documentation/classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml

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   9 <title>Compute Library: NEWinogradLayerTransformWeightsKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt; Class Template Reference</title>
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 118   <div class="summary">
 119 <a href="#pub-methods">Public Member Functions</a> &#124;
 120 <a href="#pub-static-methods">Static Public Member Functions</a>  </div>
 121   <div class="headertitle">
 122 <div class="title">NEWinogradLayerTransformWeightsKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt; Class Template Reference<span class="mlabels"><span class="mlabel">final</span></span></div>  </div>
 123 </div><!--header-->
 124 <div class="contents">
 125
 126 <p>NEON kernel to perform Winograd weights transform.
 127  <a href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#details">More...</a></p>
 128
 129 <p><code>#include &lt;<a class="el" href="_n_e_winograd_convolution_layer_kernel_8h_source.xhtml">NEWinogradConvolutionLayerKernel.h</a>&gt;</code></p>
 130 <div class="dynheader">
 131 Collaboration diagram for NEWinogradLayerTransformWeightsKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;:</div>
 132 <div class="dyncontent">
 133 <div class="center"><iframe scrolling="no" frameborder="0" src="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel__coll__graph.svg" width="246" height="320"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
 134 </div>
 135 <center><span class="legend">[<a target="top" href="graph_legend.xhtml">legend</a>]</span></center></div>
 136 <table class="memberdecls">
 137 <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
 138 Public Member Functions</h2></td></tr>
 139 <tr class="memitem:ad25daf413f7dd45f084ae22a25b8bbe5"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#ad25daf413f7dd45f084ae22a25b8bbe5">NEWinogradLayerTransformWeightsKernel</a> ()</td></tr>
 140 <tr class="memdesc:ad25daf413f7dd45f084ae22a25b8bbe5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default constructor.  <a href="#ad25daf413f7dd45f084ae22a25b8bbe5">More...</a><br /></td></tr>
 141 <tr class="separator:ad25daf413f7dd45f084ae22a25b8bbe5"><td class="memSeparator" colspan="2">&#160;</td></tr>
 142 <tr class="memitem:ab5656bb5b6334bdbe6e606c715872828"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#ab5656bb5b6334bdbe6e606c715872828">name</a> () const override</td></tr>
 143 <tr class="memdesc:ab5656bb5b6334bdbe6e606c715872828"><td class="mdescLeft">&#160;</td><td class="mdescRight">Name of the kernel.  <a href="#ab5656bb5b6334bdbe6e606c715872828">More...</a><br /></td></tr>
 144 <tr class="separator:ab5656bb5b6334bdbe6e606c715872828"><td class="memSeparator" colspan="2">&#160;</td></tr>
 145 <tr class="memitem:a6b072ab95153097e216d4b5b933c0d8c"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#a6b072ab95153097e216d4b5b933c0d8c">configure</a> (const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *weights_hwio, T *const output, const int matrix_stride, const int n_output_channels, const int n_input_channels) override</td></tr>
 146 <tr class="memdesc:a6b072ab95153097e216d4b5b933c0d8c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Configure the weights transform kernel.  <a href="#a6b072ab95153097e216d4b5b933c0d8c">More...</a><br /></td></tr>
 147 <tr class="separator:a6b072ab95153097e216d4b5b933c0d8c"><td class="memSeparator" colspan="2">&#160;</td></tr>
 148 <tr class="memitem:abfe717774e572988b63fdd5a69364eb9"><td class="memItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#abfe717774e572988b63fdd5a69364eb9">get_weight_storage_size</a> (int n_output_channels, int n_input_channels) const override</td></tr>
 149 <tr class="memdesc:abfe717774e572988b63fdd5a69364eb9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine how much memory (in units of T) to allocate for the transformed weights.  <a href="#abfe717774e572988b63fdd5a69364eb9">More...</a><br /></td></tr>
