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 <div class="header">
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 <a href="#pub-methods">Public Member Functions</a> &#124;
 <a href="#pub-static-methods">Static Public Member Functions</a>  </div>
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 <div class="title">CLDepthwiseConvolutionLayer3x3 Class Reference</div>  </div>
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 <p>Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC).
  <a href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#details">More...</a></p>

 <p><code>#include &lt;<a class="el" href="_c_l_depthwise_convolution_layer_8h_source.xhtml">CLDepthwiseConvolutionLayer.h</a>&gt;</code></p>
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 Collaboration diagram for CLDepthwiseConvolutionLayer3x3:</div>
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 Public Member Functions</h2></td></tr>
 <tr class="memitem:ac2d0894cb8f94dccd20d71ed5140a70c"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#ac2d0894cb8f94dccd20d71ed5140a70c">CLDepthwiseConvolutionLayer3x3</a> (std::shared_ptr&lt; <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> &gt; memory_manager=nullptr)</td></tr>
 <tr class="memdesc:ac2d0894cb8f94dccd20d71ed5140a70c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default constructor.  <a href="#ac2d0894cb8f94dccd20d71ed5140a70c">More...</a><br /></td></tr>
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 <tr class="memitem:ab98e7a9e71a4ca2fbd69aeb117697283"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#ab98e7a9e71a4ca2fbd69aeb117697283">CLDepthwiseConvolutionLayer3x3</a> (const <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> &amp;)=delete</td></tr>
 <tr class="memdesc:ab98e7a9e71a4ca2fbd69aeb117697283"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers)  <a href="#ab98e7a9e71a4ca2fbd69aeb117697283">More...</a><br /></td></tr>
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 <tr class="memitem:adc762e3201b5fc3e66102b3150eb03d4"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#adc762e3201b5fc3e66102b3150eb03d4">CLDepthwiseConvolutionLayer3x3</a> (<a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> &amp;&amp;)=default</td></tr>
 <tr class="memdesc:adc762e3201b5fc3e66102b3150eb03d4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default move constructor.  <a href="#adc762e3201b5fc3e66102b3150eb03d4">More...</a><br /></td></tr>
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 <tr class="memitem:a112759d936411bb8bc6d78574d2ad54c"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#a112759d936411bb8bc6d78574d2ad54c">operator=</a> (const <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> &amp;)=delete</td></tr>
 <tr class="memdesc:a112759d936411bb8bc6d78574d2ad54c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers)  <a href="#a112759d936411bb8bc6d78574d2ad54c">More...</a><br /></td></tr>
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 <tr class="memitem:afc8cdc3ccb5858350e433582a721887e"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#afc8cdc3ccb5858350e433582a721887e">operator=</a> (<a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> &amp;&amp;)=default</td></tr>
 <tr class="memdesc:afc8cdc3ccb5858350e433582a721887e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default move assignment operator.  <a href="#afc8cdc3ccb5858350e433582a721887e">More...</a><br /></td></tr>
 <tr class="separator:afc8cdc3ccb5858350e433582a721887e"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a9aac2e1411d40b334fb323c9b6b913a2"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#a9aac2e1411d40b334fb323c9b6b913a2">configure</a> (<a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *weights, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *biases, <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *output, const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &amp;conv_info, unsigned int depth_multiplier=1, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> act_info=<a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;dilation=<a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U, 1U))</td></tr>
 <tr class="memdesc:a9aac2e1411d40b334fb323c9b6b913a2"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initialize the function's source, destination, conv and border_size.  <a href="#a9aac2e1411d40b334fb323c9b6b913a2">More...</a><br /></td></tr>
 <tr class="separator:a9aac2e1411d40b334fb323c9b6b913a2"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr>
 <tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Run the kernels contained in the function.  <a href="#ad1717410afd0be936c6213a63c8005fb">More...</a><br /></td></tr>
 <tr class="separator:ad1717410afd0be936c6213a63c8005fb"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:aa9b93ef660fc3c5b4b19d3fc7b891b77"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a> () override</td></tr>
 <tr class="memdesc:aa9b93ef660fc3c5b4b19d3fc7b891b77"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prepare the function for executing.  <a href="#aa9b93ef660fc3c5b4b19d3fc7b891b77">More...</a><br /></td></tr>
 <tr class="separator:aa9b93ef660fc3c5b4b19d3fc7b891b77"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="inherit_header pub_methods_classarm__compute_1_1_i_function"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_function')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></td></tr>
 <tr class="memitem:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">~IFunction</a> ()=default</td></tr>
 <tr class="memdesc:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor.  <a href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">More...</a><br /></td></tr>
 <tr class="separator:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2">&#160;</td></tr>
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 Static Public Member Functions</h2></td></tr>
 <tr class="memitem:a87b0b2b008eb501d650caddecf96ee63"><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_c_l_depthwise_convolution_layer3x3.xhtml#a87b0b2b008eb501d650caddecf96ee63">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> *biases, 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, unsigned int depth_multiplier=1, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> act_info=<a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>(), <a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target=<a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afa362f4daec88442a387ff7cda411a38">GPUTarget::MIDGARD</a>, const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;dilation=<a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U, 1U))</td></tr>
 <tr class="memdesc:a87b0b2b008eb501d650caddecf96ee63"><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_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a>.  <a href="#a87b0b2b008eb501d650caddecf96ee63">More...</a><br /></td></tr>
 <tr class="separator:a87b0b2b008eb501d650caddecf96ee63"><td class="memSeparator" colspan="2">&#160;</td></tr>
 </table>
 <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
 <div class="textblock"><p>Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC). </p>
 <p>This function calls the following OpenCL kernels:</p>
 <ol type="1">
 <li><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel.xhtml">CLDepthwiseConvolutionLayer3x3NCHWKernel</a> (if data_layout == NCHW)</li>
 <li><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel.xhtml">CLDepthwiseConvolutionLayer3x3NHWCKernel</a> (if data_layout == NHWC)</li>
 <li><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer_reshape_weights_kernel.xhtml">CLDepthwiseConvolutionLayerReshapeWeightsKernel</a> (if data_layout == NHWC)</li>
 <li><a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml">CLFillBorderKernel</a> (if pad_x or pad_y &gt; 0) </li>
 </ol>

