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train · 48.1M rows

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--> <div id="titlearea"> <table cellspacing="0" cellpadding="0"> <tbody> <tr style="height: 46px;"> <td id="projectlogo"><img alt="Logo" src="CMSIS_Logo_Final.png"/></td> <td style="padding-left: 0.5em;"> <div id="projectname">CMSIS-NN  <span id="projectnumber">Version 1.2.0</span> </div> <div id="projectbrief">CMSIS NN Software Library</div> </td> </tr> </tbody> </table> </div> <!-- end header part --> <div id="CMSISnav" class="tabs1"> <ul class="tablist"> <script type="text/javascript"> <!-- writeComponentTabs.call(this); //--> </script> </ul> </div> <!-- Generated by Doxygen 1.8.6 --> <script type="text/javascript"> var searchBox = new SearchBox("searchBox", "search",false,'Search'); </script> <div id="navrow1" class="tabs"> <ul class="tablist"> <li><a href="index.html"><span>Main Page</span></a></li> <li><a href="pages.html"><span>Usage and Description</span></a></li> <li><a href="modules.html"><span>Reference</span></a></li> <li> <div id="MSearchBox" class="MSearchBoxInactive"> <span class="left"> <img id="MSearchSelect" src="search/mag_sel.png" onmouseover="return searchBox.OnSearchSelectShow()" onmouseout="return searchBox.OnSearchSelectHide()" alt=""/> <input type="text" id="MSearchField" value="Search" accesskey="S" onfocus="searchBox.OnSearchFieldFocus(true)" onblur="searchBox.OnSearchFieldFocus(false)" onkeyup="searchBox.OnSearchFieldChange(event)"/> </span><span class="right"> <a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a> </span> </div> </li> </ul> </div> <div id="navrow2" class="tabs2"> <ul class="tablist"> <li><a href="annotated.html"><span>Data Structures</span></a></li> <li class="current"><a href="functions.html"><span>Data Fields</span></a></li> </ul> </div> <div id="navrow3" class="tabs2"> <ul class="tablist"> <li class="current"><a href="functions.html"><span>All</span></a></li> <li><a href="functions_vars.html"><span>Variables</span></a></li> </ul> </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"> $(document).ready(function(){initNavTree('functions.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Macros</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Groups</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Pages</a></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="contents"> <div class="textblock">Here is a list of all struct and union fields with links to the structures/unions they belong to:</div><ul> <li>bytes : <a class="el" href="unionarm__nnword.html#ac7cff6480a8e29d95f29b73cb1267249">arm_nnword</a> </li> <li>half_words : <a class="el" href="unionarm__nnword.html#a9b5e49e4e2c4b7203e07b305386bb2ba">arm_nnword</a> </li> <li>word : <a class="el" href="unionarm__nnword.html#a35c7b2ae25e35e0ddcd9ec0a1a6f8d18">arm_nnword</a> </li> </ul> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/functions.html	HTML	apache-2.0	6,967
<!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"/> <title>Data Fields - Variables</title> <title>CMSIS-NN: Data Fields - Variables</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> </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: 46px;"> <td id="projectlogo"><img alt="Logo" src="CMSIS_Logo_Final.png"/></td> <td style="padding-left: 0.5em;"> <div id="projectname">CMSIS-NN  <span id="projectnumber">Version 1.2.0</span> </div> <div id="projectbrief">CMSIS NN Software Library</div> </td> </tr> </tbody> </table> </div> <!-- end header part --> <div id="CMSISnav" class="tabs1"> <ul class="tablist"> <script type="text/javascript"> <!-- writeComponentTabs.call(this); //--> </script> </ul> </div> <!-- Generated by Doxygen 1.8.6 --> <script type="text/javascript"> var searchBox = new SearchBox("searchBox", "search",false,'Search'); </script> <div id="navrow1" class="tabs"> <ul class="tablist"> <li><a href="index.html"><span>Main Page</span></a></li> <li><a href="pages.html"><span>Usage and Description</span></a></li> <li><a href="modules.html"><span>Reference</span></a></li> <li> <div id="MSearchBox" class="MSearchBoxInactive"> <span class="left"> <img id="MSearchSelect" src="search/mag_sel.png" onmouseover="return searchBox.OnSearchSelectShow()" onmouseout="return searchBox.OnSearchSelectHide()" alt=""/> <input type="text" id="MSearchField" value="Search" accesskey="S" onfocus="searchBox.OnSearchFieldFocus(true)" onblur="searchBox.OnSearchFieldFocus(false)" onkeyup="searchBox.OnSearchFieldChange(event)"/> </span><span class="right"> <a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a> </span> </div> </li> </ul> </div> <div id="navrow2" class="tabs2"> <ul class="tablist"> <li><a href="annotated.html"><span>Data Structures</span></a></li> <li class="current"><a href="functions.html"><span>Data Fields</span></a></li> </ul> </div> <div id="navrow3" class="tabs2"> <ul class="tablist"> <li><a href="functions.html"><span>All</span></a></li> <li class="current"><a href="functions_vars.html"><span>Variables</span></a></li> </ul> </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"> $(document).ready(function(){initNavTree('functions_vars.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Macros</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Groups</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Pages</a></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="contents">  <ul> <li>bytes : <a class="el" href="unionarm__nnword.html#ac7cff6480a8e29d95f29b73cb1267249">arm_nnword</a> </li> <li>half_words : <a class="el" href="unionarm__nnword.html#a9b5e49e4e2c4b7203e07b305386bb2ba">arm_nnword</a> </li> <li>word : <a class="el" href="unionarm__nnword.html#a35c7b2ae25e35e0ddcd9ec0a1a6f8d18">arm_nnword</a> </li> </ul> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/functions_vars.html	HTML	apache-2.0	6,876
<!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"/> <title>Globals</title> <title>CMSIS-NN: Globals</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> </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: 46px;"> <td id="projectlogo"><img alt="Logo" src="CMSIS_Logo_Final.png"/></td> <td style="padding-left: 0.5em;"> <div id="projectname">CMSIS-NN  <span id="projectnumber">Version 1.2.0</span> </div> <div id="projectbrief">CMSIS NN Software Library</div> </td> </tr> </tbody> </table> </div> <!-- end header part --> <div id="CMSISnav" class="tabs1"> <ul class="tablist"> <script type="text/javascript"> <!-- writeComponentTabs.call(this); //--> </script> </ul> </div> <!-- Generated by Doxygen 1.8.6 --> <script type="text/javascript"> var searchBox = new SearchBox("searchBox", "search",false,'Search'); </script> <div id="navrow1" class="tabs"> <ul class="tablist"> <li><a href="index.html"><span>Main Page</span></a></li> <li><a href="pages.html"><span>Usage and Description</span></a></li> <li><a href="modules.html"><span>Reference</span></a></li> <li> <div id="MSearchBox" class="MSearchBoxInactive"> <span class="left"> <img id="MSearchSelect" src="search/mag_sel.png" onmouseover="return searchBox.OnSearchSelectShow()" onmouseout="return searchBox.OnSearchSelectHide()" alt=""/> <input type="text" id="MSearchField" value="Search" accesskey="S" onfocus="searchBox.OnSearchFieldFocus(true)" onblur="searchBox.OnSearchFieldFocus(false)" onkeyup="searchBox.OnSearchFieldChange(event)"/> </span><span class="right"> <a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a> </span> </div> </li> </ul> </div> <div id="navrow3" class="tabs2"> <ul class="tablist"> <li class="current"><a href="globals.html"><span>All</span></a></li> <li><a href="globals_func.html"><span>Functions</span></a></li> <li><a href="globals_vars.html"><span>Variables</span></a></li> <li><a href="globals_enum.html"><span>Enumerations</span></a></li> <li><a href="globals_eval.html"><span>Enumerator</span></a></li> <li><a href="globals_defs.html"><span>Macros</span></a></li> </ul> </div> <div id="navrow4" class="tabs3"> <ul class="tablist"> <li><a href="#index_a"><span>a</span></a></li> <li><a href="#index_c"><span>c</span></a></li> <li><a href="#index_d"><span>d</span></a></li> <li><a href="#index_f"><span>f</span></a></li> <li><a href="#index_g"><span>g</span></a></li> <li><a href="#index_h"><span>h</span></a></li> <li><a href="#index_i"><span>i</span></a></li> <li><a href="#index_l"><span>l</span></a></li> <li><a href="#index_m"><span>m</span></a></li> <li><a href="#index_n"><span>n</span></a></li> <li><a href="#index_o"><span>o</span></a></li> <li><a href="#index_p"><span>p</span></a></li> <li><a href="#index_q"><span>q</span></a></li> <li><a href="#index_r"><span>r</span></a></li> <li><a href="#index_s"><span>s</span></a></li> <li><a href="#index_t"><span>t</span></a></li> <li class="current"><a href="#index_u"><span>u</span></a></li> </ul> </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"> $(document).ready(function(){initNavTree('globals.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Macros</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Groups</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Pages</a></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="contents"> <div class="textblock">Here is a list of all functions, variables, defines, enums, and typedefs with links to the files they belong to:</div> <h3><a class="anchor" id="index_a"></a>- a -</h3><ul> <li>arm_avepool_q7_HWC() : <a class="el" href="group__Pooling.html#gae4a7b07f97ec4313524c9fb9fbcb1f6a">arm_nnfunctions.h</a> , <a class="el" href="group__Pooling.html#gae4a7b07f97ec4313524c9fb9fbcb1f6a">arm_pool_q7_HWC.c</a> </li> <li>ARM_SIGMOID : <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0a49b307e029715fbaa6f3101c806b8c54">arm_nnsupportfunctions.h</a> </li> <li>ARM_TANH : <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0ac24e4db95c986f16c10dca71a4b4e1c5">arm_nnsupportfunctions.h</a> </li> </ul> <h3><a class="anchor" id="index_c"></a>- c -</h3><ul> <li>arm_convolve_1x1_HWC_q7_fast_nonsquare() : <a class="el" href="group__NNConv.html#ga110adcfdaab356c750c6270aa5e05f29">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga110adcfdaab356c750c6270aa5e05f29">arm_convolve_1x1_HWC_q7_fast_nonsquare.c</a> </li> <li>arm_convolve_HWC_q15_basic() : <a class="el" href="group__NNConv.html#ga55701f213b198084b52eab53097f1f58">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga55701f213b198084b52eab53097f1f58">arm_convolve_HWC_q15_basic.c</a> </li> <li>arm_convolve_HWC_q15_fast() : <a class="el" href="group__NNConv.html#ga4efb1ccbbaa7dd936961989dcb443f50">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga4efb1ccbbaa7dd936961989dcb443f50">arm_convolve_HWC_q15_fast.c</a> </li> <li>arm_convolve_HWC_q15_fast_nonsquare() : <a class="el" href="group__NNConv.html#ga614ec3b71eb96e29952ec3f09e7b9c3c">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga614ec3b71eb96e29952ec3f09e7b9c3c">arm_convolve_HWC_q15_fast_nonsquare.c</a> </li> <li>arm_convolve_HWC_q7_basic() : <a class="el" href="group__NNConv.html#ga210ae8d8fc1d12ee15b41f1fa6947681">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga210ae8d8fc1d12ee15b41f1fa6947681">arm_convolve_HWC_q7_basic.c</a> </li> <li>arm_convolve_HWC_q7_basic_nonsquare() : <a class="el" href="group__NNConv.html#ga4501fa22c0836002aa47ccc313dce252">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga4501fa22c0836002aa47ccc313dce252">arm_convolve_HWC_q7_basic_nonsquare.c</a> </li> <li>arm_convolve_HWC_q7_fast() : <a class="el" href="group__NNConv.html#gae00d3c1285907d59657369fc98bcc83f">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#gae00d3c1285907d59657369fc98bcc83f">arm_convolve_HWC_q7_fast.c</a> </li> <li>arm_convolve_HWC_q7_fast_nonsquare() : <a class="el" href="group__NNConv.html#gabc6d6b991024e9e5c5cdbd7489de88ef">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#gabc6d6b991024e9e5c5cdbd7489de88ef">arm_convolve_HWC_q7_fast_nonsquare.c</a> </li> <li>arm_convolve_HWC_q7_RGB() : <a class="el" href="group__NNConv.html#ga98f2ead67d7cbdf558b0cd8a3b8fc148">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga98f2ead67d7cbdf558b0cd8a3b8fc148">arm_convolve_HWC_q7_RGB.c</a> </li> <li>col_buffer : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a1f988afc6d7fe29ded1eafbf79a70386">arm_nnexamples_cifar10.cpp</a> </li> <li>CONV1_BIAS : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#a4cb0cfbbb61aa122890a656646532eeb">arm_nnexamples_cifar10_weights.h</a> </li> <li>conv1_bias : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a2dd28923edd6ae13ec6e61e1d876650c">arm_nnexamples_cifar10.cpp</a> </li> <li>CONV1_BIAS_LSHIFT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#a4150dd1364fd3534561c5c6e530f9bfb">arm_nnexamples_cifar10_weights.h</a> </li> <li>CONV1_IM_CH : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#aea8b1c41a63cf63eb6e7f049e84f22f7">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV1_IM_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a23ded220d27415ee1f6d9ac0bfdf38cb">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV1_KER_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#ad51c611a952fac7102ca15a06eabb908">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV1_OUT_CH : <a class="el" 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href="arm__nnexamples__cifar10_8cpp.html#a230b7412ffaaa297340ddcb49c828b4b">arm_nnexamples_cifar10.cpp</a> </li> <li>conv2_bias : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a686e558e4de77f778c775c9f0c9866d0">arm_nnexamples_cifar10.cpp</a> </li> <li>CONV2_BIAS : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#adbdb9a359c8e4104203e3783d8c1adb1">arm_nnexamples_cifar10_weights.h</a> </li> <li>CONV2_BIAS_LSHIFT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#afa70cc595390d9205c78a58795f070f4">arm_nnexamples_cifar10_weights.h</a> </li> <li>CONV2_IM_CH : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a060a8a5766a5eecaff9294f57301c99c">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV2_IM_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a832f71006d5c1e2bedbbcf192308d40e">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV2_KER_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a95b397cea14323e9037604cfcd245c26">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV2_OUT_CH : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a3be645ea438c983786878c0198ed9ae8">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV2_OUT_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a9953ead804e13dcd90d96dda64a330a4">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV2_OUT_RSHIFT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#ad872d34bfa54d86f9e5177dd2ff40d79">arm_nnexamples_cifar10_weights.h</a> </li> <li>CONV2_PADDING : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a39c1c3497169012a512219446613be0c">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV2_STRIDE : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a04f3292f8c8bac6dab973fb74eab2aa1">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV2_WT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#a9fd43e19e65f000a8b28d9f3505f0f6f">arm_nnexamples_cifar10_weights.h</a> </li> <li>conv2_wt : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a52875a8218c39da056e6d5bfb2030230">arm_nnexamples_cifar10.cpp</a> </li> <li>conv3_bias : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a70b571cac288e0d371eb9f5e7c3ccbdd">arm_nnexamples_cifar10.cpp</a> </li> <li>CONV3_BIAS : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#a8047897a26edb638e4f8c01734eb969b">arm_nnexamples_cifar10_weights.h</a> </li> <li>CONV3_BIAS_LSHIFT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#a5457926e12a9e6b0ae9754d509fb7918">arm_nnexamples_cifar10_weights.h</a> </li> <li>CONV3_IM_CH : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a1d0f9b2d219527c5070e20c50c0ced41">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV3_IM_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a04ab2b7e8de2668e0087448664814f87">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV3_KER_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a045174d68a25bfd7691303f1a063ac72">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV3_OUT_CH : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a2ab3ad342128296bb1102c3632131fd7">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV3_OUT_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#acf75167523a29737f045cc2280ce0914">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV3_OUT_RSHIFT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#ae38425db927f582d7b5edfcfaa03c676">arm_nnexamples_cifar10_weights.h</a> </li> <li>CONV3_PADDING : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#af7824a30efdeefbf468c24a70678131a">arm_nnexamples_cifar10_parameter.h</a> </li> <li>CONV3_STRIDE : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#af6ff8c82aa2d1f58a125fe71169b7cc1">arm_nnexamples_cifar10_parameter.h</a> </li> <li>conv3_wt : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a174a146d0ffaa32b073c84d95c489fed">arm_nnexamples_cifar10.cpp</a> </li> <li>CONV3_WT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#aa3605f1b1fafb1612311727d9b97b0f2">arm_nnexamples_cifar10_weights.h</a> </li> </ul> <h3><a class="anchor" id="index_d"></a>- d -</h3><ul> <li>arm_depthwise_conv_u8_basic_ver1() : <a class="el" href="group__NNConv.html#ga02a296cb4f6361a70c3ecf1ef1238292">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga02a296cb4f6361a70c3ecf1ef1238292">arm_depthwise_conv_u8_basic_ver1.c</a> </li> <li>arm_depthwise_separable_conv_HWC_q7() : <a class="el" href="group__NNConv.html#gad3d21b3bc6dbd6f3b97d01104349cb0a">arm_depthwise_separable_conv_HWC_q7.c</a> , <a class="el" href="group__NNConv.html#gad3d21b3bc6dbd6f3b97d01104349cb0a">arm_nnfunctions.h</a> </li> <li>arm_depthwise_separable_conv_HWC_q7_nonsquare() : <a class="el" href="group__NNConv.html#ga32ac508c5467813a84f74f96655dc697">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga32ac508c5467813a84f74f96655dc697">arm_depthwise_separable_conv_HWC_q7_nonsquare.c</a> </li> <li>DILATION_X : <a class="el" href="arm__depthwise__conv__u8__basic__ver1_8c.html#aeb98996ffa34fb40d8e91919d2ebdc56">arm_depthwise_conv_u8_basic_ver1.c</a> </li> <li>DILATION_Y : <a class="el" href="arm__depthwise__conv__u8__basic__ver1_8c.html#a9371ac7b5689f9e74a18a2d548c32033">arm_depthwise_conv_u8_basic_ver1.c</a> </li> <li>DIM_HISTORY : <a class="el" href="arm__nnexamples__gru_8cpp.html#ad9fde6ff501c9cd8a6cfc45949464c49">arm_nnexamples_gru.cpp</a> </li> <li>DIM_INPUT : <a class="el" href="arm__nnexamples__gru_8cpp.html#ac8ab7c242bba66633b8c06966da6c9bc">arm_nnexamples_gru.cpp</a> </li> <li>DIM_VEC : <a class="el" href="arm__nnexamples__gru_8cpp.html#a9b4b56c701e4258f8f6c87f225fbcebc">arm_nnexamples_gru.cpp</a> </li> </ul> <h3><a class="anchor" id="index_f"></a>- f -</h3><ul> <li>arm_fully_connected_mat_q7_vec_q15() : <a class="el" href="group__FC.html#ga4a1521e7532a1e62d71f3b12762016e2">arm_nnfunctions.h</a> , <a class="el" href="group__FC.html#ga4a1521e7532a1e62d71f3b12762016e2">arm_fully_connected_mat_q7_vec_q15.c</a> </li> <li>arm_fully_connected_mat_q7_vec_q15_opt() : <a class="el" href="group__FC.html#gae3857bb6375692e81dde8cbd70adec08">arm_fully_connected_mat_q7_vec_q15_opt.c</a> , <a class="el" href="group__FC.html#gae3857bb6375692e81dde8cbd70adec08">arm_nnfunctions.h</a> </li> <li>arm_fully_connected_q15() : <a class="el" href="group__FC.html#gaac666c212b209e636c2369dd5c75d0dc">arm_nnfunctions.h</a> , <a class="el" href="group__FC.html#gaac666c212b209e636c2369dd5c75d0dc">arm_fully_connected_q15.c</a> </li> <li>arm_fully_connected_q15_opt() : <a class="el" href="group__FC.html#ga062912078da113f5dd2004fd919a0ff2">arm_fully_connected_q15_opt.c</a> , <a class="el" href="group__FC.html#ga062912078da113f5dd2004fd919a0ff2">arm_nnfunctions.h</a> </li> <li>arm_fully_connected_q7() : <a class="el" href="group__FC.html#ga8b7e0c2e989e8c75f0dc789f3115323d">arm_fully_connected_q7.c</a> , <a class="el" href="group__FC.html#ga8b7e0c2e989e8c75f0dc789f3115323d">arm_nnfunctions.h</a> </li> <li>arm_fully_connected_q7_opt() : <a class="el" href="group__FC.html#gaf82b71ef472a38f8fc9ac414d9d07e67">arm_nnfunctions.h</a> , <a class="el" href="group__FC.html#gaf82b71ef472a38f8fc9ac414d9d07e67">arm_fully_connected_q7_opt.c</a> </li> </ul> <h3><a class="anchor" id="index_g"></a>- g -</h3><ul> <li>gru_example() : <a class="el" href="arm__nnexamples__gru_8cpp.html#ac71a806472c7c0c284a2253e71a6a27b">arm_nnexamples_gru.cpp</a> </li> </ul> <h3><a class="anchor" id="index_h"></a>- h -</h3><ul> <li>HIDDEN_STATE_BIAS : <a class="el" href="arm__nnexamples__gru__test__data_8h.html#a73d4e38a4aa9fa9d761d08d33b3a07fd">arm_nnexamples_gru_test_data.h</a> </li> <li>hidden_state_bias : <a class="el" href="arm__nnexamples__gru_8cpp.html#a40dda695923891899cb86b2f01bfd98a">arm_nnexamples_gru.cpp</a> </li> <li>HIDDEN_STATE_WEIGHT_X2 : <a class="el" href="arm__nnexamples__gru__test__data_8h.html#a9ab9fa603208647d992b3367a757979b">arm_nnexamples_gru_test_data.h</a> </li> <li>HIDDEN_STATE_WEIGHT_X4 : <a class="el" href="arm__nnexamples__gru__test__data_8h.html#a619947523492a72ab306da514e843ae3">arm_nnexamples_gru_test_data.h</a> </li> <li>hidden_state_weights : <a class="el" href="arm__nnexamples__gru_8cpp.html#ab18783e8d8449d7222ec4a64dfcc92e6">arm_nnexamples_gru.cpp</a> </li> <li>HISTORY_DATA : <a class="el" href="arm__nnexamples__gru__test__data_8h.html#a55c93e4e823bca1e77f4487d1ab9c056">arm_nnexamples_gru_test_data.h</a> </li> </ul> <h3><a class="anchor" id="index_i"></a>- i -</h3><ul> <li>image_data : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#aafa3e1726dde028f2dcce4febc1e9197">arm_nnexamples_cifar10.cpp</a> </li> <li>IMG_DATA : <a class="el" href="arm__nnexamples__cifar10__inputs_8h.html#a82161fe5498521048731fc21a04577c3">arm_nnexamples_cifar10_inputs.h</a> </li> <li>INPUT_DATA1 : <a class="el" href="arm__nnexamples__gru__test__data_8h.html#a1b0f5149443198bdde521a0a06c453c1">arm_nnexamples_gru_test_data.h</a> </li> <li>INPUT_DATA2 : <a class="el" href="arm__nnexamples__gru__test__data_8h.html#ae0d8a5f051f29980e62884ec34668026">arm_nnexamples_gru_test_data.h</a> </li> <li>INPUT_MEAN_SHIFT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#a476266acb4adb419f566006dce8829c3">arm_nnexamples_cifar10_weights.h</a> </li> <li>INPUT_RIGHT_SHIFT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#a4205de60010d416664775e3aa0f9ec62">arm_nnexamples_cifar10_weights.h</a> </li> <li>IP1_BIAS : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#ac88810411c45272e8f9144682b9d85bc">arm_nnexamples_cifar10_weights.h</a> </li> <li>ip1_bias : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#af715ce48798db09f3bed1753fed5c5fb">arm_nnexamples_cifar10.cpp</a> </li> <li>IP1_BIAS_LSHIFT : <a class="el" href="arm__nnexamples__cifar10__weights_8h.html#a3a98024d4e4c7fa2fbbc216812fb9b35">arm_nnexamples_cifar10_weights.h</a> </li> <li>IP1_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a5777b4b3cc406dc06397ba2d5bed9fda">arm_nnexamples_cifar10_parameter.h</a> </li> <li>IP1_IM_CH : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a3e4df285b7ca272ee897be69575ab6c5">arm_nnexamples_cifar10_parameter.h</a> </li> <li>IP1_IM_DIM : <a class="el" href="arm__nnexamples__cifar10__parameter_8h.html#a4c4ae51cf7195762dd43ea13825277be">arm_nnexamples_cifar10_parameter.h</a> </li> <li>IP1_OUT : <a class="el" 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--> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/globals_enum.html	HTML	apache-2.0	6,689
<!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"/> <title>Globals</title> <title>CMSIS-NN: Globals</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> </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: 46px;"> <td id="projectlogo"><img alt="Logo" src="CMSIS_Logo_Final.png"/></td> <td style="padding-left: 0.5em;"> <div id="projectname">CMSIS-NN  <span id="projectnumber">Version 1.2.0</span> </div> <div id="projectbrief">CMSIS NN Software Library</div> </td> </tr> </tbody> </table> </div> <!-- end header part --> <div id="CMSISnav" class="tabs1"> <ul class="tablist"> <script type="text/javascript"> <!-- writeComponentTabs.call(this); //--> </script> </ul> </div> <!-- Generated by Doxygen 1.8.6 --> <script type="text/javascript"> var searchBox = new SearchBox("searchBox", "search",false,'Search'); </script> <div id="navrow1" class="tabs"> <ul class="tablist"> <li><a href="index.html"><span>Main Page</span></a></li> <li><a href="pages.html"><span>Usage and Description</span></a></li> <li><a href="modules.html"><span>Reference</span></a></li> <li> <div id="MSearchBox" class="MSearchBoxInactive"> <span class="left"> <img id="MSearchSelect" src="search/mag_sel.png" onmouseover="return searchBox.OnSearchSelectShow()" onmouseout="return searchBox.OnSearchSelectHide()" alt=""/> <input type="text" id="MSearchField" value="Search" accesskey="S" onfocus="searchBox.OnSearchFieldFocus(true)" onblur="searchBox.OnSearchFieldFocus(false)" onkeyup="searchBox.OnSearchFieldChange(event)"/> </span><span class="right"> <a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a> </span> </div> </li> </ul> </div> <div id="navrow3" class="tabs2"> <ul class="tablist"> <li><a href="globals.html"><span>All</span></a></li> <li><a href="globals_func.html"><span>Functions</span></a></li> <li><a href="globals_vars.html"><span>Variables</span></a></li> <li><a href="globals_enum.html"><span>Enumerations</span></a></li> <li class="current"><a href="globals_eval.html"><span>Enumerator</span></a></li> <li><a href="globals_defs.html"><span>Macros</span></a></li> </ul> </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"> $(document).ready(function(){initNavTree('globals_eval.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Macros</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Groups</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Pages</a></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="contents">  <ul> <li>ARM_SIGMOID : <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0a49b307e029715fbaa6f3101c806b8c54">arm_nnsupportfunctions.h</a> </li> <li>ARM_TANH : <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0ac24e4db95c986f16c10dca71a4b4e1c5">arm_nnsupportfunctions.h</a> </li> </ul> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/globals_eval.html	HTML	apache-2.0	6,881
<!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"/> <title>Globals</title> <title>CMSIS-NN: Globals</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> </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: 46px;"> <td id="projectlogo"><img alt="Logo" src="CMSIS_Logo_Final.png"/></td> <td style="padding-left: 0.5em;"> <div id="projectname">CMSIS-NN  <span id="projectnumber">Version 1.2.0</span> </div> <div id="projectbrief">CMSIS NN Software Library</div> </td> </tr> </tbody> </table> </div> <!-- end header part --> <div id="CMSISnav" class="tabs1"> <ul class="tablist"> <script type="text/javascript"> <!-- writeComponentTabs.call(this); //--> </script> </ul> </div> <!-- Generated by Doxygen 1.8.6 --> <script type="text/javascript"> var searchBox = new SearchBox("searchBox", "search",false,'Search'); </script> <div id="navrow1" class="tabs"> <ul class="tablist"> <li><a href="index.html"><span>Main Page</span></a></li> <li><a href="pages.html"><span>Usage and Description</span></a></li> <li><a href="modules.html"><span>Reference</span></a></li> <li> <div id="MSearchBox" class="MSearchBoxInactive"> <span class="left"> <img id="MSearchSelect" src="search/mag_sel.png" onmouseover="return searchBox.OnSearchSelectShow()" onmouseout="return searchBox.OnSearchSelectHide()" alt=""/> <input type="text" id="MSearchField" value="Search" accesskey="S" onfocus="searchBox.OnSearchFieldFocus(true)" onblur="searchBox.OnSearchFieldFocus(false)" onkeyup="searchBox.OnSearchFieldChange(event)"/> </span><span class="right"> <a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a> </span> </div> </li> </ul> </div> <div id="navrow3" class="tabs2"> <ul class="tablist"> <li><a href="globals.html"><span>All</span></a></li> <li class="current"><a href="globals_func.html"><span>Functions</span></a></li> <li><a href="globals_vars.html"><span>Variables</span></a></li> <li><a href="globals_enum.html"><span>Enumerations</span></a></li> <li><a href="globals_eval.html"><span>Enumerator</span></a></li> <li><a href="globals_defs.html"><span>Macros</span></a></li> </ul> </div> <div id="navrow4" class="tabs3"> <ul class="tablist"> <li><a href="#index_a"><span>a</span></a></li> <li><a href="#index_c"><span>c</span></a></li> <li><a href="#index_d"><span>d</span></a></li> <li><a href="#index_f"><span>f</span></a></li> <li><a href="#index_g"><span>g</span></a></li> <li><a href="#index_m"><span>m</span></a></li> <li><a href="#index_n"><span>n</span></a></li> <li><a href="#index_q"><span>q</span></a></li> <li><a href="#index_r"><span>r</span></a></li> <li class="current"><a href="#index_s"><span>s</span></a></li> </ul> </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"> $(document).ready(function(){initNavTree('globals_func.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Macros</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Groups</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Pages</a></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="contents">   <h3><a class="anchor" id="index_a"></a>- a -</h3><ul> <li>arm_avepool_q7_HWC() : <a class="el" href="group__Pooling.html#gae4a7b07f97ec4313524c9fb9fbcb1f6a">arm_nnfunctions.h</a> , <a class="el" href="group__Pooling.html#gae4a7b07f97ec4313524c9fb9fbcb1f6a">arm_pool_q7_HWC.c</a> </li> </ul> <h3><a class="anchor" id="index_c"></a>- c -</h3><ul> <li>arm_convolve_1x1_HWC_q7_fast_nonsquare() : <a class="el" href="group__NNConv.html#ga110adcfdaab356c750c6270aa5e05f29">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga110adcfdaab356c750c6270aa5e05f29">arm_convolve_1x1_HWC_q7_fast_nonsquare.c</a> </li> <li>arm_convolve_HWC_q15_basic() : <a class="el" href="group__NNConv.html#ga55701f213b198084b52eab53097f1f58">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga55701f213b198084b52eab53097f1f58">arm_convolve_HWC_q15_basic.c</a> </li> <li>arm_convolve_HWC_q15_fast() : <a class="el" href="group__NNConv.html#ga4efb1ccbbaa7dd936961989dcb443f50">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga4efb1ccbbaa7dd936961989dcb443f50">arm_convolve_HWC_q15_fast.c</a> </li> <li>arm_convolve_HWC_q15_fast_nonsquare() : <a class="el" href="group__NNConv.html#ga614ec3b71eb96e29952ec3f09e7b9c3c">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga614ec3b71eb96e29952ec3f09e7b9c3c">arm_convolve_HWC_q15_fast_nonsquare.c</a> </li> <li>arm_convolve_HWC_q7_basic() : <a class="el" href="group__NNConv.html#ga210ae8d8fc1d12ee15b41f1fa6947681">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga210ae8d8fc1d12ee15b41f1fa6947681">arm_convolve_HWC_q7_basic.c</a> </li> <li>arm_convolve_HWC_q7_basic_nonsquare() : <a class="el" href="group__NNConv.html#ga4501fa22c0836002aa47ccc313dce252">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga4501fa22c0836002aa47ccc313dce252">arm_convolve_HWC_q7_basic_nonsquare.c</a> </li> <li>arm_convolve_HWC_q7_fast() : <a class="el" href="group__NNConv.html#gae00d3c1285907d59657369fc98bcc83f">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#gae00d3c1285907d59657369fc98bcc83f">arm_convolve_HWC_q7_fast.c</a> </li> <li>arm_convolve_HWC_q7_fast_nonsquare() : <a class="el" href="group__NNConv.html#gabc6d6b991024e9e5c5cdbd7489de88ef">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#gabc6d6b991024e9e5c5cdbd7489de88ef">arm_convolve_HWC_q7_fast_nonsquare.c</a> </li> <li>arm_convolve_HWC_q7_RGB() : <a class="el" href="group__NNConv.html#ga98f2ead67d7cbdf558b0cd8a3b8fc148">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga98f2ead67d7cbdf558b0cd8a3b8fc148">arm_convolve_HWC_q7_RGB.c</a> </li> </ul> <h3><a class="anchor" id="index_d"></a>- d -</h3><ul> <li>arm_depthwise_conv_u8_basic_ver1() : <a class="el" href="group__NNConv.html#ga02a296cb4f6361a70c3ecf1ef1238292">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga02a296cb4f6361a70c3ecf1ef1238292">arm_depthwise_conv_u8_basic_ver1.c</a> </li> <li>arm_depthwise_separable_conv_HWC_q7() : <a class="el" href="group__NNConv.html#gad3d21b3bc6dbd6f3b97d01104349cb0a">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#gad3d21b3bc6dbd6f3b97d01104349cb0a">arm_depthwise_separable_conv_HWC_q7.c</a> </li> <li>arm_depthwise_separable_conv_HWC_q7_nonsquare() : <a class="el" href="group__NNConv.html#ga32ac508c5467813a84f74f96655dc697">arm_nnfunctions.h</a> , <a class="el" href="group__NNConv.html#ga32ac508c5467813a84f74f96655dc697">arm_depthwise_separable_conv_HWC_q7_nonsquare.c</a> </li> </ul> <h3><a class="anchor" id="index_f"></a>- f -</h3><ul> <li>arm_fully_connected_mat_q7_vec_q15() : <a class="el" href="group__FC.html#ga4a1521e7532a1e62d71f3b12762016e2">arm_nnfunctions.h</a> , <a class="el" href="group__FC.html#ga4a1521e7532a1e62d71f3b12762016e2">arm_fully_connected_mat_q7_vec_q15.c</a> </li> <li>arm_fully_connected_mat_q7_vec_q15_opt() : <a class="el" href="group__FC.html#gae3857bb6375692e81dde8cbd70adec08">arm_nnfunctions.h</a> , <a class="el" href="group__FC.html#gae3857bb6375692e81dde8cbd70adec08">arm_fully_connected_mat_q7_vec_q15_opt.c</a> </li> <li>arm_fully_connected_q15() : <a class="el" href="group__FC.html#gaac666c212b209e636c2369dd5c75d0dc">arm_nnfunctions.h</a> , <a class="el" href="group__FC.html#gaac666c212b209e636c2369dd5c75d0dc">arm_fully_connected_q15.c</a> </li> <li>arm_fully_connected_q15_opt() : <a class="el" href="group__FC.html#ga062912078da113f5dd2004fd919a0ff2">arm_nnfunctions.h</a> , <a