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<div class="title">MirrorPad.cpp</div> </div>
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<a href="backends_2reference_2workloads_2_mirror_pad_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_mirror_pad_8hpp.xhtml">MirrorPad.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="_base_iterator_8hpp.xhtml">BaseIterator.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_decoders_8hpp.xhtml">Decoders.hpp</a>"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include "<a class="code" href="_encoders_8hpp.xhtml">Encoders.hpp</a>"</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="keyword">namespace</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> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment">// Convert a linear index into n-dimensional coordinates.</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment">// E.g. index = 2 returns [0, 0, 2].</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">inline</span> std::vector<unsigned int> IndexToCoord(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& shape, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOfElements = shape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>();</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(index <= numOfElements, <span class="stringliteral">"Index has to be in [0, num_elements]"</span>);</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(numOfElements != 0, <span class="stringliteral">"Cannot create coordinate from empty shape"</span>);</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> </div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  std::vector<unsigned int> coord(shape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < shape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</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>  numOfElements /= shape[i];</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  coord[i] = index / numOfElements;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  index %= numOfElements;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  }</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>  <span class="keywordflow">return</span> coord;</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="comment">// Returns the index of a given coordinate.</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment">// E.g. [0, 0, 2] returns 2.</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> CoordToIndex(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& shape, <span class="keyword">const</span> std::vector<unsigned int>& coord)</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> {</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(shape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() != 0, <span class="stringliteral">"Cannot get index from empty shape"</span>);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(coord.size() != 0, <span class="stringliteral">"Cannot get index of empty coordinate"</span>);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> </div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index = 0;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimSize = 1;</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">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = shape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); i > 0; --i)</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>  index += coord[i - 1] * dimSize;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  dimSize *= shape[i - 1];</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">return</span> index;</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> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> } <span class="comment">// anonymous namespace</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="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> {</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a4e3efb65a77cf35dc5dc09e4f3646029"> 59</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#a4e3efb65a77cf35dc5dc09e4f3646029">MirrorPad</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputInfo,</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputInfo,</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml">ITensorHandle</a>* inputHandle,</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml">ITensorHandle</a>* outputHandle,</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_pad_queue_descriptor.xhtml">PadQueueDescriptor</a>& data)</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="keyword">auto</span> padList = data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pad_descriptor.xhtml#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a>;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> paddingMode = data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_pad_descriptor.xhtml#a66f2c989f51ab6116de4380390250b69">m_PaddingMode</a>;</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>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputElements = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>();</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputDimensions = inputShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  assert(numInputDimensions == outputShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="comment">// If padding mode is Reflect then both paddings must be no greater than inputShape(i) - 1.</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// If padding mode is Symmetric then both paddings must be no greater than inputShape(i).</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> isReflect = <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(paddingMode == <a class="code" href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a74de3e45e4491e956e8dc18d841d9b00">PaddingMode::Reflect</a>);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < padList.size(); ++i)</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>  <span class="keywordflow">if</span>(padList.at(i).first > (inputShape[i] - isReflect) ||</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  padList.at(i).second > (inputShape[i] - isReflect))</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Paddings must be less (Reflect) or "</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="stringliteral">"equal (Symmetric) to the dimension size."