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<div class="title">CLGEMMLowpMatrixMultiplyKernel.cpp</div> </div>
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<a href="_c_l_g_e_m_m_lowp_matrix_multiply_kernel_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) 2017-2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_g_e_m_m_lowp_matrix_multiply_kernel_8h.xhtml">arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.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="_access_window_static_8h.xhtml">arm_compute/core/AccessWindowStatic.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="_access_window_transpose_8h.xhtml">arm_compute/core/AccessWindowTranspose.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="core_2_c_l_2_c_l_helpers_8h.xhtml">arm_compute/core/CL/CLHelpers.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="_c_l_kernel_library_8h.xhtml">arm_compute/core/CL/CLKernelLibrary.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="_i_c_l_tensor_8h.xhtml">arm_compute/core/CL/ICLTensor.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="_open_c_l_8h.xhtml">arm_compute/core/CL/OpenCL.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="_error_8h.xhtml">arm_compute/core/Error.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="arm__compute_2core_2_helpers_8h.xhtml">arm_compute/core/Helpers.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="_tensor_info_8h.xhtml">arm_compute/core/TensorInfo.h</a>&quot;</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</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="l00036"></a><span class="lineno"> 36</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_utils_8h.xhtml">arm_compute/core/Utils.h</a>&quot;</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_validate_8h.xhtml">arm_compute/core/Validate.h</a>&quot;</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_window_8h.xhtml">arm_compute/core/Window.h</a>&quot;</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_shape_calculator_8h.xhtml">arm_compute/core/utils/misc/ShapeCalculator.h</a>&quot;</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_toolchain_support_8h.xhtml">support/ToolchainSupport.h</a>&quot;</span></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="preprocessor">#include &lt;cstddef&gt;</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;<span class="preprocessor">#include &lt;cstdint&gt;</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;<span class="preprocessor">#include &lt;tuple&gt;</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a>;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml">arm_compute::misc::shape_calculator</a>;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></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;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160;<span class="keyword">namespace</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;{</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160;<span class="keyword">using</span> ElementsProcessed = <a class="code" href="classarm__compute_1_1_steps.xhtml">Steps</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;<a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> validate_arguments(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input0, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml">GEMMReshapeInfo</a> &amp;gemm_info)</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160;{</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>(input0, input1, output);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(input0, 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(input0, input1);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() &gt; 4, <span class="stringliteral">&quot;The number of dimensions for the matrix A must be &lt;= 4&quot;</span>);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() &gt; 3, <span class="stringliteral">&quot;The number of dimensions for the matrix B must be &lt;= 3&quot;</span>);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() &gt; 2 &amp;&amp; gemm_info.<a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#a00330b8913cac3b07029ac0c3350e806">reinterpret_input_as_3d</a>(), <span class="stringliteral">&quot;The input1 tensor cannot have more than 2 dimensions if input0 has to be reinterpreted as 3D&quot;</span>);</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> m = gemm_info.<a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#a137948e04c296b448be2c0de97c6adcb">m</a>();</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> n = gemm_info.<a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#a841b7b7f4c7b50931fabb298cfb7bed3">n</a>();</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> k = gemm_info.<a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#ab86946326c4e33cbfb38cef7312b4ae5">k</a>();</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; <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(m);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(n);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(k);</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; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0) != static_cast&lt;unsigned int&gt;(k));</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0) != static_cast&lt;unsigned int&gt;(n));</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1) != static_cast&lt;unsigned int&gt;(k));</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordflow">if</span>(gemm_info.<a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#a00330b8913cac3b07029ac0c3350e806">reinterpret_input_as_3d</a>())</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; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1) * input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2) != static_cast&lt;unsigned int&gt;(m));</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="keywordflow">else</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; {</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1) != static_cast&lt;unsigned int&gt;(m));</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;</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keywordflow">if</span>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>() != 0)</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> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> tensor_info_output = output-&gt;<a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()-&gt;set_tensor_shape(<a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#adca241b012a5e00ddfcdc5a8db05a2a3">compute_mm_shape</a>(*input0, *input1, <span class="keyword">false</span>, gemm_info));</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <a class="code" href="_validate_8h.xhtml#a27e4638546c88b8916f967e6e54480a9">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a>(output, &amp;tensor_info_output);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(output, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>);</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;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160;}</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160;std::pair&lt;Status, Window&gt; <a class="code" href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">validate_and_configure_window</a>(<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input0, <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input1, <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml">GEMMReshapeInfo</a> &amp;gemm_info, ElementsProcessed &amp;num_elements_processed)</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; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &amp;num_elems_processed_per_iteration_x = num_elements_processed[0];</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &amp;num_elems_processed_per_iteration_y = num_elements_processed[1];</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keywordtype">bool</span> reinterpret_input_as_3d = gemm_info.