 150 <tr class="separator:abfe717774e572988b63fdd5a69364eb9"><td class="memSeparator" colspan="2">&#160;</td></tr>
 151 <tr class="memitem:a07a976f4d6b4b62e2ffcea8b0dab6d9f"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#a07a976f4d6b4b62e2ffcea8b0dab6d9f">get_matrix_stride</a> (const KernelShape &amp;kernel_shape) const override</td></tr>
 152 <tr class="memdesc:a07a976f4d6b4b62e2ffcea8b0dab6d9f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Gets the stride between matrices in the kernel worspace.  <a href="#a07a976f4d6b4b62e2ffcea8b0dab6d9f">More...</a><br /></td></tr>
 153 <tr class="separator:a07a976f4d6b4b62e2ffcea8b0dab6d9f"><td class="memSeparator" colspan="2">&#160;</td></tr>
 154 <tr class="memitem:a112b35dd205c62ea6ed1447ef226da82"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#a112b35dd205c62ea6ed1447ef226da82">run</a> (const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>, const <a class="el" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &amp;info) override</td></tr>
 155 <tr class="memdesc:a112b35dd205c62ea6ed1447ef226da82"><td class="mdescLeft">&#160;</td><td class="mdescRight">Execute the kernel on the passed window.  <a href="#a112b35dd205c62ea6ed1447ef226da82">More...</a><br /></td></tr>
 156 <tr class="separator:a112b35dd205c62ea6ed1447ef226da82"><td class="memSeparator" colspan="2">&#160;</td></tr>
 157 <tr class="memitem:a4370ae5fda7bd455a171fc8ed4d3f283"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#a4370ae5fda7bd455a171fc8ed4d3f283">is_parallelisable</a> () const override</td></tr>
 158 <tr class="memdesc:a4370ae5fda7bd455a171fc8ed4d3f283"><td class="mdescLeft">&#160;</td><td class="mdescRight">Indicates whether or not the kernel is parallelisable.  <a href="#a4370ae5fda7bd455a171fc8ed4d3f283">More...</a><br /></td></tr>
 159 <tr class="separator:a4370ae5fda7bd455a171fc8ed4d3f283"><td class="memSeparator" colspan="2">&#160;</td></tr>
 160 <tr class="inherit_header pub_methods_classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml">INEWinogradLayerTransformWeightsKernel&lt; T &gt;</a></td></tr>
 161 <tr class="memitem:a668729f636910fd5f425cee965efee6d inherit pub_methods_classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml#a668729f636910fd5f425cee965efee6d">~INEWinogradLayerTransformWeightsKernel</a> ()</td></tr>
 162 <tr class="separator:a668729f636910fd5f425cee965efee6d inherit pub_methods_classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 163 <tr class="inherit_header pub_methods_classarm__compute_1_1_i_c_p_p_kernel"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_c_p_p_kernel')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml">ICPPKernel</a></td></tr>
 164 <tr class="memitem:a033d17a97e07cea7fe83eefcf23540f6 inherit pub_methods_classarm__compute_1_1_i_c_p_p_kernel"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml#a033d17a97e07cea7fe83eefcf23540f6">~ICPPKernel</a> ()=default</td></tr>
 165 <tr class="memdesc:a033d17a97e07cea7fe83eefcf23540f6 inherit pub_methods_classarm__compute_1_1_i_c_p_p_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default destructor.  <a href="#a033d17a97e07cea7fe83eefcf23540f6">More...</a><br /></td></tr>
 166 <tr class="separator:a033d17a97e07cea7fe83eefcf23540f6 inherit pub_methods_classarm__compute_1_1_i_c_p_p_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 167 <tr class="inherit_header pub_methods_classarm__compute_1_1_i_kernel"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_kernel')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_kernel.xhtml">IKernel</a></td></tr>
 168 <tr class="memitem:a7250cb8cbaa4104a93a2d77155085507 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a7250cb8cbaa4104a93a2d77155085507">IKernel</a> ()</td></tr>
 169 <tr class="memdesc:a7250cb8cbaa4104a93a2d77155085507 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor.  <a href="#a7250cb8cbaa4104a93a2d77155085507">More...</a><br /></td></tr>
