documentation/classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml - platform/external/ComputeLibrary - Git at Google

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 <div class="header">
   <div class="summary">
 <a href="#pub-methods">Public Member Functions</a> &#124;
 <a href="#pub-static-methods">Static Public Member Functions</a>  </div>
   <div class="headertitle">
 <div class="title">NEDirectConvolutionLayerKernel Class Reference</div>  </div>
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 <p>NEON interface for Direct Convolution Layer kernel.
  <a href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#details">More...</a></p>

 <p><code>#include &lt;<a class="el" href="_n_e_direct_convolution_layer_kernel_8h_source.xhtml">NEDirectConvolutionLayerKernel.h</a>&gt;</code></p>
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 Collaboration diagram for NEDirectConvolutionLayerKernel:</div>
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 <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
 Public Member Functions</h2></td></tr>
 <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_direct_convolution_layer_kernel.xhtml#ab5656bb5b6334bdbe6e606c715872828">name</a> () const override</td></tr>
 <tr class="memdesc:ab5656bb5b6334bdbe6e606c715872828"><td class="mdescLeft">&#160;</td><td class="mdescRight">Name of the kernel.  <a href="#ab5656bb5b6334bdbe6e606c715872828">More...</a><br /></td></tr>
 <tr class="separator:ab5656bb5b6334bdbe6e606c715872828"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:ac0cdf0dbaff299b1359714a7f70d6072"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#ac0cdf0dbaff299b1359714a7f70d6072">NEDirectConvolutionLayerKernel</a> ()</td></tr>
 <tr class="memdesc:ac0cdf0dbaff299b1359714a7f70d6072"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default constructor.  <a href="#ac0cdf0dbaff299b1359714a7f70d6072">More...</a><br /></td></tr>
 <tr class="separator:ac0cdf0dbaff299b1359714a7f70d6072"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a2cb2b9e95ff81e666d4e11b645fee8db"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#a2cb2b9e95ff81e666d4e11b645fee8db">NEDirectConvolutionLayerKernel</a> (const <a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> &amp;)=delete</td></tr>
 <tr class="memdesc:a2cb2b9e95ff81e666d4e11b645fee8db"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers)  <a href="#a2cb2b9e95ff81e666d4e11b645fee8db">More...</a><br /></td></tr>
 <tr class="separator:a2cb2b9e95ff81e666d4e11b645fee8db"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:ac299dc8386e25ebcf104989623cf6000"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#ac299dc8386e25ebcf104989623cf6000">operator=</a> (const <a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> &amp;)=delete</td></tr>
 <tr class="memdesc:ac299dc8386e25ebcf104989623cf6000"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers)  <a href="#ac299dc8386e25ebcf104989623cf6000">More...</a><br /></td></tr>
 <tr class="separator:ac299dc8386e25ebcf104989623cf6000"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a011feff0e8a189fd41f1712c2ab63745"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#a011feff0e8a189fd41f1712c2ab63745">NEDirectConvolutionLayerKernel</a> (<a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> &amp;&amp;)=default</td></tr>
 <tr class="memdesc:a011feff0e8a189fd41f1712c2ab63745"><td class="mdescLeft">&#160;</td><td class="mdescRight">Allow instances of this class to be moved.  <a href="#a011feff0e8a189fd41f1712c2ab63745">More...</a><br /></td></tr>
 <tr class="separator:a011feff0e8a189fd41f1712c2ab63745"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:aec3ec4dc8b3bda8ba2638fbb9d520322"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#aec3ec4dc8b3bda8ba2638fbb9d520322">operator=</a> (<a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> &amp;&amp;)=default</td></tr>
 <tr class="memdesc:aec3ec4dc8b3bda8ba2638fbb9d520322"><td class="mdescLeft">&#160;</td><td class="mdescRight">Allow instances of this class to be moved.  <a href="#aec3ec4dc8b3bda8ba2638fbb9d520322">More...</a><br /></td></tr>
 <tr class="separator:aec3ec4dc8b3bda8ba2638fbb9d520322"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a59e6b01f2562366f54106175432079a0"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#a59e6b01f2562366f54106175432079a0">~NEDirectConvolutionLayerKernel</a> ()=default</td></tr>
 <tr class="memdesc:a59e6b01f2562366f54106175432079a0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default destructor.  <a href="#a59e6b01f2562366f54106175432079a0">More...</a><br /></td></tr>
 <tr class="separator:a59e6b01f2562366f54106175432079a0"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a537ba0d35bcc8d5488da55d1a27c89a3"><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_direct_convolution_layer_kernel.xhtml#a537ba0d35bcc8d5488da55d1a27c89a3">configure</a> (const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input, const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *weights, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;conv_info)</td></tr>
 <tr class="memdesc:a537ba0d35bcc8d5488da55d1a27c89a3"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the input, weights, and output tensors.  <a href="#a537ba0d35bcc8d5488da55d1a27c89a3">More...</a><br /></td></tr>
 <tr class="separator:a537ba0d35bcc8d5488da55d1a27c89a3"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <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_direct_convolution_layer_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#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, const <a class="el" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &amp;info) override</td></tr>
 <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>
 <tr class="separator:a112b35dd205c62ea6ed1447ef226da82"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a423f9a45a52983b4de5e2b347f4369c7"><td class="memItemLeft" align="right" valign="top"><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_n_e_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a> () const override</td></tr>
 <tr class="memdesc:a423f9a45a52983b4de5e2b347f4369c7"><td class="mdescLeft">&#160;</td><td class="mdescRight">The size of the border for that kernel.  <a href="#a423f9a45a52983b4de5e2b347f4369c7">More...</a><br /></td></tr>
 <tr class="separator:a423f9a45a52983b4de5e2b347f4369c7"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <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>
 <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>
 <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="classarm__compute_1_1_i_c_p_p_kernel.xhtml#a033d17a97e07cea7fe83eefcf23540f6">More...</a><br /></td></tr>
 <tr class="separator:a033d17a97e07cea7fe83eefcf23540f6 inherit pub_methods_classarm__compute_1_1_i_c_p_p_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <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>
 <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>
 <tr class="memdesc:a7250cb8cbaa4104a93a2d77155085507 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor.  <a href="classarm__compute_1_1_i_kernel.xhtml#a7250cb8cbaa4104a93a2d77155085507">More...</a><br /></td></tr>
 <tr class="separator:a7250cb8cbaa4104a93a2d77155085507 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <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>
 <tr class="memdesc:a341b60d15a5e12a5b8f3825194dd3b12 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor.  <a href="classarm__compute_1_1_i_kernel.xhtml#a341b60d15a5e12a5b8f3825194dd3b12">More...</a><br /></td></tr>
 <tr class="separator:a341b60d15a5e12a5b8f3825194dd3b12 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a0466ee6ce6552c87595f0e88e73eeb1b inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a0466ee6ce6552c87595f0e88e73eeb1b">is_parallelisable</a> () const</td></tr>
 <tr class="memdesc:a0466ee6ce6552c87595f0e88e73eeb1b inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Indicates whether or not the kernel is parallelisable.  <a href="classarm__compute_1_1_i_kernel.xhtml#a0466ee6ce6552c87595f0e88e73eeb1b">More...</a><br /></td></tr>
 <tr class="separator:a0466ee6ce6552c87595f0e88e73eeb1b inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:ad34a46f53686c12a5c5e717cc9617fb6 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#ad34a46f53686c12a5c5e717cc9617fb6">window</a> () const</td></tr>
 <tr class="memdesc:ad34a46f53686c12a5c5e717cc9617fb6 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="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">More...</a><br /></td></tr>
 <tr class="separator:ad34a46f53686c12a5c5e717cc9617fb6 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
 </table><table class="memberdecls">
 <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
 Static Public Member Functions</h2></td></tr>
 <tr class="memitem:a38da9c4ac16c0ca78e5d7176aab3435e"><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_direct_convolution_layer_kernel.xhtml#a38da9c4ac16c0ca78e5d7176aab3435e">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> *weights, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;conv_info)</td></tr>
 <tr class="memdesc:a38da9c4ac16c0ca78e5d7176aab3435e"><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_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a>.  <a href="#a38da9c4ac16c0ca78e5d7176aab3435e">More...</a><br /></td></tr>
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 <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
 <div class="textblock"><p>NEON interface for Direct Convolution Layer kernel. </p>