</span>);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  }</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> </div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keyword">auto</span> inputData = MakeDecoder<float>(inputInfo, inputHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a9afbc055a017adf1bc38ee137bca6e90">Map</a>());</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keyword">auto</span> outData = MakeEncoder<float>(outputInfo, outputHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a9afbc055a017adf1bc38ee137bca6e90">Map</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>  <a class="code" href="classarmnn_1_1_decoder.xhtml">Decoder<float></a>& input = *inputData;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="classarmnn_1_1_encoder.xhtml">Encoder<float></a>& output = *outData;</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="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0; idx < numOutputElements; ++idx)</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">// Get the coordinates of the current index in vector form. E.g inx 1 = [0, 0, 0, 1 ]</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">const</span> std::vector<unsigned int> coord = IndexToCoord(outputShape, idx);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  std::vector<unsigned int> dimensions;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  std::vector<unsigned int> coords;</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>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputDimensions; ++i)</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  {</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  dimensions.emplace_back(i);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  coords.emplace_back(coord[i]);</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> </div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keyword">auto</span> isInPadding = [&](<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)</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> (coords[i] < padList[i].first || coords[i] > inputShape[i] + padList[i].first - 1);</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"> 113</span>  <span class="keyword">auto</span> getReflectIndex = [&](<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) -> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></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">if</span>(isInPadding(i))</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keywordflow">if</span>(coords[i] < padList[i].first)</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>  <span class="keywordflow">return</span> padList[i].first - coords[i];</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  }</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">return</span> 2 * inputShape[i] + padList[i].first - 2 - coords[i];</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  }</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">return</span> coords[i] - padList[i].first;</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> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">auto</span> getSymmetricIndex = [&](<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i) -> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">if</span>(isInPadding(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>  <span class="keywordflow">if</span>(coords[i] < padList[i].first)</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  {</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordflow">return</span> padList[i].first - coords[i] - 1;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  }</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keywordflow">else</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>  <span class="keywordflow">return</span> 2 * inputShape[i] + padList[i].first - 1 - coords[i];</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>  }</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keywordflow">return</span> coords[i] - padList[i].first;</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>  <span class="comment">// Location of the value in the input tensor to use in the output.</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  std::vector<unsigned int> coordOfInput;</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="comment">// any_of works as a loop here to check if any of the dimensions are in the padding.</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="comment">// If dimensions is in the padding area, then create the coordinates of the location in the</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="comment">// input tensor to use in the output.</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">// E.g.</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="comment">// Input tensor = [ 1, 2, 3 ], Rank = 1.</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="comment">// Output tensor = [ 2, 1, 2, 3, 1 ] if Reflect or [ 1, 1, 2, 3, 3 ] if Symmetric with a padding of (1, 1).</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">// So it will either return [ 1 ] or [ 0 ] which is used to set the first value in the output tensor and so on.</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">if</span>(std::any_of(dimensions.begin(), dimensions.end(), isInPadding))</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">switch</span>(paddingMode)</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a74de3e45e4491e956e8dc18d841d9b00">PaddingMode::Reflect</a>:</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>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputDimensions; ++i)</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  {</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  coordOfInput.emplace_back(getReflectIndex(i));</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  }</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordflow">break</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="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91af334649ef5e5d0ffe200751d07012626">PaddingMode::Symmetric</a>:</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  {</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputDimensions; ++i)</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  {</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  coordOfInput.emplace_back(getSymmetricIndex(i));</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">break</span>;</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>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Padding mode not supported."