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<div class="title">TensorUtils.cpp</div> </div>
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<a href="_tensor_utils_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2017-2023 Arm Ltd. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160; </div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_utils_8hpp.html">armnnUtils/TensorUtils.hpp</a>&gt;</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160; </div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_exceptions_8hpp.html">armnn/Exceptions.hpp</a>&gt;</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160; </div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_tensor_handle_8hpp.html">armnn/backends/ITensorHandle.hpp</a>&gt;</span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_assert_8hpp.html">armnn/utility/Assert.hpp</a>&gt;</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_numeric_cast_8hpp.html">armnn/utility/NumericCast.hpp</a>&gt;</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160; </div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="preprocessor">#include &lt;fmt/format.h&gt;</span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160; </div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160; </div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn_utils.html">armnnUtils</a></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;{</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; </div>
<div class="line"><a name="l00021"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#ab53d94ea22b51c6bcdf9584644bd67bb"> 21</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> <a class="code" href="namespacearmnn_utils.html#ab53d94ea22b51c6bcdf9584644bd67bb">GetTensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfBatches,</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfChannels,</div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height,</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width,</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;{</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; {</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>:</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>({numberOfBatches, numberOfChannels, height, width});</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>:</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>({numberOfBatches, height, width, numberOfChannels});</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unknown data layout [&quot;</span></div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; + std::to_string(<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(dataLayout)) +</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="stringliteral">&quot;]&quot;</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; }</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;}</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; </div>
<div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#acee63cd08da47910fc166a1990988fa8"> 40</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> <a class="code" href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">GetTensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfBatches,</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfChannels,</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height,</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width,</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout,</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType)</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;{</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; {</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>:</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({numberOfBatches, numberOfChannels, height, width}, dataType);</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>:</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({numberOfBatches, height, width, numberOfChannels}, dataType);</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unknown data layout [&quot;</span></div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; + std::to_string(<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(dataLayout)) +</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="stringliteral">&quot;]&quot;</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; }</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160;}</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; </div>
<div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#aee5883b056e03a22db41b7b471fb598e"> 60</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> <a class="code" href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">GetTensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfBatches,</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfChannels,</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth,</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height,</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width,</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout,</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType)</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160;{</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; {</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a4dd0194b114cbf51da5b3a72569863ef">DataLayout::NDHWC</a>:</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({numberOfBatches, depth, height, width, numberOfChannels}, dataType);</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015">DataLayout::NCDHW</a>:</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({numberOfBatches, numberOfChannels, depth, height, width}, dataType);</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unknown data layout [&quot;</span></div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; + std::to_string(<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(dataLayout)) +</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="stringliteral">&quot;]&quot;</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; }</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160;}</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; </div>
