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 120 <a href="validation_2reference_2_depthwise_convolution_layer_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) 2017-2018 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="_depthwise_convolution_layer_8h.xhtml">DepthwiseConvolutionLayer.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="_convolution_layer_8h.xhtml">ConvolutionLayer.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_2reference_2_utils_8h.xhtml">Utils.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tests_2validation_2_fixed_point_8h.xhtml">tests/validation/FixedPoint.h</a>&quot;</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</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="l00031"></a><span class="lineno">   31</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="l00032"></a><span class="lineno">   32</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_utils_quantized_asymm_8h.xhtml">tests/validation/reference/UtilsQuantizedAsymm.h</a>&quot;</span></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="preprocessor">#include &quot;<a class="code" href="_asymm_helpers_8h.xhtml">arm_compute/core/utils/quantization/AsymmHelpers.h</a>&quot;</span></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><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></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">namespace </span>test</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;{</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="keyword">namespace </span>validation</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;{</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="keyword">namespace </span>reference</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;{</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keyword">typename</span> TB&gt;</div><div class="line"><a name="l00053"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a61c5b469efbad8508f073665649c20ac">   53</a></span>&#160;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a61c5b469efbad8508f073665649c20ac">depthwise_convolution</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#a6743f0a130e8311e6f5b1a23df102472">src</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;weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;TB&gt;</a> &amp;biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;dst_shape, <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#acbf8f8a6dd185de04c1981c57a8963cf">conv_info</a>,</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;                                      <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier)</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;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>{ dst_shape, src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>(), 1, src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">fixed_point_position</a>() };</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <span class="comment">// Compute reference</span></div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a23a07c975b13e0133e838d850dcf30c5">filter_width</a>  = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x();</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ab9960ce2e784cfff275d273c1810797f">filter_height</a> = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().y();</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> filter_plane  = filter_width * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ab9960ce2e784cfff275d273c1810797f">filter_height</a>;</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> input_width   = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x();</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> input_height  = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().y();</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> input_depth   = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().z();</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> num_batches   = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().total_size() / (input_width * input_height * input_depth);</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> filter_half_width  = filter_width / 2;</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> filter_half_height = filter_height / 2;</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> pad_left   = conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#a377481844bf0459e5ef871cc72d72496">pad_left</a>();</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> pad_top    = conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#a2a86593e913939d9eadad26c2df65138">pad_top</a>();</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> pad_right  = conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#afaaf8f4d7fa22fe9a3f4ff41567cd886">pad_right</a>();</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> pad_bottom = conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#a2d3a66a044dcf4217d97f6b47319d5f1">pad_bottom</a>();</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> minimum_x = -pad_left + filter_half_width;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> minimum_y = -pad_top + filter_half_height;</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> maximum_x = input_width + pad_left - filter_half_width + pad_right - filter_half_width;</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> maximum_y = input_height + pad_top - filter_half_height + pad_bottom - filter_half_height;</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;    <span class="keyword">const</span> T border_value(0);</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;    <span class="keywordtype">int</span> out_pos = 0;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r &lt; num_batches; ++r)</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;        <span class="keywordflow">for</span>(<span class="keywordtype">int</span> z = 0; z &lt; input_depth; ++z)</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;            <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m = 0; m &lt; depth_multiplier; ++m)</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;                <span class="keyword">const</span> <span class="keywordtype">int</span> out_z = z * depth_multiplier + m;</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;                <span class="keywordflow">for</span>(<span class="keywordtype">int</span> y = minimum_y; y &lt; minimum_y + maximum_y; y += conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#ad2f1ea50a9e215ad8ef612a724a4866a">stride</a>().second)</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;                {</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;                    <span class="keywordflow">for</span>(<span class="keywordtype">int</span> x = minimum_x; x &lt; minimum_x + maximum_x; x += conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#ad2f1ea50a9e215ad8ef612a724a4866a">stride</a>().first)</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="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> coords(static_cast&lt;int&gt;(x), static_cast&lt;int&gt;(y), static_cast&lt;int&gt;(z), static_cast&lt;int&gt;(r));</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;                        <span class="keywordtype">size_t</span>      filter_offset = filter_plane * out_z;</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;                        T val(0);</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;                        <span class="keywordflow">for</span>(<span class="keywordtype">int</span> j = y - filter_half_height; j &lt;= static_cast&lt;int&gt;(y + filter_half_height); ++j)</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;                        {</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;                            <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = x - filter_half_width; i &lt;= static_cast&lt;int&gt;(x + filter_half_width); ++i)</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;                            {</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;                                coords.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a982730e6f0da5f9490f59bc5f6bb3f27">set</a>(0, i);</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;                                coords.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a982730e6f0da5f9490f59bc5f6bb3f27">set</a>(1, j);</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;                                val += *(weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + filter_offset) * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f489943d8618d47b1ad4611f0b9b7ff">tensor_elem_at</a>(src, coords, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a8d6b5cada83510220f59e00ce86d4d92">BorderMode::CONSTANT</a>, border_value);</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;                                ++filter_offset;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;                            }</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;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;                        <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[out_pos++] = <a class="code" href="namespacearm__compute_1_1test.xhtml#a4965b2f6821e0cf0afee738158bd8377">saturate_cast</a>&lt;T&gt;(val + *<span class="keyword">static_cast&lt;</span><span class="keyword">const </span>TB *<span class="keyword">&gt;</span>(biases(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(out_z))));</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;                }</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;        }</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;</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>;</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;}</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="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a1a53e3be4e81fac0a8edd23615195abd">  122</a></span>&#160;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a61c5b469efbad8508f073665649c20ac">depthwise_convolution</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#a6743f0a130e8311e6f5b1a23df102472">src</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;weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int32_t&gt;</a> &amp;biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;dst_shape,</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;                                            <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#acbf8f8a6dd185de04c1981c57a8963cf">conv_info</a>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier)</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;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>{ dst_shape, src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>(), 1, src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">fixed_point_position</a>(), src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>() };</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;    <span class="comment">// Create reference</span></div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span>   input_offset   = -src.<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="l00129"></a><span class="lineno">  129</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">float</span> input_scale    = src.<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="l00130"></a><span class="lineno">  130</span>&#160;    <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="l00131"></a><span class="lineno">  131</span>&#160;    <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="l00132"></a><span class="lineno">  132</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span>   output_offset  = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.quantization_info().offset;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">float</span> output_scale   = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.quantization_info().scale;</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;    <span class="keywordtype">int</span>         output_multiplier;</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    <span class="keywordtype">int</span>         output_shift;</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">float</span> multiplier = input_scale * weights_scale / output_scale;</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    <a class="code" href="namespacearm__compute_1_1quantization.xhtml#aa7bd9c3a3bcfe392c90d78e29429db26">arm_compute::quantization::calculate_quantized_multiplier_less_than_one</a>(multiplier, &amp;output_multiplier, &amp;output_shift);</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;    <span class="comment">// Compute reference</span></div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a23a07c975b13e0133e838d850dcf30c5">filter_width</a>  = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().