Google Git
Sign in
android / platform / external / ComputeLibrary / 7f09cf7df / . / documentation / _n_e_convolution_8cpp_source.xhtml
blob: 53b98faa0a20cbb0aca6670bb080e546a4156495 [file] [log] [blame]
<!-- HTML header for doxygen 1.8.15-->
<!-- Remember to use version doxygen 1.8.15 +-->
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
<meta http-equiv="X-UA-Compatible" content="IE=9"/>
<meta name="generator" content="Doxygen 1.8.15"/>
<meta name="robots" content="NOINDEX, NOFOLLOW" /> <!-- Prevent indexing by search engines -->
<title>Compute Library: src/runtime/NEON/functions/NEConvolution.cpp Source File</title>
<link href="tabs.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<link href="navtree.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="resize.js"></script>
<script type="text/javascript" src="navtreedata.js"></script>
<script type="text/javascript" src="navtree.js"></script>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(document).ready(initResizable);
/* @license-end */</script>
<link href="search/search.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="search/searchdata.js"></script>
<script type="text/javascript" src="search/search.js"></script>
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
extensions: ["tex2jax.js"],
jax: ["input/TeX","output/HTML-CSS"],
});
</script><script type="text/javascript" async="async" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script>
<link href="doxygen.css" rel="stylesheet" type="text/css" />
<link href="stylesheet.css" rel="stylesheet" type="text/css"/>
</head>
<body>
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
<div id="titlearea">
<table cellspacing="0" cellpadding="0">
<tbody>
<tr style="height: 56px;">
<img alt="Compute Library" src="https://raw.githubusercontent.com/ARM-software/ComputeLibrary/gh-pages/ACL_logo.png" style="max-width: 100%;margin-top: 15px;margin-left: 10px"/>
<td style="padding-left: 0.5em;">
<div id="projectname">
&#160;<span id="projectnumber">19.11.1</span>
</div>
</td>
</tr>
</tbody>
</table>
</div>
<!-- end header part -->
<!-- Generated by Doxygen 1.8.15 -->
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
var searchBox = new SearchBox("searchBox", "search",false,'Search');
/* @license-end */
</script>
<script type="text/javascript" src="menudata.js"></script>
<script type="text/javascript" src="menu.js"></script>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(function() {
initMenu('',true,false,'search.php','Search');
$(document).ready(function() { init_search(); });
});
/* @license-end */</script>
<div id="main-nav"></div>
</div><!-- top -->
<div id="side-nav" class="ui-resizable side-nav-resizable">
<div id="nav-tree">
<div id="nav-tree-contents">
<div id="nav-sync" class="sync"></div>
</div>
</div>
<div id="splitbar" style="-moz-user-select:none;"
class="ui-resizable-handle">
</div>
</div>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(document).ready(function(){initNavTree('_n_e_convolution_8cpp_source.xhtml','');});
/* @license-end */
</script>
<div id="doc-content">
<!-- window showing the filter options -->
<div id="MSearchSelectWindow"
onmouseover="return searchBox.OnSearchSelectShow()"
onmouseout="return searchBox.OnSearchSelectHide()"
onkeydown="return searchBox.OnSearchSelectKey(event)">
</div>
<!-- iframe showing the search results (closed by default) -->
<div id="MSearchResultsWindow">
<iframe src="javascript:void(0)" frameborder="0"
name="MSearchResults" id="MSearchResults">
</iframe>
</div>
<div class="header">
<div class="headertitle">
<div class="title">NEConvolution.cpp</div> </div>
</div><!--header-->
<div class="contents">
<a href="_n_e_convolution_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) 2016-2019 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="_n_e_convolution_8h.xhtml">arm_compute/runtime/NEON/functions/NEConvolution.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="_error_8h.xhtml">arm_compute/core/Error.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="_i_tensor_8h.xhtml">arm_compute/core/ITensor.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="_n_e_convolution_kernel_8h.xhtml">arm_compute/core/NEON/kernels/NEConvolutionKernel.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="_pixel_value_8h.xhtml">arm_compute/core/PixelValue.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="_tensor_info_8h.xhtml">arm_compute/core/TensorInfo.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="arm__compute_2core_2_utils_8h.xhtml">arm_compute/core/Utils.h</a>&quot;</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_validate_8h.xhtml">arm_compute/core/Validate.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="_n_e_scheduler_8h.xhtml">arm_compute/runtime/NEON/NEScheduler.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_allocator_8h.xhtml">arm_compute/runtime/TensorAllocator.