 <p class="definition">Definition at line <a class="el" href="_c_l_depthwise_convolution_layer_8h_source.xhtml#l00056">56</a> of file <a class="el" href="_c_l_depthwise_convolution_layer_8h_source.xhtml">CLDepthwiseConvolutionLayer.h</a>.</p>
 </div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
 <a id="ac2d0894cb8f94dccd20d71ed5140a70c"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#ac2d0894cb8f94dccd20d71ed5140a70c">&#9670;&nbsp;</a></span>CLDepthwiseConvolutionLayer3x3() <span class="overload">[1/3]</span></h2>

 <div class="memitem">
 <div class="memproto">
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           <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> </td>
           <td>(</td>
           <td class="paramtype">std::shared_ptr&lt; <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> &gt;&#160;</td>
           <td class="paramname"><em>memory_manager</em> = <code>nullptr</code></td><td>)</td>
           <td></td>
         </tr>
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 </div><div class="memdoc">

 <p>Default constructor. </p>

 <p class="definition">Definition at line <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml#l00041">41</a> of file <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml">CLDepthwiseConvolutionLayer.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    : _memory_group(std::move(memory_manager)), _kernel(<span class="keyword">nullptr</span>), _border_handler(), _permute_input_to_nchw(), _permute_weights_to_nchw(), _permute_output_to_nhwc(), _reshape_weights(), _permuted_input(),</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;      _permuted_weights(), _permuted_output(), _original_weights(<span class="keyword">nullptr</span>), _needs_permute(<span class="keyword">false</span>), _needs_weights_reshape(<span class="keyword">false</span>), _is_prepared(<span class="keyword">false</span>)</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;{</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;}</div></div><!-- fragment -->
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 <a id="ab98e7a9e71a4ca2fbd69aeb117697283"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#ab98e7a9e71a4ca2fbd69aeb117697283">&#9670;&nbsp;</a></span>CLDepthwiseConvolutionLayer3x3() <span class="overload">[2/3]</span></h2>

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           <td>(</td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> &amp;&#160;</td>
           <td class="paramname"></td><td>)</td>
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 <p>Prevent instances of this class from being copied (As this class contains pointers) </p>

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 <a id="adc762e3201b5fc3e66102b3150eb03d4"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#adc762e3201b5fc3e66102b3150eb03d4">&#9670;&nbsp;</a></span>CLDepthwiseConvolutionLayer3x3() <span class="overload">[3/3]</span></h2>

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           <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> </td>
           <td>(</td>
           <td class="paramtype"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> &amp;&amp;&#160;</td>
           <td class="paramname"></td><td>)</td>
           <td></td>
         </tr>
       </table>
   </td>
   <td class="mlabels-right">
 <span class="mlabels"><span class="mlabel">default</span></span>  </td>
   </tr>
 </table>
 </div><div class="memdoc">

 <p>Default move constructor. </p>

 </div>
 </div>
 <h2 class="groupheader">Member Function Documentation</h2>
 <a id="a9aac2e1411d40b334fb323c9b6b913a2"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#a9aac2e1411d40b334fb323c9b6b913a2">&#9670;&nbsp;</a></span>configure()</h2>

 <div class="memitem">
 <div class="memproto">
       <table class="memname">
         <tr>
           <td class="memname">void configure </td>
           <td>(</td>
           <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
           <td class="paramname"><em>input</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</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_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
           <td class="paramname"><em>biases</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</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>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">unsigned int&#160;</td>
           <td class="paramname"><em>depth_multiplier</em> = <code>1</code>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype"><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>&#160;</td>
           <td class="paramname"><em>act_info</em> = <code><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>()</code>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;&#160;</td>
           <td class="paramname"><em>dilation</em> = <code><a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U,&#160;1U)</code>&#160;</td>
         </tr>
         <tr>
           <td></td>
           <td>)</td>
           <td></td><td></td>
         </tr>
       </table>
 </div><div class="memdoc">

 <p>Initialize the function's source, destination, conv and border_size. </p>
 <dl class="params"><dt>Parameters</dt><dd>
   <table class="params">
     <tr><td class="paramdir">[in,out]</td><td class="paramname">input</td><td>Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as <code>input</code>. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">biases</td><td>Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. Data type supported: Same as <code>input</code>. </td></tr>
     <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. Data type supported: same as <code>input</code>. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">conv_info</td><td>Padding and stride information to use for the convolution. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">depth_multiplier</td><td>(Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">act_info</td><td>(Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">dilation</td><td>(Optional) Dilation, in elements, across x and y. Defaults to (1, 1). </td></tr>
   </table>
   </dd>
 </dl>

