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<div class="title">Im2Col.cpp</div> </div>
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<a href="reference_2_im2_col_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>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment"> * Copyright (c) 2018-2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_im2_col_8h.xhtml">Im2Col.h</a>&quot;</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>&quot;</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tests_2validation_2_helpers_8h.xhtml">tests/validation/Helpers.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tests_2validation_2reference_2_utils_8h.xhtml">tests/validation/reference/Utils.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;{</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="keyword">namespace </span>test</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;{</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="keyword">namespace </span>validation</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;{</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;<span class="keyword">namespace </span>reference</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;{</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ad986200da9376a05059064b4e0372445"> 39</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ad986200da9376a05059064b4e0372445">im2col_nchw</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;kernel_dims, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>)</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;{</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.data_layout() != <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> stride_x = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().first;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> stride_y = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().second;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> kernel_width = kernel_dims.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> kernel_height = kernel_dims.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> pad_x = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad().first;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> pad_y = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad().second;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> src_width = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.shape().x();</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> src_height = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.shape().y();</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> src_channels = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.shape().z();</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> batches = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.shape().total_size_upper(3);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> dst_height = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().y();</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> pad_val = <a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.data_type()) ? <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.quantization_info().uniform().offset : 0;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keywordtype">int</span> dst_idx = 0;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="comment">// Compute width and height of the convolved tensors</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; std::pair&lt;unsigned int, unsigned int&gt; convolved_dims = <a class="code" href="namespacearm__compute.xhtml#abbe3399a66c35c3c353030cd0a84c936">scaled_dimensions</a>(src_width, src_height, kernel_dims.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>, kernel_dims.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a> = 0; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a> &lt; batches; ++<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a>)</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; {</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> g = 0; g &lt; static_cast&lt;int&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>); ++g)</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; {</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> first_group_ch = g * (src_channels / <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> last_group_ch = (g + 1) * (src_channels / <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> yo = 0; yo &lt; dst_height; ++yo)</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; {</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="comment">// Compute input spatial coordinates</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> xi = (yo % convolved_dims.first) * stride_x;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> yi = (yo / convolved_dims.first) * stride_y;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> ci = first_group_ch; ci &lt; last_group_ch; ++ci)</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> yk = 0; yk &lt; kernel_height; ++yk)</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; {</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> xk = 0; xk &lt; kernel_width; ++xk)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[dst_idx++] = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f489943d8618d47b1ad4611f0b9b7ff">tensor_elem_at</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(xi + xk - pad_x, yi + yk - pad_y, ci, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a>), <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">BorderMode::CONSTANT</a>, static_cast&lt;T&gt;(pad_val));</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; }</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; }</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; }</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>)</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; {</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[dst_idx++] = static_cast&lt;T&gt;(1);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; }</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; }</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; }</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; }</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160;}</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a676e94ff38d81a5794e2bf69008c5137"> 93</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a676e94ff38d81a5794e2bf69008c5137">im2col_nhwc</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;kernel_dims, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>)</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160;{</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.data_layout() != <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> stride_x = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().first;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> stride_y = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().second;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> kernel_width = kernel_dims.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> kernel_height = kernel_dims.