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<div class="title">ConvolutionFixture.h</div> </div>
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<a href="_convolution_fixture_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>&#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">#ifndef ARM_COMPUTE_TEST_CONVOLUTION_FIXTURE</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;<span class="preprocessor">#define ARM_COMPUTE_TEST_CONVOLUTION_FIXTURE</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_assets_library_8h.xhtml">tests/AssetsLibrary.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="_globals_8h.xhtml">tests/Globals.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="_i_accessor_8h.xhtml">tests/IAccessor.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="_asserts_8h.xhtml">tests/framework/Asserts.h</a>&quot;</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_fixture_8h.xhtml">tests/framework/Fixture.h</a>&quot;</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_convolution_8h.xhtml">tests/validation/reference/Convolution.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="preprocessor">#include &lt;random&gt;</span></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><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></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>test</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>validation</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;{</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> TensorType, <span class="keyword">typename</span> AccessorType, <span class="keyword">typename</span> FunctionType, <span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1validation_1_1_convolution_validation_fixture.xhtml"> 45</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_validation_fixture.xhtml">ConvolutionValidationFixture</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml">framework::Fixture</a></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;{</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160;<span class="keyword">protected</span>:</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keyword">template</span> &lt;<span class="keyword">typename</span>...&gt;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml#a4fc01d736fe50cf5b977f755b675f11d">setup</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height, <span class="keyword">const</span> <span class="keywordtype">bool</span> is_separable = <span class="keyword">false</span>)</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; std::mt19937 gen(<a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;seed());</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; std::uniform_int_distribution&lt;uint8_t&gt; distribution(0, 255);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <span class="keyword">const</span> uint8_t constant_border_value = distribution(gen);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <span class="comment">// Generate random scale value between 1 and 255.</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; std::uniform_int_distribution&lt;uint8_t&gt; distribution_scale(1, 255);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="keyword">const</span> uint32_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a> = distribution_scale(gen);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <a class="code" href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(3 != width &amp;&amp; 5 != width &amp;&amp; 7 != width &amp;&amp; 9 != width);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(3 != height &amp;&amp; 5 != height &amp;&amp; 7 != height &amp;&amp; 9 != height);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; std::vector&lt;int16_t&gt; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adf88bb8e946175c496fb362aa458128b">conv</a>(width * height);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; _width = width;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; _height = height;</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="keywordflow">if</span>(is_separable)</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; create_separable_conv(conv.data());</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; }</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; create_conv(conv.data());</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;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; _target = compute_target(shape, output_data_type, conv.data(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; _reference = compute_reference(shape, output_data_type, conv.data(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; }</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="keywordtype">void</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; create_conv(int16_t *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adf88bb8e946175c496fb362aa458128b">conv</a>)</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; std::mt19937 gen(<a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;seed());</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; std::uniform_int_distribution&lt;int16_t&gt; distribution_int16(-32768, 32767);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; _width * _height; ++i)</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; {</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; conv[i] = distribution_int16(gen);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; }</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; }</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <span class="keywordtype">void</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; create_separable_conv(int16_t *conv)</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; std::mt19937 gen(<a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;seed());</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="comment">// Set it between -128 and 127 to ensure the matrix does not overflow</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; std::uniform_int_distribution&lt;int16_t&gt; distribution_int16(-128, 127);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; int16_t conv_row[_width];</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; int16_t conv_col[_height];</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; conv_row[0] = conv_col[0] = 1;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 1; i &lt; _width; ++i)</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; {</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; conv_row[i] = distribution_int16(gen);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; conv_col[i] = distribution_int16(gen);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; }</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; <span class="comment">// Multiply