</span>);</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  }</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  }</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  {</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputDimensions; ++i)</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  {</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  coordOfInput.emplace_back(coord[i] - padList[i].first);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  }</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  }</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="comment">// Set output value using the coordinate of the input value to use.</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> indexOfInput = CoordToIndex(inputShape, coordOfInput);</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>  input[indexOfInput];</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keyword">auto</span> inputValue = input.Get();</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> </div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  output[idx];</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  output.<a class="code" href="classarmnn_1_1_encoder.xhtml#ae3b62b846a9c239f332830b9e36030eb">Set</a>(inputValue);</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> }</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">//namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorShape::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdoc">Function that calculates the tensor elements by multiplying all dimension size which are Specified...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00181">Tensor.cpp:181</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00191">Tensor.hpp:191</a></div></div>
<div class="ttc" id="_mirror_pad_8hpp_xhtml"><div class="ttname"><a href="_mirror_pad_8hpp.xhtml">MirrorPad.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a14d24d90ab4ba2956e92e27890ba4c91af334649ef5e5d0ffe200751d07012626"><div class="ttname"><a href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91af334649ef5e5d0ffe200751d07012626">armnn::PaddingMode::Symmetric</a></div></div>
<div class="ttc" id="classarmnn_1_1_encoder_xhtml_ae3b62b846a9c239f332830b9e36030eb"><div class="ttname"><a href="classarmnn_1_1_encoder.xhtml#ae3b62b846a9c239f332830b9e36030eb">armnn::Encoder::Set</a></div><div class="ttdeci">virtual void Set(IType right)=0</div></div>
<div class="ttc" id="classarmnn_1_1_encoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_encoder.xhtml">armnn::Encoder< float ></a></div></div>
<div class="ttc" id="structarmnn_1_1_pad_descriptor_xhtml_a85f98c94e11f65a6b73f831735c040f3"><div class="ttname"><a href="structarmnn_1_1_pad_descriptor.xhtml#a85f98c94e11f65a6b73f831735c040f3">armnn::PadDescriptor::m_PadList</a></div><div class="ttdeci">std::vector< std::pair< unsigned int, unsigned int > > m_PadList</div><div class="ttdoc">Specifies the padding for input dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01199">Descriptors.hpp:1199</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.dox:6</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00066">WorkloadData.hpp:66</a></div></div>
<div class="ttc" id="structarmnn_1_1_pad_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pad_queue_descriptor.xhtml">armnn::PadQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00316">WorkloadData.hpp:316</a></div></div>
<div class="ttc" id="_encoders_8hpp_xhtml"><div class="ttname"><a href="_encoders_8hpp.xhtml">Encoders.hpp</a></div></div>
<div class="ttc" id="_base_iterator_8hpp_xhtml"><div class="ttname"><a href="_base_iterator_8hpp.xhtml">BaseIterator.hpp</a></div></div>
<div class="ttc" id="_assert_8hpp_xhtml_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00015">Assert.hpp:15</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml">armnn::ITensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00015">ITensorHandle.hpp:15</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4e3efb65a77cf35dc5dc09e4f3646029"><div class="ttname"><a href="namespacearmnn.xhtml#a4e3efb65a77cf35dc5dc09e4f3646029">armnn::MirrorPad</a></div><div class="ttdeci">void MirrorPad(const TensorInfo &inputInfo, const TensorInfo &outputInfo, const ITensorHandle *inputHandle, ITensorHandle *outputHandle, const PadQueueDescriptor &data)</div><div class="ttdef"><b>Definition:</b> <a href="backends_2reference_2workloads_2_mirror_pad_8cpp_source.xhtml#l00059">MirrorPad.cpp:59</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a14d24d90ab4ba2956e92e27890ba4c91"><div class="ttname"><a href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">armnn::PaddingMode</a></div><div class="ttdeci">PaddingMode</div><div class="ttdoc">The padding mode controls whether the padding should be filled with constant values (Constant)...</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00186">Types.hpp:186</a></div></div>
<div class="ttc" id="classarmnn_1_1_invalid_argument_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00080">Exceptions.hpp:80</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a14d24d90ab4ba2956e92e27890ba4c91a74de3e45e4491e956e8dc18d841d9b00"><div class="ttname"><a href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a74de3e45e4491e956e8dc18d841d9b00">armnn::PaddingMode::Reflect</a></div></div>
<div class="ttc" id="_decoders_8hpp_xhtml"><div class="ttname"><a href="_decoders_8hpp.xhtml">Decoders.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_pad_descriptor_xhtml_a66f2c989f51ab6116de4380390250b69"><div class="ttname"><a href="structarmnn_1_1_pad_descriptor.xhtml#a66f2c989f51ab6116de4380390250b69">armnn::PadDescriptor::m_PaddingMode</a></div><div class="ttdeci">PaddingMode m_PaddingMode</div><div class="ttdoc">Specifies the Padding mode (Constant, Reflect or Symmetric) </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01205">Descriptors.hpp:1205</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml_a9afbc055a017adf1bc38ee137bca6e90"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml#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>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdoc">Function that returns the tensor rank. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00174">Tensor.cpp:174</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00196">Tensor.hpp:196</a></div></div>
<div class="ttc" id="classarmnn_1_1_decoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_decoder.xhtml">armnn::Decoder< float ></a></div></div>
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