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> pad_x = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad().first;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> pad_y = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad().second;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> src_width = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.shape().y();</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> src_height = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.shape().z();</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> src_channels = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.shape().x();</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> batches = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.shape().total_size_upper(3);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> dst_width = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a> ? <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().x() - 1 : <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().x();</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> dst_height = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().y();</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> pad_val = <a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.data_type()) ? <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.quantization_info().uniform().offset : 0;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="comment">// Compute width and height of the convolved tensors</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; std::pair&lt;unsigned int, unsigned int&gt; convolved_dims = <a class="code" href="namespacearm__compute.xhtml#abbe3399a66c35c3c353030cd0a84c936">scaled_dimensions</a>(src_width, src_height, kernel_dims.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>, kernel_dims.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a> = 0; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a> &lt; batches; ++<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a>)</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; {</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> yo = 0; yo &lt; dst_height; ++yo)</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="comment">// Compute input spatial coordinates</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> xi = (yo % convolved_dims.first) * stride_x;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> yi = (yo / convolved_dims.first) * stride_y;</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> ci = 0; ci &lt; src_channels; ++ci)</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> yk = 0; yk &lt; kernel_height; ++yk)</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; {</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> xk = 0; xk &lt; kernel_width; ++xk)</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; {</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[ci + (xk + yk * kernel_width) * src_channels + yo * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().x() + <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a> * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().x() * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().y()] = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f489943d8618d47b1ad4611f0b9b7ff">tensor_elem_at</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(ci, xi + xk - pad_x, yi + yk - pad_y, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a>),</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">BorderMode::CONSTANT</a>, static_cast&lt;T&gt;(pad_val));</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; }</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; }</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; }</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>)</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; {</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[dst_width + yo * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().x() + <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a> * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().x() * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.shape().y()] = static_cast&lt;T&gt;(1);</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; }</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; }</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; }</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160;}</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00142"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a77f0a04bc3f800ccd330df1170e76344"> 142</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a77f0a04bc3f800ccd330df1170e76344">im2col</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;kernel_dims, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>)</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;{</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keywordflow">switch</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.data_layout())</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>:</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; {</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ad986200da9376a05059064b4e0372445">im2col_nchw</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, kernel_dims, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; }</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>:</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; {</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a676e94ff38d81a5794e2bf69008c5137">im2col_nhwc</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, kernel_dims, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; }</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; {</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <a class="code" href="_error_8h.xhtml#a7cf8d8b669b8f7b05680230be30d60f4">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;Not supported.&quot;</span>);</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; }</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; }</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160;}</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160;</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160;<span class="keyword">template</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a77f0a04bc3f800ccd330df1170e76344">im2col</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;kernel_dims, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160;<span class="keyword">template</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a77f0a04bc3f800ccd330df1170e76344">im2col</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;half&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;half&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;kernel_dims, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160;<span class="keyword">template</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a77f0a04bc3f800ccd330df1170e76344">im2col</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;kernel_dims, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">has_bias</a>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;} <span class="comment">// namespace reference</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160;} <span class="comment">// namespace validation</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a4f489943d8618d47b1ad4611f0b9b7ff"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f489943d8618d47b1ad4611f0b9b7ff">arm_compute::test::validation::tensor_elem_at</a></div><div class="ttdeci">T tensor_elem_at(const SimpleTensor&lt; T &gt; &amp;src, Coordinates coord, BorderMode border_mode, T constant_border_value)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2reference_2_utils_8h_source.xhtml#l00061">Utils.h:61</a></div></div>
