343</span>&#160;{</div><div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;}</div><div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;</div><div class="line"><a name="l00346"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ae0f1e7addec3daacb5e656e3031e84b2">  346</a></span>&#160;<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>&amp; shape,</div><div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;                       <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;                       <span class="keywordtype">float</span> quantizationScale,</div><div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;                       int32_t quantizationOffset)</div><div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;    : m_Shape(shape)</div><div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;    , m_DataType(dataType)</div><div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;{</div><div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(quantizationScale);</div><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160; 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other)<span class="keyword"> const</span></div><div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;    <span class="keywordflow">return</span> ((m_Shape == other.m_Shape) &amp;&amp;</div><div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;            (m_DataType == other.m_DataType) &amp;&amp;</div><div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;            (m_Quantization == other.m_Quantization));</div><div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;}</div><div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;</div><div class="line"><a name="l00413"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a2a944e616dc6fdde5287b17f2265307d">  413</a></span>&#160;<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>&amp; other)<span class="keyword"> const</span></div><div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;    <span class="keywordflow">return</span> !(*<span class="keyword">this</span> == other);</div><div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;}</div><div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;</div><div class="line"><a name="l00418"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">  418</a></span>&#160;<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="l00419"></a><span class="lineno">  419</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160; 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       <span class="comment">// NOTE: old default for backward compatibility</span></div><div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;        <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;    }</div><div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;</div><div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;    <span class="keywordflow">return</span> m_Quantization.m_Offset.value();</div><div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;}</div><div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;</div><div class="line"><a name="l00480"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">  480</a></span>&#160;<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="l00481"></a><span class="lineno">  481</span>&#160;{</div><div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;    m_Quantization.m_Offset = MakeOptional&lt;int32_t&gt;(offset);</div><div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;}</div><div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;</div><div class="line"><a name="l00485"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8b8fc85ce966c035d789cf22db5088a1">  485</a></span>&#160;<a class="code" href="classarmnn_1_1_optional.xhtml">Optional&lt;unsigned int&gt;</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="l00486"></a><span class="lineno">  486</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;    <span class="keywordflow">return</span> m_Quantization.m_QuantizationDim;</div><div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;}</div><div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;</div><div class="line"><a name="l00490"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">  490</a></span>&#160;<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&lt;unsigned int&gt;</a>&amp; quantizationDim)</div><div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;{</div><div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;    m_Quantization.m_QuantizationDim = quantizationDim;</div><div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;}</div><div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;</div><div class="line"><a name="l00495"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd">  495</a></span>&#160;<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="l00496"></a><span class="lineno">  496</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ad44c007f21af2d0375e3ef9400a1b275">IsQuantizedType</a>(m_DataType);</div><div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;}</div><div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;</div><div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;<span class="comment">// ---</span></div><div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160;<span class="comment">// --- BaseTensor</span></div><div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;<span class="comment">// ---</span></div><div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;</div><div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> MemoryType&gt;</div><div class="line"><a name="l00505"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">  505</a></span>&#160;<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">BaseTensor&lt;MemoryType&gt;::BaseTensor</a>()</div><div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160; : m_MemoryArea(nullptr)</div><div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;{</div><div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;}</div><div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;</div><div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> MemoryType&gt;</div><div class="line"><a name="l00511"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aa84008eafa57252bcb4cc4b2d779a6f4">  511</a></span>&#160;<a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor&lt;MemoryType&gt;::BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; info, MemoryType memoryArea)</div><div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160; : m_MemoryArea(memoryArea)</div><div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160; , m_Info(info)</div><div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;{</div><div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;}</div><div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;</div><div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> MemoryType&gt;</div><div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;<a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor&lt;MemoryType&gt;::BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor&lt;MemoryType&gt;</a>&amp; other)</div><div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160; : m_MemoryArea(other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>)</div><div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160; , m_Info(other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>())</div><div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;{</div><div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;}</div><div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;</div><div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> MemoryType&gt;</div><div class="line"><a name="l00525"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a844fc6ba8f5435b5a200072a3ec163af">  525</a></span>&#160;<a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor&lt;MemoryType&gt;</a>&amp; <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor&lt;MemoryType&gt;::operator =</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor&lt;MemoryType&gt;</a>&amp; other)</div><div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;{</div><div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;    m_Info = other.m_Info;</div><div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;    m_MemoryArea = other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>;</div><div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;}</div><div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;</div><div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;<span class="comment">// Explicit instantiations.</span></div><div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;<span class="keyword">template</span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor&lt;const void*&gt;</a>;</div><div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;<span class="keyword">template</span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor&lt;void*&gt;</a>;</div><div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;</div><div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;} <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 &amp;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="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 &amp;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#l00423">Tensor.cpp:423</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="_tensor_8hpp_xhtml"><div class="ttname"><a href="_tensor_8hpp.xhtml">Tensor.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">armnn::Dimensionality::NotSpecified</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 &amp; operator=(const TensorShape &amp;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="_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&lt; unsigned int &gt;</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="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#l00249">TypesUtils.hpp:249</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_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#l00437">Tensor.cpp:437</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&lt; unsigned int &gt; GetQuantizationDim() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00485">Tensor.cpp:485</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="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_a8bc11f1fa23ef42532f9fdd04d355270"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270">armnn::TensorInfo::GetQuantizationScales</a></div><div class="ttdeci">std::vector&lt; float &gt; GetQuantizationScales() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00442">Tensor.cpp:442</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="_numeric_cast_8hpp_xhtml"><div class="ttname"><a href="_numeric_cast_8hpp.xhtml">NumericCast.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_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 &amp;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="_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#l00025">Tensor.cpp:25</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#l00341">Tensor.cpp:341</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">armnn::TensorInfo::GetQuantizationOffset</a></div><div class="ttdeci">int32_t GetQuantizationOffset() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00469">Tensor.cpp:469</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00452">Tensor.cpp:452</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_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="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#l00464">Tensor.cpp:464</a></div></div>
<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div>
<div class="ttc" id="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_a8aeddebdcf02e1832b22203c08a6b678"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">const TensorInfo &amp; 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="_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#l00197">Exceptions.hpp:197</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 &amp; operator=(const TensorInfo &amp;other)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00398">Tensor.cpp:398</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&lt; unsigned int &gt; &amp;quantizationDim)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00490">Tensor.cpp:490</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">armnn::Dimensionality::Scalar</a></div></div>
<div class="ttc" id="_assert_8hpp_xhtml"><div class="ttname"><a href="_assert_8hpp.xhtml">Assert.hpp</a></div></div>
<div class="ttc" id="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 &amp;other) const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00406">Tensor.cpp:406</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 &amp;other) const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00413">Tensor.cpp:413</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#l00505">Tensor.cpp:505</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="namespacearmnn_xhtml_a375ca3cff9f1b005d1412dc5f3cf5b6e"><div class="ttname"><a href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t&lt; std::is_unsigned&lt; Source &gt;::value &amp;&amp;std::is_unsigned&lt; Dest &gt;::value, Dest &gt; numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00035">NumericCast.hpp:35</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="classarmnn_1_1_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#l00480">Tensor.cpp:480</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&lt; float &gt; &amp;scales)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00447">Tensor.cpp:447</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_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#l00495">Tensor.cpp:495</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#l00192">Tensor.hpp:192</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#l00126">TypesUtils.hpp:126</a></div></div>
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