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| 87 | <a href="_resize_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="_resize_8hpp.html">Resize.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="_tensor_buffer_array_view_8hpp.html">TensorBufferArrayView.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/numeric/conversion/cast.hpp></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="preprocessor">#include <cmath></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <algorithm></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="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.html">armnnUtils</a>;</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> {</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> {</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="keyword">inline</span> <span class="keywordtype">float</span> Lerp(<span class="keywordtype">float</span> a, <span class="keywordtype">float</span> b, <span class="keywordtype">float</span> w)</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">return</span> w * b + (1.f - w) * a;</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> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="keyword">inline</span> <span class="keywordtype">double</span> EuclideanDistance(<span class="keywordtype">float</span> Xa, <span class="keywordtype">float</span> Ya, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> Xb, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> Yb)</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::sqrt(pow(Xa - boost::numeric_cast<float>(Xb), 2) + pow(Ya - boost::numeric_cast<float>(Yb), 2));</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> }<span class="comment">// anonymous namespace</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"><a class="line" href="namespacearmnn.html#a25dc224be48103343302b5a6fd588fe7"> 35</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#a25dc224be48103343302b5a6fd588fe7">Resize</a>(<a class="code" href="classarmnn_1_1_decoder.html">Decoder<float></a>& in,</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& inputInfo,</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="classarmnn_1_1_encoder.html">Encoder<float></a>& out,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& outputInfo,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">DataLayoutIndexed</a> dataLayout,</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4">armnn::ResizeMethod</a> resizeMethod,</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">bool</span> alignCorners)</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="comment">// We follow the definition of TensorFlow and AndroidNN: the top-left corner of a texel in the output</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="comment">// image is projected into the input image to figure out the interpolants and weights. Note that this</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="comment">// will yield different results than if projecting the centre of output texels.</span></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="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[0];</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelCount = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>()];</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>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</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>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> sizeOffset = resizeMethod == <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a> && alignCorners ? 1 : 0;</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>  <span class="comment">// How much to scale pixel coordinates in the output image, to get the corresponding pixel coordinates</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="comment">// in the input image.</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> scaleY = boost::numeric_cast<<span class="keywordtype">float</span>>(inputHeight - sizeOffset)</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  / boost::numeric_cast<float>(outputHeight - sizeOffset);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> scaleX = boost::numeric_cast<<span class="keywordtype">float</span>>(inputWidth - sizeOffset)</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  / boost::numeric_cast<float>(outputWidth - sizeOffset);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n < batchSize; ++n)</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> c = 0; c < channelCount; ++c)</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">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> y = 0; y < outputHeight; ++y)</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>  <span class="comment">// Corresponding real-valued height coordinate in input image.</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> iy = boost::numeric_cast<<span class="keywordtype">float</span>>(y) * scaleY;</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>  <span class="comment">// Discrete height coordinate of top-left texel (in the 2x2 texel area used for interpolation).</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> fiy = floorf(iy);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> y0 = boost::numeric_cast<<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(fiy);</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="comment">// Interpolation weight (range [0,1]).</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> yw = iy - fiy;</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">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> x = 0; x < outputWidth; ++x)</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  {</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="comment">// Real-valued and discrete width coordinates in input image.</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> ix = boost::numeric_cast<<span class="keywordtype">float</span>>(x) * scaleX;</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> fix = floorf(ix);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> x0 = boost::numeric_cast<<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(fix);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="comment">// Interpolation weight (range [0,1]).</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> xw = ix - fix;</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>  <span class="comment">// Discrete width/height coordinates of texels below and to the right of (x0, y0).</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> x1 = std::min(x0 + 1, inputWidth - 1u);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> y1 = std::min(y0 + 1, inputHeight - 1u);</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>  <span class="keywordtype">float</span> interpolatedValue;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">switch</span> (resizeMethod)</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a>:</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>  in[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(inputShape, n, c, y0, x0)];</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordtype">float</span> input1 = in.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  in[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(inputShape, n, c, y0, x1)];</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordtype">float</span> input2 = in.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  in[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(inputShape, n, c, y1, x0)];</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordtype">float</span> input3 = in.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  in[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(inputShape, n, c, y1, x1)];</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordtype">float</span> input4 = in.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> ly0 = Lerp(input1, input2, xw); <span class="comment">// lerp along row y0.</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> ly1 = Lerp(input3, input4, xw); <span class="comment">// lerp along row y1.