 <p class="definition">Definition at line <a class="el" href="_n_e_direct_convolution_layer_kernel_8h_source.xhtml#l00034">34</a> of file <a class="el" href="_n_e_direct_convolution_layer_kernel_8h_source.xhtml">NEDirectConvolutionLayerKernel.h</a>.</p>
 </div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
 <a id="ac0cdf0dbaff299b1359714a7f70d6072"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#ac0cdf0dbaff299b1359714a7f70d6072">&#9670;&nbsp;</a></span>NEDirectConvolutionLayerKernel() <span class="overload">[1/3]</span></h2>

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           <td class="memname"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> </td>
           <td>(</td>
           <td class="paramname"></td><td>)</td>
           <td></td>
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 <p>Default constructor. </p>

 <p class="definition">Definition at line <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml#l01453">1453</a> of file <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml">NEDirectConvolutionLayerKernel.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>&#160;    : _input(<span class="keyword">nullptr</span>), _weights(<span class="keyword">nullptr</span>), _output(<span class="keyword">nullptr</span>), _conv_info(), _border_size(0), _kernel_size(0), _num_weight_elems_read_per_row(0), _num_elems_read_per_iteration(0),</div><div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>&#160;      _num_elems_written_per_iteration(0)</div><div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>&#160;{</div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>&#160;}</div></div><!-- fragment -->
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 <h2 class="memtitle"><span class="permalink"><a href="#a2cb2b9e95ff81e666d4e11b645fee8db">&#9670;&nbsp;</a></span>NEDirectConvolutionLayerKernel() <span class="overload">[2/3]</span></h2>