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="_toolchain_support_8h.xhtml">support/ToolchainSupport.h</a>&quot;</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="preprocessor">#include &lt;array&gt;</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;<span class="preprocessor">#include &lt;utility&gt;</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a>;</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"><a class="line" href="classarm__compute_1_1_n_e_convolution3x3.xhtml#a58d050865536a28b56a92eeaf3ac478e"> 42</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_convolution3x3.xhtml#a58d050865536a28b56a92eeaf3ac478e">NEConvolution3x3::configure</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> int16_t *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">conv</a>, uint32_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, uint8_t constant_border_value)</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;{</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keyword">auto</span> k = arm_compute::support::cpp14::make_unique&lt;NEConvolution3x3Kernel&gt;();</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; k-&gt;configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">conv</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a> == <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">BorderMode::UNDEFINED</a>);</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; _kernel = std::move(k);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; _border_handler.configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, _kernel-&gt;border_size(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(constant_border_value));</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;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> matrix_size&gt;</div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_convolution_square.xhtml#afafdfc45ea7f884ce15ac5c353f2532a"> 51</a></span>&#160;<a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml#afafdfc45ea7f884ce15ac5c353f2532a">NEConvolutionSquare&lt;matrix_size&gt;::NEConvolutionSquare</a>(std::shared_ptr&lt;IMemoryManager&gt; memory_manager)</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; : _memory_group(std::move(memory_manager)), _tmp(), _is_separable(false), _kernel_hor(), _kernel_vert(), _kernel(), _border_handler()</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;}</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">template</span> &lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> matrix_size&gt;</div><div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_convolution_square.xhtml#a58d050865536a28b56a92eeaf3ac478e"> 57</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml#a58d050865536a28b56a92eeaf3ac478e">NEConvolutionSquare&lt;matrix_size&gt;::configure</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> int16_t *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">conv</a>, uint32_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>,</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; uint8_t constant_border_value)</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="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">conv</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(output, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">DataType::S16</a>);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; std::array&lt;int16_t, matrix_size&gt; conv_col{ { 0 } };</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; std::array&lt;int16_t, matrix_size&gt; conv_row{ { 0 } };</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; _is_separable = <a class="code" href="namespacearm__compute.xhtml#a18ec57dffc5c26864be77318111dfb2a">separate_matrix</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">conv</a>, conv_col.data(), conv_row.data(), matrix_size);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keywordflow">if</span>(_is_separable)</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="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> intermediate_type = <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataType::UNKNOWN</a>;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; std::tie(std::ignore, intermediate_type) = <a class="code" href="namespacearm__compute.xhtml#a01adc12d8e07c06cdb0f03c56a455bf3">data_type_for_convolution</a>(conv_col.data(), conv_row.data(), matrix_size);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; _tmp.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;tensor_shape(), 1, intermediate_type));</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; _memory_group.manage(&amp;_tmp);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="comment">// Calculate scale</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a> == 0)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; {</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a> = <a