<div class="line"><a name="l00081"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a1c9097ab13afc54b48c503c6487aaee1"> 81</a></span>&#160;std::pair&lt;float, float&gt; <a class="code" href="namespacearmnn_utils.html#a1c9097ab13afc54b48c503c6487aaee1">FindMinMax</a>(<a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* tensorHandle)</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;{</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keyword">auto</span> tensor_data = <span class="keyword">static_cast&lt;</span><span class="keyword">const </span><span class="keywordtype">float</span> *<span class="keyword">&gt;</span>(tensorHandle-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.html#a9afbc055a017adf1bc38ee137bca6e90">Map</a>(<span class="keyword">true</span>));</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="keyword">auto</span> tensor_size = tensorHandle-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.html#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>().<a class="code" href="classarmnn_1_1_tensor_shape.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>();</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; </div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="comment">// Set min/max initially to first value in tensor</span></div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keywordtype">float</span> min = tensor_data[0];</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <span class="keywordtype">float</span> max = tensor_data[0];</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; </div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="comment">// Loop over rest of tensor and update min/max if necessary</span></div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> val = 1; val &lt; tensor_size; val++)</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; {</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keywordflow">if</span> (tensor_data[val] &lt; min)</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; {</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; min = tensor_data[val];</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; }</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (tensor_data[val] &gt; max)</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; {</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; max = tensor_data[val];</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; }</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; }</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; </div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; tensorHandle-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.html#a563609828050f1b3a7868c23f3365923">Unmap</a>();</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; </div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <span class="keywordflow">return</span> std::make_pair(min, max);</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160;}</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; </div>
<div class="line"><a name="l00108"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a2bff2aae3ae824ff74ba550488373886"> 108</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> <a class="code" href="namespacearmnn_utils.html#a2bff2aae3ae824ff74ba550488373886">ReduceDims</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; tensorShape, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimensions)</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160;{</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordflow">if</span> (tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() &lt;= dimensions)</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; {</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="keywordflow">return</span> tensorShape;</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; }</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; std::vector&lt;unsigned int&gt; newShape;</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; </div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimsToSkip = tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() - dimensions;</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimsSkipped = 0;</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="keywordtype">bool</span> insertRemainder = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; </div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; {</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <span class="keywordflow">if</span> (tensorShape[i] == 1 &amp;&amp; dimsSkipped &lt; dimsToSkip &amp;&amp; !insertRemainder)</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; {</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; ++dimsSkipped;</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; }</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; newShape.push_back(tensorShape[i]);</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="comment">// Once we insert the first dimension we can&#39;t skip any more</span></div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; insertRemainder = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; }</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>(<span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(newShape.size()), newShape.data());</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160;}</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; </div>
<div class="line"><a name="l00134"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a29e9952fc973569b267d87b04ce372c2"> 134</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> <a class="code" href="namespacearmnn_utils.html#a2bff2aae3ae824ff74ba550488373886">ReduceDims</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; tensorInfo, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimensions)</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160;{</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> strippedTensor(tensorInfo);</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> strippedShape = <a class="code" href="namespacearmnn_utils.html#a2bff2aae3ae824ff74ba550488373886">ReduceDims</a>(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), dimensions);</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; strippedTensor.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(strippedShape);</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="keywordflow">return</span> strippedTensor;</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160;}</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; </div>