 170 <tr class="separator:a7250cb8cbaa4104a93a2d77155085507 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 171 <tr class="memitem:a341b60d15a5e12a5b8f3825194dd3b12 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a341b60d15a5e12a5b8f3825194dd3b12">~IKernel</a> ()=default</td></tr>
 172 <tr class="memdesc:a341b60d15a5e12a5b8f3825194dd3b12 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor.  <a href="#a341b60d15a5e12a5b8f3825194dd3b12">More...</a><br /></td></tr>
 173 <tr class="separator:a341b60d15a5e12a5b8f3825194dd3b12 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 174 <tr class="memitem:aa6daa9b04e2035bf007e5e5c3c4396a8 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">virtual <a class="el" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#aa6daa9b04e2035bf007e5e5c3c4396a8">border_size</a> () const </td></tr>
 175 <tr class="memdesc:aa6daa9b04e2035bf007e5e5c3c4396a8 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">The size of the border for that kernel.  <a href="#aa6daa9b04e2035bf007e5e5c3c4396a8">More...</a><br /></td></tr>
 176 <tr class="separator:aa6daa9b04e2035bf007e5e5c3c4396a8 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 177 <tr class="memitem:a3f5646133956f06348b310ccc3d36353 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a> () const </td></tr>
 178 <tr class="memdesc:a3f5646133956f06348b310ccc3d36353 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">The maximum window the kernel can be executed on.  <a href="#a3f5646133956f06348b310ccc3d36353">More...</a><br /></td></tr>
 179 <tr class="separator:a3f5646133956f06348b310ccc3d36353 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 180 </table><table class="memberdecls">
 181 <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
 182 Static Public Member Functions</h2></td></tr>
 183 <tr class="memitem:a502f9b46f6aac5562a420b945981e443"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classarm__compute_1_1_status.xhtml">Status</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#a502f9b46f6aac5562a420b945981e443">validate</a> (const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, const <a class="el" href="structarm__compute_1_1_winograd_info.xhtml">WinogradInfo</a> &amp;winograd_info)</td></tr>
 184 <tr class="memdesc:a502f9b46f6aac5562a420b945981e443"><td class="mdescLeft">&#160;</td><td class="mdescRight">Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml">NEWinogradLayerTransformWeightsKernel</a>.  <a href="#a502f9b46f6aac5562a420b945981e443">More...</a><br /></td></tr>
 185 <tr class="separator:a502f9b46f6aac5562a420b945981e443"><td class="memSeparator" colspan="2">&#160;</td></tr>
 186 </table>
 187 <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
 188 <div class="textblock"><h3>template&lt;typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols&gt;<br />
 189 class arm_compute::NEWinogradLayerTransformWeightsKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</h3>
 190
 191 <p>NEON kernel to perform Winograd weights transform. </p>
 192
 193 <p>Definition at line <a class="el" href="_n_e_winograd_convolution_layer_kernel_8h_source.xhtml#l00378">378</a> of file <a class="el" href="_n_e_winograd_convolution_layer_kernel_8h_source.xhtml">NEWinogradConvolutionLayerKernel.h</a>.</p>
 194 </div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
 195 <a class="anchor" id="ad25daf413f7dd45f084ae22a25b8bbe5"></a>
 196 <div class="memitem">
 197 <div class="memproto">
 198       <table class="memname">
 199         <tr>
 200           <td class="memname"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml">NEWinogradLayerTransformWeightsKernel</a> </td>
 201           <td>(</td>
 202           <td class="paramname"></td><td>)</td>
 203           <td></td>
 204         </tr>
 205       </table>
 206 </div><div class="memdoc">
 207
 208 <p>Default constructor. </p>
 209
 210 </div>
 211 </div>
 212 <h2 class="groupheader">Member Function Documentation</h2>
 213 <a class="anchor" id="a6b072ab95153097e216d4b5b933c0d8c"></a>
 214 <div class="memitem">
 215 <div class="memproto">
 216 <table class="mlabels">