two matrices</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; _width; ++i)</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; {</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = 0; j &lt; _height; ++j)</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; conv[i * _width + j] = conv_col[i] * conv_row[j];</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;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt;</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keywordtype">void</span> fill(<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> &amp;&amp;tensor, <span class="keywordtype">int</span> i)</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; {</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill_tensor_uniform(tensor, i);</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; }</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;T&gt;</a> compute_reference(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;shape, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> output_data_type, <span class="keyword">const</span> int16_t *conv, uint32_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> border_mode, uint8_t constant_border_value)</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; <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#a6743f0a130e8311e6f5b1a23df102472">src</a>{ <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a> };</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="comment">// Fill reference</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; fill(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">src</a>, 0);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="comment">// Compute reference</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <span class="keywordflow">return</span> reference::convolution&lt;T&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">src</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adf88bb8e946175c496fb362aa458128b">conv</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value, _width, _height);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; }</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160;</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <span class="keyword">virtual</span> TensorType compute_target(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;shape, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> output_data_type, <span class="keyword">const</span> int16_t *conv, uint32_t scale, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> border_mode, uint8_t constant_border_value) = 0;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> _border_mode{};</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; TensorType _target{};</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> _reference{};</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> _width{};</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> _height{};</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160;};</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160;</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> TensorType, <span class="keyword">typename</span> AccessorType, <span class="keyword">typename</span> FunctionType, <span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00147"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1validation_1_1_convolution_square_validation_fixture.xhtml"> 147</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_square_validation_fixture.xhtml">ConvolutionSquareValidationFixture</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_validation_fixture.xhtml">ConvolutionValidationFixture&lt;TensorType, AccessorType, FunctionType, T&gt;</a></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">public</span>:</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="keyword">template</span> &lt;<span class="keyword">typename</span>...&gt;</div><div class="line"><a name="l00151"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1validation_1_1_convolution_square_validation_fixture.xhtml#a2d592461c1375d1ffd76c2fef21a37b7"> 151</a></span>&#160; <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_square_validation_fixture.xhtml#a2d592461c1375d1ffd76c2fef21a37b7">setup</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width)</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; {</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml#a4fc01d736fe50cf5b977f755b675f11d">ConvolutionValidationFixture&lt;TensorType, AccessorType, FunctionType, T&gt;::setup</a>(shape, output_data_type, border_mode, width, width);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; }</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160;</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160;<span class="keyword">protected</span>:</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; TensorType compute_target(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>, <span class="keyword">const</span> int16_t *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adf88bb8e946175c496fb362aa458128b">conv</a>, uint32_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, uint8_t constant_border_value)</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; {</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <span class="comment">// Create tensors</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; TensorType <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">src</a> = create_tensor&lt;TensorType&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; TensorType <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a> = create_tensor&lt;TensorType&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>);</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160;</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; <span class="comment">// Create and configure function</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; FunctionType <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae38161fda91461cff23b750a95e47e6f">convolution</a>;</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; convolution.<a class="code" href="classarm__compute_1_1_c_l_convolution_square.xhtml#a26e1b4686b1f2d591d62d11585114a82">configure</a>(&amp;src, &amp;dst, conv, scale, border_mode, constant_border_value);</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; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(src.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(dst.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <span class="comment">// Allocate tensors</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; src.allocator()-&gt;allocate();</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; dst.allocator()-&gt;allocate();</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; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(!src.