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author | David Monahan <david.monahan@arm.com> | 2023-03-22 16:48:58 +0000 |
---|---|---|
committer | David Monahan <david.monahan@arm.com> | 2023-03-22 16:48:58 +0000 |
commit | ae050524109f1ce827962665436ef7430f2ac479 (patch) | |
tree | a087fe0c77570971dd7979f2757426c24e91afc7 /23.02/_tensor_8hpp_source.xhtml | |
parent | 8d2ca734165a068478df7cffa46185680b05cd20 (diff) | |
download | armnn-ae050524109f1ce827962665436ef7430f2ac479.tar.gz |
IVGCVSW-7255 Update Doxygen Documentation and publish on GitHub.
* Updating Doxygen documentation for 23.02 release.
Signed-off-by: David Monahan <david.monahan@arm.com>
Change-Id: I545574ff7664b4595d2fe6a91a3c35d2ad55df82
Diffstat (limited to '23.02/_tensor_8hpp_source.xhtml')
-rw-r--r-- | 23.02/_tensor_8hpp_source.xhtml | 548 |
1 files changed, 482 insertions, 66 deletions
diff --git a/23.02/_tensor_8hpp_source.xhtml b/23.02/_tensor_8hpp_source.xhtml index 2351472dbf..dcec50004a 100644 --- a/23.02/_tensor_8hpp_source.xhtml +++ b/23.02/_tensor_8hpp_source.xhtml @@ -8,7 +8,7 @@ <head> <meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> <meta http-equiv="X-UA-Compatible" content="IE=9"/> -<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="generator" content="Doxygen 1.8.17"/> <meta name="robots" content="NOINDEX, NOFOLLOW" /> <meta name="viewport" content="width=device-width, initial-scale=1"/> <title>ArmNN: include/armnn/Tensor.hpp Source File</title> @@ -19,9 +19,6 @@ <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtreedata.js"></script> <script type="text/javascript" src="navtree.js"></script> -<script type="text/javascript"> - $(document).ready(initResizable); -</script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/searchdata.js"></script> <script type="text/javascript" src="search/search.js"></script> @@ -30,7 +27,8 @@ extensions: ["tex2jax.js"], jax: ["input/TeX","output/HTML-CSS"], }); -</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +</script> +<script type="text/javascript" async="async" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> <link href="doxygen.css" rel="stylesheet" type="text/css" /> <link href="stylesheet.css" rel="stylesheet" type="text/css"/> </head> @@ -51,18 +49,21 @@ </table> </div> <!-- end header part --> -<!-- Generated by Doxygen 1.8.13 --> +<!-- Generated by Doxygen 1.8.17 --> <script type="text/javascript"> +/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */ var searchBox = new SearchBox("searchBox", "search",false,'Search'); +/* @license-end */ </script> <script type="text/javascript" src="menudata.js"></script> <script type="text/javascript" src="menu.js"></script> <script type="text/javascript"> +/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */ $(function() { initMenu('',true,false,'search.php','Search'); $(document).ready(function() { init_search(); }); }); -</script> +/* @license-end */</script> <div id="main-nav"></div> </div><!-- top --> <div id="side-nav" class="ui-resizable side-nav-resizable"> @@ -76,7 +77,9 @@ $(function() { </div> </div> <script type="text/javascript"> -$(document).ready(function(){initNavTree('_tensor_8hpp_source.xhtml','');}); +/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */ +$(document).ready(function(){initNavTree('_tensor_8hpp_source.xhtml',''); initResizable(); }); +/* @license-end */ </script> <div id="doc-content"> <!-- window showing the filter options --> @@ -98,71 +101,484 @@ $(document).ready(function(){initNavTree('_tensor_8hpp_source.xhtml','');}); <div class="title">Tensor.hpp</div> </div> </div><!--header--> <div class="contents"> -<a href="_tensor_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017,2022 Arm Ltd and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_exceptions_8hpp.xhtml">Exceptions.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_optional_8hpp.xhtml">Optional.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_8hpp.xhtml">Types.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 <stdint.h></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <array></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <initializer_list></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <utility></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> {</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml"> 20</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> {</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> /// Empty (invalid) constructor.</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>();</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="comment"></span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment"> /// @param initDimensionsSpecificity (optional) - value to initialize the specificity of each dimension size.</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"></span> <span class="keyword">explicit</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keywordtype">bool</span> initDimensionsSpecificity = <span class="keyword">true</span>);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment"></span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> /// @param dimensionSizes - Size of each of dimension.</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"></span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> /// @param dimensionSizeList - Size of each of dimension.</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(std::initializer_list<unsigned int> dimensionSizeList);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"></span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"> /// Copy Constructor for TensorShape</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"> /// @param other - TensorShape to copy from.</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment"></span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> /// @param dimensionSizes - Size of each of dimension.</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"> /// @param dimensionsSpecificity - Flags to indicate which dimension has its size specified.</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes, <span class="keyword">const</span> <span class="keywordtype">bool</span>* dimensionsSpecificity);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment"></span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> /// @param dimensionSizeList - Size of each of dimension.</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> /// @param dimensionsSpecificityList - Flags to indicate which dimension size is specified.</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(std::initializer_list<unsigned int> dimensionSizeList,</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  std::initializer_list<bool> dimensionsSpecificityList);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"></span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"> /// Constructor for TensorShape</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> /// @param dimensionality - Parameter to indicate if the Tensor is a Scalar, a Tensor of known dimensionality</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"> /// or a Tensor of unknown dimensionality.</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="comment"></span> <span class="keyword">explicit</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> dimensionality);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="comment"></span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="comment"> /// Assignation function</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="comment"> /// @param other - TensorShape to copy from.</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"></span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment"> /// Read only operator</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="comment"></span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="comment"> /// Read and write operator</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment"></span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="comment"> /// Equality comparison operator</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="comment"> /// @param other - TensorShape to compare with.</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">operator==</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="comment"></span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="comment"> /// Inequality comparison operator</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="comment"> /// @param other - TensorShape to compare with.</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">operator!=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="comment"></span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="comment"> /// Function that returns the tensor rank.</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="comment"> /// @return - Tensor rank.</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"></span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment"> /// Function that calculates the tensor elements by multiplying all dimension size which are Specified.</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="comment"> /// @return - Total number of elements in the tensor.</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="comment"></span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="comment"> /// Function that returns the tensor type.</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="comment"> /// @return - Parameter to indicate if the Tensor is a scalar, a Tensor of known dimensionality or</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="comment"> /// a Tensor of unknown dimensionality</span></div><div class="line"><a name="l00092"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a5a212540c00931bd2a4b4041beda33ae"> 92</a></span> <span class="comment"></span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a5a212540c00931bd2a4b4041beda33ae">GetDimensionality</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Dimensionality; }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="comment"></span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="comment"> /// Gets information about if the dimension size has been specified or not</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="comment"> /// @return - Flag to indicate if the dimension "i" has a specified size.</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a3919600d4aa8d5cd801a0e0740f62308">GetDimensionSpecificity</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="comment"></span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="comment"> /// Sets the tensor rank and therefore the Dimensionality is set to Specified if it was not.</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="comment"> /// @param initDimensionsSpecificity (optional) - value to initialize the specificity of each dimension size.</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2">SetNumDimensions</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keywordtype">bool</span> initDimensionsSpecificity = <span class="keyword">false</span>);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="comment"></span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="comment"> /// Sets the size of the indicated dimension and Specificity for that dimension is set to true.</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="comment"> /// @param dimensionSize - size of one dimension.</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90">SetDimensionSize</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimensionSize);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="comment"></span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment"> /// Checks if there is at least one dimension not specified. AND of all array elements.</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="comment"> /// @return - True when all dimension sizes are specified. False when at least one dimension size is not specified.</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1">AreAllDimensionsSpecified</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="comment"></span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="comment"> /// Checks if there is at least one dimension specified. OR of all array elements.</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"> /// @return - True at least one dimension sizes is specified. False when all dimension sizes are not specified.</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b">IsAtLeastOneDimensionSpecified</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="keyword">private</span>:<span class="comment"></span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="comment"> /// Array of the dimension sizes.</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="comment"></span> std::array<unsigned int, MaxNumOfTensorDimensions> m_Dimensions{};</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="comment"></span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="comment"> /// Array of flags to indicate if the size of each of the dimensions is specified or not</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="comment"></span> std::array<bool, MaxNumOfTensorDimensions> m_DimensionsSpecificity = { {<span class="keyword">true</span>} };</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="comment"></span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="comment"> /// Tensor rank</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m_NumDimensions{};</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="comment"></span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="comment"> /// Tensor type: Specified, NotSpecified or Scalar.</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="comment"></span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> m_Dimensionality = <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Dimensionality::Specified</a>;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="comment"></span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="comment"> /// Checks if the dimension index given is within range.</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckDimensionIndex(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="comment"></span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="comment"> /// Checks if the tensor rank given is within range.