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| <a href="_convolution3d_8h.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 (c) 2017-2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <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> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <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> <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> <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> <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> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <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> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <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> <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> <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> <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> <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> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#ifndef __ARM_COMPUTE_TEST_VALIDATION_CONVOLUTION_H__</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define __ARM_COMPUTE_TEST_VALIDATION_CONVOLUTION_H__</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_asymm_helpers_8h.xhtml">arm_compute/core/utils/quantization/AsymmHelpers.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="tests_2validation_2_helpers_8h.xhtml">tests/validation/Helpers.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="_utils_quantized_asymm_8h.xhtml">tests/validation/reference/UtilsQuantizedAsymm.h</a>"</span></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> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></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="keyword">namespace </span>test</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="namespacearm__compute_1_1test_1_1convolution__3d.xhtml"> 35</a></span> <span class="keyword">namespace </span>convolution_3d</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div><div class="line"><a name="l00037"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml"> 37</a></span> <span class="keyword">namespace </span>detail</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> {</div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a03098570a566d97570169cb6d3106b6e"> 39</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a03098570a566d97570169cb6d3106b6e">is_valid_pixel</a>(<span class="keywordtype">int</span> i, <span class="keywordtype">int</span> min, <span class="keywordtype">int</span> max)</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> {</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordflow">return</span> (i >= min && i < max);</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> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment">// 3D convolution for floating point type</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> template < typename T, typename TB, typename std::enable_if < validation::is_floating_point<T>::value &&<a class="code" href="structarm__compute_1_1test_1_1validation_1_1is__floating__point.xhtml">validation::is_floating_point<TB>::value</a>, <span class="keywordtype">int</span> >::type = 0 ></div><div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a74dc80546816db5f19029d6819a8bfee"> 46</a></span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a74dc80546816db5f19029d6819a8bfee">convolution3d</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &in, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<TB></a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &out,</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordtype">int</span> i_offset, <span class="keywordtype">int</span> w_offset, <span class="keywordtype">int</span> b_offset, <span class="keywordtype">int</span> o_offset,</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordtype">int</span> xi, <span class="keywordtype">int</span> yi, <span class="keywordtype">int</span> width_in, <span class="keywordtype">int</span> height_in, <span class="keywordtype">int</span> depth_in, <span class="keywordtype">int</span> width_weights, <span class="keywordtype">int</span> height_weights, <span class="keywordtype">int</span> dilation_x = 1, <span class="keywordtype">int</span> dilation_y = 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>  <span class="keyword">const</span> T *in_ptr = in.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>() + i_offset;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keyword">const</span> T *w_ptr = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>.data() + w_offset;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">const</span> TB *b_ptr = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>.data() + b_offset;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  T *out_ptr = out.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>() + o_offset;</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">int</span> half_width_weights_start = width_weights / 2;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_height_weights_start = height_weights / 2;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="comment">// Reset accumulator</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  T acc(0);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// Compute a 2D convolution for each IFM and accumulate the result</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> ifm = 0; ifm < depth_in; ++ifm)</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="comment">// Compute the offset for the input slice</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> offset_slice_in = xi + yi * width_in + ifm * width_in * height_in;</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="comment">// Compute 2D convolution</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk)</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  {</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk)</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="comment">// Check if the pixel is out-of-bound</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a03098570a566d97570169cb6d3106b6e">is_valid_pixel</a>(xi + xk * dilation_x, 0, width_in) && <a class="code" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a03098570a566d97570169cb6d3106b6e">is_valid_pixel</a>(yi + yk * dilation_y, 0, height_in))</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  {</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> idx = xk + half_width_weights_start;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> idy = yk + half_height_weights_start;</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="keyword">const</span> T <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6266126c01687b9ea2f570a00dca5af2">i_value</a> = in_ptr[offset_slice_in + xk * dilation_x + yk * dilation_y * width_in];</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">const</span> T w_value = w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights];</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>  acc += <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6266126c01687b9ea2f570a00dca5af2">i_value</a> * w_value;</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>  }</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> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="comment">// Accumulate