<div class="line"><a name="l00142"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a0d3b1be320610515e0cac8d745d9f8c2"> 142</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> <a class="code" href="namespacearmnn_utils.html#a0d3b1be320610515e0cac8d745d9f8c2">ExpandDims</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; tensorShape, <span class="keywordtype">int</span> axis)</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;{</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputDim = tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() + 1;</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; </div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <span class="keywordflow">if</span> (axis &lt; -armnn::numeric_cast&lt;int&gt;(outputDim) || axis &gt; armnn::numeric_cast&lt;int&gt;(tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()))</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; {</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(fmt::format(<span class="stringliteral">&quot;Invalid expansion axis {} for {}D input tensor. {}&quot;</span>,</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; axis,</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(),</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; }</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; </div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <span class="keywordflow">if</span> (axis &lt; 0)</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; {</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; axis = armnn::numeric_cast&lt;int&gt;(outputDim) + axis;</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; }</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; </div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; std::vector&lt;unsigned int&gt; outputShape;</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; outputShape.reserve(tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; {</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; outputShape.push_back(tensorShape[i]);</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; }</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; outputShape.insert(outputShape.begin() + axis, 1);</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; </div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; <span class="keywordflow">return</span> { outputDim, outputShape.data() };</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160;}</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; </div>
<div class="line"><a name="l00170"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a9ef6d3649c5d3aa16a9839e3e2ad659b"> 170</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> <a class="code" href="namespacearmnn_utils.html#a9ef6d3649c5d3aa16a9839e3e2ad659b">ExpandDimsToRank</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; tensorShape, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> rank)</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160;{</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; <span class="comment">// Can&#39;t expand if rank is smaller than current shape</span></div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; <span class="keywordflow">if</span> (tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() &gt;= rank)</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; {</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <span class="keywordflow">return</span> tensorShape;</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; }</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; </div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; std::vector&lt;unsigned int&gt; newShape;</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; </div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; <span class="comment">// First add 1s to the beginning of the tensorInfo to fill in the space</span></div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; rank - tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; {</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; newShape.push_back(1);</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; }</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; </div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; <span class="comment">// Then iterate through the original shape and append it to the new shape with the added 1s</span></div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160; {</div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; newShape.push_back(tensorShape[i]);</div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160; }</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; </div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>(<span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(newShape.size()), newShape.data());</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160;}</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; </div>
<div class="line"><a name="l00195"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#ac7f0575b4a8c9ba80c5b0695ada4dd92"> 195</a></span>&#160;std::vector&lt;unsigned int&gt; <a class="code" href="namespacearmnn_utils.html#ac7f0575b4a8c9ba80c5b0695ada4dd92">SqueezeDims</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; tensorShape)</div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160;{</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; std::vector&lt;unsigned int&gt; squeezedDims;</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; </div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; {</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; <span class="keywordflow">if</span> (tensorShape[i] != 1)</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; {</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; squeezedDims.push_back(tensorShape[i]);</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; }</div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; }</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; <span class="keywordflow">return</span> squeezedDims;</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160;}</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; </div>