</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="comment"></span> <span class="keyword">static</span> <span class="keywordtype">void</span> CheckValidNumDimensions(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions) ;</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="comment"></span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="comment"> /// Checks if the size of the dimension index given is specified.</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="comment"> /// @param i - Dimension index.</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckDimensionSpecified(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="comment"></span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment"> /// Checks if this is a scalar.</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckScalar() <span class="keyword">const</span>;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment"></span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="comment"> /// Checks if the number of dimensions is unknown, i.e. rank is unspecified.</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckUnspecifiedNumDimensions() <span class="keyword">const</span>;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="comment"></span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="comment"> /// Checks if the number of dimensions is known, i.e. rank is specified.</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckSpecifiedNumDimensions() <span class="keyword">const</span>;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> };</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div><div class="line"><a name="l00152"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml"> 152</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> {</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="comment"> /// Empty (invalid) constructor.</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>();</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& shape,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordtype">float</span> quantizationScale = 0.0f,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  int32_t quantizationOffset = 0,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keywordtype">bool</span> isConstant = <span class="keyword">false</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"> 164</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordtype">float</span> quantizationScale = 0.0f,</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  int32_t quantizationOffset = 0,</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordtype">bool</span> isConstant = <span class="keyword">false</span>);</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">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="l00172"></a><span class="lineno"> 172</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keywordtype">bool</span> isConstant = <span class="keyword">false</span>);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim,</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordtype">bool</span> isConstant = <span class="keyword">false</span>);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> </div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">operator==</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">operator!=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8"> 191</a></span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Shape; }</div><div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a350bcc7d86f7d9333340a0a04be078f6"> 192</a></span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a350bcc7d86f7d9333340a0a04be078f6">GetShape</a>() { <span class="keywordflow">return</span> m_Shape; }</div><div class="line"><a name="l00193"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298"> 193</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& newShape) { m_Shape = newShape; }</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> </div><div class="line"><a name="l00195"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24"> 195</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Shape.GetNumDimensions(); }</div><div class="line"><a name="l00196"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7"> 196</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Shape.GetNumElements(); }</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div><div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3"> 198</a></span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_DataType; }</div><div class="line"><a name="l00199"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd"> 199</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd">SetDataType</a>(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> type) { m_DataType = type; }</div><div class="line"><a name="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#af672d1c9e2a120a18926cb645981fbb7"> 201</a></span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">HasMultipleQuantizationScales</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Quantization.m_Scales.size() > 1; }</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordtype">bool</span> HasPerAxisQuantization() <span class="keyword">const</span>;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  std::vector<float> GetQuantizationScales() <span class="keyword">const</span>;</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordtype">void</span> SetQuantizationScales(<span class="keyword">const</span> std::vector<float>& scales);</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordtype">float</span> GetQuantizationScale() <span class="keyword">const</span>;</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordtype">void</span> SetQuantizationScale(<span class="keywordtype">float</span> scale);</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> </div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  int32_t GetQuantizationOffset() <span class="keyword">const</span>;</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keywordtype">void</span> SetQuantizationOffset(int32_t offset);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> </div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a> GetQuantizationDim() <span class="keyword">const</span>;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="keywordtype">void</span> SetQuantizationDim(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a>& quantizationDim);</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> </div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="keywordtype">bool</span> IsQuantized() <span class="keyword">const</span>;</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordtype">bool</span> IsConstant() <span class="keyword">const</span>;</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> <span class="comment"></span></div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> <span class="comment"> /// Marks the data corresponding to this tensor info as constant.</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> <span class="comment"> ///</span></div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="comment"> /// @details: This can allow further optimization on execution</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="comment"> /// @Note: The user has to ensure that the underlying data actually is constant.</span></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> <span class="comment"></span> <span class="keywordtype">void</span> SetConstant(<span class="keyword">const</span> <span class="keywordtype">bool</span> IsConstant=<span class="keyword">true</span>);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> <span class="comment"></span></div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> <span class="comment"> /// Check that the types are the same and, if quantize, that the quantization parameters are the same.</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> <span class="comment"></span> <span class="keywordtype">bool</span> IsTypeSpaceMatch(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other) <span class="keyword">const</span>;</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> </div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> GetNumBytes() <span class="keyword">const</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"> 232</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> m_Shape;</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> m_DataType;</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordtype">bool</span> m_IsConstant;</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> <span class="comment"></span></div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> <span class="comment"> /// Vectors of scale and offset are used for per-axis quantization.</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="comment"></span> <span class="keyword">struct </span>Quantization</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  {</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  Quantization()</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  : m_Scales{}</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  , m_Offset(<a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>())</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  , m_QuantizationDim(<a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>()) {}</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> </div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  Quantization(<span class="keyword">const</span> Quantization& other)</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  : m_Scales(other.m_Scales)</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  , m_Offset(other.m_Offset)</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  , m_QuantizationDim(other.m_QuantizationDim) {}</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">operator==</a>(<span class="keyword">const</span> Quantization& other)<span class="keyword"> const</span></div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">return</span> ((m_Scales == other.m_Scales) && (m_Offset == other.m_Offset) &&</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  (m_QuantizationDim == other.m_QuantizationDim));</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> </div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  Quantization& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">operator=</a>(<span class="keyword">const</span> Quantization& other)</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  {</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordflow">if</span>(<span class="keyword">this</span> != &other)</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  {</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  m_Scales = other.m_Scales;</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  m_Offset = other.m_Offset;</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  m_QuantizationDim = other.m_QuantizationDim;</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  }</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  }</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> </div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  std::vector<float> m_Scales;</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<int32_t></a> m_Offset;</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a> m_QuantizationDim;</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>  } m_Quantization;</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> };</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div><div class="line"><a name="l00274"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44"> 274</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">BindingPointInfo</a> = std::pair<armnn::LayerBindingId, armnn::TensorInfo>;</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> </div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00277"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml"> 277</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> {</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="comment"> /// Empty (invalid) constructor.</span></div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>();</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> <span class="comment"></span></div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="comment"> /// Constructor from a raw memory pointer.</span></div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> <span class="comment"> /// @param memoryArea - Region of CPU-addressable memory where tensor data will be stored. Must be valid while</span></div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> <span class="comment"> /// workloads are on the fly. Tensor instances do not claim ownership of referenced memory regions, that is,</span></div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> <span class="comment"> /// no attempt will be made by ArmNN to free these memory regions automatically.</span></div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, MemoryType memoryArea);</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> <span class="comment"></span></div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="comment"> /// Tensors are copyable.</span></div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>& other);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> <span class="comment"></span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> <span class="comment"> /// Tensors are copyable.