<a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#a00330b8913cac3b07029ac0c3350e806">reinterpret_input_as_3d</a>();</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keywordtype">bool</span> reinterpret_output_as_3d = (gemm_info.<a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#abbd888f118c2209bf7578eb4f8942a07">depth_output_gemm3d</a>() != 0);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> win{};</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> win_out{};</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="keywordtype">bool</span> window_changed = <span class="keyword">false</span>;</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; <span class="comment">// In case both input and output have to be reinterpreted as 3D tensors,</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="comment">// force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordflow">if</span>(reinterpret_input_as_3d == reinterpret_output_as_3d)</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; reinterpret_input_as_3d = <span class="keyword">false</span>;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; reinterpret_output_as_3d = <span class="keyword">false</span>;</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; <span class="comment">// Output tensor auto inizialitation if not yet initialized</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output, input0-&gt;<a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()-&gt;set_tensor_shape(<a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#adca241b012a5e00ddfcdc5a8db05a2a3">compute_mm_shape</a>(*input0, *input1, <span class="keyword">false</span>, gemm_info)).set_data_type(<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>));</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; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> tmp_info(*output);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="keywordflow">if</span>(reinterpret_output_as_3d)</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="comment">// Since the output tensor has to be reinterpreted as 3D and the execute window is based on a 2D GEMM,</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="comment">// the window needs to be constructed on the 2D collapsed version of the tensor</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> tmp_shape(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>());</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; tmp_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a8e15e87871211f98c2b566137e38ef99">collapse</a>(2<a class="code" href="namespacearm__compute_1_1utils_1_1cast.xhtml#a2ea3d1fc01a3a442900249ca182ffa5e">U</a>, 1<a class="code" href="namespacearm__compute_1_1utils_1_1cast.xhtml#a2ea3d1fc01a3a442900249ca182ffa5e">U</a>);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; tmp_info.set_tensor_shape(tmp_shape);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; }</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">// Special case for 1xN, 2xN, 3xN and 4xN input0 tensor. num_elems_processed_per_iteration_x</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <span class="comment">// Note: if the dot product instruction is available, the 8x2 tile has to be used</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; num_elems_processed_per_iteration_x = 4;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; num_elems_processed_per_iteration_y = std::min(static_cast&lt;int&gt;(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1)), 4);</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="comment">// Note: bottom paddings are calculated manually as the output can be reinterpreted as 3D tensor</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; <span class="comment">// The only way to set properly the paddings, it is to set those explicitly through the AccessWindowStatic</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> m = reinterpret_input_as_3d ? input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[1] * input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[2] : input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[1];</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> bottom_pad = (num_elems_processed_per_iteration_y - (m % num_elems_processed_per_iteration_y)) % num_elems_processed_per_iteration_y;</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">// Configure window</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; win = <a class="code" href="namespacearm__compute.xhtml#ab7980fa5ee693e3282a76da047a1c3b5">calculate_max_window</a>(tmp_info, <a class="code" href="classarm__compute_1_1_steps.xhtml">Steps</a>(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; win_out = <a class="code" href="namespacearm__compute.xhtml#ab7980fa5ee693e3282a76da047a1c3b5">calculate_max_window</a>(*output, <a class="code" href="classarm__compute_1_1_steps.xhtml">Steps</a>(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <a class="code" href="classarm__compute_1_1_access_window_static.xhtml">AccessWindowStatic</a> input0_access(input0, 0, 0, input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0), input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1) + bottom_pad);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <a class="code" href="classarm__compute_1_1_access_window_static.xhtml">AccessWindowStatic</a> input1_access(input1, 0, 0, <a class="code" href="namespacearm__compute.xhtml#ab237a0a375cf382d52b61653248d3d4a">ceil_to_multiple</a>(input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0), num_elems_processed_per_iteration_x), input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1));</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <a class="code" href="classarm__compute_1_1_access_window_static.xhtml">AccessWindowStatic</a> output_access(output, 0, 0,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; <a class="code" href="namespacearm__compute.xhtml#ab237a0a375cf382d52b61653248d3d4a">ceil_to_multiple</a>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0), num_elems_processed_per_iteration_x),</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1) + bottom_pad);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; window_changed = <a class="code" href="namespacearm__compute.xhtml#afc4bd8e872567d9c4c57d89eb0bb3da1">update_window_and_padding</a>(win, input0_access, input1_access) || <span class="comment">// window used by the execute_window_loop</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <a class="code" href="namespacearm__compute.xhtml#afc4bd8e872567d9c4c57d89eb0bb3da1">update_window_and_padding</a>(win_out, output_access); <span class="comment">// window used to update the padding requirements of output tensor</span></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_1_coordinates.xhtml">Coordinates</a> coord;</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; coord.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a810a78f0b7cc0270f38d4136e023ea3b">set_num_dimensions</a>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>());</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; output_access.set_valid_region(win_out, <a class="code" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a>(coord, output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</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="comment">// Collapse along the Z direction</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <span class="comment">// This collapse needs to be here in order to tune the Z dimension of LWS</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> collapsed = win;</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimension_to_collapse = std::min(static_cast&lt;unsigned int&gt;(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>()), 2u);</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; collapsed = win.