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| 120 | <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) 2017-2018 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"> *asymm_int_mult</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, asymm_int_multDAMAGES 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_fixed_point_8h.xhtml">tests/validation/FixedPoint.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</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="l00030"></a><span class="lineno"> 30</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="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> {</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">namespace </span>test</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> {</div><div class="line"><a name="l00036"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1convolution__3d.xhtml"> 36</a></span> <span class="keyword">namespace </span>convolution_3d</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml"> 38</a></span> <span class="keyword">namespace </span>detail</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> {</div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a03098570a566d97570169cb6d3106b6e"> 40</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> <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">min</a>, <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">max</a>)</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">return</span> (i >= min && i < max);</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> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment">// 3D convolution for floating point type</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</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="l00047"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a74dc80546816db5f19029d6819a8bfee"> 47</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> &weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<TB></a> &bias, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &out,</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</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="l00049"></a><span class="lineno"> 49</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="l00050"></a><span class="lineno"> 50</span> {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keyword">const</span> T *in_ptr = in.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + i_offset;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">const</span> T *w_ptr = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + w_offset;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">const</span> TB *b_ptr = bias.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + b_offset;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  T *out_ptr = out.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + o_offset;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_width_weights_start = width_weights / 2;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</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="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_height_weights_start = height_weights / 2;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</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="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="comment">// Reset accumulator</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  T acc(0);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// Compute a 2D convolution for each IFM and accumulate the result</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> ifm = 0; ifm < depth_in; ++ifm)</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  {</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="comment">// Compute the offset for the input slice</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</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="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="comment">// Compute 2D convolution</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</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="l00072"></a><span class="lineno"> 72</span>  {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</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="l00074"></a><span class="lineno"> 74</span>  {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="comment">// Check if the pixel is out-of-bound</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</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="l00077"></a><span class="lineno"> 77</span>  {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> idx = xk + half_width_weights_start;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> idy = yk + half_height_weights_start;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">const</span> T i_value = in_ptr[offset_slice_in + xk * dilation_x + yk * dilation_y * width_in];</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</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="l00083"></a><span class="lineno"> 83</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  acc += i_value * w_value;</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> </div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="comment">// Accumulate the bias and store the result</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  *out_ptr = acc + (*b_ptr);</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="comment">// 3D convolution for fixed point type</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> template < typename T, typename TB, typename std::enable_if < std::is_integral<T>::value &&std::is_integral<TB>::value, <span class="keywordtype">int</span> >::type = 0 ></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</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> &weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<TB></a> &bias, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &out,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</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="l00098"></a><span class="lineno"> 98</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="l00099"></a><span class="lineno"> 99</span> {</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">const</span> T *in_ptr = in.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + i_offset;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">const</span> T *w_ptr = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + w_offset;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">const</span> T *b_ptr = bias.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + b_offset;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  T *out_ptr = out.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + o_offset;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordtype">int</span> fixed_point_position = in.