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           <td class="memname"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> </td>
           <td>(</td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> &amp;&#160;</td>
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 <p>Prevent instances of this class from being copied (As this class contains pointers) </p>

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 <h2 class="memtitle"><span class="permalink"><a href="#a011feff0e8a189fd41f1712c2ab63745">&#9670;&nbsp;</a></span>NEDirectConvolutionLayerKernel() <span class="overload">[3/3]</span></h2>

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           <td class="memname"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> </td>
           <td>(</td>
           <td class="paramtype"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> &amp;&amp;&#160;</td>
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 <h2 class="memtitle"><span class="permalink"><a href="#a59e6b01f2562366f54106175432079a0">&#9670;&nbsp;</a></span>~NEDirectConvolutionLayerKernel()</h2>

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           <td class="memname">~<a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> </td>
           <td>(</td>
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 <p>Default destructor. </p>

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 <h2 class="groupheader">Member Function Documentation</h2>
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 <h2 class="memtitle"><span class="permalink"><a href="#a423f9a45a52983b4de5e2b347f4369c7">&#9670;&nbsp;</a></span>border_size()</h2>

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           <td class="memname"><a class="el" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a> border_size </td>
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 <p>The size of the border for that kernel. </p>
 <dl class="section return"><dt>Returns</dt><dd>The width in number of elements of the border. </dd></dl>

 <p>Reimplemented from <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a4b3a97ba5dded504a2f2261c078493dd">IKernel</a>.</p>

 <p class="definition">Definition at line <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml#l01459">1459</a> of file <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml">NEDirectConvolutionLayerKernel.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>&#160;{</div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>&#160;    <span class="keywordflow">return</span> _border_size;</div><div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>&#160;}</div></div><!-- fragment -->
 <p class="reference">Referenced by <a class="el" href="_n_e_direct_convolution_layer_8cpp_source.xhtml#l00042">NEDirectConvolutionLayer::configure()</a>, and <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml#l01498">NEDirectConvolutionLayerKernel::validate()</a>.</p>

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 <h2 class="memtitle"><span class="permalink"><a href="#a537ba0d35bcc8d5488da55d1a27c89a3">&#9670;&nbsp;</a></span>configure()</h2>