class="code" href="namespacearm__compute.xhtml#a0101a40c4a6acc2af3b55afa7632f16a">calculate_matrix_scale</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">conv</a>, matrix_size);</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;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; _kernel_hor.configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, &amp;_tmp, conv_row.data(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a> == <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">BorderMode::UNDEFINED</a>);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; _kernel_vert.configure(&amp;_tmp, output, conv_col.data(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a> == <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">BorderMode::UNDEFINED</a>);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; _tmp.allocator()-&gt;allocate();</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; _border_handler.configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, _kernel_hor.border_size(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(constant_border_value));</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; }</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <span class="keywordflow">else</span></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; _kernel.configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">conv</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a> == <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">BorderMode::UNDEFINED</a>);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; _border_handler.configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, _kernel.border_size(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(constant_border_value));</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;}</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="keyword">template</span> &lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> matrix_size&gt;</div><div class="line"><a name="l00100"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_convolution_square.xhtml#ad1717410afd0be936c6213a63c8005fb"> 100</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml#ad1717410afd0be936c6213a63c8005fb">NEConvolutionSquare&lt;matrix_size&gt;::run</a>()</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160;{</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_border_handler, <a class="code" href="classarm__compute_1_1_window.xhtml#a893d17b56b9abc4423ce26e9a24ac5dc">Window::DimZ</a>);</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; <span class="keywordflow">if</span>(_is_separable)</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; {</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <a class="code" href="classarm__compute_1_1_memory_group_resource_scope.xhtml">MemoryGroupResourceScope</a> scope_mg(_memory_group);</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; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_kernel_hor, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_kernel_vert, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; }</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_kernel, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; }</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160;}</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160;<span class="keyword">template</span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml">arm_compute::NEConvolutionSquare&lt;5&gt;</a>;</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160;<span class="keyword">template</span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml">arm_compute::NEConvolutionSquare&lt;7&gt;</a>;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160;<span class="keyword">template</span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml">arm_compute::NEConvolutionSquare&lt;9&gt;</a>;</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"><a class="line" href="classarm__compute_1_1_n_e_convolution_rectangle.xhtml#ac230ba3519565b12566edfdd99859ed0"> 121</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_convolution_rectangle.xhtml#ac230ba3519565b12566edfdd99859ed0">NEConvolutionRectangle::configure</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> int16_t *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">conv</a>, uint32_t rows, uint32_t cols, uint32_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, uint8_t constant_border_value)</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160;{</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="keyword">auto</span> k = arm_compute::support::cpp14::make_unique&lt;NEConvolutionRectangleKernel&gt;();</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; k-&gt;configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">conv</a>, rows, cols, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a> == <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">BorderMode::UNDEFINED</a>);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; _kernel = std::move(k);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; _border_handler.configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, _kernel-&gt;border_size(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(constant_border_value));</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160;}</div><div class="ttc" id="namespacearm__compute_xhtml_a15a05537a472ee742404821851529327"><div class="ttname"><a href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">arm_compute::BorderMode</a></div><div class="ttdeci">BorderMode</div><div class="ttdoc">Methods available to handle borders.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00260">Types.h:260</a></div></div>