<a class="code" href="classarm__compute_1_1_window.xhtml#af6303f954929d2bdac13a4712ecf9711">collapse</a>(win, dimension_to_collapse);</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; <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> err = (window_changed) ? <a class="code" href="_error_8h.xhtml#a046fbca6a9505ce038bc02830c739fed">ARM_COMPUTE_CREATE_ERROR</a>(<a class="code" href="namespacearm__compute.xhtml#a59e56af19e754a6aa26a612ebf91d05fa62be47fdd89da032cf78dfce82239579">ErrorCode::RUNTIME_ERROR</a>, <span class="stringliteral">&quot;Insufficient Padding!&quot;</span>) : <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <span class="keywordflow">return</span> std::make_pair(err, collapsed);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160;}</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160;} <span class="comment">// namespace</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;</div><div class="line"><a name="l00168"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a759d01d5376a17c7b81131212588810a"> 168</a></span>&#160;<a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a759d01d5376a17c7b81131212588810a">CLGEMMLowpMatrixMultiplyKernel::CLGEMMLowpMatrixMultiplyKernel</a>()</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; : _input0(nullptr), _input1(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_input_as_3d(false), _reinterpret_output_as_3d(false)</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160;{</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;</div><div class="line"><a name="l00173"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a8aa57bd9c0703378b82393e8f440e9c8"> 173</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a8aa57bd9c0703378b82393e8f440e9c8">CLGEMMLowpMatrixMultiplyKernel::configure</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input0, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input1, <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml">GEMMReshapeInfo</a> &amp;gemm_info)</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160;{</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(input0, input1, output);</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; <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(validate_arguments(input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), gemm_info));</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; _input0 = input0;</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; _input1 = input1;</div><div class="line"><a name="l00181"></a><span 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reinterpret_output_as_3d to be false.</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; <span class="keywordflow">if</span>(_reinterpret_input_as_3d == _reinterpret_output_as_3d)</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160; {</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; _reinterpret_input_as_3d = <span class="keyword">false</span>;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160; _reinterpret_output_as_3d = <span class="keyword">false</span>;</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;</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160; <span class="comment">// Check if we need to slide the matrix B</span></div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_dimensions_input0 = _reinterpret_input_as_3d ? _input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() - 1 : _input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>();</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; _slide_matrix_b = (_input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() &gt;= num_dimensions_input0);</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; ElementsProcessed num_elements_processed{};</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; <span class="comment">// Configure kernel window</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; <span class="keyword">auto</span> win_config = <a class="code" href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">validate_and_configure_window</a>(input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), gemm_info, num_elements_processed);</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(win_config.first);</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; ICLKernel::configure_internal(win_config.second);</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; <span class="comment">// Create build options</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; std::string kernel_name(<span class="stringliteral">&quot; &quot;</span>);</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml">CLBuildOptions</a> build_opts;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; build_opts.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a95b46e69297fad10b27a1baa000f92cc">add_option_if</a>(_reinterpret_input_as_3d, <span class="stringliteral">&quot;-DREINTERPRET_INPUT_AS_3D&quot;</span>);</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; build_opts.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a95b46e69297fad10b27a1baa000f92cc">add_option_if</a>(_reinterpret_output_as_3d, <span class="stringliteral">&quot;-DREINTERPRET_OUTPUT_AS_3D&quot;</span>);</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; build_opts.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a95b46e69297fad10b27a1baa000f92cc">add_option_if</a>(_reinterpret_input_as_3d || _reinterpret_output_as_3d, <span class="stringliteral">&quot;-DHEIGHT_GEMM3D=&quot;</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1)));</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; build_opts.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a95b46e69297fad10b27a1baa000f92cc">add_option_if</a>(_reinterpret_input_as_3d || _reinterpret_output_as_3d, <span class="stringliteral">&quot;-DDEPTH_GEMM3D=&quot;</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2)));</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; build_opts.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a95b46e69297fad10b27a1baa000f92cc">add_option_if</a>(!_slide_matrix_b, <span class="stringliteral">&quot;-DMATRIX_B_DEPTH=&quot;</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2)));</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; build_opts.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(<span class="stringliteral">&quot;-DCOLS_A=&quot;</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0)));</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; build_opts.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(<span class="stringliteral">&quot;-DNUM_ELEMS_PROCESSED_PER_THREAD_X=&quot;</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(num_elements_processed.x()));</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; build_opts.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">add_option</a>(<span class="stringliteral">&quot;-DNUM_ELEMS_PROCESSED_PER_THREAD_Y=&quot;</span> + <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(num_elements_processed.y()));</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; kernel_name = <span class="stringliteral">&quot;gemmlowp_mm_midgard&quot;</span>;</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160;</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; <span class="comment">// Create kernel</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; _kernel = static_cast&lt;cl::Kernel&gt;(<a class="code" href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">CLKernelLibrary::get</a>().<a class="code" href="namespacearm__compute.xhtml#abc72c95941485d8a068fa38372308574">create_kernel</a>(kernel_name, build_opts.