 <p class="definition">Definition at line <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml#l00047">47</a> of file <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml">CLDepthwiseConvolutionLayer.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;{</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(input, 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    <a class="code" href="_validate_8h.xhtml#a5befbfaf6bc224eabc58b5e88b1de6d1">ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>);</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;    <span class="comment">// idx_w and idx_h only used for validation</span></div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_w = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(input-&gt;info()-&gt;data_layout(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>);</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_h = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(input-&gt;info()-&gt;data_layout(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>);</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(idx_w);</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(idx_h);</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</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#a8813441b655b97c00139c6a5a6390e97">dimension</a>(idx_w) + (<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>(idx_w) - 1) * (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>.x() - 1) &gt; input-&gt;info()-&gt;dimension(idx_w) + <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_left() + <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_right());</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#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>(idx_h) + (<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>(idx_h) - 1) * (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>.y() - 1) &gt; input-&gt;info()-&gt;dimension(idx_h) + <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_top() + <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_bottom());</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span> is_nhwc = input-&gt;info()-&gt;data_layout() == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    _needs_permute         = is_nhwc &amp;&amp; (depth_multiplier &gt; 1);</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    _needs_weights_reshape = is_nhwc &amp;&amp; (depth_multiplier == 1)</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;                             &amp;&amp; <a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(input-&gt;info()-&gt;data_type());</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    _is_prepared      = <span class="keyword">false</span>;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    _original_weights = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>;</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    ICLTensor       *input_to_use   = input;</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    <span class="keyword">const</span> ICLTensor *weights_to_use = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    ICLTensor       *output_to_use  = output;</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span> is_stride_1            = ((<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().first == <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().second) &amp;&amp; (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().first == 1));</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span> is_dot8_supported      = <a class="code" href="namespacearm__compute.xhtml#ac07e02c0066cf540a5a2665fa7d54934">dot8_supported</a>(<a class="code" href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">CLKernelLibrary::get</a>().get_device());</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span> is_stride_1_dilation_1 = (is_stride_1 &amp;&amp; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>.x() == 1 &amp;&amp; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>.y() == 1);</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    DepthwiseConvolutionReshapeInfo <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>;</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.c0        = 4;</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.transpose = is_stride_1_dilation_1 &amp;&amp; is_dot8_supported;</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    <span class="keywordflow">if</span>(_needs_permute)</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    {</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;        _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_permuted_input);</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;        _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_permuted_output);</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;        <span class="comment">// Configure the function to transform the input tensor from NHWC -&gt; NCHW</span></div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;        _permute_input_to_nchw.<a class="code" href="classarm__compute_1_1_c_l_permute.xhtml#af1f5e1b7e8bbf0768c406be880387a0d">configure</a>(input, &amp;_permuted_input, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        _permuted_input.<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#a70b6e1495b94818cce4981dbac6bdd66">set_data_layout</a>(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        <span class="comment">// Configure the function to transform the weights tensor from HWI -&gt; IHW</span></div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;        _permute_weights_to_nchw.<a class="code" href="classarm__compute_1_1_c_l_permute.xhtml#af1f5e1b7e8bbf0768c406be880387a0d">configure</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, &amp;_permuted_weights, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;        _permuted_weights.<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#a70b6e1495b94818cce4981dbac6bdd66">set_data_layout</a>(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;        _permuted_output.<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#a78839e7861ba8ffed52ca55da2745761">set_quantization_info</a>(output-&gt;info()-&gt;quantization_info());</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        input_to_use   = &amp;_permuted_input;</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        weights_to_use = &amp;_permuted_weights;</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;        output_to_use  = &amp;_permuted_output;</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;        _kernel = arm_compute::support::cpp14::make_unique&lt;CLDepthwiseConvolutionLayer3x3NCHWKernel&gt;();</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    }</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    <span class="keywordflow">else</span> <span class="keywordflow">if</span>(is_nhwc)</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    {</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;        <span class="keywordflow">if</span>(_needs_weights_reshape)</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;        {</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;            _reshape_weights.<a class="code" href="classarm__compute_1_1_c_l_depthwise_convolution_layer_reshape_weights_kernel.xhtml#a49b7bf6e6b7fc07e9fcbca39c7f77715">configure</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, &amp;_permuted_weights, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>);</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;            weights_to_use = &amp;_permuted_weights;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;        }</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;        _kernel = arm_compute::support::cpp14::make_unique&lt;CLDepthwiseConvolutionLayer3x3NHWCKernel&gt;();</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    }</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    {</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;        _kernel = arm_compute::support::cpp14::make_unique&lt;CLDepthwiseConvolutionLayer3x3NCHWKernel&gt;();</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    }</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    <span class="comment">// Configure kernel</span></div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    _kernel-&gt;set_target(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().target());</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160; 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       <span class="comment">// Allocate tensors</span></div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        _permuted_input.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;        _permuted_output.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    }</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    <span class="comment">// Configure border handler</span></div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    PixelValue &amp;&amp;zero_value(0.f);</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(input-&gt;info()-&gt;data_type()))</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    {</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;        zero_value = PixelValue(static_cast&lt;uint8_t&gt;(input-&gt;info()-&gt;quantization_info().uniform().offset));</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    }</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    _border_handler.<a class="code" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml#ae1b9fe62ed42f469f1de879c33d75c06">configure</a>(input_to_use, _kernel-&gt;border_size(), <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">BorderMode::CONSTANT</a>, zero_value);</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;}</div><div class="ttc" id="namespacearm__compute_xhtml_ac07e02c0066cf540a5a2665fa7d54934"><div class="ttname"><a href="namespacearm__compute.xhtml#ac07e02c0066cf540a5a2665fa7d54934">arm_compute::dot8_supported</a></div><div class="ttdeci">bool dot8_supported(const cl::Device &amp;device)</div><div class="ttdoc">Helper function to check whether the cl_arm_integer_dot_product_int8 extension is supported.</div><div class="ttdef"><b>Definition:</b> <a href="core_2_c_l_2_c_l_helpers_8cpp_source.xhtml#l00149">CLHelpers.cpp:149</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="namespacearm__compute_1_1test_1_1validation_xhtml_ad3fd4136244e42ad89b01c02b904336d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">arm_compute::test::validation::dilation</a></div><div class="ttdeci">dilation</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="namespacearm__compute_1_1test_1_1validation_xhtml_a1f8aca235c095df227e7444f6b237eb1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">arm_compute::test::validation::act_info</a></div><div class="ttdeci">act_info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">ConvolutionLayer.cpp:175</a></div></div>