<div class="ttc" id="_pixel_value_8h_xhtml"><div class="ttname"><a href="_pixel_value_8h.xhtml">PixelValue.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_pixel_value_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pixel_value.xhtml">arm_compute::PixelValue</a></div><div class="ttdoc">Class describing the value of a pixel for any image format.</div><div class="ttdef"><b>Definition:</b> <a href="_pixel_value_8h_source.xhtml#l00034">PixelValue.h:34</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="_i_tensor_8h_xhtml"><div class="ttname"><a href="_i_tensor_8h.xhtml">ITensor.h</a></div></div>
<div class="ttc" id="_n_e_convolution_kernel_8h_xhtml"><div class="ttname"><a href="_n_e_convolution_kernel_8h.xhtml">NEConvolutionKernel.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::Format::U8</a></div><div class="ttdoc">1 channel, 1 U8 per channel</div></div>
<div class="ttc" id="_tensor_allocator_8h_xhtml"><div class="ttname"><a href="_tensor_allocator_8h.xhtml">TensorAllocator.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_convolution_square_xhtml_afafdfc45ea7f884ce15ac5c353f2532a"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_square.xhtml#afafdfc45ea7f884ce15ac5c353f2532a">arm_compute::NEConvolutionSquare::NEConvolutionSquare</a></div><div class="ttdeci">NEConvolutionSquare(std::shared_ptr&lt; IMemoryManager &gt; memory_manager=nullptr)</div><div class="ttdoc">Default constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8cpp_source.xhtml#l00051">NEConvolution.cpp:51</a></div></div>
<div class="ttc" id="_n_e_convolution_8h_xhtml"><div class="ttname"><a href="_n_e_convolution_8h.xhtml">NEConvolution.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a01adc12d8e07c06cdb0f03c56a455bf3"><div class="ttname"><a href="namespacearm__compute.xhtml#a01adc12d8e07c06cdb0f03c56a455bf3">arm_compute::data_type_for_convolution</a></div><div class="ttdeci">std::pair&lt; DataType, DataType &gt; data_type_for_convolution(const int16_t *conv_col, const int16_t *conv_row, size_t size)</div><div class="ttdoc">Calculate accurary required by the horizontal and vertical convolution computations.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00722">Utils.h:722</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#l00466">Error.h:466</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="namespacearm__compute_xhtml_a0101a40c4a6acc2af3b55afa7632f16a"><div class="ttname"><a href="namespacearm__compute.xhtml#a0101a40c4a6acc2af3b55afa7632f16a">arm_compute::calculate_matrix_scale</a></div><div class="ttdeci">uint32_t calculate_matrix_scale(const int16_t *matrix, unsigned int matrix_size)</div><div class="ttdoc">Calculate the scale of the given square matrix.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00643">Utils.h:643</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml">arm_compute::ITensor</a></div><div class="ttdoc">Interface for NEON tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00036">ITensor.h:36</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) 2017-2019 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a8fcf2ddd9a1d58b1b280f5c0aed71845"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">arm_compute::test::validation::input</a></div><div class="ttdeci">auto input</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_l_s_t_m_layer_quantized_8cpp_source.xhtml#l00487">LSTMLayerQuantized.cpp:487</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a006546051719c5fb4b20c966a26b9c76"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a006546051719c5fb4b20c966a26b9c76">arm_compute::test::validation::conv</a></div><div class="ttdeci">std::array&lt; int16_t, 25 &gt; conv</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_8cpp_source.xhtml#l00125">Convolution.cpp:125</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_n_e_convolution_square_xhtml_a58d050865536a28b56a92eeaf3ac478e"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_square.xhtml#a58d050865536a28b56a92eeaf3ac478e">arm_compute::NEConvolutionSquare::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value=0)</div><div class="ttdoc">Initialize the function's source, destination, conv and border_mode.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8cpp_source.xhtml#l00057">NEConvolution.cpp:57</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5471e46933e7a9c4709972d91fc4ea65"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">arm_compute::test::validation::border_mode</a></div><div class="ttdeci">border_mode</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_8cpp_source.xhtml#l00118">Convolution.cpp:118</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_convolution_rectangle_xhtml_ac230ba3519565b12566edfdd99859ed0"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_rectangle.xhtml#ac230ba3519565b12566edfdd99859ed0">arm_compute::NEConvolutionRectangle::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t rows, uint32_t cols, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value=0)</div><div class="ttdoc">Initialize the function's source, destination, conv and border_mode.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8cpp_source.xhtml#l00121">NEConvolution.cpp:121</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_convolution_square_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_square.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEConvolutionSquare::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8cpp_source.xhtml#l00100">NEConvolution.cpp:100</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_convolution_square_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_square.xhtml">arm_compute::NEConvolutionSquare</a></div><div class="ttdoc">Basic function to execute convolution of size 5x5, 7x7, 9x9.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8h_source.xhtml#l00072">NEConvolution.h:72</a></div></div>