</span></div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>&);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678"> 295</a></span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info; }</div><div class="line"><a name="l00296"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#ab2e02564acd2ce6db36de310702a75de"> 296</a></span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#ab2e02564acd2ce6db36de310702a75de">GetInfo</a>() { <span class="keywordflow">return</span> m_Info; }</div><div class="line"><a name="l00297"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8"> 297</a></span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetShape(); }</div><div class="line"><a name="l00298"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a350bcc7d86f7d9333340a0a04be078f6"> 298</a></span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a350bcc7d86f7d9333340a0a04be078f6">GetShape</a>() { <span class="keywordflow">return</span> m_Info.GetShape(); }</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> </div><div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3"> 300</a></span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetDataType(); }</div><div class="line"><a name="l00301"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24"> 301</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetNumDimensions(); }</div><div class="line"><a name="l00302"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0"> 302</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetNumBytes(); }</div><div class="line"><a name="l00303"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a8846406ac37fbd2204f0be16ee05d5b7"> 303</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.GetNumElements(); }</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div><div class="line"><a name="l00305"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996"> 305</a></span>  MemoryType <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996">GetMemoryArea</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_MemoryArea; }</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> </div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="keyword">protected</span>:<span class="comment"></span></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="comment"> /// Protected destructor to stop users from making these</span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="comment"> /// (could still new one on the heap and then leak it...)</span></div><div class="line"><a name="l00310"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#abac025efeffc6e099a365bdb17b5ca3e"> 310</a></span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#abac025efeffc6e099a365bdb17b5ca3e">~BaseTensor</a>() {}</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> </div><div class="line"><a name="l00312"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49"> 312</a></span>  MemoryType <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>;</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> </div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> m_Info;</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> <span class="comment"></span></div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="comment">/// A tensor defined by a TensorInfo (shape and data type) and a mutable backing store.</span></div><div class="line"><a name="l00319"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor.xhtml"> 319</a></span> <span class="comment"></span><span class="keyword">class </span><a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a> : <span class="keyword">public</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><void*></div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> {</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span> <span class="comment"> /// Brings in the constructors and assignment operator.</span></div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> <span class="comment"></span> <span class="keyword">using</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<void*>::BaseTensor</a>;</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> };</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> <span class="comment"></span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> <span class="comment">/// A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.</span></div><div class="line"><a name="l00327"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml"> 327</a></span> <span class="comment"></span><span class="keyword">class </span><a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> : <span class="keyword">public</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> {</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span> <span class="comment"> /// Brings in the constructors and assignment operator.</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> <span class="comment"></span> <span class="keyword">using</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<const void*>::BaseTensor</a>;</div><div class="line"><a name="l00332"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#a6b6561873c02b1bd9b7a7ae8dd4a339c"> 332</a></span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml#a6b6561873c02b1bd9b7a7ae8dd4a339c">ConstTensor</a>() : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>()</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  {</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  this->GetInfo().SetConstant();</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  }</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> <span class="comment"></span></div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> <span class="comment"> /// ConstTensor implicitly constructed from non-const Tensor.</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> <span class="comment"> ///</span></div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> <span class="comment"> /// @param other - reference to a constant Tensor.</span></div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> <span class="comment"> ///</span></div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> <span class="comment"> /// @throws InvalidArgumentException when Tensor parameter TensorInfo is non-constant.</span></div><div class="line"><a name="l00342"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#a42aec46c635aa2e38932ca103d2064ed"> 342</a></span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml#a42aec46c635aa2e38932ca103d2064ed">ConstTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a>& other) : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>(other.GetInfo(), other.GetMemoryArea())</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  {</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="keywordflow">if</span> (!this->GetInfo().IsConstant())</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  {</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Invalid attempt to construct ConstTensor "</span></div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="stringliteral">"from Tensor due to non-constant TensorInfo"</span>);</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  }</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  }</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span> <span class="comment"></span></div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> <span class="comment"> /// Constructor from a backing container.</span></div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> <span class="comment"> ///</span></div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> <span class="comment"> /// @param container - An stl-like container type which implements data() and size() methods.</span></div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> <span class="comment"> /// Presence of data() and size() is a strong indicator of the continuous memory layout of the container,</span></div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> <span class="comment"> /// which is a requirement for Tensor data. Tensor instances do not claim ownership of referenced memory regions,</span></div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> <span class="comment"> /// that is, no attempt will be made by ArmNN to free these memory regions automatically.</span></div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> <span class="comment"> ///</span></div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> <span class="comment"> /// @throws InvalidArgumentException when isConstant parameter of input TensorInfo is false.</span></div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> <span class="comment"></span> <span class="keyword">template</span> < <span class="keyword">template</span><<span class="keyword">typename</span>, <span class="keyword">typename</span>...> <span class="keyword">class </span>ContainerType, <span class="keyword">typename</span> T, <span class="keyword">typename</span>...ContainerArgs ></div><div class="line"><a name="l00360"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#aa04de06d072895b6df9125338d55c205"> 360</a></span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml#aa04de06d072895b6df9125338d55c205">ConstTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, <span class="keyword">const</span> ContainerType<T, ContainerArgs...>& container)</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>(info, container.data())</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  {</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">if</span> (!this->GetInfo().IsConstant())</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  {</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Invalid attempt to construct ConstTensor from non-constant TensorInfo."</span>);</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  }</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="keywordflow">if</span> (container.size() * <span class="keyword">sizeof</span>(T) != info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>())</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  {</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Container size is not correct"</span>);</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  }</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  }</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> <span class="comment"></span></div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> <span class="comment"> /// ConstTensor constructed from TensorInfo and MemoryType template (a raw memory pointer).</span></div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> <span class="comment"> ///</span></div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> <span class="comment"> /// @param info - reference to a constant TensorInfo.</span></div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> <span class="comment"> /// @param memoryArea - Region of CPU-addressable memory where tensor data will be stored. Must be valid while</span></div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> <span class="comment"> /// workloads are on the fly. Tensor instances do not claim ownership of referenced memory regions, that is,</span></div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> <span class="comment"> /// no attempt will be made by ArmNN to free these memory regions automatically.</span></div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> <span class="comment"> ///</span></div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> <span class="comment"> /// @throws InvalidArgumentException when TensorInfo isConstant parameter is false.</span></div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span> <span class="comment"></span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00382"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#a2f83b6c57329068aa1ecdbc1e02f556f"> 382</a></span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml#a2f83b6c57329068aa1ecdbc1e02f556f">ConstTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, MemoryType memoryArea)</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>(info, memoryArea)</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  {</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordflow">if</span> (!this->GetInfo().IsConstant())</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  {</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Invalid attempt to construct ConstTensor from non-constant TensorInfo."</span>);</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  }</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  }</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span> };</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> </div><div class="line"><a name="l00392"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527"> 392</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> = std::vector<std::pair<LayerBindingId, class ConstTensor>>;</div><div class="line"><a name="l00393"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea"> 393</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> = std::vector<std::pair<LayerBindingId, class Tensor>>;</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> } <span class="comment">// namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorShape::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdoc">Function that calculates the tensor elements by multiplying all dimension size which are Specified...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00181">Tensor.cpp:181</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a77d202fcd47612eb5a4d6d23a7d4b349"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">armnn::TensorShape::operator!=</a></div><div class="ttdeci">bool operator!=(const TensorShape &other) const</div><div class="ttdoc">Inequality comparison operator. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00169">Tensor.cpp:169</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a6e6dab22049a4432e8306a301dceff52"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">armnn::TensorShape::operator[]</a></div><div class="ttdeci">unsigned int operator[](unsigned int i) const</div><div class="ttdoc">Read only operator. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00135">Tensor.cpp:135</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">armnn::Dimensionality</a></div><div class="ttdeci">Dimensionality</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00158">Types.hpp:158</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00191">Tensor.hpp:191</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a0ca6f42172d27e9799da3e3f7840ac31"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">armnn::TensorShape::operator=</a></div><div class="ttdeci">TensorShape & operator=(const TensorShape &other)</div><div class="ttdoc">Assignation function. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00124">Tensor.cpp:124</a></div></div> -<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional< unsigned int ></a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_acccb75bd1d68a81f6ddd61687f51c5a1"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1">armnn::TensorShape::AreAllDimensionsSpecified</a></div><div class="ttdeci">bool AreAllDimensionsSpecified() const</div><div class="ttdoc">Checks if there is at least one dimension not specified. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00241">Tensor.cpp:241</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a5a212540c00931bd2a4b4041beda33ae"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a5a212540c00931bd2a4b4041beda33ae">armnn::TensorShape::GetDimensionality</a></div><div class="ttdeci">Dimensionality GetDimensionality() const</div><div class="ttdoc">Function that returns the tensor type. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00092">Tensor.hpp:92</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::BaseTensor::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00297">Tensor.hpp:297</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#l00427">Tensor.cpp:427</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::BaseTensor::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00303">Tensor.hpp:303</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00392">Tensor.hpp:392</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_aa81f67ac64f0c249e26499600c45d996"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996">armnn::BaseTensor::GetMemoryArea</a></div><div class="ttdeci">MemoryType GetMemoryArea() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00305">Tensor.hpp:305</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__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.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_const_tensor_xhtml_a2f83b6c57329068aa1ecdbc1e02f556f"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#a2f83b6c57329068aa1ecdbc1e02f556f">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor(const TensorInfo &info, MemoryType memoryArea)</div><div class="ttdoc">ConstTensor constructed from TensorInfo and MemoryType template (a raw memory pointer). </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00382">Tensor.hpp:382</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#l00201">Tensor.hpp:201</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="classarmnn_1_1_tensor_info_xhtml_abe8889e8150beef5fd204b2d87b49298"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">armnn::TensorInfo::SetShape</a></div><div class="ttdeci">void SetShape(const TensorShape &newShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00193">Tensor.hpp:193</a></div></div> -<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml_a6b6561873c02b1bd9b7a7ae8dd4a339c"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#a6b6561873c02b1bd9b7a7ae8dd4a339c">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00332">Tensor.hpp:332</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00319">Tensor.hpp:319</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a07e348fae6036aecdaf41e738d1ae9ff"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">armnn::TensorShape::operator==</a></div><div class="ttdeci">bool operator==(const TensorShape &other) const</div><div class="ttdoc">Equality comparison operator. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00160">Tensor.cpp:160</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a350bcc7d86f7d9333340a0a04be078f6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a350bcc7d86f7d9333340a0a04be078f6">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">TensorShape & GetShape()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00192">Tensor.hpp:192</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a76d053cd9b4373d90682ad646dad334c"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">armnn::TensorShape::TensorShape</a></div><div class="ttdeci">TensorShape()</div><div class="ttdoc">Empty (invalid) constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00025">Tensor.cpp:25</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00048">Types.hpp:48</a></div></div> -<div class="ttc" id="_optional_8hpp_xhtml"><div class="ttname"><a href="_optional_8hpp.xhtml">Optional.hpp</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00198">Tensor.hpp:198</a></div></div> -<div class="ttc" id="_types_8hpp_xhtml"><div class="ttname"><a href="_types_8hpp.xhtml">Types.hpp</a></div></div> -<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00327">Tensor.hpp:327</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a82c7d5a6e675b1a876daa9983cd125d2"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2">armnn::TensorShape::SetNumDimensions</a></div><div class="ttdeci">void SetNumDimensions(unsigned int numDimensions, bool initDimensionsSpecificity=false)</div><div class="ttdoc">Sets the tensor rank and therefore the Dimensionality is set to Specified if it was not...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00219">Tensor.cpp:219</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00393">Tensor.hpp:393</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a350bcc7d86f7d9333340a0a04be078f6"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a350bcc7d86f7d9333340a0a04be078f6">armnn::BaseTensor::GetShape</a></div><div class="ttdeci">TensorShape & GetShape()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00298">Tensor.hpp:298</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#l00312">Tensor.hpp:312</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_ab2e02564acd2ce6db36de310702a75de"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#ab2e02564acd2ce6db36de310702a75de">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">TensorInfo & GetInfo()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00296">Tensor.hpp:296</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#l00295">Tensor.hpp:295</a></div></div> -<div class="ttc" id="classarmnn_1_1_invalid_argument_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00080">Exceptions.hpp:80</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a71975fcec1464d639f1a78f73164d1bd"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd">armnn::TensorInfo::SetDataType</a></div><div class="ttdeci">void SetDataType(DataType type)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00199">Tensor.hpp:199</a></div></div> -<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml_aa04de06d072895b6df9125338d55c205"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#aa04de06d072895b6df9125338d55c205">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor(const TensorInfo &info, const ContainerType< T, ContainerArgs... > &container)</div><div class="ttdoc">Constructor from a backing container. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00360">Tensor.hpp:360</a></div></div> -<div class="ttc" id="structarmnn_1_1_empty_optional_xhtml"><div class="ttname"><a href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a></div><div class="ttdoc">EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00032">Optional.hpp:32</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_a280670a263dc4fd40491f6d0a2737f44"><div class="ttname"><a href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">armnn::BindingPointInfo</a></div><div class="ttdeci">std::pair< armnn::LayerBindingId, armnn::TensorInfo > BindingPointInfo</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00274">Tensor.hpp:274</a></div></div> -<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml_a42aec46c635aa2e38932ca103d2064ed"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#a42aec46c635aa2e38932ca103d2064ed">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor(const Tensor &other)</div><div class="ttdoc">ConstTensor implicitly constructed from non-const Tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00342">Tensor.hpp:342</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::BaseTensor::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00301">Tensor.hpp:301</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> -<div class="ttc" id="_exceptions_8hpp_xhtml"><div class="ttname"><a href="_exceptions_8hpp.xhtml">Exceptions.hpp</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdoc">Function that returns the tensor rank. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00174">Tensor.cpp:174</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_ad82b782a8e1a05b6a3756e73c66d5f90"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90">armnn::TensorShape::SetDimensionSize</a></div><div class="ttdeci">void SetDimensionSize(unsigned int i, unsigned int dimensionSize)</div><div class="ttdoc">Sets the size of the indicated dimension and Specificity for that dimension is set to true...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00232">Tensor.cpp:232</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml">armnn::BaseTensor</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00277">Tensor.hpp:277</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_abac025efeffc6e099a365bdb17b5ca3e"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#abac025efeffc6e099a365bdb17b5ca3e">armnn::BaseTensor::~BaseTensor</a></div><div class="ttdeci">~BaseTensor()</div><div class="ttdoc">Protected destructor to stop users from making these (could still new one on the heap and then leak i...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00310">Tensor.hpp:310</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3">armnn::BaseTensor::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00300">Tensor.hpp:300</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00195">Tensor.hpp:195</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a34e12ab75d9073354565c2039f92112b"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b">armnn::TensorShape::IsAtLeastOneDimensionSpecified</a></div><div class="ttdeci">bool IsAtLeastOneDimensionSpecified() const</div><div class="ttdoc">Checks if there is at least one dimension specified. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00257">Tensor.cpp:257</a></div></div> -<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00196">Tensor.hpp:196</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_abcbdfb544ece4c31d0b37715ad0f3be0"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">armnn::BaseTensor::GetNumBytes</a></div><div class="ttdeci">unsigned int GetNumBytes() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00302">Tensor.hpp:302</a></div></div> +<a href="_tensor_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div> +<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017,2022 Arm Ltd and Contributors. All rights reserved.</span></div> +<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div> +<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div> +<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#pragma once</span></div> +<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>  </div> +<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_exceptions_8hpp.xhtml">Exceptions.hpp</a>"</span></div> +<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_optional_8hpp.xhtml">Optional.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_8hpp.xhtml">Types.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 <stdint.h></span></div> +<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <array></span></div> +<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <initializer_list></span></div> +<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <vector></span></div> +<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <utility></span></div> +<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>  </div> +<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div> +<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> {</div> +<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  </div> +<div class="line"><a name="l00020"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml"> 20</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a></div> +<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> {</div> +<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="keyword">public</span>:<span class="comment"></span></div> +<div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> /// Empty (invalid) constructor.</span></div> +<div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>();</div> +<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="comment"></span> </div> +<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment"> /// Constructor for TensorShape</span></div> +<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div> +<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment"> /// @param initDimensionsSpecificity (optional) - value to initialize the specificity of each dimension size.</span></div> +<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"></span> <span class="keyword">explicit</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keywordtype">bool</span> initDimensionsSpecificity = <span class="keyword">true</span>);</div> +<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment"></span> </div> +<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"> /// Constructor for TensorShape</span></div> +<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div> +<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> /// @param dimensionSizes - Size of each of dimension.</span></div> +<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes);</div> +<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"></span> </div> +<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment"> /// Constructor for TensorShape</span></div> +<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> /// @param dimensionSizeList - Size of each of dimension.</span></div> +<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(std::initializer_list<unsigned int> dimensionSizeList);</div> +<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"></span> </div> +<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"> /// Copy Constructor for TensorShape</span></div> +<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"> /// @param other - TensorShape to copy from.</span></div> +<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other);</div> +<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment"></span> </div> +<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"> /// Constructor for TensorShape</span></div> +<div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div> +<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> /// @param dimensionSizes - Size of each of dimension.