 <div class="ttc" id="_validate_8h_xhtml_a5befbfaf6bc224eabc58b5e88b1de6d1"><div class="ttname"><a href="_validate_8h.xhtml#a5befbfaf6bc224eabc58b5e88b1de6d1">ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00543">Validate.h:543</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a9b58d0eb9a2af8e6d7908695e1557d6c"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">arm_compute::CLScheduler::get</a></div><div class="ttdeci">static CLScheduler &amp; get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler.cpp:41</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="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="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">arm_compute::DataLayoutDimension::HEIGHT</a></div><div class="ttdoc">height</div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a33e65be485104e2e9e69fca551d6f492"><div class="ttname"><a href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">arm_compute::PermutationVector</a></div><div class="ttdeci">Strides PermutationVector</div><div class="ttdoc">Permutation vector.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00047">Types.h:47</a></div></div>
 <div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00337">Error.h:337</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_kernel_library_xhtml_acba005f5ce2c62cbf3f94d074d9007aa"><div class="ttname"><a href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">arm_compute::CLKernelLibrary::get</a></div><div class="ttdeci">static CLKernelLibrary &amp; get()</div><div class="ttdoc">Access the KernelLibrary singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l01037">CLKernelLibrary.cpp:1037</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a4083de30daebd6bdee6b35d9c8262108"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">arm_compute::CLTensor::allocator</a></div><div class="ttdeci">CLTensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor.cpp:55</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_fill_border_kernel_xhtml_ae1b9fe62ed42f469f1de879c33d75c06"><div class="ttname"><a href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml#ae1b9fe62ed42f469f1de879c33d75c06">arm_compute::CLFillBorderKernel::configure</a></div><div class="ttdeci">void configure(ICLTensor *tensor, BorderSize border_size, BorderMode border_mode, const PixelValue &amp;constant_border_value=PixelValue())</div><div class="ttdoc">Initialise the kernel's input, output and border mode.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_fill_border_kernel_8cpp_source.xhtml#l00062">CLFillBorderKernel.cpp:62</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="classarm__compute_1_1_tensor_info_xhtml_a78839e7861ba8ffed52ca55da2745761"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a78839e7861ba8ffed52ca55da2745761">arm_compute::TensorInfo::set_quantization_info</a></div><div class="ttdeci">ITensorInfo &amp; set_quantization_info(const QuantizationInfo &amp;quantization_info) override</div><div class="ttdoc">Set the quantization settings (scale and offset) of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_tensor_info_8cpp_source.xhtml#l00364">TensorInfo.cpp:364</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a70b6e1495b94818cce4981dbac6bdd66"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a70b6e1495b94818cce4981dbac6bdd66">arm_compute::TensorInfo::set_data_layout</a></div><div class="ttdeci">ITensorInfo &amp; set_data_layout(const DataLayout &amp;data_layout) override</div><div class="ttdoc">Set the data layout of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_tensor_info_8cpp_source.xhtml#l00370">TensorInfo.cpp:370</a></div></div>
 <div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00160">Error.h:160</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_memory_group_base_xhtml_ac1f67376afb7822f262a0174ef4a3104"><div class="ttname"><a href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">arm_compute::MemoryGroupBase::manage</a></div><div class="ttdeci">void manage(TensorType *obj)</div><div class="ttdoc">Sets a object to be managed by the given memory group.</div><div class="ttdef"><b>Definition:</b> <a href="_memory_group_base_8h_source.xhtml#l00102">MemoryGroupBase.h:102</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb"><div class="ttname"><a href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::Channel::U</a></div><div class="ttdoc">Cb/U channel.</div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div><div class="ttdoc">quantized, asymmetric fixed-point 8-bit number</div></div>
 <div class="ttc" id="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="_validate_8h_xhtml_aadf5c9cff86327b96d88d04649d9715e"><div class="ttname"><a href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00789">Validate.h:789</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_depthwise_convolution_layer_reshape_weights_kernel_xhtml_a49b7bf6e6b7fc07e9fcbca39c7f77715"><div class="ttname"><a href="classarm__compute_1_1_c_l_depthwise_convolution_layer_reshape_weights_kernel.xhtml#a49b7bf6e6b7fc07e9fcbca39c7f77715">arm_compute::CLDepthwiseConvolutionLayerReshapeWeightsKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output, const DepthwiseConvolutionReshapeInfo &amp;info)</div><div class="ttdoc">Initialize the function's source and destination.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_depthwise_convolution_layer_reshape_weights_kernel_8cpp_source.xhtml#l00087">CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp:87</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a14f46283f316e7f0fad301d5c1507e9f"><div class="ttname"><a href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">arm_compute::is_data_type_quantized_asymmetric</a></div><div class="ttdeci">bool is_data_type_quantized_asymmetric(DataType dt)</div><div class="ttdoc">Check if a given data type is of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01030">Utils.h:1030</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::CLTensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of OpenCL memory.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_allocator_8cpp_source.xhtml#l00119">CLTensorAllocator.cpp:119</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92"><div class="ttname"><a href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">arm_compute::PaddingMode::CONSTANT</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::DataLayout::NHWC</a></div><div class="ttdoc">Num samples, height, width, channels.</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 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="classarm__compute_1_1_c_l_permute_xhtml_af1f5e1b7e8bbf0768c406be880387a0d"><div class="ttname"><a href="classarm__compute_1_1_c_l_permute.xhtml#af1f5e1b7e8bbf0768c406be880387a0d">arm_compute::CLPermute::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output, const PermutationVector &amp;perm)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_permute_8cpp_source.xhtml#l00033">CLPermute.cpp:33</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_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>
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 <p class="reference">References <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">arm_compute::test::validation::act_info</a>, <a class="el" href="_c_l_tensor_allocator_8cpp_source.xhtml#l00119">CLTensorAllocator::allocate()</a>, <a class="el" href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor::allocator()</a>, <a class="el" href="_error_8h_source.xhtml#l00337">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00789">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>, <a class="el" href="_validate_8h_source.xhtml#l00543">ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES</a>, <a class="el" href="_error_8h_source.xhtml#l00160">ARM_COMPUTE_UNUSED</a>, <a class="el" href="_c_l_permute_8cpp_source.xhtml#l00033">CLPermute::configure()</a>, <a class="el" href="_c_l_depthwise_convolution_layer_reshape_weights_kernel_8cpp_source.xhtml#l00087">CLDepthwiseConvolutionLayerReshapeWeightsKernel::configure()</a>, <a class="el" href="_c_l_fill_border_kernel_8cpp_source.xhtml#l00062">CLFillBorderKernel::configure()</a>, <a class="el" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">arm_compute::CONSTANT</a>, <a class="el" href="_c_l_2_winograd_8cpp_source.xhtml#l00599">arm_compute::test::validation::conv_info</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="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::dilation</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</a>, <a class="el" href="_tensor_info_8h_source.xhtml#l00223">TensorInfo::dimension()</a>, <a class="el" href="core_2_c_l_2_c_l_helpers_8cpp_source.xhtml#l00149">arm_compute::dot8_supported()</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="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler::get()</a>, <a class="el" href="_c_l_kernel_library_8cpp_source.xhtml#l01037">CLKernelLibrary::get()</a>, <a class="el" href="_helpers_8inl_source.xhtml#l00326">arm_compute::get_data_layout_dimension_index()</a>, <a class="el" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">arm_compute::HEIGHT</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::info</a>, <a class="el" href="arm__compute_2core_2_utils_8h_source.xhtml#l01030">arm_compute::is_data_type_quantized_asymmetric()</a>, <a class="el" href="_memory_group_base_8h_source.xhtml#l00102">MemoryGroupBase&lt; TensorType &gt;::manage()</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::NCHW</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::NHWC</a>, <a class="el" href="_quantization_info_8h_source.xhtml#l00062">UniformQuantizationInfo::offset</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::QASYMM8</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">ITensorInfo::quantization_info()</a>, <a class="el" href="src_2core_2_tensor_info_8cpp_source.xhtml#l00370">TensorInfo::set_data_layout()</a>, <a class="el" href="src_2core_2_tensor_info_8cpp_source.xhtml#l00364">TensorInfo::set_quantization_info()</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::U</a>, <a class="el" href="_quantization_info_8h_source.xhtml#l00134">QuantizationInfo::uniform()</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>