<a class="code" href="classarm__compute_1_1_c_l_build_options.xhtml#ae3b08139a1e57323c5d7dd93f30496c8">options</a>()));</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <span class="comment">// Set config_id for enabling LWS tuning</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; _config_id = kernel_name;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; _config_id += <span class="stringliteral">&quot;_&quot;</span>;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; _config_id += (_reinterpret_input_as_3d ? <span class="stringliteral">&quot;3di_&quot;</span> : <span class="stringliteral">&quot;&quot;</span>);</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; _config_id += (_reinterpret_output_as_3d ? <span class="stringliteral">&quot;3do_&quot;</span> : <span class="stringliteral">&quot;&quot;</span>);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; _config_id += <a class="code" href="namespacearm__compute.xhtml#a0a7bb17a0a0414a7162f635776a02eb5">lower_string</a>(<a class="code" href="namespacearm__compute.xhtml#a142b55a483cadf4e1068a1a09a55e8e9">string_from_data_type</a>(input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>()));</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; _config_id += <span class="stringliteral">&quot;_&quot;</span>;</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1));</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; _config_id += <span class="stringliteral">&quot;_&quot;</span>;</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; _config_id += <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">support::cpp11::to_string</a>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0));</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160;}</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"><a class="line" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a9c52840c4fadda388888e26f655de61d"> 233</a></span>&#160;<a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a9c52840c4fadda388888e26f655de61d">CLGEMMLowpMatrixMultiplyKernel::validate</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input0, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input1, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml">GEMMReshapeInfo</a> &amp;gemm_info)</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160;{</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; ElementsProcessed num_elements_processed{};</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(validate_arguments(input0, input1, output, gemm_info));</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">validate_and_configure_window</a>(input0-&gt;<a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>().get(),</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; input1-&gt;<a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>().get(),</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; output-&gt;<a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>().get(),</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; gemm_info,</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; num_elements_processed)</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; .first);</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160;</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160;}</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"><a class="line" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e"> 247</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMLowpMatrixMultiplyKernel::run</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;window, cl::CommandQueue &amp;queue)</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160;{</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; <a class="code" href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a>(<span class="keyword">this</span>);</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <a class="code" href="_validate_8h.xhtml#a6eb9ce82815fe429250189da7592ba75">ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW</a>(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">ICLKernel::window</a>(), <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160;</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; <span class="keywordflow">if</span>(_input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() &lt; 3)</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">// The stride_z for matrix B must be zero if we do not slice</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(_input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a6b14f175bf5281f57b561e2d4e4b1f1f">strides_in_bytes</a>()[3] != 0);</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; }</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="classarm__compute_1_1_window.xhtml">Window</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a> = <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>.<a class="code" href="classarm__compute_1_1_window.xhtml#a30ca5bdbb60ee281d7f1ab34f7a4ee40">first_slice_window_3D</a>();</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> slice_matrix_b = <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</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; slice_matrix_b.<a class="code" href="classarm__compute_1_1_window.xhtml#acd3d2bba51cb84d34dd7656ad2375a6e">set</a>(<a class="code" href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">Window::DimX</a>, <a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml">Window::Dimension</a>(0, 1, 1));</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; slice_matrix_b.<a class="code" href="classarm__compute_1_1_window.xhtml#acd3d2bba51cb84d34dd7656ad2375a6e">set</a>(<a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>, <a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml">Window::Dimension</a>(0, 1, 1));</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160;</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; <span class="keywordflow">if</span>(_reinterpret_input_as_3d)</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; {</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <span class="comment">// Pass bottom paddings to the kernel if the input has to be reinterpreted as 3D tensor</span></div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx0 = 3 * <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a45601e0d46621a5b6f2e417d60e5c800">num_arguments_per_2D_tensor</a>() + 3;</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> total_cross_plane_pad = _input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">padding</a>().<a class="code" href="structarm__compute_1_1_border_size.xhtml#a3fdd42ea34070a54e696b3adc28c4be3">top</a> + _input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">padding</a>().<a class="code" href="structarm__compute_1_1_border_size.xhtml#a802ffcf1b49237efe5be8a314d3f3869">bottom</a>;</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; _kernel.setArg&lt;cl_uint&gt;(idx0, static_cast&lt;unsigned int&gt;(total_cross_plane_pad));</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;</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; <span class="keywordflow">if</span>(_reinterpret_output_as_3d)</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; {</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; <span class="comment">// Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor</span></div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx0 = 3 * <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a45601e0d46621a5b6f2e417d60e5c800">num_arguments_per_2D_tensor</a>() + 3 + (_reinterpret_input_as_3d ? 1 : 0);</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> total_cross_plane_pad = _output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">padding</a>().<a class="code" href="structarm__compute_1_1_border_size.xhtml#a3fdd42ea34070a54e696b3adc28c4be3">top</a> + _output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">padding</a>().