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           <td class="memname">void configure </td>
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           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *&#160;</td>
           <td class="paramname"><em>input</em>, </td>
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           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *&#160;</td>
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           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;&#160;</td>
           <td class="paramname"><em>conv_info</em>&#160;</td>
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 <p>Set the input, weights, and output tensors. </p>
 <dl class="section note"><dt>Note</dt><dd>: DirectConvolution only works in the following configurations: 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3</dd></dl>
 <dl class="params"><dt>Parameters</dt><dd>
   <table class="params">
     <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>The input tensor to convolve. 3 lower dimensions represent a single input [width, height, IFM], while every optional dimension from 4 and above represent a batch of inputs. Data types supported: F16/F32. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. The 3rd dimension must be the same as the input's volume 3rd dimension. Data type supported:Same as <code>input</code>. </td></tr>
     <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Output tensor. The 3rd dimensions must be equal to the 4th dimension of the <code>kernels</code> tensor. Data types supported: F16/F32 </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">conv_info</td><td>Contains padding and stride information described in <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>. </td></tr>
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 <p class="definition">Definition at line <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml#l01464">1464</a> of file <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml">NEDirectConvolutionLayerKernel.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>&#160;{</div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>&#160;    <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, output);</div><div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>&#160;</div><div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>&#160;    _input       = input;</div><div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>&#160;    _weights     = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>;</div><div class="line"><a name="l01470"></a><span class="lineno"> 1470</span>&#160;    _output      = output;</div><div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>&#160;    _conv_info   = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>;</div><div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>&#160;    _kernel_size = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a8813441b655b97c00139c6a5a6390e97">dimension</a>(<a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>));</div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>&#160;</div><div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_pad_left   = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_left();</div><div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_pad_top    = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_top();</div><div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_pad_right  = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_right();</div><div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> conv_pad_bottom = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_bottom();</div><div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>&#160;    _border_size                       = <a class="code" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a>(conv_pad_top, conv_pad_right, conv_pad_bottom, conv_pad_left);</div><div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>&#160;</div><div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>&#160;    <span class="comment">// Get convolved dimensions</span></div><div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>&#160;    <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a> = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a5d320d308c16b8ddda3c9d3f60fad79c">misc::shape_calculator::compute_deep_convolution_shape</a>(*input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>);</div><div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>&#160;</div><div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>&#160;    <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a> = input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>();</div><div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>&#160;</div><div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>&#160;    <span class="comment">// Output auto inizialitation if not yet initialized</span></div><div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>&#160;    <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a>, 1, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>);</div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>&#160;</div><div class="line"><a name="l01488"></a><span class="lineno"> 1488</span>&#160;    <span class="comment">// Perform validation step</span></div><div class="line"><a name="l01489"></a><span class="lineno"> 1489</span>&#160;    <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(validate_arguments(input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>(), output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>));</div><div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>&#160;</div><div class="line"><a name="l01491"></a><span class="lineno"> 1491</span>&#160;    <span class="comment">// Configure kernel window</span></div><div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>&#160;    <span class="keyword">auto</span> win_config = <a class="code" href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">validate_and_configure_window</a>(input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>(), output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, _num_weight_elems_read_per_row,</div><div class="line"><a name="l01493"></a><span class="lineno"> 1493</span>&#160;                                                    _num_elems_read_per_iteration, _num_elems_written_per_iteration, _border_size);</div><div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>&#160;    <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(win_config.first);</div><div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>&#160;    INEKernel::configure(win_config.second);</div><div class="line"><a name="l01496"></a><span class="lineno"> 1496</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_ad45f0c01a0713dfb6bd7232c7f396fc4"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">arm_compute::CLTensor::info</a></div><div class="ttdeci">TensorInfo * info() const override</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00035">CLTensor.cpp:35</a></div></div>
 <div class="ttc" id="structarm__compute_1_1_border_size_xhtml"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml">arm_compute::BorderSize</a></div><div class="ttdoc">Container for 2D border size.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00259">Types.h:259</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a5f63b63606dbbbe54474e6e970a6738c"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a5f63b63606dbbbe54474e6e970a6738c">arm_compute::TensorInfo::data_layout</a></div><div class="ttdeci">DataLayout data_layout() const override</div><div class="ttdoc">Get the data layout of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00297">TensorInfo.h:297</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_a5d320d308c16b8ddda3c9d3f60fad79c"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a5d320d308c16b8ddda3c9d3f60fad79c">arm_compute::misc::shape_calculator::compute_deep_convolution_shape</a></div><div class="ttdeci">TensorShape compute_deep_convolution_shape(const ITensorInfo &amp;input, const ITensorInfo &amp;weights, PadStrideInfo conv_info)</div><div class="ttdoc">Calculate the deep convolution shape output shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l00702">ShapeCalculator.h:702</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ad6630777dc2d315531f1e0b02491051f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">arm_compute::validate_and_configure_window</a></div><div class="ttdeci">std::pair&lt; Status, Window &gt; validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *output, const PadStrideInfo &amp;conv_info, unsigned int depth_multiplier, const Size2D &amp;dilation)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_native_kernel_8cpp_source.xhtml#l00221">NEDepthwiseConvolutionLayerNativeKernel.cpp:221</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00599">Winograd.cpp:599</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a8813441b655b97c00139c6a5a6390e97"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a8813441b655b97c00139c6a5a6390e97">arm_compute::TensorInfo::dimension</a></div><div class="ttdeci">size_t dimension(size_t index) const override</div><div class="ttdoc">Return the size of the requested dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00223">TensorInfo.h:223</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor.</div></div>
 <div class="ttc" id="_error_8h_xhtml_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00327">Error.h:327</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &amp;info, const TensorShape &amp;shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00201">Helpers.inl:201</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7fc93f37dac131a1a40b7921f9df3a9a"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">arm_compute::test::validation::output_shape</a></div><div class="ttdeci">output_shape</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div>
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 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a64a08a9fec5aeee8650e7182b6d171d0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">arm_compute::test::validation::weights</a></div><div class="ttdeci">CLTensor weights</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">ConvolutionLayer.cpp:180</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::DataLayoutDimension::WIDTH</a></div><div class="ttdoc">width</div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5f5b6c4337eac9e2e0046ca2304d80dc"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">arm_compute::test::validation::data_type</a></div><div class="ttdeci">data_type</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_arithmetic_addition_8cpp_source.xhtml#l00135">ArithmeticAddition.cpp:135</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a46e938020a3ac8c926d0590b7fe957db"><div class="ttname"><a href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">arm_compute::get_data_layout_dimension_index</a></div><div class="ttdeci">size_t get_data_layout_dimension_index(const DataLayout data_layout, const DataLayoutDimension data_layout_dimension)</div><div class="ttdoc">Get the index of the given dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00326">Helpers.inl:326</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00074">Types.h:74</a></div></div>
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 <p class="reference">References <a class="el" href="_validate_8h_source.xhtml#l00161">ARM_COMPUTE_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00327">ARM_COMPUTE_ERROR_THROW_ON</a>, <a class="el" href="_helpers_8inl_source.xhtml#l00201">arm_compute::auto_init_if_empty()</a>, <a class="el" href="_shape_calculator_8h_source.xhtml#l00702">arm_compute::misc::shape_calculator::compute_deep_convolution_shape()</a>, <a class="el" href="_c_l_2_winograd_8cpp_source.xhtml#l00599">arm_compute::test::validation::conv_info</a>, <a class="el" href="_tensor_info_8h_source.xhtml#l00297">TensorInfo::data_layout()</a>, <a class="el" href="_c_l_2_arithmetic_addition_8cpp_source.xhtml#l00135">arm_compute::test::validation::data_type</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">ITensorInfo::data_type()</a>, <a class="el" href="_tensor_info_8h_source.xhtml#l00223">TensorInfo::dimension()</a>, <a class="el" href="_helpers_8inl_source.xhtml#l00326">arm_compute::get_data_layout_dimension_index()</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="_c_l_tensor_8cpp_source.xhtml#l00035">CLTensor::info()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::output_shape</a>, <a class="el" href="_n_e_depthwise_convolution_layer_native_kernel_8cpp_source.xhtml#l00221">arm_compute::validate_and_configure_window()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">arm_compute::test::validation::weights</a>, and <a class="el" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::WIDTH</a>.</p>