<div class="line"><a name="l00209"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#af57864f5e03358d14c2988edae912b8b"> 209</a></span>&#160;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearmnn_utils.html#af57864f5e03358d14c2988edae912b8b">GetNumElementsBetween</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; shape,</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> firstAxisInclusive,</div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> lastAxisExclusive)</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160;{</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; <span class="keywordflow">if</span> (firstAxisInclusive &gt; lastAxisExclusive)</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; {</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(fmt::format(</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; <span class="stringliteral">&quot;GetNumElementsBetween: firstAxisInclusive [{}D] is greater than lastAxisExclusive [{}D]&quot;</span>,</div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; firstAxisInclusive,</div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; lastAxisExclusive));</div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; }</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; <span class="keywordflow">if</span> (lastAxisExclusive &gt; shape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>())</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; {</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(fmt::format(</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; <span class="stringliteral">&quot;{}: lastAxisExclusive [{}D] is greater than the number of dimensions of the tensor shape [{}D]&quot;</span></div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; <span class="stringliteral">&quot;GetNumElementsBetween&quot;</span>,</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; lastAxisExclusive,</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; shape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()));</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; }</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> count = 1;</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = firstAxisInclusive; i &lt; lastAxisExclusive; i++)</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; {</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; count *= shape[i];</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160; }</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; <span class="keywordflow">return</span> count;</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160;}</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; </div>
<div class="line"><a name="l00236"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#ac93cb1365b4bcb67df2a3164606096c5"> 236</a></span>&#160;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearmnn_utils.html#ac93cb1365b4bcb67df2a3164606096c5">GetUnsignedAxis</a>(<span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputDimension, <span class="keyword">const</span> <span class="keywordtype">int</span> axis)</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160;{</div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; <span class="keywordflow">if</span> (axis &gt;= armnn::numeric_cast&lt;int&gt;(inputDimension))</div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; {</div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(fmt::format(</div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; <span class="stringliteral">&quot;{}: axis index [{}] is not less than the number of dimensions [{}D]&quot;</span>,</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; <span class="stringliteral">&quot;GetUnsignedAxis&quot;</span>,</div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; axis,</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; inputDimension));</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; }</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; <span class="keywordflow">if</span> (axis &lt; -armnn::numeric_cast&lt;int&gt;(inputDimension))</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; {</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(fmt::format(</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; <span class="stringliteral">&quot;{}: axis index [{}] lower than the negative of the number of dimensions [{}]&quot;</span>,</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <span class="stringliteral">&quot;GetUnsignedAxis&quot;</span>,</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; axis,</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; -armnn::numeric_cast&lt;int&gt;(inputDimension)));</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; }</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; </div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> uAxis = axis &lt; 0 ?</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; inputDimension - armnn::numeric_cast&lt;unsigned int&gt;(<a class="code" href="structarmnn_1_1abs.html">abs</a>(axis))</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; : armnn::numeric_cast&lt;unsigned int&gt;(axis);</div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; <span class="keywordflow">return</span> uAxis;</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160;}</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; </div>
<div class="line"><a name="l00261"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a276aac5f7a8bdc3db4f62203870ca13b"> 261</a></span>&#160;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearmnn_utils.html#a276aac5f7a8bdc3db4f62203870ca13b">GetNumElementsAfter</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a>&amp; shape, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis)</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160;{</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDim = shape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; <span class="keywordflow">if</span> (axis &gt;= numDim)</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; {</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(fmt::format(</div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; <span class="stringliteral">&quot;{}: axis index [{}D] indexes beyond the number of dimesions of the tensor shape [{}D]&quot;</span>,</div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; <span class="stringliteral">&quot;GetNumElementsAfter&quot;</span>,</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; axis,</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; numDim));</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; }</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> count = 1;</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = axis+1; i &lt; numDim; i++)</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; {</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; count *= shape[i];</div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; }</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; <span class="keywordflow">return</span> count;</div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160;}</div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; </div>