class="el" href="group__FC.html#ga062912078da113f5dd2004fd919a0ff2">arm_fully_connected_q15_opt.c</a> </li> <li>arm_fully_connected_q7() : <a class="el" href="group__FC.html#ga8b7e0c2e989e8c75f0dc789f3115323d">arm_nnfunctions.h</a> , <a class="el" href="group__FC.html#ga8b7e0c2e989e8c75f0dc789f3115323d">arm_fully_connected_q7.c</a> </li> <li>arm_fully_connected_q7_opt() : <a class="el" href="group__FC.html#gaf82b71ef472a38f8fc9ac414d9d07e67">arm_nnfunctions.h</a> , <a class="el" href="group__FC.html#gaf82b71ef472a38f8fc9ac414d9d07e67">arm_fully_connected_q7_opt.c</a> </li> </ul> <h3><a class="anchor" id="index_g"></a>- g -</h3><ul> <li>gru_example() : <a class="el" href="arm__nnexamples__gru_8cpp.html#ac71a806472c7c0c284a2253e71a6a27b">arm_nnexamples_gru.cpp</a> </li> </ul> <h3><a class="anchor" id="index_m"></a>- m -</h3><ul> <li>arm_maxpool_q7_HWC() : <a class="el" href="group__Pooling.html#ga99afcdcc61eaf429ab3ee823702e44ce">arm_nnfunctions.h</a> , <a class="el" href="group__Pooling.html#ga99afcdcc61eaf429ab3ee823702e44ce">arm_pool_q7_HWC.c</a> </li> <li>main() : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">arm_nnexamples_cifar10.cpp</a> , <a class="el" href="arm__nnexamples__gru_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">arm_nnexamples_gru.cpp</a> </li> </ul> <h3><a class="anchor" id="index_n"></a>- n -</h3><ul> <li>arm_nn_activations_direct_q15() : <a class="el" href="group__Acti.html#ga8932b57c8d0ee757511af2d40dcc11e7">arm_nnfunctions.h</a> , <a class="el" href="group__Acti.html#ga8932b57c8d0ee757511af2d40dcc11e7">arm_nn_activations_q15.c</a> </li> <li>arm_nn_activations_direct_q7() : <a class="el" href="group__Acti.html#ga79f11131ae6767d60e03b1f6506b1af8">arm_nnfunctions.h</a> , <a class="el" href="group__Acti.html#ga79f11131ae6767d60e03b1f6506b1af8">arm_nn_activations_q7.c</a> </li> <li>arm_nn_divide_by_power_of_two() : <a class="el" href="arm__nnsupportfunctions_8h.html#ab6dbc2fd53fae3ccdd1d0d70c8d3b491">arm_nnsupportfunctions.h</a> </li> <li>arm_nn_mat_mult_kernel_q7_q15() : <a class="el" href="arm__nnfunctions_8h.html#abc4fb258cfe8500ee68e812a293a80a3">arm_nnfunctions.h</a> , <a class="el" href="arm__nn__mat__mult__kernel__q7__q15_8c.html#abc4fb258cfe8500ee68e812a293a80a3">arm_nn_mat_mult_kernel_q7_q15.c</a> </li> <li>arm_nn_mat_mult_kernel_q7_q15_reordered() : <a class="el" href="arm__nnfunctions_8h.html#aefe9c7ce9a65060a244b06dffe74c4b3">arm_nnfunctions.h</a> , <a class="el" href="arm__nn__mat__mult__kernel__q7__q15__reordered_8c.html#aefe9c7ce9a65060a244b06dffe74c4b3">arm_nn_mat_mult_kernel_q7_q15_reordered.c</a> </li> <li>arm_nn_mult_q15() : <a class="el" href="group__NNBasicMath.html#ga08f8340aa6533271b3aa6d211614fe22">arm_nnsupportfunctions.h</a> , <a class="el" href="group__NNBasicMath.html#ga08f8340aa6533271b3aa6d211614fe22">arm_nn_mult_q15.c</a> </li> <li>arm_nn_mult_q7() : <a class="el" href="group__NNBasicMath.html#gad46c9ab012cceda8ce6681c687a58c70">arm_nnsupportfunctions.h</a> , <a class="el" href="group__NNBasicMath.html#gad46c9ab012cceda8ce6681c687a58c70">arm_nn_mult_q7.c</a> </li> <li>arm_nn_sat_doubling_high_mult() : <a class="el" href="arm__nnsupportfunctions_8h.html#a51721c10f116c9f5b8d9908367989d44">arm_nnsupportfunctions.h</a> </li> </ul> <h3><a class="anchor" id="index_q"></a>- q -</h3><ul> <li>arm_q7_to_q15_no_shift() : <a class="el" href="group__nndata__convert.html#gae349de4dba8d253c89d45794ccf05680">arm_nnsupportfunctions.h</a> , <a class="el" href="group__nndata__convert.html#gae349de4dba8d253c89d45794ccf05680">arm_q7_to_q15_no_shift.c</a> </li> <li>arm_q7_to_q15_reordered_no_shift() : <a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_nnsupportfunctions.h</a> , <a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_q7_to_q15_reordered_no_shift.c</a> </li> </ul> <h3><a class="anchor" id="index_r"></a>- r -</h3><ul> <li>arm_relu_q15() : <a class="el" href="group__Acti.html#ga53bcc00e54b802919bb3c89c143ee5ba">arm_nnfunctions.h</a> , <a class="el" href="group__Acti.html#ga53bcc00e54b802919bb3c89c143ee5ba">arm_relu_q15.c</a> </li> <li>arm_relu_q7() : <a class="el" href="group__Acti.html#ga638e803b4fe00426f401783a6255ca30">arm_nnfunctions.h</a> , <a class="el" href="group__Acti.html#ga638e803b4fe00426f401783a6255ca30">arm_relu_q7.c</a> </li> </ul> <h3><a class="anchor" id="index_s"></a>- s -</h3><ul> <li>arm_softmax_q15() : <a class="el" href="group__Softmax.html#ga1cacd8b84b8363079311987d0016ebe5">arm_nnfunctions.h</a> , <a class="el" href="group__Softmax.html#ga1cacd8b84b8363079311987d0016ebe5">arm_softmax_q15.c</a> </li> <li>arm_softmax_q7() : <a class="el" href="group__Softmax.html#ga89aff212a97a3cf32d9d7ddf11a8f43e">arm_nnfunctions.h</a> , <a class="el" href="group__Softmax.html#ga89aff212a97a3cf32d9d7ddf11a8f43e">arm_softmax_q7.c</a> </li> </ul> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. 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id="MSearchResultsWindow"> <iframe src="javascript:void(0)" frameborder="0" name="MSearchResults" id="MSearchResults"> </iframe> </div> <div class="contents">   <h3><a class="anchor" id="index_c"></a>- c -</h3><ul> <li>col_buffer : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a1f988afc6d7fe29ded1eafbf79a70386">arm_nnexamples_cifar10.cpp</a> </li> <li>conv1_bias : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a2dd28923edd6ae13ec6e61e1d876650c">arm_nnexamples_cifar10.cpp</a> </li> <li>conv1_wt : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a230b7412ffaaa297340ddcb49c828b4b">arm_nnexamples_cifar10.cpp</a> </li> <li>conv2_bias : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a686e558e4de77f778c775c9f0c9866d0">arm_nnexamples_cifar10.cpp</a> </li> <li>conv2_wt : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a52875a8218c39da056e6d5bfb2030230">arm_nnexamples_cifar10.cpp</a> </li> <li>conv3_bias : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a70b571cac288e0d371eb9f5e7c3ccbdd">arm_nnexamples_cifar10.cpp</a> </li> <li>conv3_wt : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a174a146d0ffaa32b073c84d95c489fed">arm_nnexamples_cifar10.cpp</a> </li> </ul> <h3><a class="anchor" id="index_h"></a>- h -</h3><ul> <li>hidden_state_bias : <a class="el" href="arm__nnexamples__gru_8cpp.html#a40dda695923891899cb86b2f01bfd98a">arm_nnexamples_gru.cpp</a> </li> <li>hidden_state_weights : <a class="el" href="arm__nnexamples__gru_8cpp.html#ab18783e8d8449d7222ec4a64dfcc92e6">arm_nnexamples_gru.cpp</a> </li> </ul> <h3><a class="anchor" id="index_i"></a>- i -</h3><ul> <li>image_data : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#aafa3e1726dde028f2dcce4febc1e9197">arm_nnexamples_cifar10.cpp</a> </li> <li>ip1_bias : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#af715ce48798db09f3bed1753fed5c5fb">arm_nnexamples_cifar10.cpp</a> </li> <li>ip1_wt : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a244dc5b6679b33a0a85b55adbe969208">arm_nnexamples_cifar10.cpp</a> </li> </ul> <h3><a class="anchor" id="index_o"></a>- o -</h3><ul> <li>output_data : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a75c8e3727f7d3637f03ffb1d9f727313">arm_nnexamples_cifar10.cpp</a> </li> </ul> <h3><a class="anchor" id="index_r"></a>- r -</h3><ul> <li>reset_gate_bias : <a class="el" href="arm__nnexamples__gru_8cpp.html#a2a9d5c9f16ee778ecc8170d8664722c7">arm_nnexamples_gru.cpp</a> </li> <li>reset_gate_weights : <a class="el" href="arm__nnexamples__gru_8cpp.html#ac2ae1ff19167c2bb359db2b319ca1060">arm_nnexamples_gru.cpp</a> </li> </ul> <h3><a class="anchor" id="index_s"></a>- s -</h3><ul> <li>scratch_buffer : <a class="el" href="arm__nnexamples__cifar10_8cpp.html#a19548b1fad7cb85d95f5f276873a5de3">arm_nnexamples_cifar10.cpp</a> , <a class="el" href="arm__nnexamples__gru_8cpp.html#a935afa741bcc39e4c4c48b019d415d97">arm_nnexamples_gru.cpp</a> </li> <li>sigmoidHTable_q15 : <a class="el" href="arm__nn__tables_8h.html#a107a16eaa36f4392fa3ed3792ad6c2cb">arm_nn_tables.h</a> , <a class="el" href="arm__nntables_8c.html#a107a16eaa36f4392fa3ed3792ad6c2cb">arm_nntables.c</a> </li> <li>sigmoidLTable_q15 : <a class="el" href="arm__nn__tables_8h.html#a69dc528cb377690d5b37accfdfd226b1">arm_nn_tables.h</a> , <a class="el" href="arm__nntables_8c.html#a69dc528cb377690d5b37accfdfd226b1">arm_nntables.c</a> </li> <li>sigmoidTable_q15 : <a class="el" href="arm__nn__tables_8h.html#ab4d7b07c387a3537d4efe21da86115b0">arm_nn_tables.h</a> , <a class="el" href="arm__nntables_8c.html#ab4d7b07c387a3537d4efe21da86115b0">arm_nntables.c</a> </li> <li>sigmoidTable_q7 : <a class="el" href="arm__nn__tables_8h.html#ae2ff3f4e7014f535358167150bdd544f">arm_nn_tables.h</a> , <a class="el" href="arm__nntables_8c.html#ae2ff3f4e7014f535358167150bdd544f">arm_nntables.c</a> </li> </ul> <h3><a class="anchor" id="index_t"></a>- t -</h3><ul> <li>tanhHTable_q15 : <a class="el" href="arm__nntables_8c.html#a4d093f7b0dc798d4898ff4fd125b21a6">arm_nntables.c</a> </li> <li>tanhLTable_q15 : <a class="el" href="arm__nntables_8c.html#a7cb5ad2fff7e241d09024332488a706e">arm_nntables.c</a> </li> <li>tanhTable_q15 : <a class="el" href="arm__nn__tables_8h.html#a6faad2fec173b2702fd0f219a83ca320">arm_nn_tables.h</a> , <a class="el" href="arm__nntables_8c.html#a6faad2fec173b2702fd0f219a83ca320">arm_nntables.c</a> </li> <li>tanhTable_q7 : <a class="el" href="arm__nn__tables_8h.html#a4f854bdf13f630ec21b3ad074491e32f">arm_nn_tables.h</a> , <a class="el" href="arm__nntables_8c.html#a4f854bdf13f630ec21b3ad074491e32f">arm_nntables.c</a> </li> <li>test_history : <a class="el" href="arm__nnexamples__gru_8cpp.html#ac327d41d23812b53d83c2da91971cbfe">arm_nnexamples_gru.cpp</a> </li> <li>test_input1 : <a class="el" href="arm__nnexamples__gru_8cpp.html#a8b0acc149c9bd4aadfb9c1fa8345f57a">arm_nnexamples_gru.cpp</a> </li> <li>test_input2 : <a class="el" 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<!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"/> <title>Neural Network Activation Functions</title> <title>CMSIS-NN: Neural Network Activation Functions</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link 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<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"> $(document).ready(function(){initNavTree('group__Acti.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" 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class="SelectionMark"> </span>Pages</a></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="summary"> <a href="#func-members">Functions</a> </div> <div class="headertitle"> <div class="title">Neural Network Activation Functions<div class="ingroups"><a class="el" href="group__groupNN.html">Neural Network Functions</a></div></div> </div> </div><!--header--> <div class="contents"> <table class="memberdecls"> <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> Functions</h2></td></tr> <tr class="memitem:ga8932b57c8d0ee757511af2d40dcc11e7"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__Acti.html#ga8932b57c8d0ee757511af2d40dcc11e7">arm_nn_activations_direct_q15</a> (q15_t data, uint16_t size, uint16_t int_width, <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0">arm_nn_activation_type</a> type)</td></tr> <tr class="memdesc:ga8932b57c8d0ee757511af2d40dcc11e7"><td class="mdescLeft"> </td><td class="mdescRight">Q15 neural network activation function using direct table look-up. <a href="#ga8932b57c8d0ee757511af2d40dcc11e7">More...</a><br/></td></tr> <tr class="separator:ga8932b57c8d0ee757511af2d40dcc11e7"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga79f11131ae6767d60e03b1f6506b1af8"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__Acti.html#ga79f11131ae6767d60e03b1f6506b1af8">arm_nn_activations_direct_q7</a> (q7_t data, uint16_t size, uint16_t int_width, <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0">arm_nn_activation_type</a> type)</td></tr> <tr class="memdesc:ga79f11131ae6767d60e03b1f6506b1af8"><td class="mdescLeft"> </td><td class="mdescRight">Q7 neural network activation function using direct table look-up. <a href="#ga79f11131ae6767d60e03b1f6506b1af8">More...</a><br/></td></tr> <tr class="separator:ga79f11131ae6767d60e03b1f6506b1af8"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga53bcc00e54b802919bb3c89c143ee5ba"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__Acti.html#ga53bcc00e54b802919bb3c89c143ee5ba">arm_relu_q15</a> (q15_t data, uint16_t size)</td></tr> <tr class="memdesc:ga53bcc00e54b802919bb3c89c143ee5ba"><td class="mdescLeft"> </td><td class="mdescRight">Q15 RELU function. <a href="#ga53bcc00e54b802919bb3c89c143ee5ba">More...</a><br/></td></tr> <tr class="separator:ga53bcc00e54b802919bb3c89c143ee5ba"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga638e803b4fe00426f401783a6255ca30"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__Acti.html#ga638e803b4fe00426f401783a6255ca30">arm_relu_q7</a> (q7_t data, uint16_t size)</td></tr> <tr class="memdesc:ga638e803b4fe00426f401783a6255ca30"><td class="mdescLeft"> </td><td class="mdescRight">Q7 RELU function. <a href="#ga638e803b4fe00426f401783a6255ca30">More...</a><br/></td></tr> <tr class="separator:ga638e803b4fe00426f401783a6255ca30"><td class="memSeparator" colspan="2"> </td></tr> </table> <a name="details" id="details"></a><h2 class="groupheader">Description</h2> <p>Perform activation layers, including ReLU (Rectified Linear Unit), sigmoid and tanh </p> <h2 class="groupheader">Function Documentation</h2> <a class="anchor" id="ga8932b57c8d0ee757511af2d40dcc11e7"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_nn_activations_direct_q15 </td> <td>(</td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>data</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint16_t </td> <td class="paramname"><em>size</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint16_t </td> <td class="paramname"><em>int_width</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype"><a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0">arm_nn_activation_type</a> </td> <td class="paramname"><em>type</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in,out]</td><td class="paramname">data</td><td>pointer to input </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">size</td><td>number of elements </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">int_width</td><td>bit-width of the integer part, assume to be smaller than 3 </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">type</td><td>type of activation functions </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p>This is the direct table look-up approach.</p> <p>Assume here the integer part of the fixed-point is <= 3. More than 3 just not making much sense, makes no difference with saturation followed by any of these activation functions. </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0a49b307e029715fbaa6f3101c806b8c54">ARM_SIGMOID</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0ac24e4db95c986f16c10dca71a4b4e1c5">ARM_TANH</a>, <a class="el" href="arm__nn__tables_8h.html#ab4d7b07c387a3537d4efe21da86115b0">sigmoidTable_q15</a>, and <a class="el" href="arm__nn__tables_8h.html#a6faad2fec173b2702fd0f219a83ca320">tanhTable_q15</a>.</p> <p>Referenced by <a class="el" href="arm__nnexamples__gru_8cpp.html#ac71a806472c7c0c284a2253e71a6a27b">gru_example()</a>.</p> </div> </div> <a class="anchor" id="ga79f11131ae6767d60e03b1f6506b1af8"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_nn_activations_direct_q7 </td> <td>(</td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>data</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint16_t </td> <td class="paramname"><em>size</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint16_t </td> <td class="paramname"><em>int_width</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype"><a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0">arm_nn_activation_type</a> </td> <td class="paramname"><em>type</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in,out]</td><td class="paramname">data</td><td>pointer to input </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">size</td><td>number of elements </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">int_width</td><td>bit-width of the integer part, assume to be smaller than 3 </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">type</td><td>type of activation functions </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p>This is the direct table look-up approach.</p> <p>Assume here the integer part of the fixed-point is <= 3. More than 3 just not making much sense, makes no difference with saturation followed by any of these activation functions. </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0a49b307e029715fbaa6f3101c806b8c54">ARM_SIGMOID</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a7f41aa78cd9a0552fae9b348ee4831a0ac24e4db95c986f16c10dca71a4b4e1c5">ARM_TANH</a>, <a class="el" href="arm__nn__tables_8h.html#ae2ff3f4e7014f535358167150bdd544f">sigmoidTable_q7</a>, and <a class="el" href="arm__nn__tables_8h.html#a4f854bdf13f630ec21b3ad074491e32f">tanhTable_q7</a>.