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<a href="_tensor_helpers_8hpp.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> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include <<a class="code" href="_tensor_8hpp.html">armnn/Tensor.hpp</a>></span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_quantize_helper_8hpp.html">QuantizeHelper.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <boost/assert.hpp></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <boost/multi_array.hpp></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <boost/numeric/conversion/cast.hpp></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <boost/random/uniform_real_distribution.hpp></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <boost/random/mersenne_twister.hpp></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <boost/test/tools/floating_point_comparison.hpp></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <array></span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <cmath></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"><a class="line" href="_tensor_helpers_8hpp.html#a1ed60e4e5a0ec57f6483904e11fbd781"> 23</a></span> constexpr <span class="keywordtype">float</span> <a class="code" href="_tensor_helpers_8hpp.html#a1ed60e4e5a0ec57f6483904e11fbd781">g_FloatCloseToZeroTolerance</a> = 1.0e-6f;</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="keyword">template</span><<span class="keyword">typename</span> T, <span class="keywordtype">bool</span> isQuantized = true></div><div class="line"><a name="l00026"></a><span class="lineno"><a class="line" href="struct_selective_comparer.html"> 26</a></span> <span class="keyword">struct </span><a class="code" href="struct_selective_comparer.html">SelectiveComparer</a></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> {</div><div class="line"><a name="l00028"></a><span class="lineno"><a class="line" href="struct_selective_comparer.html#adeb6209a190d5004061266b1f8e31bae"> 28</a></span>  <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="struct_selective_comparer.html#adeb6209a190d5004061266b1f8e31bae">Compare</a>(T a, T b)</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  {</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keywordflow">return</span> (std::max(a, b) - std::min(a, b)) <= 1;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  }</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> };</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword">template</span><<span class="keyword">typename</span> T></div><div class="line"><a name="l00036"></a><span class="lineno"><a class="line" href="struct_selective_comparer_3_01_t_00_01false_01_4.html"> 36</a></span> <span class="keyword">struct </span><a class="code" href="struct_selective_comparer.html">SelectiveComparer</a><T, <a class="code" href="_cl_layer_tests_8cpp.html#a67e2647a90dec71bb79c8b38872ba570">false</a>></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"><a class="line" href="struct_selective_comparer_3_01_t_00_01false_01_4.html#adeb6209a190d5004061266b1f8e31bae"> 38</a></span>  <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="struct_selective_comparer_3_01_t_00_01false_01_4.html#adeb6209a190d5004061266b1f8e31bae">Compare</a>(T a, T b)</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  {</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="comment">// If a or b is zero, percent_tolerance does an exact match, so compare to a small, constant tolerance instead.</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordflow">if</span> (a == 0.0f || b == 0.0f)</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  {</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordflow">return</span> std::abs(a - b) <= <a class="code" href="_tensor_helpers_8hpp.html#a1ed60e4e5a0ec57f6483904e11fbd781">g_FloatCloseToZeroTolerance</a>;</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> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordflow">if</span> (std::isinf(a) && a == b)</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  {</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  }</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordflow">if</span> (std::isnan(a) && std::isnan(b))</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  }</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// For unquantized floats we use a tolerance of 1%.</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  boost::math::fpc::close_at_tolerance<float> comparer(boost::math::fpc::percent_tolerance(1.0f));</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordflow">return</span> comparer(a, b);</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> };</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="keyword">template</span><<span class="keyword">typename</span> T></div><div class="line"><a name="l00063"></a><span class="lineno"><a class="line" href="_tensor_helpers_8hpp.html#a833e7db5d5f7e93102e80de57a602cf7"> 63</a></span> <span class="keywordtype">bool</span> <a class="code" href="_tensor_helpers_8hpp.html#a833e7db5d5f7e93102e80de57a602cf7">SelectiveCompare</a>(T a, T b)</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> {</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">return</span> <a class="code" href="struct_selective_comparer.html">SelectiveComparer<T, armnn::IsQuantizedType<T></a>()>::<a class="code" href="struct_selective_comparer.html#adeb6209a190d5004061266b1f8e31bae">Compare</a>(a, b);</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> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="keyword">template</span><<span class="keyword">typename</span> T></div><div class="line"><a name="l00069"></a><span class="lineno"><a class="line" href="_tensor_helpers_8hpp.html#a617427516e17888a138c16d3af503cfd"> 69</a></span> <span class="keywordtype">bool</span> <a class="code" href="_tensor_helpers_8hpp.html#a617427516e17888a138c16d3af503cfd">SelectiveCompareBoolean</a>(T a, T