<div class="ttc" id="_n_e_scheduler_8h_xhtml"><div class="ttname"><a href="_n_e_scheduler_8h.xhtml">NEScheduler.h</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="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::Format::S16</a></div><div class="ttdoc">1 channel, 1 S16 per channel</div></div>
<div class="ttc" id="_validate_8h_xhtml_aadf5c9cff86327b96d88d04649d9715e"><div class="ttname"><a href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00790">Validate.h:790</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_memory_group_resource_scope_xhtml"><div class="ttname"><a href="classarm__compute_1_1_memory_group_resource_scope.xhtml">arm_compute::MemoryGroupResourceScope</a></div><div class="ttdoc">Memory group resources scope handling class.</div><div class="ttdef"><b>Definition:</b> <a href="_i_memory_group_8h_source.xhtml#l00082">IMemoryGroup.h:82</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_acec6d8ad52a28972fa74e071c1a63b6a"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">arm_compute::test::validation::scale</a></div><div class="ttdeci">scale</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_pixel_wise_multiplication_8cpp_source.xhtml#l00317">PixelWiseMultiplication.cpp:317</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_scheduler_xhtml_a4e58f95544bd5ac6559a421671bd9842"><div class="ttname"><a href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">arm_compute::IScheduler::schedule</a></div><div class="ttdeci">virtual void schedule(ICPPKernel *kernel, const Hints &amp;hints)=0</div><div class="ttdoc">Runs the kernel in the same thread as the caller synchronously.</div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_convolution3x3_xhtml_a58d050865536a28b56a92eeaf3ac478e"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution3x3.xhtml#a58d050865536a28b56a92eeaf3ac478e">arm_compute::NEConvolution3x3::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value=0)</div><div class="ttdoc">Initialize the function's source, destination, conv and border_mode.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8cpp_source.xhtml#l00042">NEConvolution.cpp:42</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_a893d17b56b9abc4423ce26e9a24ac5dc"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a893d17b56b9abc4423ce26e9a24ac5dc">arm_compute::Window::DimZ</a></div><div class="ttdeci">static constexpr size_t DimZ</div><div class="ttdoc">Alias for dimension 2 also known as Z dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00047">Window.h:47</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3"><div class="ttname"><a href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">arm_compute::BorderMode::UNDEFINED</a></div><div class="ttdoc">Borders are left undefined.</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3"><div class="ttname"><a href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">arm_compute::CLVersion::UNKNOWN</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="namespacearm__compute_xhtml_a18ec57dffc5c26864be77318111dfb2a"><div class="ttname"><a href="namespacearm__compute.xhtml#a18ec57dffc5c26864be77318111dfb2a">arm_compute::separate_matrix</a></div><div class="ttdeci">bool separate_matrix(const int16_t *conv, int16_t *conv_col, int16_t *conv_row, uint8_t size)</div><div class="ttdoc">Separate a 2D convolution into two 1D convolutions.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00583">Utils.h:583</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00074">Types.h:74</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="classarm__compute_1_1_scheduler_xhtml_a0d63ca713bab377aabcfb63c192b8429"><div class="ttname"><a href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">arm_compute::Scheduler::get</a></div><div class="ttdeci">static IScheduler &amp; get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_scheduler_8cpp_source.xhtml#l00095">Scheduler.cpp:95</a></div></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<!-- start footer part -->
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_bf9f26469d00835ba20ff8d80ee5a804.xhtml">runtime</a></li><li class="navelem"><a class="el" href="dir_a36523fc4c32a6b0076906589b6fc202.xhtml">NEON</a></li><li class="navelem"><a class="el" href="dir_4d03f28cfd35f8f734a3b0a2f1168d27.xhtml">functions</a></li><li class="navelem"><a class="el" href="_n_e_convolution_8cpp.xhtml">NEConvolution.cpp</a></li>
<li class="footer">Generated on Wed Jan 22 2020 18:07:43 for Compute Library by
<a href="http://www.doxygen.org/index.html">
<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.15 </li>
</ul>
</div>
</body>
</html>