 217   <tr>
 218   <td class="mlabels-left">
 219       <table class="memname">
 220         <tr>
 221           <td class="memname">void configure </td>
 222           <td>(</td>
 223           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *&#160;</td>
 224           <td class="paramname"><em>weights_hwio</em>, </td>
 225         </tr>
 226         <tr>
 227           <td class="paramkey"></td>
 228           <td></td>
 229           <td class="paramtype">T *const&#160;</td>
 230           <td class="paramname"><em>output</em>, </td>
 231         </tr>
 232         <tr>
 233           <td class="paramkey"></td>
 234           <td></td>
 235           <td class="paramtype">const int&#160;</td>
 236           <td class="paramname"><em>matrix_stride</em>, </td>
 237         </tr>
 238         <tr>
 239           <td class="paramkey"></td>
 240           <td></td>
 241           <td class="paramtype">const int&#160;</td>
 242           <td class="paramname"><em>n_output_channels</em>, </td>
 243         </tr>
 244         <tr>
 245           <td class="paramkey"></td>
 246           <td></td>
 247           <td class="paramtype">const int&#160;</td>
 248           <td class="paramname"><em>n_input_channels</em>&#160;</td>
 249         </tr>
 250         <tr>
 251           <td></td>
 252           <td>)</td>
 253           <td></td><td></td>
 254         </tr>
 255       </table>
 256   </td>
 257   <td class="mlabels-right">
 258 <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span>  </td>
 259   </tr>
 260 </table>
 261 </div><div class="memdoc">
 262
 263 <p>Configure the weights transform kernel. </p>
 264 <dl class="params"><dt>Parameters</dt><dd>
 265   <table class="params">
 266     <tr><td class="paramdir">[in]</td><td class="paramname">weights_hwio</td><td>Pointer to the weights tensor </td></tr>
 267     <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Pointer to working space for the output tensor in the Winograd domain. </td></tr>
 268     <tr><td class="paramdir">[in]</td><td class="paramname">matrix_stride</td><td>Stride across matrices in the output workspace. </td></tr>
 269     <tr><td class="paramdir">[in]</td><td class="paramname">n_output_channels</td><td>Number of filters. </td></tr>
 270     <tr><td class="paramdir">[in]</td><td class="paramname">n_input_channels</td><td>Number of channels in each filter. </td></tr>
 271   </table>
 272   </dd>
 273 </dl>
 274
 275 <p>Implements <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml#af722049ac6ad3c1c96df13005645d6c3">INEWinogradLayerTransformWeightsKernel&lt; T &gt;</a>.</p>
 276
 277 </div>
 278 </div>
 279 <a class="anchor" id="a07a976f4d6b4b62e2ffcea8b0dab6d9f"></a>
 280 <div class="memitem">
 281 <div class="memproto">
 282 <table class="mlabels">
 283   <tr>
 284   <td class="mlabels-left">
 285       <table class="memname">
 286         <tr>
 287           <td class="memname">int get_matrix_stride </td>
 288           <td>(</td>
 289           <td class="paramtype">const KernelShape &amp;&#160;</td>
 290           <td class="paramname"><em>kernel_shape</em></td><td>)</td>
 291           <td> const</td>
 292         </tr>
 293       </table>
 294   </td>
 295   <td class="mlabels-right">
 296 <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span>  </td>
 297   </tr>
 298 </table>
 299 </div><div class="memdoc">
 300
 301 <p>Gets the stride between matrices in the kernel worspace. </p>
 302 <dl class="params"><dt>Parameters</dt><dd>
 303   <table class="params">
 304     <tr><td class="paramdir">[in]</td><td class="paramname">kernel_shape</td><td>The shape of the weights tensor.</td></tr>
 305   </table>
 306   </dd>
 307 </dl>
 308 <dl class="section return"><dt>Returns</dt><dd>Stride expressed in bytes. </dd></dl>
 309
 310 <p>Implements <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml#a0769fae1b815e5e48086ad25c1528dec">INEWinogradLayerTransformWeightsKernel&lt; T &gt;</a>.</p>
 311
 312 </div>
 313 </div>
 314 <a class="anchor" id="abfe717774e572988b63fdd5a69364eb9"></a>