<a class="code" href="structarm__compute_1_1_border_size.xhtml#a802ffcf1b49237efe5be8a314d3f3869">bottom</a>;</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; _kernel.setArg&lt;cl_uint&gt;(idx0, static_cast&lt;unsigned int&gt;(total_cross_plane_pad));</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; }</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160;</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; <span class="keywordflow">do</span></div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; {</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> slice_b = <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a>;</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; <span class="comment">// Don&#39;t slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2</span></div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; <span class="comment">// This scenario can happen when the matrix multiplication is used to perform a convolution operation</span></div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; <span class="keywordflow">if</span>(!_slide_matrix_b)</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; {</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; slice_b = slice_matrix_b;</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; }</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160;</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0;</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb">add_2D_tensor_argument</a>(idx, _input0, <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a>);</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb">add_2D_tensor_argument</a>(idx, _input1, slice_b);</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb">add_2D_tensor_argument</a>(idx, _output, <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a>);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; _kernel.setArg&lt;cl_uint&gt;(idx++, static_cast&lt;unsigned int&gt;(_input0-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a6b14f175bf5281f57b561e2d4e4b1f1f">strides_in_bytes</a>()[2]));</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; _kernel.setArg&lt;cl_uint&gt;(idx++, static_cast&lt;unsigned int&gt;(_input1-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a6b14f175bf5281f57b561e2d4e4b1f1f">strides_in_bytes</a>()[2]));</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; _kernel.setArg&lt;cl_uint&gt;(idx++, static_cast&lt;unsigned int&gt;(_output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a6b14f175bf5281f57b561e2d4e4b1f1f">strides_in_bytes</a>()[2]));</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a6e51ab3789678d3e0b0b72178dd6c4c6">enqueue</a>(queue, *<span class="keyword">this</span>, <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a>, <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">lws_hint</a>());</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; }</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; <span class="keywordflow">while</span>(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>.<a class="code" href="classarm__compute_1_1_window.xhtml#aac792e3a11bc73bafafc4f4284c7f215">slide_window_slice_3D</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">slice</a>));</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel_xhtml_a493987e85723a8000eb26d1f00e2ad0e"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">arm_compute::CLGEMMLowpMatrixMultiplyKernel::run</a></div><div class="ttdeci">void run(const Window &amp;window, cl::CommandQueue &amp;queue) override</div><div class="ttdoc">Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_lowp_matrix_multiply_kernel_8cpp_source.xhtml#l00247">CLGEMMLowpMatrixMultiplyKernel.cpp:247</a></div></div>
<div class="ttc" id="structarm__compute_1_1_border_size_xhtml_a3fdd42ea34070a54e696b3adc28c4be3"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml#a3fdd42ea34070a54e696b3adc28c4be3">arm_compute::BorderSize::top</a></div><div class="ttdeci">unsigned int top</div><div class="ttdoc">top of the border</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00339">Types.h:339</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a1f4e725b8e1ea36b30e09dc08ae6961d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">arm_compute::ITensorInfo::num_dimensions</a></div><div class="ttdeci">virtual size_t num_dimensions() const =0</div><div class="ttdoc">The number of dimensions of the tensor (rank)</div></div>
<div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_ad34a46f53686c12a5c5e717cc9617fb6"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const</div><div class="ttdoc">The maximum window the kernel can be executed on.</div><div class="ttdef"><b>Definition:</b> <a href="_i_kernel_8cpp_source.xhtml#l00028">IKernel.cpp:28</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="_toolchain_support_8h_xhtml"><div class="ttname"><a href="_toolchain_support_8h.xhtml">ToolchainSupport.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension.</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a6e51ab3789678d3e0b0b72178dd6c4c6"><div class="ttname"><a href="namespacearm__compute.xhtml#a6e51ab3789678d3e0b0b72178dd6c4c6">arm_compute::enqueue</a></div><div class="ttdeci">void enqueue(cl::CommandQueue &amp;queue, ICLKernel &amp;kernel, const Window &amp;window, const cl::NDRange &amp;lws_hint=CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items=false)</div><div class="ttdoc">Add the kernel to the command queue with the given window.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8cpp_source.xhtml#l00039">ICLKernel.cpp:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_build_options_xhtml_ae3b08139a1e57323c5d7dd93f30496c8"><div class="ttname"><a href="classarm__compute_1_1_c_l_build_options.xhtml#ae3b08139a1e57323c5d7dd93f30496c8">arm_compute::CLBuildOptions::options</a></div><div class="ttdeci">const StringSet &amp; options() const</div><div class="ttdoc">Gets the current options list set.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l00074">CLKernelLibrary.cpp:74</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_a8f3ff7da485ff7e75dab07baadf5b4bd"><div class="ttname"><a href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00545">Validate.h:545</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad6630777dc2d315531f1e0b02491051f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">arm_compute::validate_and_configure_window</a></div><div class="ttdeci">std::pair&lt; Status, Window &gt; validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *output, const PadStrideInfo &amp;conv_info, unsigned int depth_multiplier, const Size2D &amp;dilation)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_native_kernel_8cpp_source.xhtml#l00221">NEDepthwiseConvolutionLayerNativeKernel.cpp:221</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_ab9f813c25ed75ea7b7ac2fa3926a8f55"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">arm_compute::ICLKernel::lws_hint</a></div><div class="ttdeci">cl::NDRange lws_hint() const</div><div class="ttdoc">Return the Local-Workgroup-Size hint.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00247">ICLKernel.h:247</a></div></div>
<div class="ttc" id="classarm__compute_1_1_g_e_m_m_reshape_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml">arm_compute::GEMMReshapeInfo</a></div><div class="ttdoc">GEMM reshape information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01724">Types.h:1724</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a8a1e1c105f0bdaf37db408c7cfcb77a4"><div class="ttname"><a href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ON_ERROR(status)</div><div class="ttdoc">Checks if a status contains an error and returns it.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00193">Error.h:193</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1support_1_1cpp11_xhtml_acc5dddee1cbe93a4eaf0a9f74ee96bb7"><div class="ttname"><a href="namespacearm__compute_1_1support_1_1cpp11.xhtml#acc5dddee1cbe93a4eaf0a9f74ee96bb7">arm_compute::support::cpp11::to_string</a></div><div class="ttdeci">std::string to_string(T &amp;&amp;value)</div><div class="ttdoc">Convert integer and float values to string.</div><div class="ttdef"><b>Definition:</b> <a href="_toolchain_support_8h_source.xhtml#l00242">ToolchainSupport.h:242</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor.</div></div>