<a class="code" href="classarm__compute_1_1_dimensions.xhtml#afb5cd37bb08f1029691590372e6330f0">x</a>();</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ab9960ce2e784cfff275d273c1810797f">filter_height</a> = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a691c9cb93365c2e33f3429de43244098">y</a>();</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> filter_plane  = filter_width * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ab9960ce2e784cfff275d273c1810797f">filter_height</a>;</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> input_width   = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().<a class="code" href="classarm__compute_1_1_dimensions.xhtml#afb5cd37bb08f1029691590372e6330f0">x</a>();</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> input_height  = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a691c9cb93365c2e33f3429de43244098">y</a>();</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> input_depth   = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a336121cb63ed79fa0a072eed03d694ac">z</a>();</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> num_batches   = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">total_size</a>() / (input_width * input_height * input_depth);</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> filter_half_width  = filter_width / 2;</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> filter_half_height = filter_height / 2;</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> pad_left   = conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#a377481844bf0459e5ef871cc72d72496">pad_left</a>();</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> pad_top    = conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#a2a86593e913939d9eadad26c2df65138">pad_top</a>();</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> pad_right  = conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#afaaf8f4d7fa22fe9a3f4ff41567cd886">pad_right</a>();</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> pad_bottom = conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#a2d3a66a044dcf4217d97f6b47319d5f1">pad_bottom</a>();</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> minimum_x = -pad_left + filter_half_width;</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> minimum_y = -pad_top + filter_half_height;</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> maximum_x = input_width + pad_left - filter_half_width + pad_right - filter_half_width;</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> maximum_y = input_height + pad_top - filter_half_height + pad_bottom - filter_half_height;</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;    <span class="keywordtype">int</span> out_pos = 0;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r &lt; num_batches; ++r)</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;    {</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">int</span> z = 0; z &lt; input_depth; ++z)</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;        {</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;            <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m = 0; m &lt; depth_multiplier; ++m)</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;            {</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;                <span class="keyword">const</span> <span class="keywordtype">int</span>     out_z    = z * depth_multiplier + m;</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;                <span class="keyword">const</span> int32_t bias_val = *<span class="keyword">static_cast&lt;</span><span class="keyword">const </span>int32_t *<span class="keyword">&gt;</span>(biases(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(out_z)));</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;                <span class="keywordflow">for</span>(<span class="keywordtype">int</span> y = minimum_y; y &lt; minimum_y + maximum_y; y += conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#ad2f1ea50a9e215ad8ef612a724a4866a">stride</a>().second)</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;                {</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;                    <span class="keywordflow">for</span>(<span class="keywordtype">int</span> x = minimum_x; x &lt; minimum_x + maximum_x; x += conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#ad2f1ea50a9e215ad8ef612a724a4866a">stride</a>().first)</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;                    {</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;                        <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> coords(x, y, z, r);</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                        <span class="keywordtype">int</span>         filter_offset = filter_plane * out_z;</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;                        int32_t val = 0;</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;                        <span class="keywordflow">for</span>(<span class="keywordtype">int</span> j = y - filter_half_height; j &lt;= (y + filter_half_height); ++j)</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;                        {</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;                            <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = x - filter_half_width; i &lt;= (x + filter_half_width); ++i)</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;                            {</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;                                coords.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a982730e6f0da5f9490f59bc5f6bb3f27">set</a>(0, i);</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;                                coords.