</span></div> +<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"> /// @param dimensionsSpecificity - Flags to indicate which dimension has its size specified.</span></div> +<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes, <span class="keyword">const</span> <span class="keywordtype">bool</span>* dimensionsSpecificity);</div> +<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment"></span> </div> +<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"> /// Constructor for TensorShape</span></div> +<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> /// @param dimensionSizeList - Size of each of dimension.</span></div> +<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> /// @param dimensionsSpecificityList - Flags to indicate which dimension size is specified.</span></div> +<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(std::initializer_list<unsigned int> dimensionSizeList,</div> +<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  std::initializer_list<bool> dimensionsSpecificityList);</div> +<div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"></span> </div> +<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"> /// Constructor for TensorShape</span></div> +<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> /// @param dimensionality - Parameter to indicate if the Tensor is a Scalar, a Tensor of known dimensionality</span></div> +<div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"> /// or a Tensor of unknown dimensionality.</span></div> +<div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="comment"></span> <span class="keyword">explicit</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> dimensionality);</div> +<div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="comment"></span> </div> +<div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="comment"> /// Assignation function</span></div> +<div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="comment"> /// @param other - TensorShape to copy from.</span></div> +<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other);</div> +<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"></span> </div> +<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment"> /// Read only operator</span></div> +<div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment"> /// @param i - Dimension index.</span></div> +<div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div> +<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="comment"></span> </div> +<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="comment"> /// Read and write operator</span></div> +<div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="comment"> /// @param i - Dimension index.</span></div> +<div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i);</div> +<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment"></span> </div> +<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="comment"> /// Equality comparison operator</span></div> +<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="comment"> /// @param other - TensorShape to compare with.</span></div> +<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">operator==</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other) <span class="keyword">const</span>;</div> +<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="comment"></span> </div> +<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="comment"> /// Inequality comparison operator</span></div> +<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="comment"> /// @param other - TensorShape to compare with.</span></div> +<div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">operator!=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other) <span class="keyword">const</span>;</div> +<div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="comment"></span> </div> +<div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="comment"> /// Function that returns the tensor rank.</span></div> +<div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="comment"> /// @return - Tensor rank.</span></div> +<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"></span> </div> +<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment"> /// Function that calculates the tensor elements by multiplying all dimension size which are Specified.</span></div> +<div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="comment"> /// @return - Total number of elements in the tensor.</span></div> +<div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="comment"></span> </div> +<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="comment"> /// Function that returns the tensor type.</span></div> +<div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="comment"> /// @return - Parameter to indicate if the Tensor is a scalar, a Tensor of known dimensionality or</span></div> +<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="comment"> /// a Tensor of unknown dimensionality</span></div> +<div class="line"><a name="l00092"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a5a212540c00931bd2a4b4041beda33ae"> 92</a></span> <span class="comment"></span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a5a212540c00931bd2a4b4041beda33ae">GetDimensionality</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Dimensionality; }</div> +<div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="comment"></span> </div> +<div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="comment"> /// Gets information about if the dimension size has been specified or not</span></div> +<div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="comment"> /// @param i - Dimension index.</span></div> +<div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="comment"> /// @return - Flag to indicate if the dimension "i" has a specified size.</span></div> +<div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a3919600d4aa8d5cd801a0e0740f62308">GetDimensionSpecificity</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div> +<div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="comment"></span> </div> +<div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="comment"> /// Sets the tensor rank and therefore the Dimensionality is set to Specified if it was not.</span></div> +<div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div> +<div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="comment"> /// @param initDimensionsSpecificity (optional) - value to initialize the specificity of each dimension size.</span></div> +<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2">SetNumDimensions</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keywordtype">bool</span> initDimensionsSpecificity = <span class="keyword">false</span>);</div> +<div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="comment"></span> </div> +<div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="comment"> /// Sets the size of the indicated dimension and Specificity for that dimension is set to true.</span></div> +<div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="comment"> /// @param i - Dimension index.</span></div> +<div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="comment"> /// @param dimensionSize - size of one dimension.</span></div> +<div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90">SetDimensionSize</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimensionSize);</div> +<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="comment"></span> </div> +<div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment"> /// Checks if there is at least one dimension not specified. AND of all array elements.</span></div> +<div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="comment"> /// @return - True when all dimension sizes are specified. False when at least one dimension size is not specified.</span></div> +<div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1">AreAllDimensionsSpecified</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="comment"></span> </div> +<div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="comment"> /// Checks if there is at least one dimension specified. OR of all array elements.</span></div> +<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"> /// @return - True at least one dimension sizes is specified. False when all dimension sizes are not specified.</span></div> +<div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b">IsAtLeastOneDimensionSpecified</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  </div> +<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="keyword">private</span>:<span class="comment"></span></div> +<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="comment"> /// Array of the dimension sizes.</span></div> +<div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="comment"></span> std::array<unsigned int, MaxNumOfTensorDimensions> m_Dimensions{};</div> +<div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="comment"></span> </div> +<div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="comment"> /// Array of flags to indicate if the size of each of the dimensions is specified or not</span></div> +<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="comment"></span> std::array<bool, MaxNumOfTensorDimensions> m_DimensionsSpecificity = { {<span class="keyword">true</span>} };</div> +<div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="comment"></span> </div> +<div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="comment"> /// Tensor rank</span></div> +<div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="comment"></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m_NumDimensions{};</div> +<div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="comment"></span> </div> +<div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="comment"> /// Tensor type: Specified, NotSpecified or Scalar.</span></div> +<div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="comment"></span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> m_Dimensionality = <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Dimensionality::Specified</a>;</div> +<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="comment"></span> </div> +<div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="comment"> /// Checks if the dimension index given is within range.</span></div> +<div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="comment"> /// @param i - Dimension index.</span></div> +<div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckDimensionIndex(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div> +<div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="comment"></span> </div> +<div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="comment"> /// Checks if the tensor rank given is within range.</span></div> +<div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="comment"> /// @param numDimensions - Tensor rank.</span></div> +<div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="comment"></span> <span class="keyword">static</span> <span class="keywordtype">void</span> CheckValidNumDimensions(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions) ;</div> +<div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="comment"></span> </div> +<div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="comment"> /// Checks if the size of the dimension index given is specified.</span></div> +<div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="comment"> /// @param i - Dimension index.</span></div> +<div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckDimensionSpecified(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) <span class="keyword">const</span>;</div> +<div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="comment"></span> </div> +<div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment"> /// Checks if this is a scalar.</span></div> +<div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckScalar() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment"></span> </div> +<div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="comment"> /// Checks if the number of dimensions is unknown, i.e. rank is unspecified.</span></div> +<div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckUnspecifiedNumDimensions() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="comment"></span> </div> +<div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="comment"> /// Checks if the number of dimensions is known, i.e. rank is specified.</span></div> +<div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="comment"></span> <span class="keywordtype">void</span> CheckSpecifiedNumDimensions() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00150"></a><span class="lineno"> 150</span> };</div> +<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  </div> +<div class="line"><a name="l00152"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml"> 152</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a></div> +<div class="line"><a name="l00153"></a><span class="lineno"> 153</span> {</div> +<div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="keyword">public</span>:<span class="comment"></span></div> +<div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="comment"> /// Empty (invalid) constructor.