<div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_adca241b012a5e00ddfcdc5a8db05a2a3"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#adca241b012a5e00ddfcdc5a8db05a2a3">arm_compute::misc::shape_calculator::compute_mm_shape</a></div><div class="ttdeci">TensorShape compute_mm_shape(const ITensorInfo &amp;input0, const ITensorInfo &amp;input1, bool is_interleaved_transposed, const GEMMReshapeInfo &amp;reshape_info)</div><div class="ttdoc">Calculate the matrix multiplication output shape of two tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l00822">ShapeCalculator.h:822</a></div></div>
<div class="ttc" id="_window_8h_xhtml"><div class="ttname"><a href="_window_8h.xhtml">Window.h</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_ae7eed178dac535c6e727061b1f5bc6eb"><div class="ttname"><a href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00791">Validate.h:791</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00337">Error.h:337</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_kernel_library_xhtml_acba005f5ce2c62cbf3f94d074d9007aa"><div class="ttname"><a href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">arm_compute::CLKernelLibrary::get</a></div><div class="ttdeci">static CLKernelLibrary &amp; get()</div><div class="ttdoc">Access the KernelLibrary singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l01037">CLKernelLibrary.cpp:1037</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml">arm_compute::ITensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_info_8h_source.xhtml#l00040">ITensorInfo.h:40</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00327">Error.h:327</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_1_1_dimension_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window_1_1_dimension.xhtml">arm_compute::Window::Dimension</a></div><div class="ttdoc">Describe one of the image's dimensions with a start, end and step.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00075">Window.h:75</a></div></div>
<div class="ttc" id="structarm__compute_1_1_border_size_xhtml_a802ffcf1b49237efe5be8a314d3f3869"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml#a802ffcf1b49237efe5be8a314d3f3869">arm_compute::BorderSize::bottom</a></div><div class="ttdeci">unsigned int bottom</div><div class="ttdoc">bottom of the border</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00341">Types.h:341</a></div></div>
<div class="ttc" id="classarm__compute_1_1_status_xhtml"><div class="ttname"><a href="classarm__compute_1_1_status.xhtml">arm_compute::Status</a></div><div class="ttdoc">Status class.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00052">Error.h:52</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a046fbca6a9505ce038bc02830c739fed"><div class="ttname"><a href="_error_8h.xhtml#a046fbca6a9505ce038bc02830c739fed">ARM_COMPUTE_CREATE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_CREATE_ERROR(error_code,...)</div><div class="ttdoc">Creates an error with a given message.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00167">Error.h:167</a></div></div>
<div class="ttc" id="core_2_c_l_2_c_l_helpers_8h_xhtml"><div class="ttname"><a href="core_2_c_l_2_c_l_helpers_8h.xhtml">CLHelpers.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a0a7bb17a0a0414a7162f635776a02eb5"><div class="ttname"><a href="namespacearm__compute.xhtml#a0a7bb17a0a0414a7162f635776a02eb5">arm_compute::lower_string</a></div><div class="ttdeci">std::string lower_string(const std::string &amp;val)</div><div class="ttdoc">Lower a given string.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_utils_8cpp_source.xhtml#l00327">Utils.cpp:327</a></div></div>
<div class="ttc" id="_tensor_info_8h_xhtml"><div class="ttname"><a href="_tensor_info_8h.xhtml">TensorInfo.h</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a206d6e247e0957ac3dee45d27756fc25"><div class="ttname"><a href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00244">Error.h:244</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel_xhtml_a759d01d5376a17c7b81131212588810a"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a759d01d5376a17c7b81131212588810a">arm_compute::CLGEMMLowpMatrixMultiplyKernel::CLGEMMLowpMatrixMultiplyKernel</a></div><div class="ttdeci">CLGEMMLowpMatrixMultiplyKernel()</div><div class="ttdoc">Default Constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_lowp_matrix_multiply_kernel_8cpp_source.xhtml#l00168">CLGEMMLowpMatrixMultiplyKernel.cpp:168</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab7980fa5ee693e3282a76da047a1c3b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab7980fa5ee693e3282a76da047a1c3b5">arm_compute::calculate_max_window</a></div><div class="ttdeci">Window calculate_max_window(const ValidRegion &amp;valid_region, const Steps &amp;steps=Steps(), bool skip_border=false, BorderSize border_size=BorderSize())</div><div class="ttdoc">Calculate the maximum window for a given tensor shape and border setting.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_helpers_8cpp_source.xhtml#l00028">Helpers.cpp:28</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2018 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &amp;info, const TensorShape &amp;shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00201">Helpers.inl:201</a></div></div>
<div class="ttc" id="classarm__compute_1_1_access_window_static_xhtml"><div class="ttname"><a href="classarm__compute_1_1_access_window_static.xhtml">arm_compute::AccessWindowStatic</a></div><div class="ttdoc">Implementation of a static rectangular access pattern.</div><div class="ttdef"><b>Definition:</b> <a href="_access_window_static_8h_source.xhtml#l00046">AccessWindowStatic.h:46</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 S32 per channel</div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_build_options_xhtml_a3e2b80ff5463b7d2017de847f5c32a30"><div class="ttname"><a href="classarm__compute_1_1_c_l_build_options.xhtml#a3e2b80ff5463b7d2017de847f5c32a30">arm_compute::CLBuildOptions::add_option</a></div><div class="ttdeci">void add_option(std::string option)</div><div class="ttdoc">Adds option to the existing build option list.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l00043">CLKernelLibrary.cpp:43</a></div></div>
<div class="ttc" id="classarm__compute_1_1_g_e_m_m_reshape_info_xhtml_a841b7b7f4c7b50931fabb298cfb7bed3"><div class="ttname"><a href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#a841b7b7f4c7b50931fabb298cfb7bed3">arm_compute::GEMMReshapeInfo::n</a></div><div class="ttdeci">int n() const</div><div class="ttdoc">Number of matrix B columns.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01762">Types.h:1762</a></div></div>
<div class="ttc" id="arm__compute_2core_2_utils_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_utils_8h.xhtml">Utils.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_af6303f954929d2bdac13a4712ecf9711"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#af6303f954929d2bdac13a4712ecf9711">arm_compute::Window::collapse</a></div><div class="ttdeci">Window collapse(const Window &amp;full_window, size_t first, size_t last=Coordinates::num_max_dimensions) const</div><div class="ttdoc">Collapse the dimensions between first and last.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8inl_source.xhtml#l00097">Window.inl:97</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a142b55a483cadf4e1068a1a09a55e8e9"><div class="ttname"><a href="namespacearm__compute.xhtml#a142b55a483cadf4e1068a1a09a55e8e9">arm_compute::string_from_data_type</a></div><div class="ttdeci">const std::string &amp; string_from_data_type(DataType dt)</div><div class="ttdoc">Convert a data type identity into a string.