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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> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include <<a class="code" href="_tensor_utils_8hpp.html">armnnUtils/TensorUtils.hpp</a>></span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="include_2armnn_2backends_2_i_tensor_handle_8hpp.html">armnn/backends/ITensorHandle.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <boost/assert.hpp></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <boost/format.hpp></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <boost/numeric/conversion/cast.hpp></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn_utils.html">armnnUtils</a></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> {</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#ab53d94ea22b51c6bcdf9584644bd67bb"> 19</a></span> <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="l00020"></a><span class="lineno"> 20</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfChannels,</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height,</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> {</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  {</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>:</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <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="l00029"></a><span class="lineno"> 29</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>:</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <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="l00031"></a><span class="lineno"> 31</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"Unknown data layout ["</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  + std::to_string(static_cast<int>(dataLayout)) +</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="stringliteral">"]"</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  }</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> }</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div><div class="line"><a name="l00038"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#acee63cd08da47910fc166a1990988fa8"> 38</a></span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> <a class="code" href="namespacearmnn.html#a93d269806f34407695dc10f510001c30">GetTensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfBatches,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numberOfChannels,</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height,</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width,</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout,</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType)</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> {</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>:</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <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="l00049"></a><span class="lineno"> 49</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>:</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <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="l00051"></a><span class="lineno"> 51</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"Unknown data layout ["</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  + std::to_string(static_cast<int>(dataLayout)) +</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="stringliteral">"]"</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> }</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a1c9097ab13afc54b48c503c6487aaee1"> 58</a></span> std::pair<float, float> <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="l00059"></a><span class="lineno"> 59</span> {</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keyword">auto</span> tensor_data = <span class="keyword">static_cast<</span><span class="keyword">const </span><span class="keywordtype">float</span> *<span class="keyword">></span>(tensorHandle-><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="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">auto</span> tensor_size = tensorHandle-><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="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// Set min/max initially to first value in tensor</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordtype">float</span> min = tensor_data[0];</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordtype">float</span> max = tensor_data[0];</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="comment">// Loop over rest of tensor and update min/max if necessary</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> val = 1; val < tensor_size; val++)</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  {</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordflow">if</span> (tensor_data[val] < min)</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  {</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  min = tensor_data[val];</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  }</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (tensor_data[val] > max)</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  {</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  max = tensor_data[val];</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  }</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  }</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  tensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a563609828050f1b3a7868c23f3365923">Unmap</a>();</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordflow">return</span> std::make_pair(min, max);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> }</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a0d3b1be320610515e0cac8d745d9f8c2"> 85</a></span> <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>& tensorShape, <span class="keywordtype">int</span> axis)</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> {</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <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="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordflow">if</span> (axis < -boost::numeric_cast<int>(outputDim) || axis > boost::numeric_cast<int>(tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()))</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  {</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  boost::str(boost::format(<span class="stringliteral">"Invalid expansion axis %1% for %2%D input tensor. %3%"</span>) %</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  axis %</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() %</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  }</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> </div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">if</span> (axis < 0)</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  {</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  axis = boost::numeric_cast<<span class="keywordtype">int</span>>(outputDim) + axis;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  }</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  std::vector<unsigned int> outputShape;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  {</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  outputShape.push_back(tensorShape[i]);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  }</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  outputShape.insert(outputShape.begin() + axis, 1);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>(outputDim, outputShape.data());</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> }</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#af57864f5e03358d14c2988edae912b8b"> 113</a></span> <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>& shape,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> firstAxisInclusive,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> lastAxisExclusive)</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>  BOOST_ASSERT(firstAxisInclusive <= lastAxisExclusive);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  BOOST_ASSERT(lastAxisExclusive <= shape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> count = 1;</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = firstAxisInclusive; i < lastAxisExclusive; i++)</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  {</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  count *= shape[i];</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  }</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keywordflow">return</span> count;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> }</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> </div><div class="line"><a name="l00127"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#ac93cb1365b4bcb67df2a3164606096c5"> 127</a></span> <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="l00128"></a><span class="lineno"> 128</span> {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  BOOST_ASSERT_MSG(axis < boost::numeric_cast<int>(inputDimension),</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="stringliteral">"Required axis index greater than number of dimensions."