<div class="line"><a name="l00280"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a1826e433f7e6817976a8175b4ef8296c"> 280</a></span>&#160;std::pair&lt;unsigned int, std::vector&lt;float&gt;&gt; <a class="code" href="namespacearmnn_utils.html#a1826e433f7e6817976a8175b4ef8296c">GetPerAxisParams</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>&amp; info)</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160;{</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; <span class="keyword">const</span> std::vector&lt;float&gt;&amp; scales = <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetQuantizationScales();</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; <a class="code" href="classarmnn_1_1_optional.html">armnn::Optional&lt;unsigned int&gt;</a> quantizationDim = <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetQuantizationDim();</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.HasPerAxisQuantization())</div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; {</div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(</div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; std::string(<span class="stringliteral">&quot;Per-axis quantization params not set for tensor of type &quot;</span>) +</div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; <a class="code" href="namespacearmnn.html#a81b5ff8545adad19a1c9d4ca076d552c">armnn::GetDataTypeName</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetDataType()), <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; }</div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axisFactor = <a class="code" href="namespacearmnn_utils.html#a276aac5f7a8bdc3db4f62203870ca13b">GetNumElementsAfter</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetShape(), quantizationDim.<a class="code" href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">value</a>()) ;</div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; </div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; <span class="keywordflow">return</span> { axisFactor, scales };</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160;}</div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; </div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> PrimitiveType&gt;</div>
<div class="line"><a name="l00296"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a7e3caf713986e36cff3ba9d9e442366c"> 296</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn_utils.html#a7e3caf713986e36cff3ba9d9e442366c">CheckSizes</a>(<span class="keyword">const</span> std::vector&lt;PrimitiveType&gt;&amp; data, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>&amp; tensorInfo, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size = 1)</div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160;{</div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; <span class="keywordflow">if</span> (data.size() / size != tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>())</div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; {</div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; fmt::format(<span class="stringliteral">&quot;The data does not contain the expected number of elements {} != {}. {}&quot;</span>,</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; data.size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(), <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; }</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160;}</div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; </div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> PrimitiveType&gt;</div>
<div class="line"><a name="l00307"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a573c6170ca8451709e031b6243bc187d"> 307</a></span>&#160;std::unique_ptr&lt;float[]&gt; <a class="code" href="namespacearmnn_utils.html#a573c6170ca8451709e031b6243bc187d">ToFloatArray</a>(<span class="keyword">const</span> std::vector&lt;PrimitiveType&gt;&amp; data, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>&amp; tensorInfo)</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160;{</div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; <a class="code" href="namespacearmnn_utils.html#a7e3caf713986e36cff3ba9d9e442366c">CheckSizes</a>(data, tensorInfo);</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; </div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; std::unique_ptr&lt;float[]&gt; returnBuffer(<span class="keyword">new</span> <span class="keywordtype">float</span>[tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>()]);</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160; </div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160; <span class="keywordflow">if</span> (tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#ab85cd8cc10c96a7c99c14042c251fc48">HasPerAxisQuantization</a>())</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; {</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis = tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b8fc85ce966c035d789cf22db5088a1">GetQuantizationDim</a>().