</p> </div> </div> <a class="anchor" id="ga53bcc00e54b802919bb3c89c143ee5ba"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_relu_q15 </td> <td>(</td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>data</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint16_t </td> <td class="paramname"><em>size</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in,out]</td><td class="paramname">data</td><td>pointer to input </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">size</td><td>number of elements </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p>Optimized relu with QSUB instructions. </p> </div> </div> <a class="anchor" id="ga638e803b4fe00426f401783a6255ca30"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_relu_q7 </td> <td>(</td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>data</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint16_t </td> <td class="paramname"><em>size</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in,out]</td><td class="paramname">data</td><td>pointer to input </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">size</td><td>number of elements </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p>Optimized relu with QSUB instructions. </p> <p>Referenced by <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main()</a>.</p> </div> </div> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. 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<!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"/> <title>Convolutional Neural Network Example</title> <title>CMSIS-NN: Convolutional Neural Network Example</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> </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: 46px;"> <td id="projectlogo"><img alt="Logo" src="CMSIS_Logo_Final.png"/></td> <td style="padding-left: 0.5em;"> <div id="projectname">CMSIS-NN  <span id="projectnumber">Version 1.2.0</span> </div> <div id="projectbrief">CMSIS NN Software Library</div> </td> </tr> </tbody> </table> </div> <!-- end header part --> <div id="CMSISnav" class="tabs1"> <ul class="tablist"> <script type="text/javascript"> <!-- writeComponentTabs.call(this); //--> </script> </ul> </div> <!-- Generated by Doxygen 1.8.6 --> <script type="text/javascript"> var searchBox = new SearchBox("searchBox", "search",false,'Search'); </script> <div id="navrow1" class="tabs"> <ul class="tablist"> <li><a href="index.html"><span>Main Page</span></a></li> <li><a href="pages.html"><span>Usage and Description</span></a></li> <li><a href="modules.html"><span>Reference</span></a></li> <li> <div id="MSearchBox" class="MSearchBoxInactive"> <span class="left"> <img id="MSearchSelect" src="search/mag_sel.png" onmouseover="return searchBox.OnSearchSelectShow()" onmouseout="return searchBox.OnSearchSelectHide()" alt=""/> <input type="text" id="MSearchField" value="Search" accesskey="S" onfocus="searchBox.OnSearchFieldFocus(true)" onblur="searchBox.OnSearchFieldFocus(false)" onkeyup="searchBox.OnSearchFieldChange(event)"/> </span><span class="right"> <a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a> </span> </div> </li> </ul> </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"> $(document).ready(function(){initNavTree('group__CNNExample.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Macros</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Groups</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Pages</a></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">Convolutional Neural Network Example</div> </div> </div><!--header--> <div class="contents"> <dl class="section user"><dt>Description:</dt><dd></dd></dl> <dl class="section user"><dt></dt><dd>Demonstrates a convolutional neural network (CNN) example with the use of convolution, ReLU activation, pooling and fully-connected functions.</dd></dl> <dl class="section user"><dt>Model definition:</dt><dd></dd></dl> <dl class="section user"><dt></dt><dd>The CNN used in this example is based on CIFAR-10 example from Caffe [1]. The neural network consists of 3 convolution layers interspersed by ReLU activation and max pooling layers, followed by a fully-connected layer at the end. The input to the network is a 32x32 pixel color image, which will be classified into one of the 10 output classes. This example model implementation needs 32.3 KB to store weights, 40 KB for activations and 3.1 KB for storing the <code>im2col</code> data.</dd></dl> <div class="image"> <img src="CIFAR10_CNN.gif" alt="CIFAR10_CNN.gif"/> <div class="caption"> Neural Network model definition</div></div> <dl class="section user"><dt>Variables Description:</dt><dd></dd></dl> <dl class="section user"><dt></dt><dd><ul> <li><code>conv1_wt</code>, <code>conv2_wt</code>, <code>conv3_wt</code> are convolution layer weight matrices </li> <li><code>conv1_bias</code>, <code>conv2_bias</code>, <code>conv3_bias</code> are convolution layer bias arrays </li> <li><code>ip1_wt</code>, ip1_bias point to fully-connected layer weights and biases </li> <li><code>input_data</code> points to the input image data </li> <li><code>output_data</code> points to the classification output </li> <li><code>col_buffer</code> is a buffer to store the <code>im2col</code> output </li> <li><code>scratch_buffer</code> is used to store the activation data (intermediate layer outputs)</li> </ul> </dd></dl> <dl class="section user"><dt>CMSIS DSP Software Library Functions Used:</dt><dd></dd></dl> <dl class="section user"><dt></dt><dd><ul> <li><a class="el" href="group__NNConv.html#ga98f2ead67d7cbdf558b0cd8a3b8fc148" title="Q7 version of convolution for RGB image. ">arm_convolve_HWC_q7_RGB()</a></li> <li><a class="el" href="group__NNConv.html#gae00d3c1285907d59657369fc98bcc83f" title="Fast Q7 convolution function. ">arm_convolve_HWC_q7_fast()</a></li> <li><a class="el" href="group__Acti.html#ga638e803b4fe00426f401783a6255ca30" title="Q7 RELU function. ">arm_relu_q7()</a></li> <li><a class="el" href="group__Pooling.html#ga99afcdcc61eaf429ab3ee823702e44ce" title="Q7 max pooling function. ">arm_maxpool_q7_HWC()</a></li> <li><a class="el" href="group__Pooling.html#gae4a7b07f97ec4313524c9fb9fbcb1f6a" title="Q7 average pooling function. ">arm_avepool_q7_HWC()</a></li> <li><a class="el" href="group__FC.html#gaf82b71ef472a38f8fc9ac414d9d07e67" title="Q7 opt fully-connected layer function. ">arm_fully_connected_q7_opt()</a></li> <li><a class="el" href="group__FC.html#ga8b7e0c2e989e8c75f0dc789f3115323d" title="Q7 basic fully-connected layer function. ">arm_fully_connected_q7()</a></li> </ul> </dd></dl> <p><b> Refer </b> <a class="el" href="arm__nnexamples__cifar10_8cpp.html">arm_nnexamples_cifar10.cpp</a></p> <dl class="section user"><dt>[1] https://github.com/BVLC/caffe</dt><dd></dd></dl> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/group__CNNExample.html	HTML	apache-2.0	9,387
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<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"> $(document).ready(function(){initNavTree('group__FC.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" 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class="SelectionMark"> </span>Pages</a></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="summary"> <a href="#func-members">Functions</a> </div> <div class="headertitle"> <div class="title">Fully-connected Layer Functions<div class="ingroups"><a class="el" href="group__groupNN.html">Neural Network Functions</a></div></div> </div> </div><!--header--> <div class="contents"> <table class="memberdecls"> <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> Functions</h2></td></tr> <tr class="memitem:ga4a1521e7532a1e62d71f3b12762016e2"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#ga4a1521e7532a1e62d71f3b12762016e2">arm_fully_connected_mat_q7_vec_q15</a> (const q15_t pV, const q7_t pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t bias, q15_t pOut, q15_t vec_buffer)</td></tr> <tr class="memdesc:ga4a1521e7532a1e62d71f3b12762016e2"><td class="mdescLeft"> </td><td class="mdescRight">Mixed Q15-Q7 fully-connected layer function. <a href="#ga4a1521e7532a1e62d71f3b12762016e2">More...</a><br/></td></tr> <tr class="separator:ga4a1521e7532a1e62d71f3b12762016e2"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:gae3857bb6375692e81dde8cbd70adec08"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#gae3857bb6375692e81dde8cbd70adec08">arm_fully_connected_mat_q7_vec_q15_opt</a> (const q15_t pV, const q7_t pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t bias, q15_t pOut, q15_t vec_buffer)</td></tr> <tr class="memdesc:gae3857bb6375692e81dde8cbd70adec08"><td class="mdescLeft"> </td><td class="mdescRight">Mixed Q15-Q7 opt fully-connected layer function. <a href="#gae3857bb6375692e81dde8cbd70adec08">More...</a><br/></td></tr> <tr class="separator:gae3857bb6375692e81dde8cbd70adec08"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:gaac666c212b209e636c2369dd5c75d0dc"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#gaac666c212b209e636c2369dd5c75d0dc">arm_fully_connected_q15</a> (const q15_t pV, const q15_t pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q15_t bias, q15_t pOut, q15_t vec_buffer)</td></tr> <tr class="memdesc:gaac666c212b209e636c2369dd5c75d0dc"><td class="mdescLeft"> </td><td class="mdescRight">Q15 opt fully-connected layer function. <a href="#gaac666c212b209e636c2369dd5c75d0dc">More...</a><br/></td></tr> <tr class="separator:gaac666c212b209e636c2369dd5c75d0dc"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga062912078da113f5dd2004fd919a0ff2"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#ga062912078da113f5dd2004fd919a0ff2">arm_fully_connected_q15_opt</a> (const q15_t pV, const q15_t pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q15_t bias, q15_t pOut, q15_t vec_buffer)</td></tr> <tr class="memdesc:ga062912078da113f5dd2004fd919a0ff2"><td class="mdescLeft"> </td><td class="mdescRight">Q15 opt fully-connected layer function. <a href="#ga062912078da113f5dd2004fd919a0ff2">More...</a><br/></td></tr> <tr class="separator:ga062912078da113f5dd2004fd919a0ff2"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga8b7e0c2e989e8c75f0dc789f3115323d"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#ga8b7e0c2e989e8c75f0dc789f3115323d">arm_fully_connected_q7</a> (const q7_t pV, const q7_t pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t bias, q7_t pOut, q15_t vec_buffer)</td></tr> <tr class="memdesc:ga8b7e0c2e989e8c75f0dc789f3115323d"><td class="mdescLeft"> </td><td class="mdescRight">Q7 basic fully-connected layer function. <a href="#ga8b7e0c2e989e8c75f0dc789f3115323d">More...</a><br/></td></tr> <tr class="separator:ga8b7e0c2e989e8c75f0dc789f3115323d"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:gaf82b71ef472a38f8fc9ac414d9d07e67"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#gaf82b71ef472a38f8fc9ac414d9d07e67">arm_fully_connected_q7_opt</a> (const q7_t pV, const q7_t pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t bias, q7_t pOut, q15_t vec_buffer)</td></tr> <tr class="memdesc:gaf82b71ef472a38f8fc9ac414d9d07e67"><td class="mdescLeft"> </td><td class="mdescRight">Q7 opt fully-connected layer function. <a href="#gaf82b71ef472a38f8fc9ac414d9d07e67">More...</a><br/></td></tr> <tr class="separator:gaf82b71ef472a38f8fc9ac414d9d07e67"><td class="memSeparator" colspan="2"> </td></tr> </table> <a name="details" id="details"></a><h2 class="groupheader">Description</h2> <p>Perform fully-connected layer</p> <p>Fully-connected layer is basically a matrix-vector multiplication with bias. The matrix is the weights and the input/output vectors are the activation values. Supported {weight, activation} precisions include {8-bit, 8-bit}, {16-bit, 16-bit}, and {8-bit, 16-bit}.</p> <p>Here we have two types of kernel functions. The basic function implements the function using regular GEMV approach. The opt functions operates with weights in interleaved formats. </p> <h2 class="groupheader">Function Documentation</h2> <a class="anchor" id="ga4a1521e7532a1e62d71f3b12762016e2"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_fully_connected_mat_q7_vec_q15 </td> <td>(</td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>pV</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>pM</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_vec</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>num_of_rows</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>pOut</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>vec_buffer</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl> <p><b>Buffer size:</b></p> <p>vec_buffer size: 0</p> <p>Q7_Q15 version of the fully connected layer</p> <p>Weights are in q7_t and Activations are in q15_t </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> <p>Referenced by <a class="el" href="arm__nnexamples__gru_8cpp.html#ac71a806472c7c0c284a2253e71a6a27b">gru_example()</a>.</p> </div> </div> <a class="anchor" id="gae3857bb6375692e81dde8cbd70adec08"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_fully_connected_mat_q7_vec_q15_opt </td> <td>(</td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>pV</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>pM</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_vec</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>num_of_rows</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>pOut</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>vec_buffer</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl> <p><b>Buffer size:</b></p> <p>vec_buffer size: 0</p> <p>Q7_Q15 version of the fully connected layer</p> <p>Weights are in q7_t and Activations are in q15_t</p> <p>Limitation: x4 version requires weight reordering to work</p> <p>Here we use only one pointer to read 4 rows in the weight matrix. So if the original q7_t matrix looks like this:</p> <p>\| a11 \| a12 \| a13 \| a14 \| a15 \| a16 \| a17 \|</p> <p>\| a21 \| a22 \| a23 \| a24 \| a25 \| a26 \| a27 \|</p> <p>\| a31 \| a32 \| a33 \| a34 \| a35 \| a36 \| a37 \|</p> <p>\| a41 \| a42 \| a43 \| a44 \| a45 \| a46 \| a47 \|</p> <p>\| a51 \| a52 \| a53 \| a54 \| a55 \| a56 \| a57 \|</p> <p>\| a61 \| a62 \| a63 \| a64 \| a65 \| a66 \| a67 \|</p> <p>We operates on multiple-of-4 rows, so the first four rows becomes</p> <p>\| a11 \| a21 \| a12 \| a22 \| a31 \| a41 \| a32 \| a42 \|</p> <p>\| a13 \| a23 \| a14 \| a24 \| a33 \| a43 \| a34 \| a44 \|</p> <p>\| a15 \| a25 \| a16 \| a26 \| a35 \| a45 \| a36 \| a46 \|</p> <p>The column left over will be in-order. which is: \| a17 \| a27 \| a37 \| a47 \|</p> <p>For the left-over rows, we do 1x1 computation, so the data remains as its original order.</p> <p>So the stored weight matrix looks like this:</p> <p>\| a11 \| a21 \| a12 \| a22 \| a31 \| a41 \|</p> <p>\| a32 \| a42 \| a13 \| a23 \| a14 \| a24 \|</p> <p>\| a33 \| a43 \| a34 \| a44 \| a15 \| a25 \|</p> <p>\| a16 \| a26 \| a35 \| a45 \| a36 \| a46 \|</p> <p>\| a17 \| a27 \| a37 \| a47 \| a51 \| a52 \|</p> <p>\| a53 \| a54 \| a55 \| a56 \| a57 \| a61 \|</p> <p>\| a62 \| a63 \| a64 \| a65 \| a66 \| a67 \| </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> <p>Referenced by <a class="el" href="arm__nnexamples__gru_8cpp.html#ac71a806472c7c0c284a2253e71a6a27b">gru_example()</a>.</p> </div> </div> <a class="anchor" id="gaac666c212b209e636c2369dd5c75d0dc"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_fully_connected_q15 </td> <td>(</td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>pV</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>pM</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_vec</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>num_of_rows</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>pOut</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>vec_buffer</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <p>Q15 basic fully-connected layer function.</p> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl> <p><b>Buffer size:</b></p> <p>vec_buffer size: 0 </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="ga062912078da113f5dd2004fd919a0ff2"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_fully_connected_q15_opt </td> <td>(</td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>pV</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>pM</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_vec</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>num_of_rows</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>pOut</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>vec_buffer</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl> <p><b>Buffer size:</b></p> <p>vec_buffer size: 0</p> <p>Here we use only one pointer to read 4 rows in the weight matrix. So if the original matrix looks like this:</p> <p>\| a11 \| a12 \| a13 \|</p> <p>\| a21 \| a22 \| a23 \|</p> <p>\| a31 \| a32 \| a33 \|</p> <p>\| a41 \| a42 \| a43 \|</p> <p>\| a51 \| a52 \| a53 \|</p> <p>\| a61 \| a62 \| a63 \|</p> <p>We operates on multiple-of-4 rows, so the first four rows becomes</p> <p>\| a11 \| a12 \| a21 \| a22 \| a31 \| a32 \| a41 \| a42 \|</p> <p>\| a13 \| a23 \| a33 \| a43 \|</p> <p>Remaining rows are kept the same original order.