</span></div> +<div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>();</div> +<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  </div> +<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& shape,</div> +<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div> +<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordtype">float</span> quantizationScale = 0.0f,</div> +<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  int32_t quantizationOffset = 0,</div> +<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keywordtype">bool</span> isConstant = <span class="keyword">false</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"> 164</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div> +<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div> +<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div> +<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordtype">float</span> quantizationScale = 0.0f,</div> +<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  int32_t quantizationOffset = 0,</div> +<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordtype">bool</span> isConstant = <span class="keyword">false</span>);</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#a21c2ae9fa438faf42669dadda628080c">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="l00172"></a><span class="lineno"> 172</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div> +<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div> +<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim,</div> +<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keywordtype">bool</span> isConstant = <span class="keyword">false</span>);</div> +<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  </div> +<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div> +<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div> +<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div> +<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div> +<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim,</div> +<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordtype">bool</span> isConstant = <span class="keyword">false</span>);</div> +<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  </div> +<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">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="l00185"></a><span class="lineno"> 185</span>  </div> +<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#ac45c8c0052476cd66ef732de76dd9bc8">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="l00187"></a><span class="lineno"> 187</span>  </div> +<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a586e1eec08e847abfeb3de3a4038c5ce">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="l00189"></a><span class="lineno"> 189</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a2a944e616dc6fdde5287b17f2265307d">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="l00190"></a><span class="lineno"> 190</span>  </div> +<div class="line"><a name="l00191"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8"> 191</a></span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Shape; }</div> +<div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a350bcc7d86f7d9333340a0a04be078f6"> 192</a></span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a350bcc7d86f7d9333340a0a04be078f6">GetShape</a>() { <span class="keywordflow">return</span> m_Shape; }</div> +<div class="line"><a name="l00193"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298"> 193</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& newShape) { m_Shape = newShape; }</div> +<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  </div> +<div class="line"><a name="l00195"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24"> 195</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Shape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); }</div> +<div class="line"><a name="l00196"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7"> 196</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Shape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(); }</div> +<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  </div> +<div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3"> 198</a></span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_DataType; }</div> +<div class="line"><a name="l00199"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd"> 199</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd">SetDataType</a>(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> type) { m_DataType = type; }</div> +<div class="line"><a name="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#af672d1c9e2a120a18926cb645981fbb7"> 201</a></span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">HasMultipleQuantizationScales</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Quantization.m_Scales.size() > 1; }</div> +<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  </div> +<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48">HasPerAxisQuantization</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  </div> +<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  std::vector<float> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270">GetQuantizationScales</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">SetQuantizationScales</a>(<span class="keyword">const</span> std::vector<float>& scales);</div> +<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  </div> +<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordtype">float</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(<span class="keywordtype">float</span> scale);</div> +<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  </div> +<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  int32_t <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(int32_t offset);</div> +<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  </div> +<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b8fc85ce966c035d789cf22db5088a1">GetQuantizationDim</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">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="l00216"></a><span class="lineno"> 216</span>  </div> +<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd">IsQuantized</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  </div> +<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>() <span class="keyword">const</span>;</div> +<div class="line"><a name="l00220"></a><span class="lineno"> 220</span> <span class="comment"></span> </div> +<div class="line"><a name="l00221"></a><span class="lineno"> 221</span> <span class="comment"> /// Marks the data corresponding to this tensor info as constant.</span></div> +<div class="line"><a name="l00222"></a><span class="lineno"> 222</span> <span class="comment"> ///</span></div> +<div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="comment"> /// @details: This can allow further optimization on execution</span></div> +<div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="comment"> /// @Note: The user has to ensure that the underlying data actually is constant.</span></div> +<div class="line"><a name="l00225"></a><span class="lineno"> 225</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8ffca1e21bdfa7f945617acd606aac91">SetConstant</a>(<span class="keyword">const</span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>=<span class="keyword">true</span>);</div> +<div class="line"><a name="l00226"></a><span class="lineno"> 226</span> <span class="comment"></span> </div> +<div class="line"><a name="l00227"></a><span class="lineno"> 227</span> <span class="comment"> /// Check that the types are the same and, if quantize, that the quantization parameters are the same.</span></div> +<div class="line"><a name="l00228"></a><span class="lineno"> 228</span> <span class="comment"></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a22f377fc4e10dc1773a3f979061e85f1">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="l00229"></a><span class="lineno"> 229</span>  </div> +<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>() <span class="keyword">const</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"> 232</span> <span class="keyword">private</span>:</div> +<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> m_Shape;</div> +<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> m_DataType;</div> +<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordtype">bool</span> m_IsConstant;</div> +<div class="line"><a name="l00236"></a><span class="lineno"> 236</span> <span class="comment"></span> </div> +<div class="line"><a name="l00237"></a><span class="lineno"> 237</span> <span class="comment"> /// Vectors of scale and offset are used for per-axis quantization.</span></div> +<div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="comment"></span> <span class="keyword">struct </span>Quantization</div> +<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  {</div> +<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  Quantization()</div> +<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  : m_Scales{}</div> +<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  , m_Offset(EmptyOptional())</div> +<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  , m_QuantizationDim(EmptyOptional()) {}</div> +<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  </div> +<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  Quantization(<span class="keyword">const</span> Quantization& other)</div> +<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  : m_Scales(other.m_Scales)</div> +<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  , m_Offset(other.m_Offset)</div> +<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  , m_QuantizationDim(other.m_QuantizationDim) {}</div> +<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  </div> +<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a586e1eec08e847abfeb3de3a4038c5ce">operator==</a>(<span class="keyword">const</span> Quantization& other)<span class="keyword"> const</span></div> +<div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="keyword"> </span>{</div> +<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">return</span> ((m_Scales == other.m_Scales) && (m_Offset == other.m_Offset) &&</div> +<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  (m_QuantizationDim == other.m_QuantizationDim));</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>  </div> +<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  Quantization& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#ac45c8c0052476cd66ef732de76dd9bc8">operator=</a>(<span class="keyword">const</span> Quantization& other)</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>  <span class="keywordflow">if</span>(<span class="keyword">this</span> != &other)</div> +<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  {</div> +<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  m_Scales = other.m_Scales;</div> +<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  m_Offset = other.m_Offset;</div> +<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  m_QuantizationDim = other.m_QuantizationDim;</div> +<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  }</div> +<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div> +<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  }</div> +<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  </div> +<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  std::vector<float> m_Scales;</div> +<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  Optional<int32_t> m_Offset;</div> +<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  Optional<unsigned int> m_QuantizationDim;</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>  } m_Quantization;</div> +<div class="line"><a name="l00272"></a><span class="lineno"> 272</span> };</div> +<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  </div> +<div class="line"><a name="l00274"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44"> 274</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">BindingPointInfo</a> = std::pair<armnn::LayerBindingId, armnn::TensorInfo>;</div> +<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  </div> +<div class="line"><a name="l00276"></a><span class="lineno"> 276</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div> +<div class="line"><a name="l00277"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml"> 277</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a></div> +<div class="line"><a name="l00278"></a><span class="lineno"> 278</span> {</div> +<div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="keyword">public</span>:<span class="comment"></span></div> +<div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="comment"> /// Empty (invalid) constructor.</span></div> +<div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">BaseTensor</a>();</div> +<div class="line"><a name="l00282"></a><span class="lineno"> 282</span> <span class="comment"></span> </div> +<div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="comment"> /// Constructor from a raw memory pointer.</span></div> +<div class="line"><a name="l00284"></a><span class="lineno"> 284</span> <span class="comment"> /// @param memoryArea - Region of CPU-addressable memory where tensor data will be stored. Must be valid while</span></div> +<div class="line"><a name="l00285"></a><span class="lineno"> 285</span> <span class="comment"> /// workloads are on the fly. Tensor instances do not claim ownership of referenced memory regions, that is,</span></div> +<div class="line"><a name="l00286"></a><span class="lineno"> 286</span> <span class="comment"> /// no attempt will be made by ArmNN to free these memory regions automatically.</span></div> +<div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, MemoryType memoryArea);</div> +<div class="line"><a name="l00288"></a><span class="lineno"> 288</span> <span class="comment"></span> </div> +<div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="comment"> /// Tensors are copyable.</span></div> +<div class="line"><a name="l00290"></a><span class="lineno"> 290</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>& other);</div> +<div class="line"><a name="l00291"></a><span class="lineno"> 291</span> <span class="comment"></span> </div> +<div class="line"><a name="l00292"></a><span class="lineno"> 292</span> <span class="comment"> /// Tensors are copyable.