 <p class="reference">Referenced by <a class="el" href="_n_e_direct_convolution_layer_8cpp_source.xhtml#l00042">NEDirectConvolutionLayer::configure()</a>.</p>

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 <p>Name of the kernel. </p>
 <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>

 <p>Implements <a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml#a1a30ad8f276a2310571c36239554831a">ICPPKernel</a>.</p>

 <p class="definition">Definition at line <a class="el" href="_n_e_direct_convolution_layer_kernel_8h_source.xhtml#l00037">37</a> of file <a class="el" href="_n_e_direct_convolution_layer_kernel_8h_source.xhtml">NEDirectConvolutionLayerKernel.h</a>.</p>
 <div class="fragment"><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    {</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;        <span class="keywordflow">return</span> <span class="stringliteral">&quot;NEDirectConvolutionLayerKernel&quot;</span>;</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    }</div></div><!-- fragment -->
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 <h2 class="memtitle"><span class="permalink"><a href="#ac299dc8386e25ebcf104989623cf6000">&#9670;&nbsp;</a></span>operator=() <span class="overload">[1/2]</span></h2>

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 <p>Prevent instances of this class from being copied (As this class contains pointers) </p>

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 <h2 class="memtitle"><span class="permalink"><a href="#aec3ec4dc8b3bda8ba2638fbb9d520322">&#9670;&nbsp;</a></span>operator=() <span class="overload">[2/2]</span></h2>

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           <td>(</td>
           <td class="paramtype"><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a> &amp;&amp;&#160;</td>
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 <p>Allow instances of this class to be moved. </p>

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 <p>Execute the kernel on the passed window. </p>
 <dl class="section warning"><dt>Warning</dt><dd>If <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a0466ee6ce6552c87595f0e88e73eeb1b" 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#ad34a46f53686c12a5c5e717cc9617fb6" title="The maximum window the kernel can be executed on.">window()</a></dd></dl>
 <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#ad34a46f53686c12a5c5e717cc9617fb6" title="The maximum window the kernel can be executed on.">window()</a> method</dd>
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 The width of the window has to be a multiple of num_elems_processed_per_iteration().</dd></dl>
 <dl class="params"><dt>Parameters</dt><dd>
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     <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#ad34a46f53686c12a5c5e717cc9617fb6" title="The maximum window the kernel can be executed on.">window()</a>) </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">info</td><td>Info about executing thread and CPU. </td></tr>
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 <p>Implements <a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml#af814ff5e96f40f1cccf809b2b4ee19ef">ICPPKernel</a>.</p>