</p> <p>So the stored weight matrix looks like this:</p> <p>\| a11 \| a12 \| a21 \| a22 \| a31 \| a32 \| a41 \| a42 \|</p> <p>\| a13 \| a23 \| a33 \| a43 \| a51 \| a52 \| a53 \| a61 \|</p> <p>\| a62 \| a63 \| </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="ga8b7e0c2e989e8c75f0dc789f3115323d"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_fully_connected_q7 </td> <td>(</td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>pV</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>pM</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_vec</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>num_of_rows</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>pOut</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>vec_buffer</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl> <p><b>Buffer size:</b></p> <p>vec_buffer size: dim_vec</p> <p>This basic function is designed to work with regular weight matrix without interleaving. </p> <p>References <a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_q7_to_q15_reordered_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="gaf82b71ef472a38f8fc9ac414d9d07e67"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_fully_connected_q7_opt </td> <td>(</td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>pV</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>pM</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_vec</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>num_of_rows</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>pOut</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>vec_buffer</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl> <p><b>Buffer size:</b></p> <p>vec_buffer size: dim_vec</p> <p>This opt function is designed to work with interleaved weight matrix. The vector input is assumed in q7_t format, we call arm_q7_to_q15_no_shift_shuffle function to expand into q15_t format with certain weight re-ordering, refer to the function comments for more details. Here we use only one pointer to read 4 rows in the weight matrix. So if the original q7_t matrix looks like this:</p> <p>\| a11 \| a12 \| a13 \| a14 \| a15 \| a16 \| a17 \|</p> <p>\| a21 \| a22 \| a23 \| a24 \| a25 \| a26 \| a27 \|</p> <p>\| a31 \| a32 \| a33 \| a34 \| a35 \| a36 \| a37 \|</p> <p>\| a41 \| a42 \| a43 \| a44 \| a45 \| a46 \| a47 \|</p> <p>\| a51 \| a52 \| a53 \| a54 \| a55 \| a56 \| a57 \|</p> <p>\| a61 \| a62 \| a63 \| a64 \| a65 \| a66 \| a67 \|</p> <p>We operates on multiple-of-4 rows, so the first four rows becomes</p> <p>\| a11 \| a21 \| a13 \| a23 \| a31 \| a41 \| a33 \| a43 \|</p> <p>\| a12 \| a22 \| a14 \| a24 \| a32 \| a42 \| a34 \| a44 \|</p> <p>\| a15 \| a25 \| a35 \| a45 \| a16 \| a26 \| a36 \| a46 \|</p> <p>So within the kernel, we first read the re-ordered vector in as:</p> <p>\| b1 \| b3 \| and \| b2 \| b4 \|</p> <p>the four q31_t weights will look like</p> <p>\| a11 \| a13 \|, \| a21 \| a23 \|, \| a31 \| a33 \|, \| a41 \| a43 \|</p> <p>\| a12 \| a14 \|, \| a22 \| a24 \|, \| a32 \| a34 \|, \| a42 \| a44 \|</p> <p>The column left over will be in-order. which is:</p> <p>\| a17 \| a27 \| a37 \| a47 \|</p> <p>For the left-over rows, we do 1x1 computation, so the data remains as its original order.</p> <p>So the stored weight matrix looks like this:</p> <p>\| a11 \| a21 \| a13 \| a23 \| a31 \| a41 \|</p> <p>\| a33 \| a43 \| a12 \| a22 \| a14 \| a24 \|</p> <p>\| a32 \| a42 \| a34 \| a44 \| a15 \| a25 \|</p> <p>\| a35 \| a45 \| a16 \| a26 \| a36 \| a46 \|</p> <p>\| a17 \| a27 \| a37 \| a47 \| a51 \| a52 \|</p> <p>\| a53 \| a54 \| a55 \| a56 \| a57 \| a61 \|</p> <p>\| a62 \| a63 \| a64 \| a65 \| a66 \| a67 \| </p> <p>References <a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_q7_to_q15_reordered_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> <p>Referenced by <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main()</a>.</p> </div> </div> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. 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<!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"/> <title>Gated Recurrent Unit Example</title> <title>CMSIS-NN: Gated Recurrent Unit Example</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> </head> <body> <div id="top"><!-- do not remove this div, it is closed by doxygen! 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It contains two sigmoid gates and one hidden state. </dd></dl> <dl class="section user"><dt></dt><dd>The computation can be summarized as: <pre>z[t] = sigmoid( W_z ⋅ {h[t-1],x[t]} ) r[t] = sigmoid( W_r ⋅ {h[t-1],x[t]} ) n[t] = tanh( W_n ⋅ [r[t] × {h[t-1], x[t]} ) h[t] = (1 - z[t]) × h[t-1] + z[t] × n[t] </pre> <div class="image"> <img src="GRU.gif" alt="GRU.gif"/> <div class="caption"> Gate Recurrent Unit Diagram</div></div> </dd></dl> <dl class="section user"><dt>Variables Description:</dt><dd></dd></dl> <dl class="section user"><dt></dt><dd><ul> <li><code>update_gate_weights</code>, <code>reset_gate_weights</code>, <code>hidden_state_weights</code> are weights corresponding to update gate (W_z), reset gate (W_r), and hidden state (W_n). </li> <li><code>update_gate_bias</code>, <code>reset_gate_bias</code>, <code>hidden_state_bias</code> are layer bias arrays </li> <li><code>test_input1</code>, <code>test_input2</code>, <code>test_history</code> are the inputs and initial history</li> </ul> </dd></dl> <dl class="section user"><dt></dt><dd>The buffer is allocated as: </dd></dl> <dl class="section user"><dt></dt><dd>\| reset \| input \| history \| update \| hidden_state \| </dd></dl> <dl class="section user"><dt></dt><dd>In this way, the concatination is automatically done since (reset, input) and (input, history) are physically concatinated in memory. </dd></dl> <dl class="section user"><dt></dt><dd>The ordering of the weight matrix should be adjusted accordingly.</dd></dl> <dl class="section user"><dt>CMSIS DSP Software Library Functions Used:</dt><dd></dd></dl> <dl class="section user"><dt></dt><dd><ul> <li><a class="el" href="group__FC.html#gae3857bb6375692e81dde8cbd70adec08" title="Mixed Q15-Q7 opt fully-connected layer function. ">arm_fully_connected_mat_q7_vec_q15_opt()</a></li> <li><a class="el" href="group__Acti.html#ga8932b57c8d0ee757511af2d40dcc11e7" title="Q15 neural network activation function using direct table look-up. ">arm_nn_activations_direct_q15()</a></li> <li>arm_mult_q15()</li> <li>arm_offset_q15()</li> <li>arm_sub_q15()</li> <li>arm_copy_q15()</li> </ul> </dd></dl> <p><b> Refer </b> <a class="el" href="arm__nnexamples__gru_8cpp.html">arm_nnexamples_gru.cpp</a> </p> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/group__GRUExample.html	HTML	apache-2.0	8,830
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const uint16_t out_shift, uint32_t blockSize)</td></tr> <tr class="memdesc:ga08f8340aa6533271b3aa6d211614fe22"><td class="mdescLeft"> </td><td class="mdescRight">Q7 vector multiplication with variable output shifts. <a href="#ga08f8340aa6533271b3aa6d211614fe22">More...</a><br/></td></tr> <tr class="separator:ga08f8340aa6533271b3aa6d211614fe22"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:gad46c9ab012cceda8ce6681c687a58c70"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNBasicMath.html#gad46c9ab012cceda8ce6681c687a58c70">arm_nn_mult_q7</a> (q7_t pSrcA, q7_t pSrcB, q7_t pDst, const uint16_t out_shift, uint32_t blockSize)</td></tr> <tr class="memdesc:gad46c9ab012cceda8ce6681c687a58c70"><td class="mdescLeft"> </td><td class="mdescRight">Q7 vector multiplication with variable output shifts. <a href="#gad46c9ab012cceda8ce6681c687a58c70">More...</a><br/></td></tr> <tr class="separator:gad46c9ab012cceda8ce6681c687a58c70"><td class="memSeparator" colspan="2"> </td></tr> </table> <a name="details" id="details"></a><h2 class="groupheader">Description</h2> <p>Basic Math Functions for Neural Network Computation </p> <h2 class="groupheader">Function Documentation</h2> <a class="anchor" id="ga08f8340aa6533271b3aa6d211614fe22"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_nn_mult_q15 </td> <td>(</td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>pSrcA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>pSrcB</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>pDst</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint32_t </td> <td class="paramname"><em>blockSize</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pSrcA</td><td>pointer to the first input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pSrcB</td><td>pointer to the second input vector </td></tr> <tr><td class="paramdir">[out]</td><td class="paramname">pDst</td><td>pointer to the output vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">blockSize</td><td>number of samples in each vector </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p><b>Scaling and Overflow Behavior:</b> </p> <dl class="section user"><dt></dt><dd>The function uses saturating arithmetic. Results outside of the allowable Q15 range [0x8000 0x7FFF] will be saturated. </dd></dl> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="gad46c9ab012cceda8ce6681c687a58c70"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_nn_mult_q7 </td> <td>(</td> <td class="paramtype">q7_t  </td> <td class="paramname"><em>pSrcA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>pSrcB</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>pDst</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint32_t </td> <td class="paramname"><em>blockSize</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pSrcA</td><td>pointer to the first input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pSrcB</td><td>pointer to the second input vector </td></tr> <tr><td class="paramdir">[out]</td><td class="paramname">*pDst</td><td>pointer to the output vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">blockSize</td><td>number of samples in each vector </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p><b>Scaling and Overflow Behavior:</b> </p> <dl class="section user"><dt></dt><dd>The function uses saturating arithmetic. Results outside of the allowable Q7 range [0x80 0x7F] will be saturated. </dd></dl> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/group__NNBasicMath.html	HTML	apache-2.0	12,813
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(const q7_t Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q7_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q7_t bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:ga110adcfdaab356c750c6270aa5e05f29"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q7 version of 1x1 convolution (non-sqaure shape) <a href="#ga110adcfdaab356c750c6270aa5e05f29">More...</a><br/></td></tr> <tr class="separator:ga110adcfdaab356c750c6270aa5e05f29"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga55701f213b198084b52eab53097f1f58"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga55701f213b198084b52eab53097f1f58">arm_convolve_HWC_q15_basic</a> (const q15_t Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q15_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q15_t bias, const uint16_t bias_shift, const uint16_t out_shift, q15_t Im_out, const uint16_t dim_im_out, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:ga55701f213b198084b52eab53097f1f58"><td class="mdescLeft"> </td><td class="mdescRight">Basic Q15 convolution function. <a href="#ga55701f213b198084b52eab53097f1f58">More...</a><br/></td></tr> <tr class="separator:ga55701f213b198084b52eab53097f1f58"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga4efb1ccbbaa7dd936961989dcb443f50"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga4efb1ccbbaa7dd936961989dcb443f50">arm_convolve_HWC_q15_fast</a> (const q15_t Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q15_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q15_t bias, const uint16_t bias_shift, const uint16_t out_shift, q15_t Im_out, const uint16_t dim_im_out, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:ga4efb1ccbbaa7dd936961989dcb443f50"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q15 convolution function. <a href="#ga4efb1ccbbaa7dd936961989dcb443f50">More...</a><br/></td></tr> <tr class="separator:ga4efb1ccbbaa7dd936961989dcb443f50"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga614ec3b71eb96e29952ec3f09e7b9c3c"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga614ec3b71eb96e29952ec3f09e7b9c3c">arm_convolve_HWC_q15_fast_nonsquare</a> (const q15_t Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q15_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q15_t bias, const uint16_t bias_shift, const uint16_t out_shift, q15_t Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:ga614ec3b71eb96e29952ec3f09e7b9c3c"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q15 convolution function (non-sqaure shape) <a href="#ga614ec3b71eb96e29952ec3f09e7b9c3c">More...</a><br/></td></tr> <tr class="separator:ga614ec3b71eb96e29952ec3f09e7b9c3c"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga210ae8d8fc1d12ee15b41f1fa6947681"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga210ae8d8fc1d12ee15b41f1fa6947681">arm_convolve_HWC_q7_basic</a> (const q7_t Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q7_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q7_t bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t Im_out, const uint16_t dim_im_out, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:ga210ae8d8fc1d12ee15b41f1fa6947681"><td class="mdescLeft"> </td><td class="mdescRight">Basic Q7 convolution function. <a href="#ga210ae8d8fc1d12ee15b41f1fa6947681">More...</a><br/></td></tr> <tr class="separator:ga210ae8d8fc1d12ee15b41f1fa6947681"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga4501fa22c0836002aa47ccc313dce252"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga4501fa22c0836002aa47ccc313dce252">arm_convolve_HWC_q7_basic_nonsquare</a> (const q7_t Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q7_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q7_t bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:ga4501fa22c0836002aa47ccc313dce252"><td class="mdescLeft"> </td><td class="mdescRight">Basic Q7 convolution function (non-sqaure shape) <a href="#ga4501fa22c0836002aa47ccc313dce252">More...</a><br/></td></tr> <tr class="separator:ga4501fa22c0836002aa47ccc313dce252"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:gae00d3c1285907d59657369fc98bcc83f"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#gae00d3c1285907d59657369fc98bcc83f">arm_convolve_HWC_q7_fast</a> (const q7_t Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q7_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q7_t bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t Im_out, const uint16_t dim_im_out, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:gae00d3c1285907d59657369fc98bcc83f"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q7 convolution function. <a href="#gae00d3c1285907d59657369fc98bcc83f">More...</a><br/></td></tr> <tr class="separator:gae00d3c1285907d59657369fc98bcc83f"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:gabc6d6b991024e9e5c5cdbd7489de88ef"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#gabc6d6b991024e9e5c5cdbd7489de88ef">arm_convolve_HWC_q7_fast_nonsquare</a> (const q7_t Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q7_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q7_t bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:gabc6d6b991024e9e5c5cdbd7489de88ef"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q7 convolution function (non-sqaure shape) <a href="#gabc6d6b991024e9e5c5cdbd7489de88ef">More...</a><br/></td></tr> <tr class="separator:gabc6d6b991024e9e5c5cdbd7489de88ef"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga98f2ead67d7cbdf558b0cd8a3b8fc148"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga98f2ead67d7cbdf558b0cd8a3b8fc148">arm_convolve_HWC_q7_RGB</a> (const q7_t Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q7_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q7_t bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t Im_out, const uint16_t dim_im_out, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:ga98f2ead67d7cbdf558b0cd8a3b8fc148"><td class="mdescLeft"> </td><td class="mdescRight">Q7 convolution function for RGB image. <a href="#ga98f2ead67d7cbdf558b0cd8a3b8fc148">More...