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 <h2 class="memtitle"><span class="permalink"><a href="#a112759d936411bb8bc6d78574d2ad54c">&#9670;&nbsp;</a></span>operator=() <span class="overload">[1/2]</span></h2>

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           <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a>&amp; operator= </td>
           <td>(</td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</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="#afc8cdc3ccb5858350e433582a721887e">&#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_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a> &amp;&amp;&#160;</td>
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 <p>Default move assignment operator. </p>

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 <h2 class="memtitle"><span class="permalink"><a href="#aa9b93ef660fc3c5b4b19d3fc7b891b77">&#9670;&nbsp;</a></span>prepare()</h2>

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           <td class="memname">void prepare </td>
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 <p>Prepare the function for executing. </p>
 <p>Any one off pre-processing step required by the function is handled here</p>
 <dl class="section note"><dt>Note</dt><dd>Prepare stage might not need all the function's buffers' backing memory to be available in order to execute </dd></dl>

 <p>Reimplemented from <a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">IFunction</a>.</p>

 <p class="definition">Definition at line <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml#l00224">224</a> of file <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml">CLDepthwiseConvolutionLayer.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;{</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    <span class="keywordflow">if</span>(!_is_prepared)</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;    {</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;        <span class="keywordflow">if</span>(_needs_permute)</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;        {</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;            <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!_original_weights-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a209ea2ddfdfa80703799c92da8beb643">is_used</a>());</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;            _permuted_weights.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;            _permute_weights_to_nchw.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;            _original_weights-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">mark_as_unused</a>();</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;        }</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;        <span class="keywordflow">if</span>(_needs_weights_reshape)</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;        {</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;            <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(_needs_permute);</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;            <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!_original_weights-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a209ea2ddfdfa80703799c92da8beb643">is_used</a>());</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;            _permuted_weights.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;            <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_reshape_weights);</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;            _original_weights-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">mark_as_unused</a>();</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;        }</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;        _is_prepared = <span class="keyword">true</span>;</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;    }</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a9b58d0eb9a2af8e6d7908695e1557d6c"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">arm_compute::CLScheduler::get</a></div><div class="ttdeci">static CLScheduler &amp; get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler.cpp:41</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a209ea2ddfdfa80703799c92da8beb643"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a209ea2ddfdfa80703799c92da8beb643">arm_compute::ITensor::is_used</a></div><div class="ttdeci">bool is_used() const</div><div class="ttdoc">Flags if the tensor is used or not.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8cpp_source.xhtml#l00162">ITensor.cpp:162</a></div></div>
 <div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00337">Error.h:337</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a4083de30daebd6bdee6b35d9c8262108"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">arm_compute::CLTensor::allocator</a></div><div class="ttdeci">CLTensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor.cpp:55</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a9bc00234de9adf8c99a21eb1d7d494c2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">arm_compute::ITensor::mark_as_unused</a></div><div class="ttdeci">void mark_as_unused() const</div><div class="ttdoc">Marks a tensor as unused.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8cpp_source.xhtml#l00167">ITensor.cpp:167</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_c_l_simple_function_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::ICLSimpleFunction::run</a></div><div class="ttdeci">void run() override final</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_simple_function_8cpp_source.xhtml#l00037">ICLSimpleFunction.cpp:37</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_ae1a643e517f50bf0392fb6516dd7cf67"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">arm_compute::CLScheduler::enqueue</a></div><div class="ttdeci">void enqueue(ICLKernel &amp;kernel, bool flush=true)</div><div class="ttdoc">Schedule the execution of the passed kernel if possible.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00095">CLScheduler.cpp:95</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::CLTensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of OpenCL memory.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_allocator_8cpp_source.xhtml#l00119">CLTensorAllocator.cpp:119</a></div></div>
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 <p class="reference">References <a class="el" href="_c_l_tensor_allocator_8cpp_source.xhtml#l00119">CLTensorAllocator::allocate()</a>, <a class="el" href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor::allocator()</a>, <a class="el" href="_error_8h_source.xhtml#l00337">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00095">CLScheduler::enqueue()</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler::get()</a>, <a class="el" href="_i_tensor_8cpp_source.xhtml#l00162">ITensor::is_used()</a>, <a class="el" href="_i_tensor_8cpp_source.xhtml#l00167">ITensor::mark_as_unused()</a>, and <a class="el" href="_i_c_l_simple_function_8cpp_source.xhtml#l00037">ICLSimpleFunction::run()</a>.</p>