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(!dst.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; <span class="comment">// Fill tensors</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; this-&gt;fill(AccessorType(src), 0);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; this-&gt;fill(AccessorType(dst), 1);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160;</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; <span class="comment">// Compute function</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; convolution.run();</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; <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="l00185"></a><span class="lineno"> 185</span>&#160; }</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160;};</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> TensorType, <span class="keyword">typename</span> AccessorType, <span class="keyword">typename</span> FunctionType, <span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00189"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1validation_1_1_convolution_separable_validation_fixture.xhtml"> 189</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_separable_validation_fixture.xhtml">ConvolutionSeparableValidationFixture</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_validation_fixture.xhtml">ConvolutionValidationFixture&lt;TensorType, AccessorType, FunctionType, T&gt;</a></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;<span class="keyword">public</span>:</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; <span class="keyword">template</span> &lt;<span class="keyword">typename</span>...&gt;</div><div class="line"><a name="l00193"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1validation_1_1_convolution_separable_validation_fixture.xhtml#a2d592461c1375d1ffd76c2fef21a37b7"> 193</a></span>&#160; <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_separable_validation_fixture.xhtml#a2d592461c1375d1ffd76c2fef21a37b7">setup</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width)</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; {</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml#a4fc01d736fe50cf5b977f755b675f11d">ConvolutionValidationFixture&lt;TensorType, AccessorType, FunctionType, T&gt;::setup</a>(shape, output_data_type, border_mode, width, width, <span class="keyword">true</span>);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; }</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="keyword">protected</span>:</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; TensorType compute_target(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>, <span class="keyword">const</span> int16_t *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adf88bb8e946175c496fb362aa458128b">conv</a>, uint32_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, uint8_t constant_border_value)</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; <span class="comment">// Create tensors</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; TensorType <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">src</a> = create_tensor&lt;TensorType&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; TensorType <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a> = create_tensor&lt;TensorType&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>);</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; <span class="comment">// Create and configure function</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; FunctionType <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae38161fda91461cff23b750a95e47e6f">convolution</a>;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; convolution.<a class="code" href="classarm__compute_1_1_c_l_convolution_square.xhtml#a26e1b4686b1f2d591d62d11585114a82">configure</a>(&amp;src, &amp;dst, conv, scale, border_mode, constant_border_value);</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; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(src.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(dst.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</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="comment">// Allocate tensors</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; src.allocator()-&gt;allocate();</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; dst.allocator()-&gt;allocate();</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160;</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(!src.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(!dst.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160;</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; <span class="comment">// Fill tensors</span></div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; this-&gt;fill(AccessorType(src), 0);</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; this-&gt;fill(AccessorType(dst), 1);</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; <span class="comment">// Compute function</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; convolution.run();</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</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="l00227"></a><span class="lineno"> 227</span>&#160; }</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160;};</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160;</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> TensorType, <span class="keyword">typename</span> AccessorType, <span class="keyword">typename</span> FunctionType, <span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00231"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1validation_1_1_convolution_rectangle_validation_fixture.xhtml"> 231</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_rectangle_validation_fixture.xhtml">ConvolutionRectangleValidationFixture</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_validation_fixture.xhtml">ConvolutionValidationFixture&lt;TensorType, AccessorType, FunctionType, T&gt;</a></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160;{</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; <span class="keyword">template</span> &lt;<span class="keyword">typename</span>...