</a><br/></td></tr> <tr class="separator:ga98f2ead67d7cbdf558b0cd8a3b8fc148"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga02a296cb4f6361a70c3ecf1ef1238292"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga02a296cb4f6361a70c3ecf1ef1238292">arm_depthwise_conv_u8_basic_ver1</a> (const uint8_t input, const uint16_t input_x, const uint16_t input_y, const uint16_t input_ch, const uint8_t kernel, const uint16_t kernel_x, const uint16_t kernel_y, const int16_t ch_mult, const int16_t pad_x, const int16_t pad_y, const int16_t stride_x, const int16_t stride_y, const int16_t dilation_x, const int16_t dilation_y, const int32_t bias, const int32_t input_offset, const int32_t filter_offset, const int32_t output_offset, uint8_t output, const uint16_t output_x, const uint16_t output_y, const int32_t output_activation_min, const int32_t output_activation_max, const int32_t out_shift, const int32_t out_mult)</td></tr> <tr class="memdesc:ga02a296cb4f6361a70c3ecf1ef1238292"><td class="mdescLeft"> </td><td class="mdescRight">uint8 depthwise convolution function with asymmetric quantization for even number of channel multiplier and input channels. Unless specified otherwise, arguments are mandatory. Both square and non-square inputs are accepted. <a href="#ga02a296cb4f6361a70c3ecf1ef1238292">More...</a><br/></td></tr> <tr class="separator:ga02a296cb4f6361a70c3ecf1ef1238292"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:gad3d21b3bc6dbd6f3b97d01104349cb0a"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#gad3d21b3bc6dbd6f3b97d01104349cb0a">arm_depthwise_separable_conv_HWC_q7</a> (const q7_t Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q7_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q7_t bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t Im_out, const uint16_t dim_im_out, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:gad3d21b3bc6dbd6f3b97d01104349cb0a"><td class="mdescLeft"> </td><td class="mdescRight">Q7 depthwise separable convolution function. <a href="#gad3d21b3bc6dbd6f3b97d01104349cb0a">More...</a><br/></td></tr> <tr class="separator:gad3d21b3bc6dbd6f3b97d01104349cb0a"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga32ac508c5467813a84f74f96655dc697"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga32ac508c5467813a84f74f96655dc697">arm_depthwise_separable_conv_HWC_q7_nonsquare</a> (const q7_t Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q7_t wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q7_t bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t bufferA, q7_t bufferB)</td></tr> <tr class="memdesc:ga32ac508c5467813a84f74f96655dc697"><td class="mdescLeft"> </td><td class="mdescRight">Q7 depthwise separable convolution function (non-square shape) <a href="#ga32ac508c5467813a84f74f96655dc697">More...</a><br/></td></tr> <tr class="separator:ga32ac508c5467813a84f74f96655dc697"><td class="memSeparator" colspan="2"> </td></tr> </table> <a name="details" id="details"></a><h2 class="groupheader">Description</h2> <p>Perform convolution layer</p> <p>The convolution is implemented in 2 steps: im2col and GEMM</p> <p>im2col is a process of converting each patch of image data into a column. After im2col, the convolution is computed as matrix-matrix multiplication.</p> <p>To reduce the memory footprint, the im2col is performed partially. Each iteration, only a few column (i.e., patches) are generated and computed with GEMM kernels similar to CMSIS-DSP arm_mat_mult functions. </p> <h2 class="groupheader">Function Documentation</h2> <a class="anchor" id="ga110adcfdaab356c750c6270aa5e05f29"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_convolve_1x1_HWC_q7_fast_nonsquare </td> <td>(</td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding size x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding size y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> <p>This function is optimized for convolution with 1x1 kernel size (i.e., dim_kernel_x=1 and dim_kernel_y=1). It can be used for the second half of MobileNets [1] after depthwise separable convolution.</p> <p>This function is the version with full list of optimization tricks, but with some contraints: ch_im_in is multiple of 4 ch_im_out is multiple of 2</p> <p>[1] MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications <a href="https://arxiv.org/abs/1704.04861">https://arxiv.org/abs/1704.04861</a> </p> <p>References <a class="el" href="arm__nnfunctions_8h.html#aefe9c7ce9a65060a244b06dffe74c4b3">arm_nn_mat_mult_kernel_q7_q15_reordered()</a>, <a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_q7_to_q15_reordered_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="ga55701f213b198084b52eab53097f1f58"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_convolve_HWC_q15_basic </td> <td>(</td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl> <p><b>Buffer size:</b></p> <p>bufferA size: ch_im_indim_kerneldim_kernel</p> <p>bufferB size: 0</p> <p>This basic version is designed to work for any input tensor and weight dimension. </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="ga4efb1ccbbaa7dd936961989dcb443f50"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_convolve_HWC_q15_fast </td> <td>(</td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> <p><b>Buffer size:</b></p> <p>bufferA size: 2ch_im_indim_kerneldim_kernel</p> <p>bufferB size: 0</p> <p><b>Input dimension constraints:</b></p> <p>ch_im_in is multiple of 2</p> <p>ch_im_out is multipe of 2 </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="ga614ec3b71eb96e29952ec3f09e7b9c3c"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_convolve_HWC_q15_fast_nonsquare </td> <td>(</td> <td class="paramtype">const q15_t  </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding size x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding size y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> <p><b>Buffer size:</b></p> <p>bufferA size: 2ch_im_indim_kerneldim_kernel</p> <p>bufferB size: 0</p> <p><b>Input dimension constraints:</b></p> <p>ch_im_in is multiple of 2</p> <p>ch_im_out is multipe of 2 </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="ga210ae8d8fc1d12ee15b41f1fa6947681"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_convolve_HWC_q7_basic </td> <td>(</td> <td class="paramtype">const q7_t  </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl> <p><b>Buffer size:</b></p> <p>bufferA size: 2ch_im_indim_kerneldim_kernel</p> <p>bufferB size: 0</p> <p>This basic version is designed to work for any input tensor and weight dimension. </p> <p>References <a class="el" href="arm__nnfunctions_8h.html#abc4fb258cfe8500ee68e812a293a80a3">arm_nn_mat_mult_kernel_q7_q15()</a>, <a class="el" href="group__nndata__convert.html#gae349de4dba8d253c89d45794ccf05680">arm_q7_to_q15_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="ga4501fa22c0836002aa47ccc313dce252"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_convolve_HWC_q7_basic_nonsquare </td> <td>(</td> <td class="paramtype">const q7_t  </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding size x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding size y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code> </dd></dl> <p>References <a class="el" href="arm__nnfunctions_8h.html#abc4fb258cfe8500ee68e812a293a80a3">arm_nn_mat_mult_kernel_q7_q15()</a>, <a class="el" href="group__nndata__convert.html#gae349de4dba8d253c89d45794ccf05680">arm_q7_to_q15_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="gae00d3c1285907d59657369fc98bcc83f"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_convolve_HWC_q7_fast </td> <td>(</td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> <p><b>Buffer size:</b></p> <p>bufferA size: 2ch_im_indim_kerneldim_kernel</p> <p>bufferB size: 0</p> <p><b>Input dimension constraints:</b></p> <p>ch_im_in is multiple of 4 ( because of the SIMD32 read and swap )</p> <p>ch_im_out is multipe of 2 ( bacause 2x2 mat_mult kernel )</p> <p>The im2col converts the Q7 tensor input into Q15 column, which is stored in bufferA. There is reordering happenning during this im2col process with arm_q7_to_q15_reordered_no_shift. For every four elements, the second and third elements are swapped.</p> <p>The computation kernel arm_nn_mat_mult_kernel_q7_q15_reordered does the GEMM computation with the reordered columns.</p> <p>To speed-up the determination of the padding condition, we split the computation into 3x3 parts, i.e., {top, mid, bottom} X {left, mid, right}. This reduces the total number of boundary condition checks and improves the data copying performance. </p> <p>References <a class="el" href="arm__nnfunctions_8h.html#aefe9c7ce9a65060a244b06dffe74c4b3">arm_nn_mat_mult_kernel_q7_q15_reordered()</a>, <a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_q7_to_q15_reordered_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> <p>Referenced by <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main()</a>.</p> </div> </div> <a class="anchor" id="gabc6d6b991024e9e5c5cdbd7489de88ef"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_convolve_HWC_q7_fast_nonsquare </td> <td>(</td> <td class="paramtype">const q7_t  </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding size x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding size y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> <p>This function is the version with full list of optimization tricks, but with some contraints: ch_im_in is multiple of 4 ch_im_out is multiple of 2 </p> <p>References <a class="el" href="arm__nnfunctions_8h.html#aefe9c7ce9a65060a244b06dffe74c4b3">arm_nn_mat_mult_kernel_q7_q15_reordered()</a>, <a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_q7_to_q15_reordered_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> </div> </div> <a class="anchor" id="ga98f2ead67d7cbdf558b0cd8a3b8fc148"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_convolve_HWC_q7_RGB </td> <td>(</td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <p>Q7 version of convolution for RGB image.</p> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> <p><b>Buffer size:</b></p> <p>bufferA size: 2ch_im_indim_kerneldim_kernel</p> <p>bufferB size: 0</p> <p><b>Input dimension constraints:</b></p> <p>ch_im_in equals 3</p> <p>This kernel is written exclusively for convolution with ch_im_in equals 3. This applies on the first layer of CNNs which has input image with RGB format. </p> <p>References <a class="el" href="arm__nnfunctions_8h.html#abc4fb258cfe8500ee68e812a293a80a3">arm_nn_mat_mult_kernel_q7_q15()</a>, <a class="el" href="unionarm__nnword.html#a9b5e49e4e2c4b7203e07b305386bb2ba">arm_nnword::half_words</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>, and <a class="el" href="unionarm__nnword.html#a35c7b2ae25e35e0ddcd9ec0a1a6f8d18">arm_nnword::word</a>.</p> <p>Referenced by <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main()</a>.</p> </div> </div> <a class="anchor" id="ga02a296cb4f6361a70c3ecf1ef1238292"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_depthwise_conv_u8_basic_ver1 </td> <td>(</td> <td class="paramtype">const uint8_t  </td> <td class="paramname"><em>input</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>input_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>input_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>input_ch</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint8_t * </td> <td class="paramname"><em>kernel</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>kernel_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>kernel_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int16_t </td> <td class="paramname"><em>ch_mult</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int16_t </td> <td class="paramname"><em>pad_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int16_t </td> <td class="paramname"><em>pad_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int16_t </td> <td class="paramname"><em>stride_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int16_t </td> <td class="paramname"><em>stride_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int16_t </td> <td class="paramname"><em>dilation_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int16_t </td> <td class="paramname"><em>dilation_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int32_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int32_t </td> <td class="paramname"><em>input_offset</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int32_t </td> <td class="paramname"><em>filter_offset</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int32_t </td> <td class="paramname"><em>output_offset</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint8_t * </td> <td class="paramname"><em>output</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>output_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>output_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int32_t </td> <td class="paramname"><em>output_activation_min</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int32_t </td> <td class="paramname"><em>output_activation_max</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int32_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const int32_t </td> <td class="paramname"><em>out_mult</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <p>uint8 depthwise convolution function with asymmetric quantization for even number of channel multiplier and input channels. Unless specified otherwise, arguments are mandatory.</p> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">input_x</td><td>Width of input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">input_y</td><td>Height of input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">input_ch</td><td>Channels in input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">kernel</td><td>Pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">kernel_x</td><td>Width of kernel </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">kernel_y</td><td>Height of kernel </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_mult</td><td>Number of channel multiplier </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pad_x</td><td>Padding sizes x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">pad_y</td><td>Padding sizes y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>Convolution stride along the width </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>Convolution stride along the height </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dilation_x</td><td>Dilation along width. Not used and intended for future enhancement. </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dilation_y</td><td>Dilation along height. Not used and intended for future enhancement. </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>Pointer to optional bias values. If no bias is availble, NULL is expected </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">input_offset</td><td>Input tensor zero offset </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">filter_offset</td><td>Kernel tensor zero offset </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">output_offset</td><td>Output tensor zero offset </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">output</td><td>Pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">output_x</td><td>Width of output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">output_y</td><td>Height of output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">output_activation_min</td><td>Minimum value to clamp the output to. Range : {0, 255} </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">output_activation_max</td><td>Minimum value to clamp the output to. Range : {0, 255} </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>Amount of right-shift for output </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_mult</td><td>Output multiplier for requantization </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns one of the following <code>ARM_MATH_SIZE_MISMATCH</code> - Not supported dimension of tensors <code>ARM_MATH_SUCCESS</code> - Successful operation <code>ARM_MATH_ARGUMENT_ERROR</code> - Implementation not available</dd></dl> <p><b> Input constraints</b> ch_mult is multiple of 2 kernel_x is multiple of 2 </p> <p>References <a class="el" href="arm__nnsupportfunctions_8h.html#ab6dbc2fd53fae3ccdd1d0d70c8d3b491">arm_nn_divide_by_power_of_two()</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a51721c10f116c9f5b8d9908367989d44">arm_nn_sat_doubling_high_mult()</a>, <a class="el" href="arm__depthwise__conv__u8__basic__ver1_8c.html#aeb98996ffa34fb40d8e91919d2ebdc56">DILATION_X</a>, <a class="el" href="arm__depthwise__conv__u8__basic__ver1_8c.html#a9371ac7b5689f9e74a18a2d548c32033">DILATION_Y</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a2953f124ae444ebdd2b2a0873ac36b7e">LEFT_SHIFT</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a26af54489c1401b91595bf0c92ef87c4">RIGHT_SHIFT</a>.