 <p class="definition">Definition at line <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml#l01518">1518</a> of file <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml">NEDirectConvolutionLayerKernel.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>&#160;{</div><div class="line"><a name="l01520"></a><span class="lineno"> 1520</span>&#160;    <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>);</div><div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>&#160;    <a class="code" href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a>(<span class="keyword">this</span>);</div><div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>&#160;    <a class="code" href="_validate_8h.xhtml#a6eb9ce82815fe429250189da7592ba75">ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW</a>(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">INEKernel::window</a>(), <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l01523"></a><span class="lineno"> 1523</span>&#160;    <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(_input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">buffer</a>() == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>&#160;</div><div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> kernel_size = _weights-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(_weights-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>));</div><div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>&#160;</div><div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>&#160;    <span class="keywordflow">if</span>(_input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>() == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>&#160;    {</div><div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>&#160;        <span class="keywordflow">switch</span>(kernel_size)</div><div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>&#160;        {</div><div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>&#160;            <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>&#160;            {</div><div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>&#160;                <span class="keywordflow">switch</span>(_input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>())</div><div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>&#160;                {</div><div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>&#160;                    <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>:</div><div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>&#160;                        convolve_1x1&lt;float, float&gt;(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, _num_elems_read_per_iteration, _num_elems_written_per_iteration, _input, _weights, _output, _conv_info);</div><div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>&#160;                        <span class="keywordflow">break</span>;</div><div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>&#160;<span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>&#160;                    <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>:</div><div class="line"><a name="l01540"></a><span class="lineno"> 1540</span>&#160;                        convolve_1x1&lt;float16_t, float16_t&gt;(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, _num_elems_read_per_iteration, _num_elems_written_per_iteration, _input, _weights, _output, _conv_info);</div><div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>&#160;                        <span class="keywordflow">break</span>;</div><div class="line"><a name="l01542"></a><span class="lineno"> 1542</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */</span><span class="preprocessor"></span></div><div class="line"><a name="l01543"></a><span class="lineno"> 1543</span>&#160;                    <span class="keywordflow">default</span>:</div><div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>&#160;                        <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;Data type not supported&quot;</span>);</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>&#160;                        <span class="keywordflow">break</span>;</div><div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>&#160;                }</div><div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>&#160;            }</div><div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>&#160;            <span class="keywordflow">case</span> 3:</div><div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>&#160;            {</div><div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>&#160;                <span class="keywordflow">switch</span>(_input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>())</div><div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>&#160;                {</div><div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>&#160;                    <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>:</div><div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>&#160;                        convolve_3x3&lt;float, float&gt;(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, _num_elems_read_per_iteration, _num_elems_written_per_iteration, _input, _weights, _output, _conv_info);</div><div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>&#160;                        <span class="keywordflow">break</span>;</div><div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>&#160;<span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>&#160;                    <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>:</div><div class="line"><a name="l01558"></a><span class="lineno"> 1558</span>&#160;                        convolve_3x3&lt;float16_t, float16_t&gt;(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, _num_elems_read_per_iteration, _num_elems_written_per_iteration, _input, _weights, _output, _conv_info);</div><div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>&#160;                        <span class="keywordflow">break</span>;</div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */</span><span class="preprocessor"></span></div><div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>&#160;                    <span class="keywordflow">default</span>:</div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>&#160;                        <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;Data type not supported&quot;</span>);</div><div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>&#160;                        <span class="keywordflow">break</span>;</div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>&#160;                }</div><div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>&#160;            }</div><div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>&#160;            <span class="keywordflow">case</span> 5:</div><div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>&#160;            {</div><div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>&#160;                <span class="keywordflow">switch</span>(_input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>())</div><div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>&#160;                {</div><div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>&#160;                    <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>:</div><div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>&#160;                        convolve_5x5&lt;float, float&gt;(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, _num_elems_read_per_iteration, _num_elems_written_per_iteration, _input, _weights, _output, _conv_info);</div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>&#160;                        <span class="keywordflow">break</span>;</div><div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>&#160;                    <span class="keywordflow">default</span>:</div><div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>&#160;                        <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;Data type not supported&quot;</span>);</div><div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>&#160;                        <span class="keywordflow">break</span>;</div><div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>&#160;                }</div><div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>&#160;            }</div><div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>&#160;            <span class="keywordflow">default</span>:</div><div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>&#160;            {</div><div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>&#160;                <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;Only kernel sizes 1x1, 3x3 and 5x5 are supported.&quot;</span>);</div><div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>&#160;            }</div><div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>&#160;        }</div><div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>&#160;    }</div><div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>&#160;    {</div><div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">int</span> kernel_size = _weights-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(_weights-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>));</div><div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">int</span> stride_x    = std::get&lt;0&gt;(_conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#a6e324c1bd1111876469ea247da156147">stride</a>());</div><div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">int</span> stride_y    = std::get&lt;1&gt;(_conv_info.<a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml#a6e324c1bd1111876469ea247da156147">stride</a>());</div><div class="line"><a name="l01592"></a><span class="lineno"> 1592</span>&#160;</div><div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>&#160;        <span class="keywordflow">switch</span>(_input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>())</div><div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>&#160;        {</div><div class="line"><a name="l01595"></a><span class="lineno"> 1595</span>&#160;            <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>:</div><div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>&#160;            {</div><div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>&#160;                <span class="keywordflow">if</span>(kernel_size == 9 &amp;&amp; stride_x == 1 &amp;&amp; stride_y == 1)</div><div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>&#160;                {</div><div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>&#160;                    <span class="keyword">using</span> vtype = <a class="code" href="structarm__compute_1_1wrapper_1_1traits_1_1neon__vector.xhtml">wrapper::traits::neon_vector&lt;float, 4&gt;</a>;</div><div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>&#160;                    convolve_9x9_nhwc&lt;vtype&gt;(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, _num_elems_read_per_iteration, _input, _weights, _output, _conv_info);</div><div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>&#160;                }</div><div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>&#160;                <span class="keywordflow">else</span></div><div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>&#160;                {</div><div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>&#160;                    convolver_nhwc&lt;float&gt;::convolve(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, kernel_size, _num_elems_read_per_iteration, _input, _weights, _output, _conv_info);</div><div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>&#160;                }</div><div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>&#160;            }</div><div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>&#160;            <span class="keywordflow">default</span>:</div><div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>&#160;                <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;Data type not supported&quot;</span>);</div><div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>&#160;        }</div><div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>&#160;    }</div><div class="line"><a name="l01613"></a><span class="lineno"> 1613</span>&#160;}</div><div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00261">Error.h:261</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_ad34a46f53686c12a5c5e717cc9617fb6"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const</div><div class="ttdoc">The maximum window the kernel can be executed on.</div><div class="ttdef"><b>Definition:</b> <a href="_i_kernel_8cpp_source.xhtml#l00028">IKernel.cpp:28</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension.</div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor.</div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel</div></div>
 <div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00337">Error.h:337</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel</div></div>
 <div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00160">Error.h:160</a></div></div>
 <div class="ttc" id="structarm__compute_1_1wrapper_1_1traits_1_1neon__vector_xhtml"><div class="ttname"><a href="structarm__compute_1_1wrapper_1_1traits_1_1neon__vector.xhtml">arm_compute::wrapper::traits::neon_vector</a></div><div class="ttdoc">Create the appropriate NEON vector given its type and size in terms of elements.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2wrapper_2traits_8h_source.xhtml#l00044">traits.h:44</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_ab988210662dbd3bf32fd563c7dd1bdbf"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">arm_compute::ITensor::buffer</a></div><div class="ttdeci">virtual uint8_t * buffer() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return a pointer to CPU memory.</div></div>
 <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml_a6e324c1bd1111876469ea247da156147"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml#a6e324c1bd1111876469ea247da156147">arm_compute::PadStrideInfo::stride</a></div><div class="ttdeci">std::pair&lt; unsigned int, unsigned int &gt; stride() const</div><div class="ttdoc">Get the stride.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00724">Types.h:724</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width.</div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::DataLayoutDimension::WIDTH</a></div><div class="ttdoc">width</div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a46e938020a3ac8c926d0590b7fe957db"><div class="ttname"><a href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">arm_compute::get_data_layout_dimension_index</a></div><div class="ttdeci">size_t get_data_layout_dimension_index(const DataLayout data_layout, const DataLayoutDimension data_layout_dimension)</div><div class="ttdoc">Get the index of the given dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00326">Helpers.inl:326</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a4f4125dba5283887b34f889b1c615c0c"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">arm_compute::test::validation::info</a></div><div class="ttdeci">info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div>
 <div class="ttc" id="_validate_8h_xhtml_a6eb9ce82815fe429250189da7592ba75"><div class="ttname"><a href="_validate_8h.xhtml#a6eb9ce82815fe429250189da7592ba75">ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00205">Validate.h:205</a></div></div>
 <div class="ttc" id="_validate_8h_xhtml_a1b35b0d258183cf9ef36adf684d0b88c"><div class="ttname"><a href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00940">Validate.h:940</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a367b5090ab432bc7de2c32369e087ab1"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">arm_compute::ITensorInfo::data_layout</a></div><div class="ttdeci">virtual DataLayout data_layout() const =0</div><div class="ttdoc">Get the data layout of the tensor.</div></div>
 </div><!-- fragment -->
 <p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00261">ARM_COMPUTE_ERROR</a>, <a class="el" href="_error_8h_source.xhtml#l00337">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00205">ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW</a>, <a class="el" href="_validate_8h_source.xhtml#l00940">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a>, <a class="el" href="_error_8h_source.xhtml#l00160">ARM_COMPUTE_UNUSED</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">ITensor::buffer()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">ITensorInfo::data_layout()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">ITensorInfo::data_type()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::F16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="_helpers_8inl_source.xhtml#l00326">arm_compute::get_data_layout_dimension_index()</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::info</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::NCHW</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00724">PadStrideInfo::stride()</a>, <a class="el" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::WIDTH</a>, and <a class="el" href="_i_kernel_8cpp_source.xhtml#l00028">IKernel::window()</a>.</p>