&gt;</div><div class="line"><a name="l00235"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1validation_1_1_convolution_rectangle_validation_fixture.xhtml#adccf14465cd979b50b5f89eb92acb7c6"> 235</a></span>&#160; <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1test_1_1validation_1_1_convolution_rectangle_validation_fixture.xhtml#adccf14465cd979b50b5f89eb92acb7c6">setup</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height)</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; {</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml#a4fc01d736fe50cf5b977f755b675f11d">ConvolutionValidationFixture&lt;TensorType, AccessorType, FunctionType, T&gt;::setup</a>(shape, output_data_type, border_mode, width, height);</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; }</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160;</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160;<span class="keyword">protected</span>:</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; TensorType compute_target(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>, <span class="keyword">const</span> int16_t *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adf88bb8e946175c496fb362aa458128b">conv</a>, uint32_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, uint8_t constant_border_value)</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; {</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; <span class="comment">// Create tensors</span></div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; TensorType <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">src</a> = create_tensor&lt;TensorType&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; TensorType <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a> = create_tensor&lt;TensorType&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">output_data_type</a>);</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; <span class="comment">// Create and configure function</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; FunctionType <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae38161fda91461cff23b750a95e47e6f">convolution</a>;</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; convolution.<a class="code" href="classarm__compute_1_1_c_l_convolution_square.xhtml#a26e1b4686b1f2d591d62d11585114a82">configure</a>(&amp;src, &amp;dst, conv, this-&gt;_width, this-&gt;_height, scale, border_mode, constant_border_value);</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160;</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(src.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(dst.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160;</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; <span class="comment">// Allocate tensors</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; src.allocator()-&gt;allocate();</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; dst.allocator()-&gt;allocate();</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160;</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(!src.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(!dst.info()-&gt;is_resizable(), <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160;</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; <span class="comment">// Fill tensors</span></div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; this-&gt;fill(AccessorType(src), 0);</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; this-&gt;fill(AccessorType(dst), 1);</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; <span class="comment">// Compute function</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; convolution.run();</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160;</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</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="l00269"></a><span class="lineno"> 269</span>&#160; }</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160;};</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160;} <span class="comment">// namespace validation</span></div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* ARM_COMPUTE_TEST_CONVOLUTION_FIXTURE */</span><span class="preprocessor"></span></div><div class="ttc" id="namespacearm__compute_xhtml_a15a05537a472ee742404821851529327"><div class="ttname"><a href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">arm_compute::BorderMode</a></div><div class="ttdeci">BorderMode</div><div class="ttdoc">Methods available to handle borders. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00221">Types.h:221</a></div></div>
<div class="ttc" id="_i_accessor_8h_xhtml"><div class="ttname"><a href="_i_accessor_8h.xhtml">IAccessor.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_convolution_square_xhtml_a26e1b4686b1f2d591d62d11585114a82"><div class="ttname"><a href="classarm__compute_1_1_c_l_convolution_square.xhtml#a26e1b4686b1f2d591d62d11585114a82">arm_compute::CLConvolutionSquare::configure</a></div><div class="ttdeci">void configure(ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value=0)</div><div class="ttdoc">Initialize the function&amp;#39;s source, destination, conv and border_mode. </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1validation_1_1_convolution_validation_fixture_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1validation_1_1_convolution_validation_fixture.xhtml">arm_compute::test::validation::ConvolutionValidationFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_convolution_fixture_8h_source.xhtml#l00045">ConvolutionFixture.h:45</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00133">Convolution.cpp:133</a></div></div>
<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>
<div class="ttc" id="core_2_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00306">Error.h:306</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::Format::U8</a></div><div class="ttdoc">1 channel, 1 U8 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1validation_1_1_convolution_rectangle_validation_fixture_xhtml_adccf14465cd979b50b5f89eb92acb7c6"><div class="ttname"><a href="classarm__compute_1_1test_1_1validation_1_1_convolution_rectangle_validation_fixture.xhtml#adccf14465cd979b50b5f89eb92acb7c6">arm_compute::test::validation::ConvolutionRectangleValidationFixture::setup</a></div><div class="ttdeci">void setup(TensorShape shape, DataType output_data_type, BorderMode border_mode, const unsigned int width, const unsigned int height)</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_fixture_8h_source.xhtml#l00235">ConvolutionFixture.h:235</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_adf88bb8e946175c496fb362aa458128b"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#adf88bb8e946175c496fb362aa458128b">arm_compute::test::validation::conv</a></div><div class="ttdeci">int16_t conv[25]</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00140">Convolution.cpp:140</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1validation_1_1_convolution_square_validation_fixture_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1validation_1_1_convolution_square_validation_fixture.xhtml">arm_compute::test::validation::ConvolutionSquareValidationFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_convolution_fixture_8h_source.xhtml#l00147">ConvolutionFixture.h:147</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1validation_1_1_convolution_rectangle_validation_fixture_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1validation_1_1_convolution_rectangle_validation_fixture.xhtml">arm_compute::test::validation::ConvolutionRectangleValidationFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_convolution_fixture_8h_source.xhtml#l00231">ConvolutionFixture.h:231</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">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>