</p> </div> </div> <a class="anchor" id="gad3d21b3bc6dbd6f3b97d01104349cb0a"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_depthwise_separable_conv_HWC_q7 </td> <td>(</td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> <p><b>Buffer size:</b></p> <p>bufferA size: 2ch_im_indim_kerneldim_kernel</p> <p>bufferB size: 0</p> <p><b>Input dimension constraints:</b></p> <p>ch_im_in equals ch_im_out</p> <p>Implementation: There are 3 nested loop here: Inner loop: calculate each output value with MAC instruction over an accumulator Mid loop: loop over different output channel Outer loop: loop over different output (x, y) </p> <p>References <a class="el" href="unionarm__nnword.html#ac7cff6480a8e29d95f29b73cb1267249">arm_nnword::bytes</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>, and <a class="el" href="unionarm__nnword.html#a35c7b2ae25e35e0ddcd9ec0a1a6f8d18">arm_nnword::word</a>.</p> </div> </div> <a class="anchor" id="ga32ac508c5467813a84f74f96655dc697"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">arm_status arm_depthwise_separable_conv_HWC_q7_nonsquare </td> <td>(</td> <td class="paramtype">const q7_t  </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>wt</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>bias</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>bias_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>out_shift</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_x</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out_y</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferB</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding sizes x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding sizes y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> <p>This function is the version with full list of optimization tricks, but with some contraints: ch_im_in is multiple of 2 ch_im_out is multiple of 2 </p> <p>References <a class="el" href="unionarm__nnword.html#ac7cff6480a8e29d95f29b73cb1267249">arm_nnword::bytes</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>, and <a class="el" href="unionarm__nnword.html#a35c7b2ae25e35e0ddcd9ec0a1a6f8d18">arm_nnword::word</a>.</p> </div> </div> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. 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<!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"/> <title>Neural Network Pooling Functions</title> <title>CMSIS-NN: Neural Network Pooling Functions</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link 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dim_im_in, const uint16_t ch_im_in, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const uint16_t dim_im_out, q7_t bufferA, q7_t Im_out)</td></tr> <tr class="memdesc:ga99afcdcc61eaf429ab3ee823702e44ce"><td class="mdescLeft"> </td><td class="mdescRight">Q7 max pooling function. <a href="#ga99afcdcc61eaf429ab3ee823702e44ce">More...</a><br/></td></tr> <tr class="separator:ga99afcdcc61eaf429ab3ee823702e44ce"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:gae4a7b07f97ec4313524c9fb9fbcb1f6a"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__Pooling.html#gae4a7b07f97ec4313524c9fb9fbcb1f6a">arm_avepool_q7_HWC</a> (q7_t Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const uint16_t dim_im_out, q7_t bufferA, q7_t Im_out)</td></tr> <tr class="memdesc:gae4a7b07f97ec4313524c9fb9fbcb1f6a"><td class="mdescLeft"> </td><td class="mdescRight">Q7 average pooling function. <a href="#gae4a7b07f97ec4313524c9fb9fbcb1f6a">More...</a><br/></td></tr> <tr class="separator:gae4a7b07f97ec4313524c9fb9fbcb1f6a"><td class="memSeparator" colspan="2"> </td></tr> </table> <a name="details" id="details"></a><h2 class="groupheader">Description</h2> <p>Perform pooling functions, including max pooling and average pooling </p> <h2 class="groupheader">Function Documentation</h2> <a class="anchor" id="gae4a7b07f97ec4313524c9fb9fbcb1f6a"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_avepool_q7_HWC </td> <td>(</td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p><b>Buffer size:</b></p> <p>bufferA size: 2dim_im_outch_im_in</p> <p>The pooling function is implemented as split x-pooling then y-pooling.</p> <p>This pooling function is input-destructive. Input data is undefined after calling this function. </p> <p>References <a class="el" href="group__nndata__convert.html#gae349de4dba8d253c89d45794ccf05680">arm_q7_to_q15_no_shift()</a>.</p> </div> </div> <a class="anchor" id="ga99afcdcc61eaf429ab3ee823702e44ce"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_maxpool_q7_HWC </td> <td>(</td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>ch_im_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_kernel</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>padding</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>stride</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_im_out</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>bufferA</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>Im_out</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> <tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p><b>Buffer size:</b></p> <p>bufferA size: 0</p> <p>The pooling function is implemented as split x-pooling then y-pooling.</p> <p>This pooling function is input-destructive. Input data is undefined after calling this function. </p> <p>Referenced by <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main()</a>.</p> </div> </div> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/group__Pooling.html	HTML	apache-2.0	15,552
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<!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"/> <title>Softmax Functions</title> <title>CMSIS-NN: Softmax Functions</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" 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p_out)</td></tr> <tr class="memdesc:ga1cacd8b84b8363079311987d0016ebe5"><td class="mdescLeft"> </td><td class="mdescRight">Q15 softmax function. <a href="#ga1cacd8b84b8363079311987d0016ebe5">More...</a><br/></td></tr> <tr class="separator:ga1cacd8b84b8363079311987d0016ebe5"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ga89aff212a97a3cf32d9d7ddf11a8f43e"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__Softmax.html#ga89aff212a97a3cf32d9d7ddf11a8f43e">arm_softmax_q7</a> (const q7_t vec_in, const uint16_t dim_vec, q7_t p_out)</td></tr> <tr class="memdesc:ga89aff212a97a3cf32d9d7ddf11a8f43e"><td class="mdescLeft"> </td><td class="mdescRight">Q7 softmax function. <a href="#ga89aff212a97a3cf32d9d7ddf11a8f43e">More...</a><br/></td></tr> <tr class="separator:ga89aff212a97a3cf32d9d7ddf11a8f43e"><td class="memSeparator" colspan="2"> </td></tr> </table> <a name="details" id="details"></a><h2 class="groupheader">Description</h2> <p>EXP(2) based softmax function </p> <h2 class="groupheader">Function Documentation</h2> <a class="anchor" id="ga1cacd8b84b8363079311987d0016ebe5"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_softmax_q15 </td> <td>(</td> <td class="paramtype">const q15_t * </td> <td class="paramname"><em>vec_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_vec</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>p_out</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">vec_in</td><td>pointer to input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>input vector dimention </td></tr> <tr><td class="paramdir">[out]</td><td class="paramname">p_out</td><td>pointer to output vector </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p>Here, instead of typical e based softmax, we use 2-based softmax, i.e.,:</p> <p>y_i = 2^(x_i) / sum(2^x_j)</p> <p>The relative output will be different here. But mathematically, the gradient will be the same with a log(2) scaling factor. </p> </div> </div> <a class="anchor" id="ga89aff212a97a3cf32d9d7ddf11a8f43e"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_softmax_q7 </td> <td>(</td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>vec_in</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">const uint16_t </td> <td class="paramname"><em>dim_vec</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q7_t * </td> <td class="paramname"><em>p_out</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">vec_in</td><td>pointer to input vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>input vector dimention </td></tr> <tr><td class="paramdir">[out]</td><td class="paramname">p_out</td><td>pointer to output vector </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p>Here, instead of typical natural logarithm e based softmax, we use 2-based softmax here, i.e.,:</p> <p>y_i = 2^(x_i) / sum(2^x_j)</p> <p>The relative output will be different here. But mathematically, the gradient will be the same with a log(2) scaling factor. </p> <p>Referenced by <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main()</a>.</p> </div> </div> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/group__Softmax.html	HTML	apache-2.0	11,339
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<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"> $(document).ready(function(){initNavTree('group__nndata__convert.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" 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class="memdesc:gae349de4dba8d253c89d45794ccf05680"><td class="mdescLeft"> </td><td class="mdescRight">Converts the elements of the Q7 vector to Q15 vector without left-shift. <a href="#gae349de4dba8d253c89d45794ccf05680">More...</a><br/></td></tr> <tr class="separator:gae349de4dba8d253c89d45794ccf05680"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:gaba8fd446d5f54760b406ee63b25d1aee"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_q7_to_q15_reordered_no_shift</a> (const q7_t pSrc, q15_t pDst, uint32_t blockSize)</td></tr> <tr class="memdesc:gaba8fd446d5f54760b406ee63b25d1aee"><td class="mdescLeft"> </td><td class="mdescRight">Converts the elements of the Q7 vector to reordered Q15 vector without left-shift. <a href="#gaba8fd446d5f54760b406ee63b25d1aee">More...</a><br/></td></tr> <tr class="separator:gaba8fd446d5f54760b406ee63b25d1aee"><td class="memSeparator" colspan="2"> </td></tr> </table> <a name="details" id="details"></a><h2 class="groupheader">Description</h2> <p>Perform data type conversion in-between neural network operations </p> <h2 class="groupheader">Function Documentation</h2> <a class="anchor" id="gae349de4dba8d253c89d45794ccf05680"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_q7_to_q15_no_shift </td> <td>(</td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>pSrc</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>pDst</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint32_t </td> <td class="paramname"><em>blockSize</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pSrc</td><td>points to the Q7 input vector </td></tr> <tr><td class="paramdir">[out]</td><td class="paramname">pDst</td><td>points to the Q15 output vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">blockSize</td><td>length of the input vector </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <dl class="section user"><dt>Description: </dt><dd></dd></dl> <p>The equation used for the conversion process is:</p> <pre> pDst[n] = (q15_t) pSrc[n]; 0 <= n < blockSize. </pre> <p>Referenced by <a class="el" href="group__Pooling.html#gae4a7b07f97ec4313524c9fb9fbcb1f6a">arm_avepool_q7_HWC()</a>, <a class="el" href="group__NNConv.html#ga210ae8d8fc1d12ee15b41f1fa6947681">arm_convolve_HWC_q7_basic()</a>, and <a class="el" href="group__NNConv.html#ga4501fa22c0836002aa47ccc313dce252">arm_convolve_HWC_q7_basic_nonsquare()</a>.</p> </div> </div> <a class="anchor" id="gaba8fd446d5f54760b406ee63b25d1aee"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">void arm_q7_to_q15_reordered_no_shift </td> <td>(</td> <td class="paramtype">const q7_t * </td> <td class="paramname"><em>pSrc</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">q15_t * </td> <td class="paramname"><em>pDst</em>, </td> </tr> <tr> <td class="paramkey"></td> <td></td> <td class="paramtype">uint32_t </td> <td class="paramname"><em>blockSize</em> </td> </tr> <tr> <td></td> <td>)</td> <td></td><td></td> </tr> </table> </div><div class="memdoc"> <dl class="params"><dt>Parameters</dt><dd> <table class="params"> <tr><td class="paramdir">[in]</td><td class="paramname">pSrc</td><td>points to the Q7 input vector </td></tr> <tr><td class="paramdir">[out]</td><td class="paramname">pDst</td><td>points to the Q15 output vector </td></tr> <tr><td class="paramdir">[in]</td><td class="paramname">blockSize</td><td>length of the input vector </td></tr> </table> </dd> </dl> <dl class="section return"><dt>Returns</dt><dd>none.</dd></dl> <p>This function does the q7 to q15 expansion with re-ordering</p> <pre> \| A1 \| A2 \| A3 \| A4 \|</pre><pre> 0 7 8 15 16 23 24 31 </pre><p>is converted into:</p> <pre> \| A1 \| A3 \| and \| A2 \| A4 \|</pre><pre> 0 15 16 31 0 15 16 31 </pre><p>This looks strange but is natural considering how sign-extension is done at assembly level.</p> <p>The expansion of other other oprand will follow the same rule so that the end results are the same.</p> <p>The tail (i.e., last (N % 4) elements) will still be in original order. </p> <p>Referenced by <a class="el" href="group__NNConv.html#ga110adcfdaab356c750c6270aa5e05f29">arm_convolve_1x1_HWC_q7_fast_nonsquare()</a>, <a class="el" href="group__NNConv.html#gae00d3c1285907d59657369fc98bcc83f">arm_convolve_HWC_q7_fast()</a>, <a class="el" href="group__NNConv.html#gabc6d6b991024e9e5c5cdbd7489de88ef">arm_convolve_HWC_q7_fast_nonsquare()</a>, <a class="el" href="group__FC.html#ga8b7e0c2e989e8c75f0dc789f3115323d">arm_fully_connected_q7()</a>, and <a class="el" href="group__FC.html#gaf82b71ef472a38f8fc9ac414d9d07e67">arm_fully_connected_q7_opt()</a>.</p> </div> </div> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. 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The descrition of the kernels are included in the function description. The implementation details are also described in this paper [1].</p> <h2>Block Diagram </h2> <div class="image"> <img src="CMSIS-NN-OVERVIEW.PNG" alt="CMSIS-NN-OVERVIEW.PNG"/> </div> <h2>Examples </h2> <p>The library ships with a number of examples which demonstrate how to use the library functions.</p> <h2>Pre-processor Macros </h2> <p>Each library project have differant pre-processor macros.</p> <ul> <li>ARM_MATH_DSP:</li> </ul> <p>Define macro ARM_MATH_DSP, If the silicon supports DSP instructions.</p> <ul> <li>ARM_MATH_BIG_ENDIAN:</li> </ul> <p>Define macro ARM_MATH_BIG_ENDIAN to build the library for big endian targets. By default library builds for little endian targets.</p> <ul> <li>ARM_NN_TRUNCATE:</li> </ul> <p>Define macro ARM_NN_TRUNCATE to use floor instead of round-to-the-nearest-int for the computation.</p> <h2>Copyright Notice </h2> <p>Copyright (C) 2010-2018 Arm Limited. All rights reserved.</p> <p>[1] CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs <a href="https://arxiv.org/abs/1801.06601">https://arxiv.org/abs/1801.06601</a> </p> </div></div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/index.html	HTML	apache-2.0	8,135
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href="group__GRUExample.html" target="_self">Gated Recurrent Unit Example</a></td><td class="desc"></td></tr> <tr id="row_2_" class="even"><td class="entry"><img id="arr_2_" src="ftv2mnode.png" alt="o" width="16" height="22" onclick="toggleFolder('2_')"/><a class="el" href="group__groupNN.html" target="_self">Neural Network Functions</a></td><td class="desc"></td></tr> <tr id="row_2_0_"><td class="entry"><img src="ftv2vertline.png" alt="\|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><a class="el" href="group__Acti.html" target="_self">Neural Network Activation Functions</a></td><td class="desc"></td></tr> <tr id="row_2_1_" class="even"><td class="entry"><img src="ftv2vertline.png" alt="\|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><a class="el" href="group__NNConv.html" target="_self">Neural Network Convolution Functions</a></td><td class="desc"></td></tr> <tr id="row_2_2_"><td class="entry"><img src="ftv2vertline.png" alt="\|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><a class="el" href="group__FC.html" target="_self">Fully-connected Layer Functions</a></td><td class="desc"></td></tr> <tr id="row_2_3_" class="even"><td class="entry"><img src="ftv2vertline.png" alt="\|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><a class="el" href="group__Pooling.html" target="_self">Neural Network Pooling Functions</a></td><td class="desc"></td></tr> <tr id="row_2_4_"><td class="entry"><img src="ftv2vertline.png" alt="\|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><a class="el" href="group__Softmax.html" target="_self">Softmax Functions</a></td><td class="desc"></td></tr> <tr id="row_3_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><a class="el" href="group__nndata__convert.html" target="_self">Neural Network Data Conversion Functions</a></td><td class="desc"></td></tr> <tr id="row_4_"><td class="entry"><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><a class="el" href="group__NNBasicMath.html" target="_self">Basic Math Functions for Neural Network Computation</a></td><td class="desc"></td></tr> </table> </div><!-- directory --> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. 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var modules = [ [ "Convolutional Neural Network Example", "group__CNNExample.html", null ], [ "Gated Recurrent Unit Example", "group__GRUExample.html", null ], [ "Neural Network Functions", "group__groupNN.html", "group__groupNN" ], [ "Neural Network Data Conversion Functions", "group__nndata__convert.html", "group__nndata__convert" ], [ "Basic Math Functions for Neural Network Computation", "group__NNBasicMath.html", "group__NNBasicMath" ] ];	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/modules.js	JavaScript	apache-2.0	467