 315 <div class="memitem">
 316 <div class="memproto">
 317 <table class="mlabels">
 318   <tr>
 319   <td class="mlabels-left">
 320       <table class="memname">
 321         <tr>
 322           <td class="memname">unsigned int get_weight_storage_size </td>
 323           <td>(</td>
 324           <td class="paramtype">int&#160;</td>
 325           <td class="paramname"><em>n_output_channels</em>, </td>
 326         </tr>
 327         <tr>
 328           <td class="paramkey"></td>
 329           <td></td>
 330           <td class="paramtype">int&#160;</td>
 331           <td class="paramname"><em>n_input_channels</em>&#160;</td>
 332         </tr>
 333         <tr>
 334           <td></td>
 335           <td>)</td>
 336           <td></td><td> const</td>
 337         </tr>
 338       </table>
 339   </td>
 340   <td class="mlabels-right">
 341 <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span>  </td>
 342   </tr>
 343 </table>
 344 </div><div class="memdoc">
 345
 346 <p>Determine how much memory (in units of T) to allocate for the transformed weights. </p>
 347 <dl class="params"><dt>Parameters</dt><dd>
 348   <table class="params">
 349     <tr><td class="paramdir">[in]</td><td class="paramname">n_output_channels</td><td>Number of output feature maps. </td></tr>
 350     <tr><td class="paramdir">[in]</td><td class="paramname">n_input_channels</td><td>Number of input feature maps.</td></tr>
 351   </table>
 352   </dd>
 353 </dl>
 354 <dl class="section return"><dt>Returns</dt><dd>Storage size (in units of T) required. </dd></dl>
 355
 356 <p>Implements <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml#ad670ceec7efb9583d3ab5ae0700bf028">INEWinogradLayerTransformWeightsKernel&lt; T &gt;</a>.</p>
 357
 358 </div>
 359 </div>
 360 <a class="anchor" id="a4370ae5fda7bd455a171fc8ed4d3f283"></a>
 361 <div class="memitem">
 362 <div class="memproto">
 363 <table class="mlabels">
 364   <tr>
 365   <td class="mlabels-left">
 366       <table class="memname">
 367         <tr>
 368           <td class="memname">bool is_parallelisable </td>
 369           <td>(</td>
 370           <td class="paramname"></td><td>)</td>
 371           <td> const</td>
 372         </tr>
 373       </table>
 374   </td>
 375   <td class="mlabels-right">
 376 <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span>  </td>
 377   </tr>
 378 </table>
 379 </div><div class="memdoc">
 380
 381 <p>Indicates whether or not the kernel is parallelisable. </p>
 382 <p>If the kernel is parallelisable then the window returned by <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353" title="The maximum window the kernel can be executed on. ">window()</a> can be split into sub-windows which can then be run in parallel.</p>
 383 <p>If the kernel is not parallelisable then only the window returned by <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353" title="The maximum window the kernel can be executed on. ">window()</a> can be passed to <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#a112b35dd205c62ea6ed1447ef226da82" title="Execute the kernel on the passed window. ">run()</a></p>
 384 <dl class="section return"><dt>Returns</dt><dd>True if the kernel is parallelisable </dd></dl>
 385
 386 <p>Reimplemented from <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#abfab8f0d4928e1081d9f65b77933e24a">IKernel</a>.</p>
 387
 388 </div>
 389 </div>
 390 <a class="anchor" id="ab5656bb5b6334bdbe6e606c715872828"></a>
 391 <div class="memitem">
 392 <div class="memproto">
 393 <table class="mlabels">
 394   <tr>
 395   <td class="mlabels-left">
 396       <table class="memname">
 397         <tr>
 398           <td class="memname">const char* name </td>
 399           <td>(</td>
 400           <td class="paramname"></td><td>)</td>
 401           <td> const</td>
 402         </tr>
 403       </table>
 404   </td>
 405   <td class="mlabels-right">
 406 <span class="mlabels"><span class="mlabel">inline</span><span class="mlabel">override</span><span class="mlabel">virtual</span></span>  </td>