the bias and store the result</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  *out_ptr = acc + (*b_ptr);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> }</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="comment">// 3D convolution for QASYMM8 type</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> template < typename T, typename TB, typename std::enable_if < std::is_same<T, uint8_t>::value &&std::is_same<TB, int32_t>::value, <span class="keywordtype">int</span> >::type = 0 ></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a74dc80546816db5f19029d6819a8bfee">convolution3d</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &in, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<TB></a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &out,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keywordtype">int</span> i_offset, <span class="keywordtype">int</span> w_offset, <span class="keywordtype">int</span> b_offset, <span class="keywordtype">int</span> o_offset,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordtype">int</span> xi, <span class="keywordtype">int</span> yi, <span class="keywordtype">int</span> width_in, <span class="keywordtype">int</span> height_in, <span class="keywordtype">int</span> depth_in, <span class="keywordtype">int</span> width_weights, <span class="keywordtype">int</span> height_weights, <span class="keywordtype">int</span> dilation_x = 1, <span class="keywordtype">int</span> dilation_y = 1)</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>  <span class="keyword">const</span> T *in_ptr = in.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>() + i_offset;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">const</span> T *w_ptr = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>.data() + w_offset;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">const</span> TB *b_ptr = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>.data() + b_offset;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  T *out_ptr = out.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>() + o_offset;</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>  <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml">UniformQuantizationInfo</a> iq_info = in.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().uniform();</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml">UniformQuantizationInfo</a> wq_info = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>.quantization_info().uniform();</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml">UniformQuantizationInfo</a> oq_info = out.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().uniform();</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">const</span> <span class="keywordtype">int</span> input_offset = -iq_info.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">offset</a>;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> input_scale = iq_info.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a>;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> weights_offset = -wq_info.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">offset</a>;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> weights_scale = wq_info.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a>;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> output_offset = oq_info.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">offset</a>;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> output_scale = oq_info.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a>;</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="keywordtype">int</span> output_multiplier = 0;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordtype">int</span> output_shift = 0;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> multiplier = input_scale * weights_scale / output_scale;</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="namespacearm__compute_1_1quantization.xhtml#a22032f9cf47deae265eafb65ff55b594">arm_compute::quantization::calculate_quantized_multiplier_less_than_one</a>(multiplier, &output_multiplier, &output_shift);</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_width_weights_start = width_weights / 2;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start;</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_height_weights_start = height_weights / 2;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start;</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>  <span class="comment">// Reset accumulator</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  int32_t acc(0);</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>  <span class="comment">// Compute a 2D convolution for each IFM and accumulate the result</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> ifm = 0; ifm < depth_in; ++ifm)</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="comment">// Compute the offset for the input slice</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> offset_slice_in = xi + yi * width_in + ifm * width_in * height_in;</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="comment">// Compute 2D convolution</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk)</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">for</span>(<span class="keywordtype">int</span> xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk)</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="comment">// Check if the pixel is out-of-bound</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a03098570a566d97570169cb6d3106b6e">is_valid_pixel</a>(xi + xk * dilation_x, 0, width_in) && <a class="code" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a03098570a566d97570169cb6d3106b6e">is_valid_pixel</a>(yi + yk * dilation_y, 0, height_in))</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="keyword">const</span> <span class="keywordtype">int</span> idx = xk + half_width_weights_start;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> idy = yk + half_height_weights_start;</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="keyword">const</span> uint8_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6266126c01687b9ea2f570a00dca5af2">i_value</a> = in_ptr[offset_slice_in + xk * dilation_x + yk * dilation_y * width_in];</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keyword">const</span> uint8_t w_value = w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights];</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>  acc += (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6266126c01687b9ea2f570a00dca5af2">i_value</a> + input_offset) * (w_value + weights_offset);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  }</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  }</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</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>  <span class="comment">// Accumulate the bias</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  acc += (*b_ptr);</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>  acc = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5bab95cbeb5c6bf05049df7afd32d823">validation::asymm_rounding_divide_by_pow2</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aea27abcd3d58d627282320dfdd213596">validation::asymm_int_mult</a>(acc, output_multiplier), output_shift);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  