<a class="code" href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">value</a>();</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; <span class="keyword">auto</span> axisDimensionality = tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[axis];</div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; <span class="keyword">auto</span> axisFactor = <a class="code" href="namespacearmnn_utils.html#a276aac5f7a8bdc3db4f62203870ca13b">armnnUtils::GetNumElementsAfter</a>(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), axis);</div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160; </div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(); ++i)</div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; {</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axisIndex;</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; </div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; <span class="keywordflow">if</span> (i &lt; axisFactor)</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; {</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160; axisIndex = 0;</div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; }</div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160; {</div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160; axisIndex = (i / axisFactor) % axisDimensionality;</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160; }</div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; returnBuffer[i] = Dequantize&lt;PrimitiveType&gt;(data[i],</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8bc11f1fa23ef42532f9fdd04d355270">GetQuantizationScales</a>()[axisIndex],</div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160; tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>());</div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; }</div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; }</div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; {</div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(); ++i)</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; {</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; returnBuffer[i] = Dequantize&lt;PrimitiveType&gt;(data[i],</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>(),</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>());</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; }</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; }</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160; <span class="keywordflow">return</span> returnBuffer;</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160;}</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160; </div>
<div class="line"><a name="l00348"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a949e191038ae0bfd9a0597a7de353a27"> 348</a></span>&#160;std::unique_ptr&lt;float[]&gt; <a class="code" href="namespacearmnn_utils.html#a573c6170ca8451709e031b6243bc187d">ToFloatArray</a>(<span class="keyword">const</span> std::vector&lt;uint8_t&gt;&amp; data, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>&amp; tensorInfo)</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160;{</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160; <span class="keywordflow">if</span> (tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">DataType::QAsymmS8</a> || tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>)</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160; {</div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>&#160; <a class="code" href="namespacearmnn_utils.html#a7e3caf713986e36cff3ba9d9e442366c">CheckSizes</a>(data, tensorInfo);</div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>&#160; std::vector&lt;int8_t&gt; buffer(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div>
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>&#160; ::memcpy(buffer.data(), data.data(), data.size());</div>
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>&#160; <span class="keywordflow">return</span> ToFloatArray&lt;int8_t&gt;(buffer, tensorInfo);</div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>&#160; }</div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>)</div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>&#160; {</div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160; <a class="code" href="namespacearmnn_utils.html#a7e3caf713986e36cff3ba9d9e442366c">CheckSizes</a>(data, tensorInfo);</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160; <span class="keywordflow">return</span> ToFloatArray&lt;uint8_t&gt;(data, tensorInfo);</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>&#160; }</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>)</div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>&#160; {</div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>&#160; <a class="code" href="namespacearmnn_utils.html#a7e3caf713986e36cff3ba9d9e442366c">CheckSizes</a>(data, tensorInfo, 4);</div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>&#160; std::vector&lt;int32_t&gt; buffer(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>&#160; ::memcpy(buffer.data(), data.data(), data.size());</div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>&#160; <span class="keywordflow">return</span> ToFloatArray&lt;int32_t&gt;(buffer, tensorInfo);</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>&#160; }</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d">DataType::Signed64</a>)</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>&#160; {</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>&#160; <a class="code" href="namespacearmnn_utils.html#a7e3caf713986e36cff3ba9d9e442366c">CheckSizes</a>(data, tensorInfo, 8);</div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>&#160; std::vector&lt;int64_t&gt; buffer(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>&#160; ::memcpy(buffer.data(), data.data(), data.size());</div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>&#160; <span class="keywordflow">return</span> ToFloatArray&lt;int64_t&gt;(buffer, tensorInfo);</div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>&#160; }</div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>&#160; fmt::format(<span class="stringliteral">&quot;Unsupported datatype {}. {}&quot;</span>,</div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>&#160; <a class="code" href="namespacearmnn.html#a81b5ff8545adad19a1c9d4ca076d552c">GetDataTypeName</a>(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>()),</div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>&#160; <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>&#160;}</div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>&#160; </div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>&#160;} <span class="comment">// namespace armnnUtils</span></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#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.html#l00198">Tensor.hpp:198</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_optional_html"><div class="ttname"><a href="classarmnn_1_1_optional.html">armnn::Optional&lt; unsigned int &gt;</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015">armnn::DataLayout::NCDHW</a></div><div class="ttdeci">@ NCDHW</div></div>