 <p class="reference">Referenced by <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml#l00205">CLDepthwiseConvolutionLayer3x3::run()</a>.</p>

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 <h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">&#9670;&nbsp;</a></span>run()</h2>

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           <td class="memname">void run </td>
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 <p>Run the kernels contained in the function. </p>
 <p>For NEON kernels:</p><ul>
 <li>Multi-threading is used for the kernels which are parallelisable.</li>
 <li>By default std::thread::hardware_concurrency() threads are used.</li>
 </ul>
 <dl class="section note"><dt>Note</dt><dd><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml#ae64eebaa07f4d2da6cc2ba538c3cb095">CPPScheduler::set_num_threads()</a> can be used to manually set the number of threads</dd></dl>
 <p>For OpenCL kernels:</p><ul>
 <li>All the kernels are enqueued on the queue associated with <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue.">CLScheduler</a>.</li>
 <li>The queue is then flushed.</li>
 </ul>
 <dl class="section note"><dt>Note</dt><dd>The function will not block until the kernels are executed. It is the user's responsibility to wait. </dd>
 <dd>
 Will call <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77" title="Prepare the function for executing.">prepare()</a> on first run if hasn't been done </dd></dl>

 <p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p>

 <p class="definition">Definition at line <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml#l00205">205</a> of file <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml">CLDepthwiseConvolutionLayer.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;{</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    <a class="code" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>();</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;    MemoryGroupResourceScope scope_mg(_memory_group);</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    <span class="keywordflow">if</span>(_needs_permute)</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;    {</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;        _permute_input_to_nchw.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;    }</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_border_handler);</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;    <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(*_kernel);</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;    <span class="keywordflow">if</span>(_needs_permute)</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;    {</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;        _permute_output_to_nhwc.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;    }</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_xhtml_aa9b93ef660fc3c5b4b19d3fc7b891b77"><div class="ttname"><a href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">arm_compute::CLDepthwiseConvolutionLayer3x3::prepare</a></div><div class="ttdeci">void prepare() override</div><div class="ttdoc">Prepare the function for executing.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml#l00224">CLDepthwiseConvolutionLayer.cpp:224</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a9b58d0eb9a2af8e6d7908695e1557d6c"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">arm_compute::CLScheduler::get</a></div><div class="ttdeci">static CLScheduler &amp; get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler.cpp:41</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_c_l_simple_function_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::ICLSimpleFunction::run</a></div><div class="ttdeci">void run() override final</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_simple_function_8cpp_source.xhtml#l00037">ICLSimpleFunction.cpp:37</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_ae1a643e517f50bf0392fb6516dd7cf67"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">arm_compute::CLScheduler::enqueue</a></div><div class="ttdeci">void enqueue(ICLKernel &amp;kernel, bool flush=true)</div><div class="ttdoc">Schedule the execution of the passed kernel if possible.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00095">CLScheduler.cpp:95</a></div></div>
 </div><!-- fragment -->
 <p class="reference">References <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00095">CLScheduler::enqueue()</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler::get()</a>, <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml#l00224">CLDepthwiseConvolutionLayer3x3::prepare()</a>, and <a class="el" href="_i_c_l_simple_function_8cpp_source.xhtml#l00037">ICLSimpleFunction::run()</a>.</p>

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 <h2 class="memtitle"><span class="permalink"><a href="#a87b0b2b008eb501d650caddecf96ee63">&#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>
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           <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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           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *&#160;</td>
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           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *&#160;</td>
           <td class="paramname"><em>biases</em>, </td>
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           <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>
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           <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>, </td>
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           <td class="paramtype">unsigned int&#160;</td>
           <td class="paramname"><em>depth_multiplier</em> = <code>1</code>, </td>
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           <td></td>
           <td class="paramtype"><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>&#160;</td>
           <td class="paramname"><em>act_info</em> = <code><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>()</code>, </td>
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           <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a>&#160;</td>
           <td class="paramname"><em>gpu_target</em> = <code><a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afa362f4daec88442a387ff7cda411a38">GPUTarget::MIDGARD</a></code>, </td>
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           <td></td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;&#160;</td>
           <td class="paramname"><em>dilation</em> = <code><a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U,&#160;1U)</code>&#160;</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_c_l_depthwise_convolution_layer3x3.xhtml">CLDepthwiseConvolutionLayer3x3</a>. </p>
 <dl class="params"><dt>Parameters</dt><dd>
   <table class="params">
     <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Source tensor info. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>Weights tensor info. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as <code>input</code>. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">biases</td><td>Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed. Data type supported: Same as <code>input</code>, S32 when input is QASYMM8. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Destination tensor. Data type supported: same as <code>input</code>. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">conv_info</td><td>Padding and stride information to use for the convolution. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">depth_multiplier</td><td>(Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">act_info</td><td>(Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">gpu_target</td><td>(Optional) GPU target to validate the kernel for. Defaults to midgard. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">dilation</td><td>(Optional) Dilation, in elements, across x and y. Defaults to (1, 1).</td></tr>
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 </dl>
 <dl class="section return"><dt>Returns</dt><dd>a status </dd></dl>