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 <h2 class="memtitle"><span class="permalink"><a href="#a38da9c4ac16c0ca78e5d7176aab3435e">&#9670;&nbsp;</a></span>validate()</h2>

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           <td class="memname"><a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> validate </td>
           <td>(</td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *&#160;</td>
           <td class="paramname"><em>input</em>, </td>
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         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *&#160;</td>
           <td class="paramname"><em>weights</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *&#160;</td>
           <td class="paramname"><em>output</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;&#160;</td>
           <td class="paramname"><em>conv_info</em>&#160;</td>
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           <td>)</td>
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 <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_direct_convolution_layer_kernel.xhtml">NEDirectConvolutionLayerKernel</a>. </p>
 <dl class="params"><dt>Parameters</dt><dd>
   <table class="params">
     <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>The input tensor to convolve. 3 lower dimensions represent a single input [width, height, IFM], while every optional dimension from 4 and above represent a batch of inputs. Data types supported: F16/F32. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. The 3rd dimension must be the same as the input's volume 3rd dimension. Data type supported:Same as <code>input</code>. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Output tensor. The 3rd dimensions must be equal to the 4th dimension of the <code>kernels</code> tensor. Data types supported: F16/F32 </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">conv_info</td><td>Contains padding and stride information described in <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>.</td></tr>
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 <dl class="section return"><dt>Returns</dt><dd>a status </dd></dl>