<div class="ttc" id="tests_2validation_2reference_2_utils_8h_xhtml"><div class="ttname"><a href="tests_2validation_2reference_2_utils_8h.xhtml">Utils.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_abbe3399a66c35c3c353030cd0a84c936"><div class="ttname"><a href="namespacearm__compute.xhtml#abbe3399a66c35c3c353030cd0a84c936">arm_compute::scaled_dimensions</a></div><div class="ttdeci">std::pair&lt; unsigned int, unsigned int &gt; scaled_dimensions(unsigned int width, unsigned int height, unsigned int kernel_width, unsigned int kernel_height, const PadStrideInfo &amp;pad_stride_info, const Size2D &amp;dilation=Size2D(1U, 1U))</div><div class="ttdoc">Returns expected width and height of output scaled tensor depending on dimensions rounding mode.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_utils_8cpp_source.xhtml#l00402">Utils.cpp:402</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_aa76b4a6e74940dabc5b7fc6b2dab3545"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">arm_compute::test::validation::b</a></div><div class="ttdeci">SimpleTensor&lt; float &gt; b</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_2_d_f_t_8cpp_source.xhtml#l00157">DFT.cpp:157</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_ad986200da9376a05059064b4e0372445"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ad986200da9376a05059064b4e0372445">arm_compute::test::validation::reference::im2col_nchw</a></div><div class="ttdeci">void im2col_nchw(const SimpleTensor&lt; T &gt; &amp;src, SimpleTensor&lt; T &gt; &amp;dst, const Size2D &amp;kernel_dims, const PadStrideInfo &amp;conv_info, bool has_bias, unsigned int num_groups)</div><div class="ttdef"><b>Definition:</b> <a href="reference_2_im2_col_8cpp_source.xhtml#l00039">Im2Col.cpp:39</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a7cf8d8b669b8f7b05680230be30d60f4"><div class="ttname"><a href="_error_8h.xhtml#a7cf8d8b669b8f7b05680230be30d60f4">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(msg)</div><div class="ttdoc">Print the given message then throw an std::runtime_error.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00352">Error.h:352</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00599">Winograd.cpp:599</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00466">Error.h:466</a></div></div>
<div class="ttc" id="tests_2validation_2_helpers_8h_xhtml"><div class="ttname"><a href="tests_2validation_2_helpers_8h.xhtml">Helpers.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2019 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div>
<div class="ttc" id="_im2_col_8h_xhtml"><div class="ttname"><a href="_im2_col_8h.xhtml">Im2Col.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_size2_d_xhtml_a02afeaaf8574e7a78d6b466ff2695052"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">arm_compute::Size2D::height</a></div><div class="ttdeci">size_t height</div><div class="ttdoc">Height of the image region or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00093">Size2D.h:93</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a77f0a04bc3f800ccd330df1170e76344"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a77f0a04bc3f800ccd330df1170e76344">arm_compute::test::validation::reference::im2col</a></div><div class="ttdeci">void im2col(const SimpleTensor&lt; T &gt; &amp;src, SimpleTensor&lt; T &gt; &amp;dst, const Size2D &amp;kernel_dims, const PadStrideInfo &amp;conv_info, bool has_bias, unsigned int num_groups)</div><div class="ttdef"><b>Definition:</b> <a href="reference_2_im2_col_8cpp_source.xhtml#l00142">Im2Col.cpp:142</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a2270b3e1d20651d2d8341c858c890830"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">arm_compute::test::validation::num_groups</a></div><div class="ttdeci">const unsigned int num_groups</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00148">Im2Col.cpp:148</a></div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item.</div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml">arm_compute::PadStrideInfo</a></div><div class="ttdoc">Padding and stride information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00685">Types.h:685</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_adbf67dcee294e673cf796f1ed8aeb6a4"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">arm_compute::test::validation::dst</a></div><div class="ttdeci">CLTensor dst</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00102">AbsoluteDifference.cpp:102</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a676e94ff38d81a5794e2bf69008c5137"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a676e94ff38d81a5794e2bf69008c5137">arm_compute::test::validation::reference::im2col_nhwc</a></div><div class="ttdeci">void im2col_nhwc(const SimpleTensor&lt; T &gt; &amp;src, SimpleTensor&lt; T &gt; &amp;dst, const Size2D &amp;kernel_dims, const PadStrideInfo &amp;conv_info, bool has_bias)</div><div class="ttdef"><b>Definition:</b> <a href="reference_2_im2_col_8cpp_source.xhtml#l00093">Im2Col.cpp:93</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a9aeced5a5128f60a31ea3e327a45ee21"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a9aeced5a5128f60a31ea3e327a45ee21">arm_compute::test::validation::has_bias</a></div><div class="ttdeci">const bool has_bias</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00147">Im2Col.cpp:147</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width.</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a14f46283f316e7f0fad301d5c1507e9f"><div class="ttname"><a href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">arm_compute::is_data_type_quantized_asymmetric</a></div><div class="ttdeci">bool is_data_type_quantized_asymmetric(DataType dt)</div><div class="ttdoc">Check if a given data type is of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01044">Utils.h:1044</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">arm_compute::test::SimpleTensor</a></div><div class="ttdoc">Simple tensor object that stores elements in a consecutive chunk of memory.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00059">SimpleTensor.h:59</a></div></div>
<div class="ttc" id="classarm__compute_1_1_size2_d_xhtml_a02bed8590a9ddf520e58a060059518ec"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">arm_compute::Size2D::width</a></div><div class="ttdeci">size_t width</div><div class="ttdoc">Width of the image region or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00092">Size2D.h:92</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92"><div class="ttname"><a href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">arm_compute::PaddingMode::CONSTANT</a></div></div>
<div class="ttc" id="classarm__compute_1_1_size2_d_xhtml"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml">arm_compute::Size2D</a></div><div class="ttdoc">Class for specifying the size of an image or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00034">Size2D.h:34</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::DataLayout::NHWC</a></div><div class="ttdoc">Num samples, height, width, channels.</div></div>
<div class="ttc" id="arm__compute_2core_2_types_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_types_8h.xhtml">Types.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a989ab3e96426615bb98e04e0235088ca"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">arm_compute::test::validation::src</a></div><div class="ttdeci">cast configure &amp; src</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_cast_8cpp_source.xhtml#l00169">Cast.cpp:169</a></div></div>
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