</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  interpolatedValue = Lerp(ly0, ly1, yw);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  }</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a>:</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  {</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="comment">// calculate euclidean distance to the 4 neighbours</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keyword">auto</span> distance00 = EuclideanDistance(fix, fiy, x0, y0);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keyword">auto</span> distance01 = EuclideanDistance(fix, fiy, x0, y1);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keyword">auto</span> distance10 = EuclideanDistance(fix, fiy, x1, y0);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keyword">auto</span> distance11 = EuclideanDistance(fix, fiy, x1, y1);</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="keyword">auto</span> <a class="code" href="structarmnn_1_1minimum.html">minimum</a> = std::min( { distance00, distance01, distance10, distance11 } );</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> xNearest = 0;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yNearest = 0;</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="keywordflow">if</span> (<a class="code" href="structarmnn_1_1minimum.html">minimum</a> == distance00)</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>  xNearest = x0;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  yNearest = y0;</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="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="structarmnn_1_1minimum.html">minimum</a> == distance01)</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>  xNearest = x0;</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  yNearest = y1;</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">else</span> <span class="keywordflow">if</span> (<a class="code" href="structarmnn_1_1minimum.html">minimum</a> == distance10)</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>  xNearest = x1;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  yNearest = y0;</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>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="structarmnn_1_1minimum.html">minimum</a> == distance11)</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  xNearest = x1;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  yNearest = y1;</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">else</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  {</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Resize Nearest Neighbor failure"</span>);</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>  in[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(inputShape, n, c, yNearest, xNearest)];</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  interpolatedValue = in.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keywordflow">break</span>;</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">default</span>:</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Unknown resize method: "</span> +</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  std::to_string(static_cast<int>(resizeMethod)));</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>  out[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(outputShape, n, c, y, x)];</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  out.<a class="code" href="classarmnn_1_1_encoder.html#ae3b62b846a9c239f332830b9e36030eb">Set</a>(interpolatedValue);</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>  }</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>  }</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> </div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> } <span class="comment">//namespace armnn</span></div><div class="ttc" id="_resize_8hpp_html"><div class="ttname"><a href="_resize_8hpp.html">Resize.hpp</a></div></div> |
| 88 | <div class="ttc" id="namespacearmnn_html_a9a2af2f8c4af4f9efa8e79417d505ac4"><div class="ttname"><a href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4">armnn::ResizeMethod</a></div><div class="ttdeci">ResizeMethod</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00100">Types.hpp:100</a></div></div> |
| 89 | <div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a61c00316c443adc233c24e85c6c5b740"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">armnnUtils::DataLayoutIndexed::GetHeightIndex</a></div><div class="ttdeci">unsigned int GetHeightIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00024">DataLayoutIndexed.hpp:24</a></div></div> |
| 90 | <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> |
| 91 | <div class="ttc" id="structarmnn_1_1minimum_html"><div class="ttname"><a href="structarmnn_1_1minimum.html">armnn::minimum</a></div><div class="ttdef"><b>Definition:</b> <a href="_minimum_8hpp_source.html#l00012">Minimum.hpp:12</a></div></div> |
| 92 | <div class="ttc" id="classarmnn_1_1_decoder_html"><div class="ttname"><a href="classarmnn_1_1_decoder.html">armnn::Decoder< float ></a></div></div> |
| 93 | <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> |
| 94 | <div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a414e6f95548e6f7a01d5028b55ad3941"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">armnnUtils::DataLayoutIndexed::GetWidthIndex</a></div><div class="ttdeci">unsigned int GetWidthIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00025">DataLayoutIndexed.hpp:25</a></div></div> |
| 95 | <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> |
| 96 | <div class="ttc" id="classarmnn_1_1_encoder_html"><div class="ttname"><a href="classarmnn_1_1_encoder.html">armnn::Encoder< float ></a></div></div> |
| 97 | <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> |
| 98 | <div class="ttc" id="_tensor_buffer_array_view_8hpp_html"><div class="ttname"><a href="_tensor_buffer_array_view_8hpp.html">TensorBufferArrayView.hpp</a></div></div> |
| 99 | <div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a861b2621ee46e4b63379988b360b8cd9"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">armnnUtils::DataLayoutIndexed::GetChannelsIndex</a></div><div class="ttdeci">unsigned int GetChannelsIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00023">DataLayoutIndexed.hpp:23</a></div></div> |
| 100 | <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> |
| 101 | <div class="ttc" id="classarmnn_1_1_decoder_html_ac729108381e2340bea12877971713ecb"><div class="ttname"><a href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">armnn::Decoder::Get</a></div><div class="ttdeci">virtual IType Get() const =0</div></div> |
| 102 | <div class="ttc" id="namespacearmnn_html_a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f"><div class="ttname"><a href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a></div></div> |
| 103 | <div class="ttc" id="namespacearmnn_html_a25dc224be48103343302b5a6fd588fe7"><div class="ttname"><a href="namespacearmnn.html#a25dc224be48103343302b5a6fd588fe7">armnn::Resize</a></div><div class="ttdeci">void Resize(Decoder< float > &in, const TensorInfo &inputInfo, Encoder< float > &out, const TensorInfo &outputInfo, DataLayoutIndexed dataLayout, armnn::ResizeMethod resizeMethod, bool alignCorners)</div><div class="ttdef"><b>Definition:</b> <a href="_resize_8cpp_source.html#l00035">Resize.cpp:35</a></div></div> |
| 104 | <div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00017">DataLayoutIndexed.hpp:17</a></div></div> |
| 105 | <div class="ttc" id="namespacearmnn_html_a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f"><div class="ttname"><a href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a></div></div> |
| 106 | <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> |
| 107 | <div class="ttc" id="classarmnn_1_1_encoder_html_ae3b62b846a9c239f332830b9e36030eb"><div class="ttname"><a href="classarmnn_1_1_encoder.html#ae3b62b846a9c239f332830b9e36030eb">armnn::Encoder::Set</a></div><div class="ttdeci">virtual void Set(IType right)=0</div></div> |
| 108 | <div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a1e25d8623da985a43597b5756c73b206"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">armnnUtils::DataLayoutIndexed::GetIndex</a></div><div class="ttdeci">unsigned int GetIndex(const armnn::TensorShape &shape, unsigned int batchIndex, unsigned int channelIndex, unsigned int heightIndex, unsigned int widthIndex) const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00027">DataLayoutIndexed.hpp:27</a></div></div> |
| 109 | </div><!-- fragment --></div><!-- contents --> |
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| 114 | <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.html">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.html">backends</a></li><li class="navelem"><a class="el" href="dir_efae4012d0e357ebeaba7d02491d70e5.html">reference</a></li><li class="navelem"><a class="el" href="dir_d2f3b8e2e64df3181ebe92efcc0a3012.html">workloads</a></li><li class="navelem"><a class="el" href="_resize_8cpp.html">Resize.cpp</a></li> |
| 115 | <li class="footer">Generated on Fri Mar 13 2020 16:06:58 for ArmNN by |
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