acc += output_offset;</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  acc = utility::clamp<int32_t>(acc, 0, 255);</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="comment">// Store the result</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  *out_ptr = acc;</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> }</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> } <span class="comment">// namespace detail</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> } <span class="comment">// namespace convolution_3d</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> } <span class="comment">// namespace test</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> } <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="preprocessor">#endif </span><span class="comment">/*__ARM_COMPUTE_TEST_VALIDATION_CONVOLUTION_H__ */</span><span class="preprocessor"></span></div><div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5bab95cbeb5c6bf05049df7afd32d823"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5bab95cbeb5c6bf05049df7afd32d823">arm_compute::test::validation::asymm_rounding_divide_by_pow2</a></div><div class="ttdeci">int32_t asymm_rounding_divide_by_pow2(int32_t x, int exponent)</div><div class="ttdoc">Rounded to nearest division by a power-of-two.</div><div class="ttdef"><b>Definition:</b> <a href="_utils_quantized_asymm_8h_source.xhtml#l00036">UtilsQuantizedAsymm.h:36</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1quantization_xhtml_a22032f9cf47deae265eafb65ff55b594"><div class="ttname"><a href="namespacearm__compute_1_1quantization.xhtml#a22032f9cf47deae265eafb65ff55b594">arm_compute::quantization::calculate_quantized_multiplier_less_than_one</a></div><div class="ttdeci">arm_compute::Status calculate_quantized_multiplier_less_than_one(float multiplier, int *quant_multiplier, int *right_shift)</div><div class="ttdoc">Calculate quantized representation of multiplier with value less than one.</div><div class="ttdef"><b>Definition:</b> <a href="_asymm_helpers_8cpp_source.xhtml#l00035">AsymmHelpers.cpp:35</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1test_1_1validation_1_1is__floating__point_xhtml"><div class="ttname"><a href="structarm__compute_1_1test_1_1validation_1_1is__floating__point.xhtml">arm_compute::test::validation::is_floating_point</a></div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_helpers_8h_source.xhtml#l00044">Helpers.h:44</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="structarm__compute_1_1_uniform_quantization_info_xhtml"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml">arm_compute::UniformQuantizationInfo</a></div><div class="ttdoc">Quantization info when assuming per layer quantization.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00039">QuantizationInfo.h:39</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_uniform_quantization_info_xhtml_a1d28dec57cce925ad92342891bd71e7c"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">arm_compute::UniformQuantizationInfo::scale</a></div><div class="ttdeci">float scale</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00061">QuantizationInfo.h:61</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail_xhtml_a03098570a566d97570169cb6d3106b6e"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a03098570a566d97570169cb6d3106b6e">arm_compute::test::convolution_3d::detail::is_valid_pixel</a></div><div class="ttdeci">bool is_valid_pixel(int i, int min, int max)</div><div class="ttdef"><b>Definition:</b> <a href="_convolution3d_8h_source.xhtml#l00039">Convolution3d.h:39</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) 2017-2018 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="namespacearm__compute_1_1test_1_1validation_xhtml_aea27abcd3d58d627282320dfdd213596"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#aea27abcd3d58d627282320dfdd213596">arm_compute::test::validation::asymm_int_mult</a></div><div class="ttdeci">int32_t asymm_int_mult(int32_t a, int32_t b)</div><div class="ttdoc">Multiplication of two integers.</div><div class="ttdef"><b>Definition:</b> <a href="_utils_quantized_asymm_8h_source.xhtml#l00044">UtilsQuantizedAsymm.h:44</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a6266126c01687b9ea2f570a00dca5af2"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a6266126c01687b9ea2f570a00dca5af2">arm_compute::test::validation::i_value</a></div><div class="ttdeci">i_value</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_g_e_m_m_reshape_l_h_s_matrix_8cpp_source.xhtml#l00245">GEMMReshapeLHSMatrix.cpp:245</a></div></div> |
| <div class="ttc" id="_utils_quantized_asymm_8h_xhtml"><div class="ttname"><a href="_utils_quantized_asymm_8h.xhtml">UtilsQuantizedAsymm.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a3a77be8aebd8e00522b32061d46ccdbd"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">arm_compute::test::validation::bias</a></div><div class="ttdeci">CLTensor bias</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00181">ConvolutionLayer.cpp:181</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="structarm__compute_1_1_uniform_quantization_info_xhtml_a97bd6c077f3c7769f575b82988b9b668"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">arm_compute::UniformQuantizationInfo::offset</a></div><div class="ttdeci">int32_t offset</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00062">QuantizationInfo.h:62</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a64a08a9fec5aeee8650e7182b6d171d0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">arm_compute::test::validation::weights</a></div><div class="ttdeci">CLTensor weights</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">ConvolutionLayer.cpp:180</a></div></div> |
| <div class="ttc" id="_asymm_helpers_8h_xhtml"><div class="ttname"><a href="_asymm_helpers_8h.xhtml">AsymmHelpers.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ac74736e3863207232a23b7181c1d0f44"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">arm_compute::test::SimpleTensor::quantization_info</a></div><div class="ttdeci">QuantizationInfo quantization_info() const override</div><div class="ttdoc">Quantization info in case of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00333">SimpleTensor.h:333</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail_xhtml_a74dc80546816db5f19029d6819a8bfee"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a74dc80546816db5f19029d6819a8bfee">arm_compute::test::convolution_3d::detail::convolution3d</a></div><div class="ttdeci">void convolution3d(const SimpleTensor< T > &in, const SimpleTensor< T > &weights, const SimpleTensor< TB > &bias, SimpleTensor< T > &out, int i_offset, int w_offset, int b_offset, int o_offset, int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights, int dilation_x=1, int dilation_y=1)</div><div class="ttdef"><b>Definition:</b> <a href="_convolution3d_8h_source.xhtml#l00046">Convolution3d.h:46</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a4ae7e1f6885eb47c11062cc74e6a6e19"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">arm_compute::test::SimpleTensor::data</a></div><div class="ttdeci">const T * data() const</div><div class="ttdoc">Constant pointer to the underlying buffer.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00419">SimpleTensor.h:419</a></div></div> |
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