 <p class="definition">Definition at line <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml#l01498">1498</a> of file <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml">NEDirectConvolutionLayerKernel.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>&#160;{</div><div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_weight_elems_read_per_row   = 0;</div><div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_read_per_iteration    = 0;</div><div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_written_per_iteration = 0;</div><div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>&#160;    <a class="code" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a>   <a class="code" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>                     = {};</div><div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>&#160;    <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(validate_arguments(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>));</div><div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>&#160;    <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">validate_and_configure_window</a>(input-&gt;<a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>().get(),</div><div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>&#160;                                                              <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;clone().get(),</div><div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>&#160;                                                              output-&gt;<a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>().get(),</div><div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>&#160;                                                              <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>&#160;                                                              num_weight_elems_read_per_row,</div><div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>&#160;                                                              num_elems_read_per_iteration,</div><div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>&#160;                                                              num_elems_written_per_iteration,</div><div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>&#160;                                                              <a class="code" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>)</div><div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>&#160;                                .first);</div><div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>&#160;</div><div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>&#160;}</div><div class="ttc" id="structarm__compute_1_1_border_size_xhtml"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml">arm_compute::BorderSize</a></div><div class="ttdoc">Container for 2D border size.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00259">Types.h:259</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ad6630777dc2d315531f1e0b02491051f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad6630777dc2d315531f1e0b02491051f">arm_compute::validate_and_configure_window</a></div><div class="ttdeci">std::pair&lt; Status, Window &gt; validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *output, const PadStrideInfo &amp;conv_info, unsigned int depth_multiplier, const Size2D &amp;dilation)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_depthwise_convolution_layer_native_kernel_8cpp_source.xhtml#l00221">NEDepthwiseConvolutionLayerNativeKernel.cpp:221</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00599">Winograd.cpp:599</a></div></div>
 <div class="ttc" id="_error_8h_xhtml_a8a1e1c105f0bdaf37db408c7cfcb77a4"><div class="ttname"><a href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ON_ERROR(status)</div><div class="ttdoc">Checks if a status contains an error and returns it.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00193">Error.h:193</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_status_xhtml"><div class="ttname"><a href="classarm__compute_1_1_status.xhtml">arm_compute::Status</a></div><div class="ttdoc">Status class.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00052">Error.h:52</a></div></div>
 <div class="ttc" id="classarm__compute_1_1misc_1_1_i_cloneable_xhtml_a4d10e5012a872e7f78f2b539b673049d"><div class="ttname"><a href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">arm_compute::misc::ICloneable::clone</a></div><div class="ttdeci">virtual std::unique_ptr&lt; T &gt; clone() const =0</div><div class="ttdoc">Provide a clone of the current object of class T.</div></div>
 <div class="ttc" id="classarm__compute_1_1_n_e_direct_convolution_layer_kernel_xhtml_a423f9a45a52983b4de5e2b347f4369c7"><div class="ttname"><a href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">arm_compute::NEDirectConvolutionLayerKernel::border_size</a></div><div class="ttdeci">BorderSize border_size() const override</div><div class="ttdoc">The size of the border for that kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml#l01459">NEDirectConvolutionLayerKernel.cpp:1459</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a64a08a9fec5aeee8650e7182b6d171d0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">arm_compute::test::validation::weights</a></div><div class="ttdeci">CLTensor weights</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">ConvolutionLayer.cpp:180</a></div></div>
 </div><!-- fragment -->
 <p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00193">ARM_COMPUTE_RETURN_ON_ERROR</a>, <a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml#l01459">NEDirectConvolutionLayerKernel::border_size()</a>, <a class="el" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">ICloneable&lt; T &gt;::clone()</a>, <a class="el" href="_c_l_2_winograd_8cpp_source.xhtml#l00599">arm_compute::test::validation::conv_info</a>, <a class="el" href="_n_e_depthwise_convolution_layer_native_kernel_8cpp_source.xhtml#l00221">arm_compute::validate_and_configure_window()</a>, and <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">arm_compute::test::validation::weights</a>.</p>

 <p class="reference">Referenced by <a class="el" href="_n_e_direct_convolution_layer_8cpp_source.xhtml#l00074">NEDirectConvolutionLayer::validate()</a>.</p>

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 <hr/>The documentation for this class was generated from the following files:<ul>
 <li>arm_compute/core/NEON/kernels/<a class="el" href="_n_e_direct_convolution_layer_kernel_8h_source.xhtml">NEDirectConvolutionLayerKernel.h</a></li>
 <li>src/core/NEON/kernels/<a class="el" href="_n_e_direct_convolution_layer_kernel_8cpp_source.xhtml">NEDirectConvolutionLayerKernel.cpp</a></li>
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