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a982730e6f0da5f9490f59bc5f6bb3f27">set</a>(1, j);</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;                                <span class="keyword">const</span> <span class="keyword">auto</span>    in_val = tensor_elem_at&lt;uint8_t&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">src</a>, coords, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a8d6b5cada83510220f59e00ce86d4d92">BorderMode::CONSTANT</a>, -input_offset);</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;                                <span class="keyword">const</span> uint8_t w_val  = *(weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + filter_offset);</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;                                val += (in_val + input_offset) * (w_val + weights_offset);</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;                                ++filter_offset;</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;                            }</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;                        }</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;                        val += bias_val;</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;                        val = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5bab95cbeb5c6bf05049df7afd32d823">asymm_rounding_divide_by_pow2</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aea27abcd3d58d627282320dfdd213596">asymm_int_mult</a>(val, output_multiplier), output_shift);</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;                        val += output_offset;</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;                        val = std::max&lt;int32_t&gt;(val, 0);</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;                        val = std::min&lt;int32_t&gt;(val, 255);</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;                        <span class="comment">// Store the result</span></div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;                        <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[out_pos++] = val;</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;                    }</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;                }</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;            }</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;        }</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;    }</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>;</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;}</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a61c5b469efbad8508f073665649c20ac">depthwise_convolution</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#a6743f0a130e8311e6f5b1a23df102472">src</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;weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> &amp;biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;dst_shape,</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;                                                   <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#acbf8f8a6dd185de04c1981c57a8963cf">conv_info</a>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier);</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;half&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a61c5b469efbad8508f073665649c20ac">depthwise_convolution</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;src, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;half&gt;</a> &amp;weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;half&gt;</a> &amp;biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;dst_shape,</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;                                                  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;conv_info, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth_multiplier);</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;} <span class="comment">// namespace reference</span></div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;} <span class="comment">// namespace validation</span></div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;} <span class="comment">// namespace arm_compute</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_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>
 122 <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a336121cb63ed79fa0a072eed03d694ac"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a336121cb63ed79fa0a072eed03d694ac">arm_compute::Dimensions::z</a></div><div class="ttdeci">T z() const </div><div class="ttdoc">Alias to access the size of the third dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00091">Dimensions.h:91</a></div></div>
 123 <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
 124 <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>
 125 <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a9a3e72153aeb3ed212e9c3698774e881"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">arm_compute::test::SimpleTensor::data_type</a></div><div class="ttdeci">DataType data_type() const override</div><div class="ttdoc">Data type of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00337">SimpleTensor.h:337</a></div></div>
 126 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a61c5b469efbad8508f073665649c20ac"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a61c5b469efbad8508f073665649c20ac">arm_compute::test::validation::reference::depthwise_convolution</a></div><div class="ttdeci">SimpleTensor&lt; T &gt; depthwise_convolution(const SimpleTensor&lt; T &gt; &amp;src, const SimpleTensor&lt; T &gt; &amp;weights, const SimpleTensor&lt; TB &gt; &amp;biases, const TensorShape &amp;dst_shape, const PadStrideInfo &amp;conv_info, unsigned int depth_multiplier)</div><div class="ttdoc">Perform a depthwise convolution. </div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_depthwise_convolution_layer_8cpp_source.xhtml#l00053">DepthwiseConvolutionLayer.cpp:53</a></div></div>
 127 <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>
 128 <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>
 129 <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_aba5871b3e4a65d057ec1c28fce8b00ba"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">arm_compute::test::SimpleTensor::shape</a></div><div class="ttdeci">TensorShape shape() const override</div><div class="ttdoc">Shape of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00294">SimpleTensor.h:294</a></div></div>
 130 <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>
 131 <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a982730e6f0da5f9490f59bc5f6bb3f27"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a982730e6f0da5f9490f59bc5f6bb3f27">arm_compute::Dimensions::set</a></div><div class="ttdeci">void set(size_t dimension, T value)</div><div class="ttdoc">Accessor to set the value of one of the dimensions. </div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00074">Dimensions.h:74</a></div></div>
 132 <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>
 133 <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_afb5cd37bb08f1029691590372e6330f0"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#afb5cd37bb08f1029691590372e6330f0">arm_compute::Dimensions::x</a></div><div class="ttdeci">T x() const </div><div class="ttdoc">Alias to access the size of the first dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00081">Dimensions.h:81</a></div></div>