</span></div> +<div class="line"><a name="l00293"></a><span class="lineno"> 293</span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a844fc6ba8f5435b5a200072a3ec163af">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a>&);</div> +<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  </div> +<div class="line"><a name="l00295"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678"> 295</a></span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info; }</div> +<div class="line"><a name="l00296"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#ab2e02564acd2ce6db36de310702a75de"> 296</a></span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#ab2e02564acd2ce6db36de310702a75de">GetInfo</a>() { <span class="keywordflow">return</span> m_Info; }</div> +<div class="line"><a name="l00297"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8"> 297</a></span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(); }</div> +<div class="line"><a name="l00298"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a350bcc7d86f7d9333340a0a04be078f6"> 298</a></span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a350bcc7d86f7d9333340a0a04be078f6">GetShape</a>() { <span class="keywordflow">return</span> m_Info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(); }</div> +<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  </div> +<div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3"> 300</a></span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>(); }</div> +<div class="line"><a name="l00301"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24"> 301</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); }</div> +<div class="line"><a name="l00302"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0"> 302</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>(); }</div> +<div class="line"><a name="l00303"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a8846406ac37fbd2204f0be16ee05d5b7"> 303</a></span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(); }</div> +<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  </div> +<div class="line"><a name="l00305"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996"> 305</a></span>  MemoryType <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996">GetMemoryArea</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>; }</div> +<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  </div> +<div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="keyword">protected</span>:<span class="comment"></span></div> +<div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="comment"> /// Protected destructor to stop users from making these</span></div> +<div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="comment"> /// (could still new one on the heap and then leak it...)</span></div> +<div class="line"><a name="l00310"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#abac025efeffc6e099a365bdb17b5ca3e"> 310</a></span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#abac025efeffc6e099a365bdb17b5ca3e">~BaseTensor</a>() {}</div> +<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  </div> +<div class="line"><a name="l00312"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49"> 312</a></span>  MemoryType <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>;</div> +<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  </div> +<div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="keyword">private</span>:</div> +<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> m_Info;</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> <span class="comment"></span> </div> +<div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="comment">/// A tensor defined by a TensorInfo (shape and data type) and a mutable backing store.</span></div> +<div class="line"><a name="l00319"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor.xhtml"> 319</a></span> <span class="comment"></span><span class="keyword">class </span><a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a> : <span class="keyword">public</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><void*></div> +<div class="line"><a name="l00320"></a><span class="lineno"> 320</span> {</div> +<div class="line"><a name="l00321"></a><span class="lineno"> 321</span> <span class="keyword">public</span>:<span class="comment"></span></div> +<div class="line"><a name="l00322"></a><span class="lineno"> 322</span> <span class="comment"> /// Brings in the constructors and assignment operator.</span></div> +<div class="line"><a name="l00323"></a><span class="lineno"> 323</span> <span class="comment"></span> <span class="keyword">using</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<void*>::BaseTensor</a>;</div> +<div class="line"><a name="l00324"></a><span class="lineno"> 324</span> };</div> +<div class="line"><a name="l00325"></a><span class="lineno"> 325</span> <span class="comment"></span> </div> +<div class="line"><a name="l00326"></a><span class="lineno"> 326</span> <span class="comment">/// A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.</span></div> +<div class="line"><a name="l00327"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml"> 327</a></span> <span class="comment"></span><span class="keyword">class </span><a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> : <span class="keyword">public</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*></div> +<div class="line"><a name="l00328"></a><span class="lineno"> 328</span> {</div> +<div class="line"><a name="l00329"></a><span class="lineno"> 329</span> <span class="keyword">public</span>:<span class="comment"></span></div> +<div class="line"><a name="l00330"></a><span class="lineno"> 330</span> <span class="comment"> /// Brings in the constructors and assignment operator.</span></div> +<div class="line"><a name="l00331"></a><span class="lineno"> 331</span> <span class="comment"></span> <span class="keyword">using</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<const void*>::BaseTensor</a>;</div> +<div class="line"><a name="l00332"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#a6b6561873c02b1bd9b7a7ae8dd4a339c"> 332</a></span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml#a6b6561873c02b1bd9b7a7ae8dd4a339c">ConstTensor</a>() : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>()</div> +<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  {</div> +<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  this-><a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8ffca1e21bdfa7f945617acd606aac91">SetConstant</a>();</div> +<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  }</div> +<div class="line"><a name="l00336"></a><span class="lineno"> 336</span> <span class="comment"></span> </div> +<div class="line"><a name="l00337"></a><span class="lineno"> 337</span> <span class="comment"> /// ConstTensor implicitly constructed from non-const Tensor.</span></div> +<div class="line"><a name="l00338"></a><span class="lineno"> 338</span> <span class="comment"> ///</span></div> +<div class="line"><a name="l00339"></a><span class="lineno"> 339</span> <span class="comment"> /// @param other - reference to a constant Tensor.</span></div> +<div class="line"><a name="l00340"></a><span class="lineno"> 340</span> <span class="comment"> ///</span></div> +<div class="line"><a name="l00341"></a><span class="lineno"> 341</span> <span class="comment"> /// @throws InvalidArgumentException when Tensor parameter TensorInfo is non-constant.</span></div> +<div class="line"><a name="l00342"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#a42aec46c635aa2e38932ca103d2064ed"> 342</a></span> <span class="comment"></span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml#a42aec46c635aa2e38932ca103d2064ed">ConstTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a>& other) : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>(other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>(), other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996">GetMemoryArea</a>())</div> +<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  {</div> +<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="keywordflow">if</span> (!this-><a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>().IsConstant())</div> +<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  {</div> +<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Invalid attempt to construct ConstTensor "</span></div> +<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="stringliteral">"from Tensor due to non-constant TensorInfo"</span>);</div> +<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  }</div> +<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  }</div> +<div class="line"><a name="l00350"></a><span class="lineno"> 350</span> <span class="comment"></span> </div> +<div class="line"><a name="l00351"></a><span class="lineno"> 351</span> <span class="comment"> /// Constructor from a backing container.</span></div> +<div class="line"><a name="l00352"></a><span class="lineno"> 352</span> <span class="comment"> ///</span></div> +<div class="line"><a name="l00353"></a><span class="lineno"> 353</span> <span class="comment"> /// @param container - An stl-like container type which implements data() and size() methods.</span></div> +<div class="line"><a name="l00354"></a><span class="lineno"> 354</span> <span class="comment"> /// Presence of data() and size() is a strong indicator of the continuous memory layout of the container,</span></div> +<div class="line"><a name="l00355"></a><span class="lineno"> 355</span> <span class="comment"> /// which is a requirement for Tensor data. Tensor instances do not claim ownership of referenced memory regions,</span></div> +<div class="line"><a name="l00356"></a><span class="lineno"> 356</span> <span class="comment"> /// that is, no attempt will be made by ArmNN to free these memory regions automatically.</span></div> +<div class="line"><a name="l00357"></a><span class="lineno"> 357</span> <span class="comment"> ///</span></div> +<div class="line"><a name="l00358"></a><span class="lineno"> 358</span> <span class="comment"> /// @throws InvalidArgumentException when isConstant parameter of input TensorInfo is false.</span></div> +<div class="line"><a name="l00359"></a><span class="lineno"> 359</span> <span class="comment"></span> <span class="keyword">template</span> < <span class="keyword">template</span><<span class="keyword">typename</span>, <span class="keyword">typename</span>...> <span class="keyword">class </span>ContainerType, <span class="keyword">typename</span> T, <span class="keyword">typename</span>...ContainerArgs ></div> +<div class="line"><a name="l00360"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#aa04de06d072895b6df9125338d55c205"> 360</a></span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml#aa04de06d072895b6df9125338d55c205">ConstTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& info, <span class="keyword">const</span> ContainerType<T, ContainerArgs...>& container)</div> +<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, container.data())</div> +<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  {</div> +<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">if</span> (!this-><a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>().IsConstant())</div> +<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  {</div> +<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Invalid attempt to construct ConstTensor from non-constant TensorInfo."</span>);</div> +<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  }</div> +<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="keywordflow">if</span> (container.size() * <span class="keyword">sizeof</span>(T) != <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetNumBytes())</div> +<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  {</div> +<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Container size is not correct"</span>);</div> +<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  }</div> +<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  }</div> +<div class="line"><a name="l00372"></a><span class="lineno"> 372</span> <span class="comment"></span> </div> +<div class="line"><a name="l00373"></a><span class="lineno"> 373</span> <span class="comment"> /// ConstTensor constructed from TensorInfo and MemoryType template (a raw memory pointer).</span></div> +<div class="line"><a name="l00374"></a><span class="lineno"> 374</span> <span class="comment"> ///</span></div> +<div class="line"><a name="l00375"></a><span class="lineno"> 375</span> <span class="comment"> /// @param info - reference to a constant TensorInfo.</span></div> +<div class="line"><a name="l00376"></a><span class="lineno"> 376</span> <span class="comment"> /// @param memoryArea - Region of CPU-addressable memory where tensor data will be stored. Must be valid while</span></div> +<div class="line"><a name="l00377"></a><span class="lineno"> 377</span> <span class="comment"> /// workloads are on the fly. Tensor instances do not claim ownership of referenced memory regions, that is,</span></div> +<div class="line"><a name="l00378"></a><span class="lineno"> 378</span> <span class="comment"> /// no attempt will be made by ArmNN to free these memory regions automatically.</span></div> +<div class="line"><a name="l00379"></a><span class="lineno"> 379</span> <span class="comment"> ///</span></div> +<div class="line"><a name="l00380"></a><span class="lineno"> 380</span> <span class="comment"> /// @throws InvalidArgumentException when TensorInfo isConstant parameter is false.</span></div> +<div class="line"><a name="l00381"></a><span class="lineno"> 381</span> <span class="comment"></span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div> +<div class="line"><a name="l00382"></a><span class="lineno"><a class="line" href="classarmnn_1_1_const_tensor.xhtml#a2f83b6c57329068aa1ecdbc1e02f556f"> 382</a></span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml#a2f83b6c57329068aa1ecdbc1e02f556f">ConstTensor</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="l00383"></a><span class="lineno"> 383</span>  : <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor</a><const void*>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, memoryArea)</div> +<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  {</div> +<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordflow">if</span> (!this-><a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>().IsConstant())</div> +<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  {</div> +<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Invalid attempt to construct ConstTensor from non-constant TensorInfo."</span>);</div> +<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  }</div> +<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  }</div> +<div class="line"><a name="l00390"></a><span class="lineno"> 390</span> };</div> +<div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  </div> +<div class="line"><a name="l00392"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527"> 392</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> = std::vector<std::pair<LayerBindingId, class ConstTensor>>;</div> +<div class="line"><a name="l00393"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea"> 393</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> = std::vector<std::pair<LayerBindingId, class Tensor>>;</div> +<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  </div> +<div class="line"><a name="l00395"></a><span class="lineno"> 395</span> } <span class="comment">// namespace armnn</span></div> </div><!