 <p class="definition">Definition at line <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml#l00139">139</a> of file <a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml">CLDepthwiseConvolutionLayer.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;{</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_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="l00143"></a><span class="lineno">  143</span>&#160;    <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(input-&gt;data_layout() == <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataLayout::UNKNOWN</a>);</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span>                      is_quantized           = <a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(input-&gt;data_type());</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span>                      is_nhwc                = input-&gt;data_layout() == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span>                      needs_permute          = is_nhwc &amp;&amp; (depth_multiplier &gt; 1);</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span>                      needs_weights_reshape  = is_nhwc &amp;&amp; (depth_multiplier == 1) &amp;&amp; is_quantized;</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span>                      is_stride_1            = ((<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().first == <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().second) &amp;&amp; (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride().first == 1));</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span>                      is_stride_1_dilation_1 = (is_stride_1 &amp;&amp; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>.x() == 1 &amp;&amp; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>.y() == 1);</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span>                      is_dot8_supported      = <a class="code" href="namespacearm__compute.xhtml#ac07e02c0066cf540a5a2665fa7d54934">dot8_supported</a>(<a class="code" href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">CLKernelLibrary::get</a>().get_device());</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    DepthwiseConvolutionReshapeInfo <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>;</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.c0        = 4;</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.transpose = is_stride_1_dilation_1 &amp;&amp; is_dot8_supported;</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    <span class="keywordflow">if</span>(is_quantized)</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    {</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;        <span class="keyword">const</span> UniformQuantizationInfo iq_info = input-&gt;quantization_info().uniform();</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;        <span class="keyword">const</span> UniformQuantizationInfo wq_info = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;quantization_info().uniform();</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;        <span class="keyword">const</span> UniformQuantizationInfo oq_info = (output-&gt;total_size() == 0) ? iq_info : output-&gt;quantization_info().uniform();</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">float</span> multiplier = iq_info.scale * wq_info.scale / oq_info.scale;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;        <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(multiplier);</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(multiplier &gt; 1.0f);</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;    }</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    <span class="keywordflow">if</span>(needs_permute)</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;    {</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;        TensorShape permuted_input_shape   = input-&gt;tensor_shape();</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;        TensorShape permuted_weights_shape = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;tensor_shape();</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;        TensorShape permuted_output_shape  = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#ac7147815227e7ba91814cfdcd38f23ed">shape_calculator::compute_depthwise_convolution_shape</a>(*input, *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, depth_multiplier, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>);</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;        <a class="code" href="namespacearm__compute.xhtml#a21c3e11887f3acf9284ca763372c7da0">permute</a>(permuted_input_shape, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;        <a class="code" href="namespacearm__compute.xhtml#a21c3e11887f3acf9284ca763372c7da0">permute</a>(permuted_weights_shape, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;        <a class="code" href="namespacearm__compute.xhtml#a21c3e11887f3acf9284ca763372c7da0">permute</a>(permuted_output_shape, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;        <span class="keyword">const</span> TensorInfo permuted_input   = input-&gt;clone()-&gt;set_is_resizable(<span class="keyword">true</span>).reset_padding().set_tensor_shape(permuted_input_shape).set_data_layout(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;        <span class="keyword">const</span> TensorInfo permuted_weights = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;clone()-&gt;set_is_resizable(<span class="keyword">true</span>).reset_padding().set_tensor_shape(permuted_weights_shape).set_data_layout(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;        <span class="keyword">const</span> TensorInfo permuted_output  = output-&gt;clone()-&gt;set_is_resizable(<span class="keyword">true</span>).reset_padding().set_tensor_shape(permuted_output_shape).set_data_layout(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;        <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel.xhtml#a46abfb5a58cedce793acc288374afa88">CLDepthwiseConvolutionLayer3x3NCHWKernel::validate</a>(&amp;permuted_input, &amp;permuted_weights, biases, &amp;permuted_output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, depth_multiplier, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, gpu_target,</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;                                                                                       <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>));</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    }</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    <span class="keywordflow">else</span> <span class="keywordflow">if</span>(is_nhwc)</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    {</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;        <span class="keywordflow">if</span>(needs_weights_reshape)</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;        {</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;            <span class="keyword">auto</span> reshaped_weights_shape = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a3f10bc0f3e2a0126ce8c26e3d6a8fb96">arm_compute::misc::shape_calculator::compute_reshaped_depthwise_weights_shape</a>(*<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>);</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;            <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel.xhtml#a0ddd829ec27b6f67b924291fac0381cb">CLDepthwiseConvolutionLayer3x3NHWCKernel::validate</a>(input, &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-&gt;clone()-&gt;set_tensor_shape(reshaped_weights_shape), biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, depth_multiplier,</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;                                                                                           <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>));</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;        }</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;        <span class="keywordflow">else</span></div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;        {</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;            <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel.xhtml#a0ddd829ec27b6f67b924291fac0381cb">CLDepthwiseConvolutionLayer3x3NHWCKernel::validate</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, depth_multiplier, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>));</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;        }</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;    }</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;    {</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;        <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel.xhtml#a46abfb5a58cedce793acc288374afa88">CLDepthwiseConvolutionLayer3x3NCHWKernel::validate</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, depth_multiplier, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, gpu_target, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>));</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    }</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;    <span class="keywordflow">return</span> Status{};</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel_xhtml_a0ddd829ec27b6f67b924291fac0381cb"><div class="ttname"><a href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel.xhtml#a0ddd829ec27b6f67b924291fac0381cb">arm_compute::CLDepthwiseConvolutionLayer3x3NHWCKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &amp;conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info=ActivationLayerInfo(), const Size2D &amp;dilation=Size2D(1U, 1U))</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLDepthwiseConvolutionLa...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel_8cpp_source.xhtml#l00312">CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp:312</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ac07e02c0066cf540a5a2665fa7d54934"><div class="ttname"><a href="namespacearm__compute.xhtml#ac07e02c0066cf540a5a2665fa7d54934">arm_compute::dot8_supported</a></div><div class="ttdeci">bool dot8_supported(const cl::Device &amp;device)</div><div class="ttdoc">Helper function to check whether the cl_arm_integer_dot_product_int8 extension is supported.</div><div class="ttdef"><b>Definition:</b> <a href="core_2_c_l_2_c_l_helpers_8cpp_source.xhtml#l00149">CLHelpers.cpp:149</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_ac7147815227e7ba91814cfdcd38f23ed"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#ac7147815227e7ba91814cfdcd38f23ed">arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape</a></div><div class="ttdeci">TensorShape compute_depthwise_convolution_shape(const ITensorInfo &amp;input, const ITensorInfo &amp;weights, PadStrideInfo conv_info, unsigned int depth_multiplier, const Size2D &amp;dilation=Size2D(1U, 1U))</div><div class="ttdoc">Calculate the depthwise convolution output shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l00410">ShapeCalculator.h:410</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ad3fd4136244e42ad89b01c02b904336d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">arm_compute::test::validation::dilation</a></div><div class="ttdeci">dilation</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="namespacearm__compute_1_1test_1_1validation_xhtml_a1f8aca235c095df227e7444f6b237eb1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">arm_compute::test::validation::act_info</a></div><div class="ttdeci">act_info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">ConvolutionLayer.cpp:175</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="namespacearm__compute_xhtml_a33e65be485104e2e9e69fca551d6f492"><div class="ttname"><a href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">arm_compute::PermutationVector</a></div><div class="ttdeci">Strides PermutationVector</div><div class="ttdoc">Permutation vector.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00047">Types.h:47</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_kernel_library_xhtml_acba005f5ce2c62cbf3f94d074d9007aa"><div class="ttname"><a href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">arm_compute::CLKernelLibrary::get</a></div><div class="ttdeci">static CLKernelLibrary &amp; get()</div><div class="ttdoc">Access the KernelLibrary singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l01037">CLKernelLibrary.cpp:1037</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_a3f10bc0f3e2a0126ce8c26e3d6a8fb96"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a3f10bc0f3e2a0126ce8c26e3d6a8fb96">arm_compute::misc::shape_calculator::compute_reshaped_depthwise_weights_shape</a></div><div class="ttdeci">TensorShape compute_reshaped_depthwise_weights_shape(const ITensorInfo &amp;input, const DepthwiseConvolutionReshapeInfo &amp;info)</div><div class="ttdoc">Calculate the reshaped shape of the weights to use in depthwise convolution.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l00261">ShapeCalculator.h:261</a></div></div>
 <div class="ttc" id="_error_8h_xhtml_a206d6e247e0957ac3dee45d27756fc25"><div class="ttname"><a href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00244">Error.h:244</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a21c3e11887f3acf9284ca763372c7da0"><div class="ttname"><a href="namespacearm__compute.xhtml#a21c3e11887f3acf9284ca763372c7da0">arm_compute::permute</a></div><div class="ttdeci">void permute(Dimensions&lt; T &gt; &amp;dimensions, const PermutationVector &amp;perm)</div><div class="ttdoc">Permutes given Dimensions according to a permutation vector.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00570">Helpers.h:570</a></div></div>
 <div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00160">Error.h:160</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb"><div class="ttname"><a href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::Channel::U</a></div><div class="ttdoc">Cb/U channel.</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_a14f46283f316e7f0fad301d5c1507e9f"><div class="ttname"><a href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">arm_compute::is_data_type_quantized_asymmetric</a></div><div class="ttdeci">bool is_data_type_quantized_asymmetric(DataType dt)</div><div class="ttdoc">Check if a given data type is of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01030">Utils.h:1030</a></div></div>
 <div class="ttc" id="_validate_8h_xhtml_aff911654521523937ff24372a870b89f"><div class="ttname"><a href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00163">Validate.h:163</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel_xhtml_a46abfb5a58cedce793acc288374afa88"><div class="ttname"><a href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel.xhtml#a46abfb5a58cedce793acc288374afa88">arm_compute::CLDepthwiseConvolutionLayer3x3NCHWKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &amp;conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info=ActivationLayerInfo(), GPUTarget gpu_target=GPUTarget::MIDGARD, const Size2D &amp;dilation=Size2D(1U, 1U))</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLDepthwiseConvolutionLa...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel_8cpp_source.xhtml#l00326">CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp:326</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3"><div class="ttname"><a href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">arm_compute::CLVersion::UNKNOWN</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::DataLayout::NHWC</a></div><div class="ttdoc">Num samples, height, width, channels.</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 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><!-- fragment -->
 <p class="reference">References <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">arm_compute::test::validation::act_info</a>, <a class="el" href="_error_8h_source.xhtml#l00244">ARM_COMPUTE_RETURN_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00163">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00193">ARM_COMPUTE_RETURN_ON_ERROR</a>, <a class="el" href="_error_8h_source.xhtml#l00160">ARM_COMPUTE_UNUSED</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="_shape_calculator_8h_source.xhtml#l00410">arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape()</a>, <a class="el" href="_shape_calculator_8h_source.xhtml#l00261">arm_compute::misc::shape_calculator::compute_reshaped_depthwise_weights_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="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="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::dilation</a>, <a class="el" href="core_2_c_l_2_c_l_helpers_8cpp_source.xhtml#l00149">arm_compute::dot8_supported()</a>, <a class="el" href="_c_l_kernel_library_8cpp_source.xhtml#l01037">CLKernelLibrary::get()</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="arm__compute_2core_2_utils_8h_source.xhtml#l01030">arm_compute::is_data_type_quantized_asymmetric()</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::NCHW</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::NHWC</a>, <a class="el" href="arm__compute_2core_2_helpers_8h_source.xhtml#l00570">arm_compute::permute()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">ITensorInfo::quantization_info()</a>, <a class="el" href="_quantization_info_8h_source.xhtml#l00061">UniformQuantizationInfo::scale</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">ITensorInfo::tensor_shape()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">ITensorInfo::total_size()</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::U</a>, <a class="el" href="_quantization_info_8h_source.xhtml#l00134">QuantizationInfo::uniform()</a>, <a class="el" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">arm_compute::UNKNOWN</a>, <a class="el" href="_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel_8cpp_source.xhtml#l00326">CLDepthwiseConvolutionLayer3x3NCHWKernel::validate()</a>, <a class="el" href="_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel_8cpp_source.xhtml#l00312">CLDepthwiseConvolutionLayer3x3NHWCKernel::validate()</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="_c_l_depthwise_convolution_layer_8cpp_source.xhtml#l00380">CLDepthwiseConvolutionLayer::validate()</a>.</p>

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 <hr/>The documentation for this class was generated from the following files:<ul>
 <li>arm_compute/runtime/CL/functions/<a class="el" href="_c_l_depthwise_convolution_layer_8h_source.xhtml">CLDepthwiseConvolutionLayer.h</a></li>
 <li>src/runtime/CL/functions/<a class="el" href="_c_l_depthwise_convolution_layer_8cpp_source.xhtml">CLDepthwiseConvolutionLayer.cpp</a></li>
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