 407   </tr>
 408 </table>
 409 </div><div class="memdoc">
 410
 411 <p>Name of the kernel. </p>
 412 <dl class="section return"><dt>Returns</dt><dd><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> name </dd></dl>
 413
 414 <p>Implements <a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml#a1a30ad8f276a2310571c36239554831a">ICPPKernel</a>.</p>
 415
 416 <p>Definition at line <a class="el" href="_n_e_winograd_convolution_layer_kernel_8h_source.xhtml#l00383">383</a> of file <a class="el" href="_n_e_winograd_convolution_layer_kernel_8h_source.xhtml">NEWinogradConvolutionLayerKernel.h</a>.</p>
 417
 418 <p>References <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_input_kernel.xhtml#a2ac7c7acdb2d7dea85085c2dff52687f">INEWinogradLayerTransformInputKernel&lt; T &gt;::configure()</a>, <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_input_kernel.xhtml#ae25b6ed77179808984b17c39e078ad96">INEWinogradLayerTransformInputKernel&lt; T &gt;::get_matrix_stride()</a>, <a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a096668313a9a819d54a2e65ec21ff0cc">arm_compute::test::validation::info()</a>, <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#abfab8f0d4928e1081d9f65b77933e24a">IKernel::is_parallelisable()</a>, <a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml#af814ff5e96f40f1cccf809b2b4ee19ef">ICPPKernel::run()</a>, <a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6813132c943295888972727864ea5c2f">arm_compute::test::validation::validate()</a>, <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">IKernel::window()</a>, and <a class="el" href="_c_l_2_winograd_8cpp_source.xhtml#l00173">arm_compute::test::validation::winograd_info</a>.</p>
 419 <div class="fragment"><div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;    {</div><div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;        <span class="keywordflow">return</span> <span class="stringliteral">&quot;NEWinogradLayerTransformWeightsKernel&quot;</span>;</div><div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;    }</div></div><!-- fragment -->
 420 </div>
 421 </div>
 422 <a class="anchor" id="a112b35dd205c62ea6ed1447ef226da82"></a>
 423 <div class="memitem">
 424 <div class="memproto">
 425 <table class="mlabels">
 426   <tr>
 427   <td class="mlabels-left">
 428       <table class="memname">
 429         <tr>
 430           <td class="memname">void run </td>
 431           <td>(</td>
 432           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
 433           <td class="paramname"><em>window</em>, </td>
 434         </tr>
 435         <tr>
 436           <td class="paramkey"></td>
 437           <td></td>
 438           <td class="paramtype">const <a class="el" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &amp;&#160;</td>
 439           <td class="paramname"><em>info</em>&#160;</td>
 440         </tr>
 441         <tr>
 442           <td></td>
 443           <td>)</td>
 444           <td></td><td></td>
 445         </tr>
 446       </table>
 447   </td>
 448   <td class="mlabels-right">
 449 <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span>  </td>
 450   </tr>
 451 </table>
 452 </div><div class="memdoc">
 453
 454 <p>Execute the kernel on the passed window. </p>
 455 <dl class="section warning"><dt>Warning</dt><dd>If <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#a4370ae5fda7bd455a171fc8ed4d3f283" title="Indicates whether or not the kernel is parallelisable. ">is_parallelisable()</a> returns false then the passed window must be equal to <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353" title="The maximum window the kernel can be executed on. ">window()</a></dd></dl>
 456 <dl class="section note"><dt>Note</dt><dd>The window has to be a region within the window returned by the <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353" title="The maximum window the kernel can be executed on. ">window()</a> method</dd>
 457 <dd>
 458 The width of the window has to be a multiple of num_elems_processed_per_iteration().</dd></dl>