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_utils_8cpp_source.xhtml#l00144">Utils.cpp:144</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_aa96e81276ee4f87ab386cd05a5539a7d"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">arm_compute::Window::DimX</a></div><div class="ttdeci">static constexpr size_t DimX</div><div class="ttdoc">Alias for dimension 0 also known as X dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00043">Window.h:43</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_afc4bd8e872567d9c4c57d89eb0bb3da1"><div class="ttname"><a href="namespacearm__compute.xhtml#afc4bd8e872567d9c4c57d89eb0bb3da1">arm_compute::update_window_and_padding</a></div><div class="ttdeci">bool update_window_and_padding(Window &amp;win, Ts &amp;&amp;... patterns)</div><div class="ttdoc">Update window and padding size for each of the access patterns.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00402">Helpers.h:402</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00160">Error.h:160</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_a27e4638546c88b8916f967e6e54480a9"><div class="ttname"><a href="_validate_8h.xhtml#a27e4638546c88b8916f967e6e54480a9">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00443">Validate.h:443</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel_xhtml_a9c52840c4fadda388888e26f655de61d"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a9c52840c4fadda388888e26f655de61d">arm_compute::CLGEMMLowpMatrixMultiplyKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, const GEMMReshapeInfo &amp;gemm_info=GEMMReshapeInfo())</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLGEMMLowpMatrixMultiply...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_lowp_matrix_multiply_kernel_8cpp_source.xhtml#l00233">CLGEMMLowpMatrixMultiplyKernel.cpp:233</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape &amp; tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab237a0a375cf382d52b61653248d3d4a"><div class="ttname"><a href="namespacearm__compute.xhtml#ab237a0a375cf382d52b61653248d3d4a">arm_compute::ceil_to_multiple</a></div><div class="ttdeci">auto ceil_to_multiple(S value, T divisor) -&gt; decltype(((value+divisor - 1)/divisor) *divisor)</div><div class="ttdoc">Computes the smallest number larger or equal to value that is a multiple of divisor.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00066">Utils.h:66</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div><div class="ttdoc">quantized, asymmetric fixed-point 8-bit number</div></div>
<div class="ttc" id="classarm__compute_1_1_steps_xhtml"><div class="ttname"><a href="classarm__compute_1_1_steps.xhtml">arm_compute::Steps</a></div><div class="ttdoc">Class to describe a number of elements in each dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_steps_8h_source.xhtml#l00040">Steps.h:40</a></div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item.</div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a86084036bd3851575ef871ad5bf079a7"><div class="ttname"><a href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MSG(cond,...)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00214">Error.h:214</a></div></div>
<div class="ttc" id="_c_l_g_e_m_m_lowp_matrix_multiply_kernel_8h_xhtml"><div class="ttname"><a href="_c_l_g_e_m_m_lowp_matrix_multiply_kernel_8h.xhtml">CLGEMMLowpMatrixMultiplyKernel.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1utils_1_1cast_xhtml_a2ea3d1fc01a3a442900249ca182ffa5e"><div class="ttname"><a href="namespacearm__compute_1_1utils_1_1cast.xhtml#a2ea3d1fc01a3a442900249ca182ffa5e">arm_compute::utils::cast::U</a></div><div class="ttdeci">U</div><div class="ttdef"><b>Definition:</b> <a href="_saturate_cast_8h_source.xhtml#l00057">SaturateCast.h:57</a></div></div>
<div class="ttc" id="_shape_calculator_8h_xhtml"><div class="ttname"><a href="_shape_calculator_8h.xhtml">ShapeCalculator.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1misc_1_1_i_cloneable_xhtml_a4d10e5012a872e7f78f2b539b673049d"><div class="ttname"><a href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">arm_compute::misc::ICloneable::clone</a></div><div class="ttdeci">virtual std::unique_ptr&lt; T &gt; clone() const =0</div><div class="ttdoc">Provide a clone of the current object of class T.</div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div>
<div class="ttc" id="classarm__compute_1_1_g_e_m_m_reshape_info_xhtml_ab86946326c4e33cbfb38cef7312b4ae5"><div class="ttname"><a href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#ab86946326c4e33cbfb38cef7312b4ae5">arm_compute::GEMMReshapeInfo::k</a></div><div class="ttdeci">int k() const</div><div class="ttdoc">Number of matrix A columns or matrix B rows.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01770">Types.h:1770</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_build_options_xhtml_a95b46e69297fad10b27a1baa000f92cc"><div class="ttname"><a href="classarm__compute_1_1_c_l_build_options.xhtml#a95b46e69297fad10b27a1baa000f92cc">arm_compute::CLBuildOptions::add_option_if</a></div><div class="ttdeci">void add_option_if(bool cond, std::string option)</div><div class="ttdoc">Adds option if a given condition is true;.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l00048">CLKernelLibrary.cpp:48</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_acd3d2bba51cb84d34dd7656ad2375a6e"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#acd3d2bba51cb84d34dd7656ad2375a6e">arm_compute::Window::set</a></div><div class="ttdeci">void set(size_t dimension, const Dimension &amp;dim)</div><div class="ttdoc">Set the values of a given dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8inl_source.xhtml#l00048">Window.inl:48</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a07b929c34ad1dc823d8315876aa403ce"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">arm_compute::ITensorInfo::padding</a></div><div class="ttdeci">virtual PaddingSize padding() const =0</div><div class="ttdoc">Padding of tensor.</div></div>
<div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a45601e0d46621a5b6f2e417d60e5c800"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a45601e0d46621a5b6f2e417d60e5c800">arm_compute::ICLKernel::num_arguments_per_2D_tensor</a></div><div class="ttdeci">static constexpr unsigned int num_arguments_per_2D_tensor()</div><div class="ttdoc">Returns the number of arguments enqueued per 2D tensor object.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00192">ICLKernel.h:192</a></div></div>
<div class="ttc" id="_error_8h_xhtml"><div class="ttname"><a href="_error_8h.xhtml">Error.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_build_options_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_build_options.xhtml">arm_compute::CLBuildOptions</a></div><div class="ttdoc">Build options.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8h_source.xhtml#l00037">CLKernelLibrary.h:37</a></div></div>
<div class="ttc" id="_access_window_transpose_8h_xhtml"><div class="ttname"><a href="_access_window_transpose_8h.xhtml">AccessWindowTranspose.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_abc72c95941485d8a068fa38372308574"><div class="ttname"><a href="namespacearm__compute.xhtml#abc72c95941485d8a068fa38372308574">arm_compute::create_kernel</a></div><div class="ttdeci">std::unique_ptr&lt; Kernel &gt; create_kernel()</div><div class="ttdoc">Helper function to create and return a unique_ptr pointed to a CL/GLES kernel object.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00086">Helpers.h:86</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_aac792e3a11bc73bafafc4f4284c7f215"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#aac792e3a11bc73bafafc4f4284c7f215">arm_compute::Window::slide_window_slice_3D</a></div><div class="ttdeci">bool slide_window_slice_3D(Window &amp;slice) const</div><div class="ttdoc">Slide the passed 3D window slice.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00319">Window.h:319</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a59e56af19e754a6aa26a612ebf91d05fa62be47fdd89da032cf78dfce82239579"><div class="ttname"><a href="namespacearm__compute.xhtml#a59e56af19e754a6aa26a612ebf91d05fa62be47fdd89da032cf78dfce82239579">arm_compute::ErrorCode::RUNTIME_ERROR</a></div><div class="ttdoc">Generic runtime error.</div></div>