b)</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> {</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordflow">return</span> (((a == 0) && (b == 0)) || ((a != 0) && (b != 0)));</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> };</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, std::<span class="keywordtype">size_t</span> n></div><div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="_tensor_helpers_8hpp.html#a0b8fbb443d2cf34a41f6aaae934e3dcb"> 75</a></span> boost::test_tools::predicate_result <a class="code" href="_tensor_helpers_8hpp.html#a0b8fbb443d2cf34a41f6aaae934e3dcb">CompareTensors</a>(<span class="keyword">const</span> boost::multi_array<T, n>& a,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keyword">const</span> boost::multi_array<T, n>& b,</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keywordtype">bool</span> compareBoolean = <span class="keyword">false</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>  <span class="comment">// Checks they are same shape.</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<n; i++)</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">if</span> (a.shape()[i] != b.shape()[i])</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>  boost::test_tools::predicate_result res(<span class="keyword">false</span>);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  res.message() << <span class="stringliteral">"Different shapes ["</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  << a.shape()[i]</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  << <span class="stringliteral">"!="</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  << b.shape()[i]</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  << <span class="stringliteral">"]"</span>;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keywordflow">return</span> res;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  }</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="comment">// Now compares element-wise.</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="comment">// Fun iteration over n dimensions.</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  std::array<unsigned int, n> indices;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < n; i++)</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>  indices[i] = 0;</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::stringstream errorString;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordtype">int</span> numFailedElements = 0;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  constexpr <span class="keywordtype">int</span> maxReportedDifferences = 3;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordflow">while</span> (<span class="keyword">true</span>)</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  {</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordtype">bool</span> comparison;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// As true for uint8_t is non-zero (1-255) we must have a dedicated compare for Booleans.</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordflow">if</span>(compareBoolean)</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  comparison = <a class="code" href="_tensor_helpers_8hpp.html#a617427516e17888a138c16d3af503cfd">SelectiveCompareBoolean</a>(a(indices), b(indices));</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  }</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  comparison = <a class="code" href="_tensor_helpers_8hpp.html#a833e7db5d5f7e93102e80de57a602cf7">SelectiveCompare</a>(a(indices), b(indices));</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  }</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keywordflow">if</span> (!comparison)</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>  ++numFailedElements;</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">if</span> (numFailedElements <= maxReportedDifferences)</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>  <span class="keywordflow">if</span> (numFailedElements >= 2)</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  {</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  errorString << <span class="stringliteral">", "</span>;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  }</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  errorString << <span class="stringliteral">"["</span>;</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < n; ++i)</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  {</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  errorString << indices[i];</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordflow">if</span> (i != n - 1)</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  errorString << <span class="stringliteral">","</span>;</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  }</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>  errorString << <span class="stringliteral">"]"</span>;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  errorString << <span class="stringliteral">" ("</span> << +a(indices) << <span class="stringliteral">" != "</span> << +b(indices) << <span class="stringliteral">")"</span>;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  }</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  }</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  ++indices[n - 1];</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=n-1; i>0; i--)</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  {</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="keywordflow">if</span> (indices[i] == a.shape()[i])</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  {</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  indices[i] = 0;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  ++indices[i - 1];</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  }</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> </div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">if</span> (indices[0] == a.shape()[0])</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  {</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  }</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  }</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  boost::test_tools::predicate_result comparisonResult(<span class="keyword">true</span>);</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keywordflow">if</span> (numFailedElements > 0)</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>  comparisonResult = <span class="keyword">false</span>;</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  comparisonResult.message() << numFailedElements << <span class="stringliteral">" different values at: "</span>;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keywordflow">if</span> (numFailedElements > maxReportedDifferences)</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  {</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  errorString << <span class="stringliteral">", ... (and "</span> << (numFailedElements - maxReportedDifferences) << <span class="stringliteral">" other differences)"</span>;</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  }</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  comparisonResult.message() << errorString.str();</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  }</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">return</span> comparisonResult;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> }</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> <span class="comment">// Creates a boost::multi_array with the shape defined by the given TensorInfo.</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, std::<span class="keywordtype">size_t</span> n></div><div class="line"><a name="l00179"></a><span class="lineno"><a class="line" href="_tensor_helpers_8hpp.html#a9c063a8b0e52737d20184cd36dcf483e"> 179</a></span> boost::multi_array<T, n> <a class="code" href="_tensor_helpers_8hpp.html#a9c063a8b0e52737d20184cd36dcf483e">MakeTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& tensorInfo)</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> {</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  std::array<unsigned int, n> shape;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < n; i++)</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  {</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  shape[i] = tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[i];</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  }</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordflow">return</span> boost::multi_array<T, n>(shape);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> }</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="comment">// Creates a boost::multi_array with the shape defined by the given TensorInfo and contents defined by the given vector.</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, std::<span class="keywordtype">size_t</span> n></div><div class="line"><a name="l00193"></a><span class="lineno"><a class="line" href="_tensor_helpers_8hpp.html#aca9db6ac279d665c182b8bc1be743d4b"> 193</a></span> boost::multi_array<T, n> <a class="code" href="_tensor_helpers_8hpp.html#a9c063a8b0e52737d20184cd36dcf483e">MakeTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& tensorInfo, <span class="keyword">const</span> std::vector<T>& flat)</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> {</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  BOOST_ASSERT_MSG(flat.size() == tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(), <span class="stringliteral">"Wrong number of components supplied to tensor"</span>);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  std::array<unsigned int, n> shape;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> </div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="comment">// NOTE: tensorInfo.GetNumDimensions() might be different from n</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> returnDimensions = <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(n);</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> actualDimensions = tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paddedDimensions =</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  returnDimensions > actualDimensions ? returnDimensions - actualDimensions : 0u;</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> </div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < returnDimensions; i++)</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  {</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordflow">if</span> (i < paddedDimensions)</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  {</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  shape[i] = 1u;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  }</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  {</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  shape[i] = tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[i - paddedDimensions];</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  }</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  }</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> </div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  boost::const_multi_array_ref<T, n> arrayRef(&flat[0], shape);</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordflow">return</span> boost::multi_array<T, n>(arrayRef);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> }</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> </div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, std::<span class="keywordtype">size_t</span> n></div><div class="line"><a name="l00223"></a><span class="lineno"><a class="line" href="_tensor_helpers_8hpp.html#a1268c19758dd636d0da80d16d2a4f2f4"> 223</a></span> boost::multi_array<T, n> <a class="code" href="_tensor_helpers_8hpp.html#a1268c19758dd636d0da80d16d2a4f2f4">MakeRandomTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& tensorInfo,</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> seed,</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordtype">float</span> min = -10.0f,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="keywordtype">float</span> max = 10.0f)</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> {</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  boost::random::mt19937 gen(seed);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  boost::random::uniform_real_distribution<float> dist(min, max);</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> </div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  std::vector<float> init(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < init.size(); i++)</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  {</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  init[i] = dist(gen);</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  }</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> qScale = tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>();</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="keyword">const</span> int32_t qOffset = tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>();</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <span class="keywordflow">return</span> MakeTensor<T, n>(tensorInfo, armnnUtils::QuantizedVector<T>(init, qScale, qOffset));</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> }</div><div class="ttc" id="classarmnn_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#l00264">Tensor.cpp:264</a></div></div>
<div class="ttc" id="struct_selective_comparer_3_01_t_00_01false_01_4_html_adeb6209a190d5004061266b1f8e31bae"><div class="ttname"><a href="struct_selective_comparer_3_01_t_00_01false_01_4.html#adeb6209a190d5004061266b1f8e31bae">SelectiveComparer< T, false >::Compare</a></div><div class="ttdeci">static bool Compare(T a, T b)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.html#l00038">TensorHelpers.hpp:38</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00092">Tensor.hpp:92</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="_cl_layer_tests_8cpp_html_a67e2647a90dec71bb79c8b38872ba570"><div class="ttname"><a href="_cl_layer_tests_8cpp.html#a67e2647a90dec71bb79c8b38872ba570">false</a></div><div class="ttdeci">DataLayout::NHWC false</div><div class="ttdef"><b>Definition:</b> <a href="_cl_layer_tests_8cpp_source.html#l00103">ClLayerTests.cpp:103</a></div></div>
<div class="ttc" id="struct_selective_comparer_html_adeb6209a190d5004061266b1f8e31bae"><div class="ttname"><a href="struct_selective_comparer.html#adeb6209a190d5004061266b1f8e31bae">SelectiveComparer::Compare</a></div><div class="ttdeci">static bool Compare(T a, T b)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.html#l00028">TensorHelpers.hpp:28</a></div></div>
<div class="ttc" id="_quantize_helper_8hpp_html"><div class="ttname"><a href="_quantize_helper_8hpp.html">QuantizeHelper.hpp</a></div></div>
<div class="ttc" id="_tensor_helpers_8hpp_html_a1268c19758dd636d0da80d16d2a4f2f4"><div class="ttname"><a href="_tensor_helpers_8hpp.html#a1268c19758dd636d0da80d16d2a4f2f4">MakeRandomTensor</a></div><div class="ttdeci">boost::multi_array< T, n > MakeRandomTensor(const armnn::TensorInfo &tensorInfo, unsigned int seed, float min=-10.0f, float max=10.0f)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.html#l00223">TensorHelpers.hpp:223</a></div></div>
<div class="ttc" id="_tensor_helpers_8hpp_html_a1ed60e4e5a0ec57f6483904e11fbd781"><div class="ttname"><a href="_tensor_helpers_8hpp.html#a1ed60e4e5a0ec57f6483904e11fbd781">g_FloatCloseToZeroTolerance</a></div><div class="ttdeci">constexpr float g_FloatCloseToZeroTolerance</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.html#l00023">TensorHelpers.hpp:23</a></div></div>
<div class="ttc" id="classarmnn_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#l00093">Tensor.hpp:93</a></div></div>
<div class="ttc" id="struct_selective_comparer_html"><div class="ttname"><a href="struct_selective_comparer.html">SelectiveComparer</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.html#l00026">TensorHelpers.hpp:26</a></div></div>
<div class="ttc" id="_tensor_8hpp_html"><div class="ttname"><a href="_tensor_8hpp.html">Tensor.hpp</a></div></div>
<div class="ttc" id="_tensor_helpers_8hpp_html_a617427516e17888a138c16d3af503cfd"><div class="ttname"><a href="_tensor_helpers_8hpp.html#a617427516e17888a138c16d3af503cfd">SelectiveCompareBoolean</a></div><div class="ttdeci">bool SelectiveCompareBoolean(T a, T b)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.html#l00069">TensorHelpers.hpp:69</a></div></div>
<div class="ttc" id="_tensor_helpers_8hpp_html_a833e7db5d5f7e93102e80de57a602cf7"><div class="ttname"><a href="_tensor_helpers_8hpp.html#a833e7db5d5f7e93102e80de57a602cf7">SelectiveCompare</a></div><div class="ttdeci">bool SelectiveCompare(T a, T b)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.html#l00063">TensorHelpers.hpp:63</a></div></div>
<div class="ttc" id="_tensor_helpers_8hpp_html_a9c063a8b0e52737d20184cd36dcf483e"><div class="ttname"><a href="_tensor_helpers_8hpp.html#a9c063a8b0e52737d20184cd36dcf483e">MakeTensor</a></div><div class="ttdeci">boost::multi_array< T, n > MakeTensor(const armnn::TensorInfo &tensorInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.html#l00179">TensorHelpers.hpp:179</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="_tensor_helpers_8hpp_html_a0b8fbb443d2cf34a41f6aaae934e3dcb"><div class="ttname"><a href="_tensor_helpers_8hpp.html#a0b8fbb443d2cf34a41f6aaae934e3dcb">CompareTensors</a></div><div class="ttdeci">boost::test_tools::predicate_result CompareTensors(const boost::multi_array< T, n > &a, const boost::multi_array< T, n > &b, bool compareBoolean=false)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.html#l00075">TensorHelpers.hpp:75</a></div></div>
<div class="ttc" id="classarmnn_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#l00247">Tensor.cpp:247</a></div></div>
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