<div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00062">Types.hpp:62</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_ac7f0575b4a8c9ba80c5b0695ada4dd92"><div class="ttname"><a href="namespacearmnn_utils.html#ac7f0575b4a8c9ba80c5b0695ada4dd92">armnnUtils::SqueezeDims</a></div><div class="ttdeci">std::vector&lt; unsigned int &gt; SqueezeDims(const armnn::TensorShape &amp;tensorShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00195">TensorUtils.cpp:195</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8bc11f1fa23ef42532f9fdd04d355270"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8bc11f1fa23ef42532f9fdd04d355270">armnn::TensorInfo::GetQuantizationScales</a></div><div class="ttdeci">std::vector&lt; float &gt; GetQuantizationScales() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00451">Tensor.cpp:451</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div><div class="ttdeci">@ NHWC</div></div>
<div class="ttc" id="anamespacearmnn_utils_html_ac93cb1365b4bcb67df2a3164606096c5"><div class="ttname"><a href="namespacearmnn_utils.html#ac93cb1365b4bcb67df2a3164606096c5">armnnUtils::GetUnsignedAxis</a></div><div class="ttdeci">unsigned int GetUnsignedAxis(const unsigned int inputDimension, const int axis)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00236">TensorUtils.cpp:236</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00461">Tensor.cpp:461</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_a9ef6d3649c5d3aa16a9839e3e2ad659b"><div class="ttname"><a href="namespacearmnn_utils.html#a9ef6d3649c5d3aa16a9839e3e2ad659b">armnnUtils::ExpandDimsToRank</a></div><div class="ttdeci">armnn::TensorShape ExpandDimsToRank(const armnn::TensorShape &amp;tensorShape, unsigned int rank)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00170">TensorUtils.cpp:170</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a81b5ff8545adad19a1c9d4ca076d552c"><div class="ttname"><a href="namespacearmnn.html#a81b5ff8545adad19a1c9d4ca076d552c">armnn::GetDataTypeName</a></div><div class="ttdeci">constexpr const char * GetDataTypeName(DataType dataType)</div><div class="ttdef"><b>Definition:</b> <a href="_types_utils_8hpp_source.html#l00233">TypesUtils.hpp:233</a></div></div>
<div class="ttc" id="a_exceptions_8hpp_html_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00203">Exceptions.hpp:203</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html">armnn::ITensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_handle_8hpp_source.html#l00016">ITensorHandle.hpp:16</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html_affd5aae75cad90f472f96cfd25a13f29"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html#affd5aae75cad90f472f96cfd25a13f29">armnn::ITensorHandle::GetShape</a></div><div class="ttdeci">virtual TensorShape GetShape() const =0</div><div class="ttdoc">Get the number of elements for each dimension ordered from slowest iterating dimension to fastest ite...</div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div><div class="ttdeci">@ QAsymmU8</div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div><div class="ttdeci">@ QSymmS8</div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_ab85cd8cc10c96a7c99c14042c251fc48"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#ab85cd8cc10c96a7c99c14042c251fc48">armnn::TensorInfo::HasPerAxisQuantization</a></div><div class="ttdeci">bool HasPerAxisQuantization() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00446">Tensor.cpp:446</a></div></div>
<div class="ttc" id="a_numeric_cast_8hpp_html"><div class="ttname"><a href="_numeric_cast_8hpp.html">NumericCast.hpp</a></div></div>
<div class="ttc" id="a_tensor_utils_8hpp_html"><div class="ttname"><a href="_tensor_utils_8hpp.html">TensorUtils.hpp</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_a1826e433f7e6817976a8175b4ef8296c"><div class="ttname"><a href="namespacearmnn_utils.html#a1826e433f7e6817976a8175b4ef8296c">armnnUtils::GetPerAxisParams</a></div><div class="ttdeci">std::pair&lt; unsigned int, std::vector&lt; float &gt; &gt; GetPerAxisParams(const armnn::TensorInfo &amp;info)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00280">TensorUtils.cpp:280</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a4dd0194b114cbf51da5b3a72569863ef"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a4dd0194b114cbf51da5b3a72569863ef">armnn::DataLayout::NDHWC</a></div><div class="ttdeci">@ NDHWC</div></div>
<div class="ttc" id="a_assert_8hpp_html"><div class="ttname"><a href="_assert_8hpp.html">Assert.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="a_i_tensor_handle_8hpp_html"><div class="ttname"><a href="_i_tensor_handle_8hpp.html">ITensorHandle.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html#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.html#l00174">Tensor.cpp:174</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8b8fc85ce966c035d789cf22db5088a1"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8b8fc85ce966c035d789cf22db5088a1">armnn::TensorInfo::GetQuantizationDim</a></div><div class="ttdeci">Optional&lt; unsigned int &gt; GetQuantizationDim() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00498">Tensor.cpp:498</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00048">Types.hpp:48</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html"><div class="ttname"><a href="namespacearmnn_utils.html">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_compatible_types_8hpp_source.html#l00010">CompatibleTypes.hpp:10</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_invalid_argument_exception_html"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00080">Exceptions.hpp:80</a></div></div>