<div class="ttc" id="_validate_8h_xhtml_aff911654521523937ff24372a870b89f"><div class="ttname"><a href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00163">Validate.h:163</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_ad2d402364fa822b0b7775081291eeca9"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">arm_compute::Window::DimY</a></div><div class="ttdeci">static constexpr size_t DimY</div><div class="ttdoc">Alias for dimension 1 also known as Y dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00045">Window.h:45</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_ac74dad3e61f79334f5e73f3c3ac603cb"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb">arm_compute::ICLKernel::add_2D_tensor_argument</a></div><div class="ttdeci">void add_2D_tensor_argument(unsigned int &amp;idx, const ICLTensor *tensor, const Window &amp;window)</div><div class="ttdoc">Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00134">ICLKernel.h:134</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_a921b705e9e3e0fe928928447869e62a5"><div class="ttname"><a href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00161">Validate.h:161</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_c_l_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_tensor.xhtml">arm_compute::ICLTensor</a></div><div class="ttdoc">Interface for OpenCL tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_tensor_8h_source.xhtml#l00042">ICLTensor.h:42</a></div></div>
<div class="ttc" id="_i_c_l_tensor_8h_xhtml"><div class="ttname"><a href="_i_c_l_tensor_8h.xhtml">ICLTensor.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a18064e0011c3869d884653e9e7c47b66"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">arm_compute::ITensorInfo::total_size</a></div><div class="ttdeci">virtual size_t total_size() const =0</div><div class="ttdoc">Returns the total size of the tensor in bytes.</div></div>
<div class="ttc" id="classarm__compute_1_1_g_e_m_m_reshape_info_xhtml_a137948e04c296b448be2c0de97c6adcb"><div class="ttname"><a href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#a137948e04c296b448be2c0de97c6adcb">arm_compute::GEMMReshapeInfo::m</a></div><div class="ttdeci">int m() const</div><div class="ttdoc">Number of matrix A rows.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01754">Types.h:1754</a></div></div>
<div class="ttc" id="_c_l_kernel_library_8h_xhtml"><div class="ttname"><a href="_c_l_kernel_library_8h.xhtml">CLKernelLibrary.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel_xhtml_a8aa57bd9c0703378b82393e8f440e9c8"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a8aa57bd9c0703378b82393e8f440e9c8">arm_compute::CLGEMMLowpMatrixMultiplyKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMReshapeInfo &amp;gemm_info=GEMMReshapeInfo())</div><div class="ttdoc">Initialise the kernel's input and output.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_lowp_matrix_multiply_kernel_8cpp_source.xhtml#l00173">CLGEMMLowpMatrixMultiplyKernel.cpp:173</a></div></div>
<div class="ttc" id="_open_c_l_8h_xhtml"><div class="ttname"><a href="_open_c_l_8h.xhtml">OpenCL.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_g_e_m_m_reshape_info_xhtml_abbd888f118c2209bf7578eb4f8942a07"><div class="ttname"><a href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#abbd888f118c2209bf7578eb4f8942a07">arm_compute::GEMMReshapeInfo::depth_output_gemm3d</a></div><div class="ttdeci">int depth_output_gemm3d() const</div><div class="ttdoc">Depth (third dimension) of the output tensor to be used with the GEMM3D kernel.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01797">Types.h:1797</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div>
<div class="ttc" id="arm__compute_2core_2_helpers_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_helpers_8h.xhtml">Helpers.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml">arm_compute::misc::shape_calculator</a></div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l00040">ShapeCalculator.h:40</a></div></div>
<div class="ttc" id="_access_window_static_8h_xhtml"><div class="ttname"><a href="_access_window_static_8h.xhtml">AccessWindowStatic.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a810a78f0b7cc0270f38d4136e023ea3b"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a810a78f0b7cc0270f38d4136e023ea3b">arm_compute::Dimensions::set_num_dimensions</a></div><div class="ttdeci">void set_num_dimensions(size_t num_dimensions)</div><div class="ttdoc">Set number of dimensions.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00128">Dimensions.h:128</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a6b14f175bf5281f57b561e2d4e4b1f1f"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a6b14f175bf5281f57b561e2d4e4b1f1f">arm_compute::ITensorInfo::strides_in_bytes</a></div><div class="ttdeci">virtual const Strides &amp; strides_in_bytes() const =0</div><div class="ttdoc">The strides in bytes for accessing each dimension of the tensor.</div></div>
<div class="ttc" id="structarm__compute_1_1_valid_region_xhtml"><div class="ttname"><a href="structarm__compute_1_1_valid_region.xhtml">arm_compute::ValidRegion</a></div><div class="ttdoc">Container for valid region of a window.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00174">Types.h:174</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_a30ca5bdbb60ee281d7f1ab34f7a4ee40"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a30ca5bdbb60ee281d7f1ab34f7a4ee40">arm_compute::Window::first_slice_window_3D</a></div><div class="ttdeci">Window first_slice_window_3D() const</div><div class="ttdoc">First 3D slice of the window.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00275">Window.h:275</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="_validate_8h_xhtml_a6eb9ce82815fe429250189da7592ba75"><div class="ttname"><a href="_validate_8h.xhtml#a6eb9ce82815fe429250189da7592ba75">ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00205">Validate.h:205</a></div></div>
<div class="ttc" id="classarm__compute_1_1_g_e_m_m_reshape_info_xhtml_a00330b8913cac3b07029ac0c3350e806"><div class="ttname"><a href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#a00330b8913cac3b07029ac0c3350e806">arm_compute::GEMMReshapeInfo::reinterpret_input_as_3d</a></div><div class="ttdeci">bool reinterpret_input_as_3d() const</div><div class="ttdoc">Flag which specifies if the input tensor has to be reinterpreted as 3D.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01805">Types.h:1805</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml">arm_compute::Window</a></div><div class="ttdoc">Describe a multidimensional execution window.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00039">Window.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a8e15e87871211f98c2b566137e38ef99"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a8e15e87871211f98c2b566137e38ef99">arm_compute::TensorShape::collapse</a></div><div class="ttdeci">void collapse(size_t n, size_t first=0)</div><div class="ttdoc">Collapse the first n dimensions.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00132">TensorShape.h:132</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_a1b35b0d258183cf9ef36adf684d0b88c"><div class="ttname"><a href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00940">Validate.h:940</a></div></div>
<div class="ttc" id="_validate_8h_xhtml"><div class="ttname"><a href="_validate_8h.xhtml">Validate.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a548131b3d37da47a2e9d32111c88dfe1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a548131b3d37da47a2e9d32111c88dfe1">arm_compute::test::validation::reference::slice</a></div><div class="ttdeci">SimpleTensor&lt; T &gt; slice(const SimpleTensor&lt; T &gt; &amp;src, Coordinates starts, Coordinates ends)</div><div class="ttdef"><b>Definition:</b> <a href="_slice_operations_8cpp_source.xhtml#l00038">SliceOperations.cpp:38</a></div></div>
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