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">fixed_point_position</a>();</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_width_weights_start = width_weights / 2;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</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="l00108"></a><span class="lineno"> 108</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_height_weights_start = height_weights / 2;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</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="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keyword">using namespace </span>fixed_point_arithmetic;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keyword">using</span> promoted_type = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits.xhtml#ac20ca549fa27b2eed44367745055a233">fixed_point_arithmetic::traits::promote_t<T></a>;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="comment">// Reset accumulator</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  fixed_point<promoted_type> acc(0, fixed_point_position);</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="comment">// Compute a 2D convolution for each IFM and accumulate the result</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> ifm = 0; ifm < depth_in; ++ifm)</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="comment">// Compute the offset for the input slice</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</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="l00122"></a><span class="lineno"> 122</span> </div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="comment">// Compute 2D convolution</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</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="l00125"></a><span class="lineno"> 125</span>  {</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</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="l00127"></a><span class="lineno"> 127</span>  {</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="comment">// Check if the pixel is out-of-bound</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</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="l00130"></a><span class="lineno"> 130</span>  {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> idx = xk + half_width_weights_start;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> idy = yk + half_height_weights_start;</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="keyword">const</span> fixed_point<promoted_type> i_value(in_ptr[offset_slice_in + xk * dilation_x + yk * dilation_y * width_in], fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keyword">const</span> fixed_point<promoted_type> w_value(w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights], fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keyword">const</span> fixed_point<promoted_type> iw = i_value * w_value;</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  acc = iw + acc;</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>  }</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  }</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  }</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// Get the bias</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keyword">const</span> fixed_point<promoted_type> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">b</a>(*b_ptr, fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="comment">// Accumulate the bias and covert back</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  acc = acc + <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">b</a>;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  fixed_point<T> res(acc);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  *out_ptr = res.raw();</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> <span class="comment">// 3D convolution for QASYMM8 type</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00154"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1convolution__3d_1_1detail.xhtml#a0be4a57124877f215e0d37de9e538e81"> 154</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<uint8_t></a> &in, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<uint8_t></a> &weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<int32_t></a> &bias, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<uint8_t></a> &out,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</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="l00156"></a><span class="lineno"> 156</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, <span class="keywordtype">int</span> dilation_y)</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> {</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keyword">const</span> uint8_t *in_ptr = in.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + i_offset;</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keyword">const</span> uint8_t *w_ptr = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + w_offset;</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keyword">const</span> int32_t *b_ptr = bias.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + b_offset;</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  uint8_t *out_ptr = out.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + o_offset;</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> input_offset = -in.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().<a class="code" href="structarm__compute_1_1_quantization_info.xhtml#aed7ea92f45bd273dde380a45ddced592">offset</a>;</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> input_scale = in.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().<a class="code" href="structarm__compute_1_1_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a>;</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> weights_offset = -weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().<a class="code" href="structarm__compute_1_1_quantization_info.xhtml#aed7ea92f45bd273dde380a45ddced592">offset</a>;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> weights_scale = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().<a class="code" href="structarm__compute_1_1_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a>;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> output_offset = out.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().<a class="code" href="structarm__compute_1_1_quantization_info.xhtml#aed7ea92f45bd273dde380a45ddced592">offset</a>;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> output_scale = out.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().<a class="code" href="structarm__compute_1_1_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a>;</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> </div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keywordtype">int</span> output_multiplier = 0;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordtype">int</span> output_shift = 0;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> multiplier = input_scale * weights_scale / output_scale;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <a class="code" href="namespacearm__compute_1_1quantization.xhtml#aa7bd9c3a3bcfe392c90d78e29429db26">arm_compute::quantization::calculate_quantized_multiplier_less_than_one</a>(multiplier, &output_multiplier, &output_shift);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_width_weights_start = width_weights / 2;</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</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="l00177"></a><span class="lineno"> 177</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> half_height_weights_start = height_weights / 2;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</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="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="comment">// Reset accumulator</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  int32_t acc(0);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="comment">// Compute a 2D convolution for each IFM and accumulate the result</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> ifm = 0; ifm < depth_in; ++ifm)</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  {</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="comment">// Compute the offset for the input slice</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</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="l00188"></a><span class="lineno"> 188</span> </div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="comment">// Compute 2D convolution</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</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="l00191"></a><span class="lineno"> 191</span>  {</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</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="l00193"></a><span class="lineno"> 193</span>  {</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="comment">// Check if the pixel is out-of-bound</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</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="l00196"></a><span