<div class="ttc" id="anamespacearmnn_html_aa815fde54f6d8e8aa5b4f0301cf4178b"><div class="ttname"><a href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">armnn::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo(const ITensorHandle *tensorHandle)</div><div class="ttdoc">float32 helpers</div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.html#l00033">RefWorkloadUtils.hpp:33</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_a0d3b1be320610515e0cac8d745d9f8c2"><div class="ttname"><a href="namespacearmnn_utils.html#a0d3b1be320610515e0cac8d745d9f8c2">armnnUtils::ExpandDims</a></div><div class="ttdeci">armnn::TensorShape ExpandDims(const armnn::TensorShape &amp;tensorShape, int axis)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00142">TensorUtils.cpp:142</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html_a563609828050f1b3a7868c23f3365923"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html#a563609828050f1b3a7868c23f3365923">armnn::ITensorHandle::Unmap</a></div><div class="ttdeci">virtual void Unmap() const =0</div><div class="ttdoc">Unmap the tensor data.</div></div>
<div class="ttc" id="anamespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div><div class="ttdeci">@ info</div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00200">Tensor.hpp:200</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div><div class="ttdeci">@ Signed32</div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div><div class="ttdeci">@ QAsymmS8</div></div>
<div class="ttc" id="anamespacearmnn_utils_html_af57864f5e03358d14c2988edae912b8b"><div class="ttname"><a href="namespacearmnn_utils.html#af57864f5e03358d14c2988edae912b8b">armnnUtils::GetNumElementsBetween</a></div><div class="ttdeci">unsigned int GetNumElementsBetween(const armnn::TensorShape &amp;shape, unsigned int firstAxisInclusive, unsigned int lastAxisExclusive)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00209">TensorUtils.cpp:209</a></div></div>
<div class="ttc" id="astructarmnn_1_1abs_html"><div class="ttname"><a href="structarmnn_1_1abs.html">armnn::abs</a></div><div class="ttdef"><b>Definition:</b> <a href="_abs_8hpp_source.html#l00013">Abs.hpp:13</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape &amp; GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00193">Tensor.hpp:193</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_a7e3caf713986e36cff3ba9d9e442366c"><div class="ttname"><a href="namespacearmnn_utils.html#a7e3caf713986e36cff3ba9d9e442366c">armnnUtils::CheckSizes</a></div><div class="ttdeci">void CheckSizes(const std::vector&lt; PrimitiveType &gt; &amp;data, const armnn::TensorInfo &amp;tensorInfo, unsigned int size=1)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00296">TensorUtils.cpp:296</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_a276aac5f7a8bdc3db4f62203870ca13b"><div class="ttname"><a href="namespacearmnn_utils.html#a276aac5f7a8bdc3db4f62203870ca13b">armnnUtils::GetNumElementsAfter</a></div><div class="ttdeci">unsigned int GetNumElementsAfter(const armnn::TensorShape &amp;shape, unsigned int axis)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00261">TensorUtils.cpp:261</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_abe8889e8150beef5fd204b2d87b49298"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">armnn::TensorInfo::SetShape</a></div><div class="ttdeci">void SetShape(const TensorShape &amp;newShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00195">Tensor.hpp:195</a></div></div>
<div class="ttc" id="a_exceptions_8hpp_html"><div class="ttname"><a href="_exceptions_8hpp.html">Exceptions.hpp</a></div></div>
<div class="ttc" id="anamespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">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.html#l00006">01_00_quick_start.dox:6</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_a1c9097ab13afc54b48c503c6487aaee1"><div class="ttname"><a href="namespacearmnn_utils.html#a1c9097ab13afc54b48c503c6487aaee1">armnnUtils::FindMinMax</a></div><div class="ttdeci">std::pair&lt; float, float &gt; FindMinMax(armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00081">TensorUtils.cpp:81</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_a2bff2aae3ae824ff74ba550488373886"><div class="ttname"><a href="namespacearmnn_utils.html#a2bff2aae3ae824ff74ba550488373886">armnnUtils::ReduceDims</a></div><div class="ttdeci">armnn::TensorShape ReduceDims(const armnn::TensorShape &amp;tensorInfo, unsigned int dimensions)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00108">TensorUtils.cpp:108</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d">armnn::DataType::Signed64</a></div><div class="ttdeci">@ Signed64</div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#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.html#l00482">Tensor.cpp:482</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_a573c6170ca8451709e031b6243bc187d"><div class="ttname"><a href="namespacearmnn_utils.html#a573c6170ca8451709e031b6243bc187d">armnnUtils::ToFloatArray</a></div><div class="ttdeci">std::unique_ptr&lt; float[]&gt; ToFloatArray(const std::vector&lt; PrimitiveType &gt; &amp;data, const armnn::TensorInfo &amp;tensorInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00307">TensorUtils.cpp:307</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_ab53d94ea22b51c6bcdf9584644bd67bb"><div class="ttname"><a href="namespacearmnn_utils.html#ab53d94ea22b51c6bcdf9584644bd67bb">armnnUtils::GetTensorShape</a></div><div class="ttdeci">armnn::TensorShape GetTensorShape(unsigned int numberOfBatches, unsigned int numberOfChannels, unsigned int height, unsigned int width, const armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00021">TensorUtils.cpp:21</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_html_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html#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.html#l00181">Tensor.cpp:181</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_optional_reference_switch_html_a77c7d528ac063d870b8c8426ec81c1c3"><div class="ttname"><a href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">armnn::OptionalReferenceSwitch::value</a></div><div class="ttdeci">const T &amp; value() const</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00146">Optional.hpp:146</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div><div class="ttdeci">@ NCHW</div></div>
<div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html_a9afbc055a017adf1bc38ee137bca6e90"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html#a9afbc055a017adf1bc38ee137bca6e90">armnn::ITensorHandle::Map</a></div><div class="ttdeci">virtual const void * Map(bool blocking=true) const =0</div><div class="ttdoc">Map the tensor data for access.</div></div>
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