</span>);</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  BOOST_ASSERT_MSG(axis >= -boost::numeric_cast<int>(inputDimension),</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="stringliteral">"Required axis index lower than negative of the number of dimensions"</span>);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> uAxis = axis < 0 ?</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  inputDimension - boost::numeric_cast<<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(<a class="code" href="structarmnn_1_1abs.html">abs</a>(axis))</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  : boost::numeric_cast<unsigned int>(axis);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keywordflow">return</span> uAxis;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> }</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"><a class="line" href="namespacearmnn_utils.html#a276aac5f7a8bdc3db4f62203870ca13b"> 140</a></span> <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>& shape, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis)</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> {</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <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="l00143"></a><span class="lineno"> 143</span>  BOOST_ASSERT(axis <= numDim - 1);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> count = 1;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = axis; i < numDim; i++)</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  {</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  count *= shape[i];</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  }</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">return</span> count;</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="namespacearmnn_utils.html#a1826e433f7e6817976a8175b4ef8296c"> 152</a></span> std::pair<unsigned int, std::vector<float>> <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>& <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</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">const</span> std::vector<float>& scales = info.<a class="code" href="classarmnn_1_1_tensor_info.html#a8bc11f1fa23ef42532f9fdd04d355270">GetQuantizationScales</a>();</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="classarmnn_1_1_optional.html">armnn::Optional<unsigned int></a> quantizationDim = info.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b8fc85ce966c035d789cf22db5088a1">GetQuantizationDim</a>();</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keywordflow">if</span> (!info.<a class="code" href="classarmnn_1_1_tensor_info.html#ab85cd8cc10c96a7c99c14042c251fc48">HasPerAxisQuantization</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>  <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="l00159"></a><span class="lineno"> 159</span>  std::string(<span class="stringliteral">"Per-axis quantization params not set for tensor of type "</span>) +</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <a class="code" href="namespacearmnn.html#a81b5ff8545adad19a1c9d4ca076d552c">armnn::GetDataTypeName</a>(info.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>()), <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  }</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axisFactor = <a class="code" href="namespacearmnn_utils.html#a276aac5f7a8bdc3db4f62203870ca13b">GetNumElementsAfter</a>(info.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), quantizationDim.<a class="code" href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">value</a>());</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>  <span class="keywordflow">return</span> { axisFactor, scales };</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> }</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> } <span class="comment">// namespace armnnUtils</span></div><div class="ttc" id="namespacearmnn_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#l00019">TensorUtils.cpp:19</a></div></div>
+<div class="ttc" id="classarmnn_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#l00232">Tensor.cpp:232</a></div></div>
+<div class="ttc" id="classarmnn_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="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00043">Tensor.hpp:43</a></div></div>
+<div class="ttc" id="namespacearmnn_utils_html_a1c9097ab13afc54b48c503c6487aaee1"><div class="ttname"><a href="namespacearmnn_utils.html#a1c9097ab13afc54b48c503c6487aaee1">armnnUtils::FindMinMax</a></div><div class="ttdeci">std::pair< float, float > FindMinMax(armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00058">TensorUtils.cpp:58</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div>
+<div class="ttc" id="namespacearmnn_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#l00127">TensorUtils.cpp:127</a></div></div>
+<div class="ttc" id="classarmnn_1_1_optional_html"><div class="ttname"><a href="classarmnn_1_1_optional.html">armnn::Optional< unsigned int ></a></div></div>
+<div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
+<div class="ttc" id="classarmnn_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#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="_tensor_utils_8hpp_html"><div class="ttname"><a href="_tensor_utils_8hpp.html">TensorUtils.hpp</a></div></div>
+<div class="ttc" id="classarmnn_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>
+<div class="ttc" id="include_2armnn_2backends_2_i_tensor_handle_8hpp_html"><div class="ttname"><a href="include_2armnn_2backends_2_i_tensor_handle_8hpp.html">ITensorHandle.hpp</a></div></div>
+<div class="ttc" id="classarmnn_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="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.html#l00016">ITensorHandle.hpp:16</a></div></div>
+<div class="ttc" id="_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#l00169">Exceptions.hpp:169</a></div></div>
+<div class="ttc" id="classarmnn_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="classarmnn_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>
+<div class="ttc" id="namespacearmnn_utils_html"><div class="ttname"><a href="namespacearmnn_utils.html">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00013">DataLayoutIndexed.hpp:13</a></div></div>
+<div class="ttc" id="classarmnn_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< unsigned int > GetQuantizationDim() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00280">Tensor.cpp:280</a></div></div>
+<div class="ttc" id="namespacearmnn_utils_html_a1826e433f7e6817976a8175b4ef8296c"><div class="ttname"><a href="namespacearmnn_utils.html#a1826e433f7e6817976a8175b4ef8296c">armnnUtils::GetPerAxisParams</a></div><div class="ttdeci">std::pair< unsigned int, std::vector< float > > GetPerAxisParams(const armnn::TensorInfo &info)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00152">TensorUtils.cpp:152</a></div></div>
+<div class="ttc" id="namespacearmnn_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 &tensorShape, int axis)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00085">TensorUtils.cpp:85</a></div></div>
+<div class="ttc" id="classarmnn_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="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00106">Tensor.cpp:106</a></div></div>
+<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
+<div class="ttc" id="classarmnn_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< float > GetQuantizationScales() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00237">Tensor.cpp:237</a></div></div>
+<div class="ttc" id="classarmnn_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="structarmnn_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="namespacearmnn_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#l00048">Types.hpp:48</a></div></div>
+<div class="ttc" id="namespacearmnn_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#l00032">Types.hpp:32</a></div></div>
+<div class="ttc" id="classarmnn_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="classarmnn_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#l00095">Tensor.hpp:95</a></div></div>
+<div class="ttc" id="namespacearmnn_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 &shape, unsigned int firstAxisInclusive, unsigned int lastAxisExclusive)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.html#l00113">TensorUtils.cpp:113</a></div></div>
+<div class="ttc" id="classarmnn_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 & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00088">Tensor.hpp:88</a></div></div>
+<div class="ttc" id="namespacearmnn_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#l00165">TypesUtils.hpp:165</a></div></div>
+<div class="ttc" id="namespacearmnn_html_a93d269806f34407695dc10f510001c30"><div class="ttname"><a href="namespacearmnn.html#a93d269806f34407695dc10f510001c30">armnn::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & 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#l00025">RefWorkloadUtils.hpp:25</a></div></div>
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