<!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"/> <title>Namespace Members</title> <title>CMSIS-NN: Namespace Members</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); 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All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/namespacemembers.html	HTML	apache-2.0	8,367
<!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"/> <title>Namespace Members</title> <title>CMSIS-NN: Namespace Members</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> </head> <body> <div id="top"><!-- do not remove this div, it is closed by doxygen! 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All rights reserved. <!-- <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 --> </li> </ul> </div> </body> </html>	YifuLiu/AliOS-Things	components/cmsis/docs/NN/html/namespacemembers_func.html	HTML	apache-2.0	6,640
<!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"/> <title>Namespace Members</title> <title>CMSIS-NN: Namespace Members</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); 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</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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Macros</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Groups</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Pages</a></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="contents">  <ul> <li>hidden_bias : <a class="el" href="namespacepara__gen.html#a0f6c4400e131b103d2fd89e420d6c308">para_gen</a> </li> <li>hidden_weight : <a class="el" href="namespacepara__gen.html#a1a6edb73b72a6bbf443e6e450186660c">para_gen</a> </li> <li>history_data : <a class="el" href="namespacepara__gen.html#acdb294668ecca9a6f849afa4156883cd">para_gen</a> </li> <li>input_data1 : <a class="el" href="namespacepara__gen.html#a845220c0c6574ced6cdaf7b1d2983d6d">para_gen</a> </li> <li>input_data2 : <a class="el" href="namespacepara__gen.html#acb820c3015e6a212ad2fe82f7939965a">para_gen</a> </li> <li>new_weight : <a class="el" href="namespacepara__gen.html#aead9af07b473ce5bbd93619e3319355c">para_gen</a> </li> <li>outfile : <a class="el" href="namespacepara__gen.html#a2e1a6685422a591fcb7801e9fd8ad574">para_gen</a> </li> <li>reset_bias : <a class="el" href="namespacepara__gen.html#a3da798c88974b5d760f3e97288a0c490">para_gen</a> </li> <li>reset_weight : <a class="el" href="namespacepara__gen.html#a4ebba057829420c878a0a29ee9c71582">para_gen</a> </li> <li>row_dim : <a class="el" href="namespacepara__gen.html#a26cc0a96186b2e6b238d783d9364f14d">para_gen</a> </li> <li>update_bias : <a class="el" href="namespacepara__gen.html#a3b9bab83acf3b4296f46165da08ddbc9">para_gen</a> </li> <li>update_weight : <a class="el" href="namespacepara__gen.html#ab8ce9efdee9cd118a25831839f9c5943">para_gen</a> </li> <li>vec_dim : <a class="el" href="namespacepara__gen.html#ad97bcbf0472c82d537ee41c0196e3b2a">para_gen</a> </li> <li>weight : <a class="el" href="namespacepara__gen.html#af3dbe004474bc66ad55591f470ff008c">para_gen</a> </li> </ul> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. 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<!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"/> <title>para_gen Namespace Reference</title> <title>CMSIS-NN: para_gen Namespace Reference</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link 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colspan="2"> </td></tr> <tr class="memitem:a75db0b43a1b942aa87ff10fd3b73dc8d"><td class="memItemLeft" align="right" valign="top">def </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a75db0b43a1b942aa87ff10fd3b73dc8d">convert_q7_q15_weights</a></td></tr> <tr class="separator:a75db0b43a1b942aa87ff10fd3b73dc8d"><td class="memSeparator" colspan="2"> </td></tr> </table><table class="memberdecls"> <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="var-members"></a> Variables</h2></td></tr> <tr class="memitem:ad97bcbf0472c82d537ee41c0196e3b2a"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#ad97bcbf0472c82d537ee41c0196e3b2a">vec_dim</a></td></tr> <tr class="separator:ad97bcbf0472c82d537ee41c0196e3b2a"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a26cc0a96186b2e6b238d783d9364f14d"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a26cc0a96186b2e6b238d783d9364f14d">row_dim</a></td></tr> <tr class="separator:a26cc0a96186b2e6b238d783d9364f14d"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ab8ce9efdee9cd118a25831839f9c5943"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#ab8ce9efdee9cd118a25831839f9c5943">update_weight</a></td></tr> <tr class="separator:ab8ce9efdee9cd118a25831839f9c5943"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a4ebba057829420c878a0a29ee9c71582"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a4ebba057829420c878a0a29ee9c71582">reset_weight</a></td></tr> <tr class="separator:a4ebba057829420c878a0a29ee9c71582"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a1a6edb73b72a6bbf443e6e450186660c"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a1a6edb73b72a6bbf443e6e450186660c">hidden_weight</a></td></tr> <tr class="separator:a1a6edb73b72a6bbf443e6e450186660c"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a3b9bab83acf3b4296f46165da08ddbc9"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a3b9bab83acf3b4296f46165da08ddbc9">update_bias</a></td></tr> <tr class="separator:a3b9bab83acf3b4296f46165da08ddbc9"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a3da798c88974b5d760f3e97288a0c490"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a3da798c88974b5d760f3e97288a0c490">reset_bias</a></td></tr> <tr class="separator:a3da798c88974b5d760f3e97288a0c490"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a0f6c4400e131b103d2fd89e420d6c308"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a0f6c4400e131b103d2fd89e420d6c308">hidden_bias</a></td></tr> <tr class="separator:a0f6c4400e131b103d2fd89e420d6c308"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a845220c0c6574ced6cdaf7b1d2983d6d"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a845220c0c6574ced6cdaf7b1d2983d6d">input_data1</a></td></tr> <tr class="separator:a845220c0c6574ced6cdaf7b1d2983d6d"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:acb820c3015e6a212ad2fe82f7939965a"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#acb820c3015e6a212ad2fe82f7939965a">input_data2</a></td></tr> <tr class="separator:acb820c3015e6a212ad2fe82f7939965a"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:acdb294668ecca9a6f849afa4156883cd"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#acdb294668ecca9a6f849afa4156883cd">history_data</a></td></tr> <tr class="separator:acdb294668ecca9a6f849afa4156883cd"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a2e1a6685422a591fcb7801e9fd8ad574"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a2e1a6685422a591fcb7801e9fd8ad574">outfile</a></td></tr> <tr class="separator:a2e1a6685422a591fcb7801e9fd8ad574"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:af3dbe004474bc66ad55591f470ff008c"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#af3dbe004474bc66ad55591f470ff008c">weight</a></td></tr> <tr class="separator:af3dbe004474bc66ad55591f470ff008c"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:aead9af07b473ce5bbd93619e3319355c"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#aead9af07b473ce5bbd93619e3319355c">new_weight</a></td></tr> <tr class="separator:aead9af07b473ce5bbd93619e3319355c"><td class="memSeparator" colspan="2"> </td></tr> </table> <h2 class="groupheader">Function Documentation</h2> <a class="anchor" id="a75db0b43a1b942aa87ff10fd3b73dc8d"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">def para_gen.convert_q7_q15_weights </td> <td>(</td> <td class="paramtype"> </td> <td class="paramname"><em>weights</em></td><td>)</td> <td></td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="ab7f5de20ae32542da9f83a8e99850722"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">def para_gen.convert_to_x4_weights </td> <td>(</td> <td class="paramtype"> </td> <td class="paramname"><em>weights</em></td><td>)</td> <td></td> </tr> </table> </div><div class="memdoc"> </div> </div> <h2 class="groupheader">Variable Documentation</h2> <a class="anchor" id="a0f6c4400e131b103d2fd89e420d6c308"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.hidden_bias</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="a1a6edb73b72a6bbf443e6e450186660c"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.hidden_weight</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="acdb294668ecca9a6f849afa4156883cd"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.history_data</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="a845220c0c6574ced6cdaf7b1d2983d6d"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.input_data1</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="acb820c3015e6a212ad2fe82f7939965a"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.input_data2</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="aead9af07b473ce5bbd93619e3319355c"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.new_weight</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="a2e1a6685422a591fcb7801e9fd8ad574"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.outfile</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="a3da798c88974b5d760f3e97288a0c490"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.reset_bias</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="a4ebba057829420c878a0a29ee9c71582"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.reset_weight</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="a26cc0a96186b2e6b238d783d9364f14d"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">int para_gen.row_dim</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="a3b9bab83acf3b4296f46165da08ddbc9"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.update_bias</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="ab8ce9efdee9cd118a25831839f9c5943"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.update_weight</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="ad97bcbf0472c82d537ee41c0196e3b2a"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">int para_gen.vec_dim</td> </tr> </table> </div><div class="memdoc"> </div> </div> <a class="anchor" id="af3dbe004474bc66ad55591f470ff008c"></a> <div class="memitem"> <div class="memproto"> <table class="memname"> <tr> <td class="memname">tuple para_gen.weight</td> </tr> </table> </div><div class="memdoc"> </div> </div> </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="namespacepara__gen.html">para_gen</a></li> <li class="footer">Generated on Wed Jul 10 2019 15:20:50 for CMSIS-NN Version 1.2.0 by Arm Ltd. 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<!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"/> <title>Namespace List</title> <title>CMSIS-NN: Namespace List</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> </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: 46px;"> <td id="projectlogo"><img alt="Logo" src="CMSIS_Logo_Final.png"/></td> <td style="padding-left: 0.5em;"> <div id="projectname">CMSIS-NN  <span id="projectnumber">Version 1.2.0</span> </div> <div id="projectbrief">CMSIS NN Software Library</div> </td> </tr> </tbody> </table> </div> <!-- end header part --> <div id="CMSISnav" class="tabs1"> <ul class="tablist"> <script type="text/javascript"> <!-- writeComponentTabs.call(this); //--> </script> </ul> </div> <!-- Generated by Doxygen 1.8.6 --> <script type="text/javascript"> var searchBox = new SearchBox("searchBox", "search",false,'Search'); </script> <div id="navrow1" class="tabs"> <ul class="tablist"> <li><a href="index.html"><span>Main Page</span></a></li> <li><a href="pages.html"><span>Usage and Description</span></a></li> <li><a href="modules.html"><span>Reference</span></a></li> <li> <div id="MSearchBox" class="MSearchBoxInactive"> <span class="left"> <img id="MSearchSelect" src="search/mag_sel.png" onmouseover="return searchBox.OnSearchSelectShow()" onmouseout="return searchBox.OnSearchSelectHide()" alt=""/> <input type="text" id="MSearchField" value="Search" accesskey="S" onfocus="searchBox.OnSearchFieldFocus(true)" onblur="searchBox.OnSearchFieldFocus(false)" onkeyup="searchBox.OnSearchFieldChange(event)"/> </span><span class="right"> <a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a> </span> </div> </li> </ul> </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"> $(document).ready(function(){initNavTree('namespaces.html','');}); </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)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Macros</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Groups</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Pages</a></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">Namespace List</div> </div> </div><!--header--> <div class="contents"> <div class="textblock">Here is a list of all namespaces with brief descriptions:</div><div class="directory"> <table class="directory"> <tr id="row_0_" class="even"><td class="entry"><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2ns.png" alt="N" width="24" height="22" /><a class="el" href="namespacepara__gen.html" target="_self">para_gen</a></td><td class="desc"></td></tr> </table> </div><!-- directory --> </div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! 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<!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"/> <title>Usage and Description</title> <title>CMSIS-NN: Usage and Description</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <link href="cmsis.css" rel="stylesheet" type="text/css" /> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <script type="text/javascript" src="printComponentTabs.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> </head> <body> <div id="top"><!-- do not remove this div, it is closed by doxygen! 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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> Functions</h2></td></tr> <tr class="memitem:ab7f5de20ae32542da9f83a8e99850722"><td class="memItemLeft" align="right" valign="top">def </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#ab7f5de20ae32542da9f83a8e99850722">para_gen.convert_to_x4_weights</a></td></tr> <tr class="separator:ab7f5de20ae32542da9f83a8e99850722"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a75db0b43a1b942aa87ff10fd3b73dc8d"><td class="memItemLeft" align="right" valign="top">def </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a75db0b43a1b942aa87ff10fd3b73dc8d">para_gen.convert_q7_q15_weights</a></td></tr> <tr class="separator:a75db0b43a1b942aa87ff10fd3b73dc8d"><td class="memSeparator" colspan="2"> </td></tr> </table><table class="memberdecls"> <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="var-members"></a> Variables</h2></td></tr> <tr class="memitem:ad97bcbf0472c82d537ee41c0196e3b2a"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#ad97bcbf0472c82d537ee41c0196e3b2a">para_gen.vec_dim</a></td></tr> <tr class="separator:ad97bcbf0472c82d537ee41c0196e3b2a"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a26cc0a96186b2e6b238d783d9364f14d"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacepara__gen.html#a26cc0a96186b2e6b238d783d9364f14d">para_gen.row_dim</a></td></tr> <tr class="separator:a26cc0a96186b2e6b238d783d9364f14d"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ab8ce9efdee9cd118a25831839f9c5943"><td class="memItemLeft" align="right" valign="top">tuple </td><td class="memItemRight" valign="bottom"><a class="el" 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