<div class="ttc" id="classarm__compute_1_1test_1_1framework_1_1_fixture_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml">arm_compute::test::framework::Fixture</a></div><div class="ttdoc">Abstract fixture class. </div><div class="ttdef"><b>Definition:</b> <a href="_fixture_8h_source.xhtml#l00037">Fixture.h:37</a></div></div>
<div class="ttc" id="_convolution_8h_xhtml"><div class="ttname"><a href="_convolution_8h.xhtml">Convolution.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5471e46933e7a9c4709972d91fc4ea65"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">arm_compute::test::validation::border_mode</a></div><div class="ttdeci">border_mode</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00133">Convolution.cpp:133</a></div></div>
<div class="ttc" id="_globals_8h_xhtml"><div class="ttname"><a href="_globals_8h.xhtml">Globals.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_aa30f40707893f8201695a2c20e2d8c7d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#aa30f40707893f8201695a2c20e2d8c7d">arm_compute::test::validation::output_data_type</a></div><div class="ttdeci">output_data_type</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00133">Convolution.cpp:133</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a71326f0909d77386e29b511e1990a11f"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">arm_compute::test::library</a></div><div class="ttdeci">std::unique_ptr&lt; AssetsLibrary &gt; library</div><div class="ttdef"><b>Definition:</b> <a href="main_8cpp_source.xhtml#l00059">main.cpp:59</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb"><div class="ttname"><a href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::Channel::U</a></div><div class="ttdoc">Cb/U channel. </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1framework_1_1_fixture_xhtml_a4fc01d736fe50cf5b977f755b675f11d"><div class="ttname"><a href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml#a4fc01d736fe50cf5b977f755b675f11d">arm_compute::test::framework::Fixture::setup</a></div><div class="ttdeci">void setup()</div><div class="ttdoc">Setup function. </div><div class="ttdef"><b>Definition:</b> <a href="_fixture_8h_source.xhtml#l00048">Fixture.h:48</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1validation_1_1_convolution_separable_validation_fixture_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1validation_1_1_convolution_separable_validation_fixture.xhtml">arm_compute::test::validation::ConvolutionSeparableValidationFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_convolution_fixture_8h_source.xhtml#l00189">ConvolutionFixture.h:189</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ae38161fda91461cff23b750a95e47e6f"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ae38161fda91461cff23b750a95e47e6f">arm_compute::test::validation::convolution</a></div><div class="ttdeci">CLConvolution5x5 convolution</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00146">Convolution.cpp:146</a></div></div>
<div class="ttc" id="_assets_library_8h_xhtml"><div class="ttname"><a href="_assets_library_8h.xhtml">AssetsLibrary.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_adbf67dcee294e673cf796f1ed8aeb6a4"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">arm_compute::test::validation::dst</a></div><div class="ttdeci">CLTensor dst</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00137">Convolution.cpp:137</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">arm_compute::test::SimpleTensor</a></div><div class="ttdoc">Simple tensor object that stores elements in a consecutive chunk of memory. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00059">SimpleTensor.h:59</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_acec6d8ad52a28972fa74e071c1a63b6a"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">arm_compute::test::validation::scale</a></div><div class="ttdeci">scale</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_pixel_wise_multiplication_8cpp_source.xhtml#l00176">PixelWiseMultiplication.cpp:176</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1validation_1_1_convolution_square_validation_fixture_xhtml_a2d592461c1375d1ffd76c2fef21a37b7"><div class="ttname"><a href="classarm__compute_1_1test_1_1validation_1_1_convolution_square_validation_fixture.xhtml#a2d592461c1375d1ffd76c2fef21a37b7">arm_compute::test::validation::ConvolutionSquareValidationFixture::setup</a></div><div class="ttdeci">void setup(TensorShape shape, DataType output_data_type, BorderMode border_mode, const unsigned int width)</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_fixture_8h_source.xhtml#l00151">ConvolutionFixture.h:151</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_af3c1de77fd86df539395c75c17ec230e"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">arm_compute::test::validation::ARM_COMPUTE_EXPECT</a></div><div class="ttdeci">ARM_COMPUTE_EXPECT(src.info() -&gt;is_resizable(), framework::LogLevel::ERRORS)</div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">arm_compute::test::framework::LogLevel::ERRORS</a></div></div>
<div class="ttc" id="arm__compute_2core_2_types_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_types_8h.xhtml">Types.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00072">Types.h:72</a></div></div>
<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>
<div class="ttc" id="_tensor_shape_8h_xhtml"><div class="ttname"><a href="_tensor_shape_8h.xhtml">TensorShape.h</a></div></div>
<div class="ttc" id="_asserts_8h_xhtml"><div class="ttname"><a href="_asserts_8h.xhtml">Asserts.h</a></div></div>
<div class="ttc" id="_fixture_8h_xhtml"><div class="ttname"><a href="_fixture_8h.xhtml">Fixture.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1validation_1_1_convolution_separable_validation_fixture_xhtml_a2d592461c1375d1ffd76c2fef21a37b7"><div class="ttname"><a href="classarm__compute_1_1test_1_1validation_1_1_convolution_separable_validation_fixture.xhtml#a2d592461c1375d1ffd76c2fef21a37b7">arm_compute::test::validation::ConvolutionSeparableValidationFixture::setup</a></div><div class="ttdeci">void setup(TensorShape shape, DataType output_data_type, BorderMode border_mode, const unsigned int width)</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_fixture_8h_source.xhtml#l00193">ConvolutionFixture.h:193</a></div></div>
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