 459 <dl class="params"><dt>Parameters</dt><dd>
 460   <table class="params">
 461     <tr><td class="paramdir">[in]</td><td class="paramname">window</td><td>Region on which to execute the kernel. (Must be a region of the window returned by <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353" title="The maximum window the kernel can be executed on. ">window()</a>) </td></tr>
 462     <tr><td class="paramdir">[in]</td><td class="paramname">info</td><td>Info about executing thread and CPU. </td></tr>
 463   </table>
 464   </dd>
 465 </dl>
 466
 467 <p>Implements <a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml#af814ff5e96f40f1cccf809b2b4ee19ef">ICPPKernel</a>.</p>
 468
 469 </div>
 470 </div>
 471 <a class="anchor" id="a502f9b46f6aac5562a420b945981e443"></a>
 472 <div class="memitem">
 473 <div class="memproto">
 474 <table class="mlabels">
 475   <tr>
 476   <td class="mlabels-left">
 477       <table class="memname">
 478         <tr>
 479           <td class="memname">static <a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> validate </td>
 480           <td>(</td>
 481           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *&#160;</td>
 482           <td class="paramname"><em>input</em>, </td>
 483         </tr>
 484         <tr>
 485           <td class="paramkey"></td>
 486           <td></td>
 487           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *&#160;</td>
 488           <td class="paramname"><em>output</em>, </td>
 489         </tr>
 490         <tr>
 491           <td class="paramkey"></td>
 492           <td></td>
 493           <td class="paramtype">const <a class="el" href="structarm__compute_1_1_winograd_info.xhtml">WinogradInfo</a> &amp;&#160;</td>
 494           <td class="paramname"><em>winograd_info</em>&#160;</td>
 495         </tr>
 496         <tr>
 497           <td></td>
 498           <td>)</td>
 499           <td></td><td></td>
 500         </tr>
 501       </table>
 502   </td>
 503   <td class="mlabels-right">
 504 <span class="mlabels"><span class="mlabel">static</span></span>  </td>
 505   </tr>
 506 </table>
 507 </div><div class="memdoc">
 508
 509 <p>Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml">NEWinogradLayerTransformWeightsKernel</a>. </p>
 510 <dl class="params"><dt>Parameters</dt><dd>
 511   <table class="params">
 512     <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Source tensor info. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout). kernel_x must be 3 and equal to kernel_y. Data types supported: F32. </td></tr>
 513     <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Destination tensor info. The output is a 3D tensor with dimensions [OFM, IFM, 16] or [OFM, IFM, 36]. Data type supported: same as <code>input</code> </td></tr>
 514     <tr><td class="paramdir">[in]</td><td class="paramname">winograd_info</td><td>Contains Winograd's information described in <a class="el" href="structarm__compute_1_1_winograd_info.xhtml">WinogradInfo</a></td></tr>
 515   </table>
 516   </dd>
 517 </dl>
 518 <dl class="section return"><dt>Returns</dt><dd>a status </dd></dl>
 519
 520 </div>
 521 </div>
 522 <hr/>The documentation for this class was generated from the following file:<ul>
 523 <li>arm_compute/core/NEON/kernels/<a class="el" href="_n_e_winograd_convolution_layer_kernel_8h_source.xhtml">NEWinogradConvolutionLayerKernel.h</a></li>
 524 </ul>
 525 </div><!-- contents -->
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 529   <ul>
 530     <li class="navelem"><a class="el" href="namespacearm__compute.xhtml">arm_compute</a></li><li class="navelem"><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml">NEWinogradLayerTransformWeightsKernel</a></li>
 531     <li class="footer">Generated on Wed May 23 2018 11:36:43 for Compute Library by
 532     <a href="http://www.doxygen.org/index.html">
 533     <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li>
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