-- fragment --></div><!-- contents --> </div><!-- doc-content --> +<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_a844fc6ba8f5435b5a200072a3ec163af"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a844fc6ba8f5435b5a200072a3ec163af">armnn::BaseTensor::operator=</a></div><div class="ttdeci">BaseTensor & operator=(const BaseTensor &)</div><div class="ttdoc">Tensors are copyable.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00544">Tensor.cpp:544</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a350bcc7d86f7d9333340a0a04be078f6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a350bcc7d86f7d9333340a0a04be078f6">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">TensorShape & GetShape()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00192">Tensor.hpp:192</a></div></div> +<div class="ttc" id="anamespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">armnn::Dimensionality::Specified</a></div><div class="ttdeci">@ Specified</div></div> +<div class="ttc" id="aclassarmnn_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#l00478">Tensor.cpp:478</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00461">Tensor.cpp:461</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_ab2e02564acd2ce6db36de310702a75de"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#ab2e02564acd2ce6db36de310702a75de">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">TensorInfo & GetInfo()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00296">Tensor.hpp:296</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a71975fcec1464d639f1a78f73164d1bd"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd">armnn::TensorInfo::SetDataType</a></div><div class="ttdeci">void SetDataType(DataType type)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00199">Tensor.hpp:199</a></div></div> +<div class="ttc" id="aclassarmnn_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="anamespacearmnn_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#l00158">Types.hpp:158</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a5a212540c00931bd2a4b4041beda33ae"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a5a212540c00931bd2a4b4041beda33ae">armnn::TensorShape::GetDimensionality</a></div><div class="ttdeci">Dimensionality GetDimensionality() const</div><div class="ttdoc">Function that returns the tensor type.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00092">Tensor.hpp:92</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00473">Tensor.cpp:473</a></div></div> +<div class="ttc" id="a_optional_8hpp_xhtml"><div class="ttname"><a href="_optional_8hpp.xhtml">Optional.hpp</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_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#l00414">Tensor.cpp:414</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_const_tensor_xhtml_a2f83b6c57329068aa1ecdbc1e02f556f"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#a2f83b6c57329068aa1ecdbc1e02f556f">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor(const TensorInfo &info, MemoryType memoryArea)</div><div class="ttdoc">ConstTensor constructed from TensorInfo and MemoryType template (a raw memory pointer).</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00382">Tensor.hpp:382</a></div></div> +<div class="ttc" id="aclassarmnn_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#l00422">Tensor.cpp:422</a></div></div> +<div class="ttc" id="aclassarmnn_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#l00405">Tensor.cpp:405</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::BaseTensor::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00301">Tensor.hpp:301</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a77d202fcd47612eb5a4d6d23a7d4b349"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">armnn::TensorShape::operator!=</a></div><div class="ttdeci">bool operator!=(const TensorShape &other) const</div><div class="ttdoc">Inequality comparison operator.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00169">Tensor.cpp:169</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00327">Tensor.hpp:327</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_a350bcc7d86f7d9333340a0a04be078f6"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a350bcc7d86f7d9333340a0a04be078f6">armnn::BaseTensor::GetShape</a></div><div class="ttdeci">TensorShape & GetShape()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00298">Tensor.hpp:298</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a519efe8ff6dc3aacdfe8a999415e3e4e"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">armnn::TensorInfo::SetQuantizationDim</a></div><div class="ttdeci">void SetQuantizationDim(const Optional< unsigned int > &quantizationDim)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00499">Tensor.cpp:499</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_const_tensor_xhtml_a6b6561873c02b1bd9b7a7ae8dd4a339c"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#a6b6561873c02b1bd9b7a7ae8dd4a339c">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor()</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00332">Tensor.hpp:332</a></div></div> +<div class="ttc" id="aclassarmnn_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#l00312">Tensor.hpp:312</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a0ca6f42172d27e9799da3e3f7840ac31"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">armnn::TensorShape::operator=</a></div><div class="ttdeci">TensorShape & operator=(const TensorShape &other)</div><div class="ttdoc">Assignation function.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00124">Tensor.cpp:124</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_abac025efeffc6e099a365bdb17b5ca3e"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#abac025efeffc6e099a365bdb17b5ca3e">armnn::BaseTensor::~BaseTensor</a></div><div class="ttdeci">~BaseTensor()</div><div class="ttdoc">Protected destructor to stop users from making these (could still new one on the heap and then leak i...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00310">Tensor.hpp:310</a></div></div> +<div class="ttc" id="aclassarmnn_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#l00277">Tensor.hpp:277</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a8ffca1e21bdfa7f945617acd606aac91"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8ffca1e21bdfa7f945617acd606aac91">armnn::TensorInfo::SetConstant</a></div><div class="ttdeci">void SetConstant(const bool IsConstant=true)</div><div class="ttdoc">Marks the data corresponding to this tensor info as constant.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00514">Tensor.cpp:514</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a07e348fae6036aecdaf41e738d1ae9ff"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">armnn::TensorShape::operator==</a></div><div class="ttdeci">bool operator==(const TensorShape &other) const</div><div class="ttdoc">Equality comparison operator.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00160">Tensor.cpp:160</a></div></div> +<div class="ttc" id="anamespacearmnn_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__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.dox:6</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a1a8675f9d64c3fb59e6af15362bb6332"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">armnn::TensorInfo::SetQuantizationScales</a></div><div class="ttdeci">void SetQuantizationScales(const std::vector< float > &scales)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00456">Tensor.cpp:456</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_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#l00489">Tensor.cpp:489</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_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#l00524">Tensor.cpp:524</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_1_1_base_tensor_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3">armnn::BaseTensor::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00300">Tensor.hpp:300</a></div></div> +<div class="ttc" id="aclassarmnn_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#l00504">Tensor.cpp:504</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a945263e85c27f3216a8323cfc16d8919"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">armnn::TensorInfo::IsConstant</a></div><div class="ttdeci">bool IsConstant() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00509">Tensor.cpp:509</a></div></div> +<div class="ttc" id="anamespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00392">Tensor.hpp:392</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00195">Tensor.hpp:195</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_1_1_const_tensor_xhtml_aa04de06d072895b6df9125338d55c205"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#aa04de06d072895b6df9125338d55c205">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor(const TensorInfo &info, const ContainerType< T, ContainerArgs... > &container)</div><div class="ttdoc">Constructor from a backing container.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00360">Tensor.hpp:360</a></div></div> +<div class="ttc" id="aclassarmnn_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#l00432">Tensor.cpp:432</a></div></div> +<div class="ttc" id="aclassarmnn_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#l00196">Tensor.hpp:196</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_1_1_tensor_info_xhtml_ab85cd8cc10c96a7c99c14042c251fc48"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48">armnn::TensorInfo::HasPerAxisQuantization</a></div><div class="ttdeci">bool HasPerAxisQuantization() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00446">Tensor.cpp:446</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_abcbdfb544ece4c31d0b37715ad0f3be0"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">armnn::BaseTensor::GetNumBytes</a></div><div class="ttdeci">unsigned int GetNumBytes() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00302">Tensor.hpp:302</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00191">Tensor.hpp:191</a></div></div> +<div class="ttc" id="aclassarmnn_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="anamespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00048">Types.hpp:48</a></div></div> +<div class="ttc" id="aclassarmnn_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#l00494">Tensor.cpp:494</a></div></div> +<div class="ttc" id="anamespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00393">Tensor.hpp:393</a></div></div> +<div class="ttc" id="aclassarmnn_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#l00427">Tensor.cpp:427</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_const_tensor_xhtml_a42aec46c635aa2e38932ca103d2064ed"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml#a42aec46c635aa2e38932ca103d2064ed">armnn::ConstTensor::ConstTensor</a></div><div class="ttdeci">ConstTensor(const Tensor &other)</div><div class="ttdoc">ConstTensor implicitly constructed from non-const Tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00342">Tensor.hpp:342</a></div></div> +<div class="ttc" id="a_exceptions_8hpp_xhtml"><div class="ttname"><a href="_exceptions_8hpp.xhtml">Exceptions.hpp</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_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#l00201">Tensor.hpp:201</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_abe8889e8150beef5fd204b2d87b49298"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">armnn::TensorInfo::SetShape</a></div><div class="ttdeci">void SetShape(const TensorShape &newShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00193">Tensor.hpp:193</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::BaseTensor::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00297">Tensor.hpp:297</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00319">Tensor.hpp:319</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_1_1_tensor_info_xhtml_a8bc11f1fa23ef42532f9fdd04d355270"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270">armnn::TensorInfo::GetQuantizationScales</a></div><div class="ttdeci">std::vector< float > GetQuantizationScales() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00451">Tensor.cpp:451</a></div></div> +<div class="ttc" id="a_types_8hpp_xhtml"><div class="ttname"><a href="_types_8hpp.xhtml">Types.hpp</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_1_1_base_tensor_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::BaseTensor::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00303">Tensor.hpp:303</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_aa81f67ac64f0c249e26499600c45d996"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aa81f67ac64f0c249e26499600c45d996">armnn::BaseTensor::GetMemoryArea</a></div><div class="ttdeci">MemoryType GetMemoryArea() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00305">Tensor.hpp:305</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_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="aclassarmnn_1_1_tensor_info_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00198">Tensor.hpp:198</a></div></div> +<div class="ttc" id="aclassarmnn_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="aclassarmnn_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#l00295">Tensor.hpp:295</a></div></div> +<div class="ttc" id="anamespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div><div class="ttdeci">@ info</div></div> +<div class="ttc" id="anamespacearmnn_xhtml_a280670a263dc4fd40491f6d0a2737f44"><div class="ttname"><a href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">armnn::BindingPointInfo</a></div><div class="ttdeci">std::pair< armnn::LayerBindingId, armnn::TensorInfo > BindingPointInfo</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00274">Tensor.hpp:274</a></div></div> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="navelem"><a class="el" href="dir_d44c64559bbebec7f509842c48db8b23.xhtml">include</a></li><li class="navelem"><a class="el" href="dir_2b72cc348e06937955e62ebdd8a13436.xhtml">armnn</a></li><li class="navelem"><a class="el" href="_tensor_8hpp.xhtml">Tensor.hpp</a></li> - <li 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