class="lineno"> 196</span>  {</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> idx = xk + half_width_weights_start;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> idy = yk + half_height_weights_start;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keyword">const</span> uint8_t i_value = in_ptr[offset_slice_in + xk * dilation_x + yk * dilation_y * width_in];</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</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="l00202"></a><span class="lineno"> 202</span> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  acc += (i_value + input_offset) * (w_value + weights_offset);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  }</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  }</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  }</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  }</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> </div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="comment">// Accumulate the bias</span></div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  acc += (*b_ptr);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> </div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  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="l00213"></a><span class="lineno"> 213</span>  acc += output_offset;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  acc = utility::clamp<int32_t>(acc, 0, 255);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="comment">// Store the result</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  *out_ptr = acc;</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> }</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> } <span class="comment">// namespace detail</span></div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> } <span class="comment">// namespace convolution_3d</span></div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> } <span class="comment">// namespace test</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> } <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00223"></a><span class="lineno"> 223</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> |
| 121 | <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_aabcf39e3917f842dbc5fbb0d802f24d5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">arm_compute::test::fixed_point_arithmetic::detail::min</a></div><div class="ttdeci">fixed_point< T > min(fixed_point< T > x, fixed_point< T > y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00897">FixedPoint.h:897</a></div></div> |
| 122 | <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> |
| 123 | <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_xhtml_ac20ca549fa27b2eed44367745055a233"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits.xhtml#ac20ca549fa27b2eed44367745055a233">arm_compute::test::fixed_point_arithmetic::traits::promote_t</a></div><div class="ttdeci">typename promote< T >::type promote_t</div><div class="ttdoc">Get promoted type. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00078">FixedPoint.h:78</a></div></div> |
| 124 | <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> |
| 125 | <div class="ttc" id="namespacearm__compute_1_1quantization_xhtml_aa7bd9c3a3bcfe392c90d78e29429db26"><div class="ttname"><a href="namespacearm__compute_1_1quantization.xhtml#aa7bd9c3a3bcfe392c90d78e29429db26">arm_compute::quantization::calculate_quantized_multiplier_less_than_one</a></div><div class="ttdeci">arm_compute::Status calculate_quantized_multiplier_less_than_one(double multiplier, int *quant_multiplier, int *right_shift)</div><div class="ttdoc">Calculate quantized representation of multiplier with value less than one. </div></div> |
| 126 | <div class="ttc" id="tests_2validation_2_fixed_point_8h_xhtml"><div class="ttname"><a href="tests_2validation_2_fixed_point_8h.xhtml">FixedPoint.h</a></div></div> |
| 127 | <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#l00040">Convolution3d.h:40</a></div></div> |
| 128 | <div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">This file contains all available output stages for GEMMLowp on OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00001">00_introduction.dox:1</a></div></div> |
| 129 | <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> |
| 130 | <div class="ttc" id="structarm__compute_1_1_quantization_info_xhtml_a1d28dec57cce925ad92342891bd71e7c"><div class="ttname"><a href="structarm__compute_1_1_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">arm_compute::QuantizationInfo::scale</a></div><div class="ttdeci">float scale</div><div class="ttdoc">scale </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00167">Types.h:167</a></div></div> |
| 131 | <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a0c52a8f0085b55d907af7210ef2069d0"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">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#l00398">SimpleTensor.h:398</a></div></div> |
| 132 | <div class="ttc" id="_utils_quantized_asymm_8h_xhtml"><div class="ttname"><a href="_utils_quantized_asymm_8h.xhtml">UtilsQuantizedAsymm.h</a></div></div> |
| 133 | <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> |
| 134 | <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ad91bb73431b4de1f4946ed949d444849"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">arm_compute::test::fixed_point_arithmetic::detail::max</a></div><div class="ttdeci">fixed_point< T > max(fixed_point< T > x, fixed_point< T > y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00902">FixedPoint.h:902</a></div></div> |
| 135 | <div class="ttc" id="_asymm_helpers_8h_xhtml"><div class="ttname"><a href="_asymm_helpers_8h.xhtml">AsymmHelpers.h</a></div></div> |
| 136 | <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#l00312">SimpleTensor.h:312</a></div></div> |
| 137 | <div class="ttc" id="structarm__compute_1_1_quantization_info_xhtml_aed7ea92f45bd273dde380a45ddced592"><div class="ttname"><a href="structarm__compute_1_1_quantization_info.xhtml#aed7ea92f45bd273dde380a45ddced592">arm_compute::QuantizationInfo::offset</a></div><div class="ttdeci">int offset</div><div class="ttdoc">offset </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00168">Types.h:168</a></div></div> |
| 138 | <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7b8004eef325a40dd43eb80755610fff"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">arm_compute::test::validation::b</a></div><div class="ttdeci">CLTensor b</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_g_e_m_m_8cpp_source.xhtml#l00122">GEMM.cpp:122</a></div></div> |
| 139 | <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#l00047">Convolution3d.h:47</a></div></div> |
| 140 | <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a35ccf2eb0c18a15feab2db98b307b78b"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">arm_compute::test::SimpleTensor::fixed_point_position</a></div><div class="ttdeci">int fixed_point_position() const override</div><div class="ttdoc">Number of bits for the fractional part. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00306">SimpleTensor.h:306</a></div></div> |
| 141 | </div><!-- fragment --></div><!-- contents --> |
| 142 | </div><!-- doc-content --> |
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| 146 | <li class="navelem"><a class="el" href="dir_59425e443f801f1f2fd8bbe4959a3ccf.xhtml">tests</a></li><li class="navelem"><a class="el" href="dir_e7c7b16542faa38cb4655ff1750d3604.xhtml">validation</a></li><li class="navelem"><a class="el" href="dir_46fdb196cebdbffe77dac340cde62f29.xhtml">reference</a></li><li class="navelem"><a class="el" href="_convolution3d_8h.xhtml">Convolution3d.h</a></li> |
| 147 | <li class="footer">Generated on Wed May 23 2018 11:36:38 for Compute Library by |
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| 149 | <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li> |
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