 134 <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>
 135 <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>
 136 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a23a07c975b13e0133e838d850dcf30c5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a23a07c975b13e0133e838d850dcf30c5">arm_compute::test::validation::filter_width</a></div><div class="ttdeci">filter_width</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00387">Convolution.cpp:387</a></div></div>
 137 <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>
 138 <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml_ad2f1ea50a9e215ad8ef612a724a4866a"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml#ad2f1ea50a9e215ad8ef612a724a4866a">arm_compute::PadStrideInfo::stride</a></div><div class="ttdeci">std::pair&lt; unsigned int, unsigned int &gt; stride() const </div><div class="ttdoc">Get the stride. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00619">Types.h:619</a></div></div>
 139 <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>
 140 <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml_a2d3a66a044dcf4217d97f6b47319d5f1"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml#a2d3a66a044dcf4217d97f6b47319d5f1">arm_compute::PadStrideInfo::pad_bottom</a></div><div class="ttdeci">unsigned int pad_bottom() const </div><div class="ttdoc">Get the bottom padding. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00660">Types.h:660</a></div></div>
 141 <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#l00571">Types.h:571</a></div></div>
 142 <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_convolution_8cpp_source.xhtml#l00137">Convolution.cpp:137</a></div></div>
 143 <div class="ttc" id="_utils_quantized_asymm_8h_xhtml"><div class="ttname"><a href="_utils_quantized_asymm_8h.xhtml">UtilsQuantizedAsymm.h</a></div></div>
 144 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_acbf8f8a6dd185de04c1981c57a8963cf"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#acbf8f8a6dd185de04c1981c57a8963cf">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#l00360">Winograd.cpp:360</a></div></div>
 145 <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml_afaaf8f4d7fa22fe9a3f4ff41567cd886"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml#afaaf8f4d7fa22fe9a3f4ff41567cd886">arm_compute::PadStrideInfo::pad_right</a></div><div class="ttdeci">unsigned int pad_right() const </div><div class="ttdoc">Get the right padding. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00650">Types.h:650</a></div></div>
 146 <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>
 147 <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a691c9cb93365c2e33f3429de43244098"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a691c9cb93365c2e33f3429de43244098">arm_compute::Dimensions::y</a></div><div class="ttdeci">T y() const </div><div class="ttdoc">Alias to access the size of the second dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00086">Dimensions.h:86</a></div></div>
 148 <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml_a377481844bf0459e5ef871cc72d72496"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml#a377481844bf0459e5ef871cc72d72496">arm_compute::PadStrideInfo::pad_left</a></div><div class="ttdeci">unsigned int pad_left() const </div><div class="ttdoc">Get the left padding. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00645">Types.h:645</a></div></div>
 149 <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a4965b2f6821e0cf0afee738158bd8377"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a4965b2f6821e0cf0afee738158bd8377">arm_compute::test::saturate_cast</a></div><div class="ttdeci">T saturate_cast(T val)</div><div class="ttdoc">Saturate a value of type T against the numeric limits of type U. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00373">Utils.h:373</a></div></div>
 150 <div class="ttc" id="namespacearm__compute_xhtml_a15a05537a472ee742404821851529327a8d6b5cada83510220f59e00ce86d4d92"><div class="ttname"><a href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a8d6b5cada83510220f59e00ce86d4d92">arm_compute::BorderMode::CONSTANT</a></div><div class="ttdoc">Pixels outside the image are assumed to have a constant value. </div></div>
 151 <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a4eaec01ba2c12093db609d1034ad0bc1"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">arm_compute::TensorShape::total_size</a></div><div class="ttdeci">size_t total_size() const </div><div class="ttdoc">Collapses all dimensions to a single linear total size. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00157">TensorShape.h:157</a></div></div>
 152 <div class="ttc" id="_depthwise_convolution_layer_8h_xhtml"><div class="ttname"><a href="_depthwise_convolution_layer_8h.xhtml">DepthwiseConvolutionLayer.h</a></div></div>
 153 <div class="ttc" id="_asymm_helpers_8h_xhtml"><div class="ttname"><a href="_asymm_helpers_8h.xhtml">AsymmHelpers.h</a></div></div>
 154 <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>
 155 <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>
 156 <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>
 157 <div class="ttc" id="_convolution_layer_8h_xhtml"><div class="ttname"><a href="_convolution_layer_8h.xhtml">ConvolutionLayer.h</a></div></div>
 158 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a6743f0a130e8311e6f5b1a23df102472"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">arm_compute::test::validation::src</a></div><div class="ttdeci">convolution configure &amp; src</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00147">Convolution.cpp:147</a></div></div>
 159 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ab9960ce2e784cfff275d273c1810797f"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ab9960ce2e784cfff275d273c1810797f">arm_compute::test::validation::filter_height</a></div><div class="ttdeci">filter_height</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00388">Convolution.cpp:388</a></div></div>
 160 <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml_a2a86593e913939d9eadad26c2df65138"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml#a2a86593e913939d9eadad26c2df65138">arm_compute::PadStrideInfo::pad_top</a></div><div class="ttdeci">unsigned int pad_top() const </div><div class="ttdoc">Get the top padding. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00655">Types.h:655</a></div></div>
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