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<div class="title">CLConvolutionSquare&lt; matrix_size &gt; Class Template Reference</div> </div>
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<p>Basic function to execute square convolution.Currently it supports 5x5, 7x7, 9x9.
<a href="classarm__compute_1_1_c_l_convolution_square.xhtml#details">More...</a></p>
<p><code>#include &lt;<a class="el" href="_c_l_convolution_8h_source.xhtml">CLConvolution.h</a>&gt;</code></p>
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Collaboration diagram for CLConvolutionSquare&lt; matrix_size &gt;:</div>
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Public Member Functions</h2></td></tr>
<tr class="memitem:af1fdf57638e930af4a602f3a8393ccc4"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_convolution_square.xhtml#af1fdf57638e930af4a602f3a8393ccc4">CLConvolutionSquare</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:af1fdf57638e930af4a602f3a8393ccc4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default constructor. <a href="#af1fdf57638e930af4a602f3a8393ccc4">More...</a><br/></td></tr>
<tr class="separator:af1fdf57638e930af4a602f3a8393ccc4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a26e1b4686b1f2d591d62d11585114a82"><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_convolution_square.xhtml#a26e1b4686b1f2d591d62d11585114a82">configure</a> (<a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input, <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *output, const int16_t *conv, uint32_t scale, <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> border_mode, uint8_t constant_border_value=0)</td></tr>
<tr class="memdesc:a26e1b4686b1f2d591d62d11585114a82"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initialize the function's source, destination, conv and border_mode. <a href="#a26e1b4686b1f2d591d62d11585114a82">More...</a><br/></td></tr>
<tr class="separator:a26e1b4686b1f2d591d62d11585114a82"><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_convolution_square.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>
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<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="#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">More...</a><br/></td></tr>
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</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><h3>template&lt;unsigned int matrix_size&gt;<br/>
class arm_compute::CLConvolutionSquare&lt; matrix_size &gt;</h3>
<p>Basic function to execute square convolution.Currently it supports 5x5, 7x7, 9x9. </p>
<p>This function calls the following OpenCL kernels:</p>
<ol type="1">
<li><a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml">CLFillBorderKernel</a> (executed if border_mode == CONSTANT or border_mode == REPLICATE)</li>
<li><a class="el" href="classarm__compute_1_1_c_l_convolution_kernel.xhtml">CLConvolutionKernel</a> or<br/>
<a class="el" href="classarm__compute_1_1_c_l_separable_convolution_hor_kernel.xhtml">CLSeparableConvolutionHorKernel</a> and <a class="el" href="classarm__compute_1_1_c_l_separable_convolution_vert_kernel.xhtml">CLSeparableConvolutionVertKernel</a> (if convolution matrix is separable) </li>
</ol>
<p>Definition at line <a class="el" href="_c_l_convolution_8h_source.xhtml#l00072">72</a> of file <a class="el" href="_c_l_convolution_8h_source.xhtml">CLConvolution.h</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
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<td class="memname"><a class="el" href="classarm__compute_1_1_c_l_convolution_square.xhtml">CLConvolutionSquare</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>
</table>
</div><div class="memdoc">
<p>Default constructor. </p>
</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
<a class="anchor" id="a26e1b4686b1f2d591d62d11585114a82"></a>
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<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"><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 int16_t *&#160;</td>
<td class="paramname"><em>conv</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">uint32_t&#160;</td>
<td class="paramname"><em>scale</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a>&#160;</td>
<td class="paramname"><em>border_mode</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">uint8_t&#160;</td>
<td class="paramname"><em>constant_border_value</em> = <code>0</code>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
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<p>Initialize the function's source, destination, conv and border_mode. </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 types supported: U8. (Written to only for <code>border_mode</code> != UNDEFINED) </td></tr>
<tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor, Data types supported: U8 or S16. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">conv</td><td>matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">scale</td><td>Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">border_mode</td><td>Strategy to use for borders. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">constant_border_value</td><td>(Optional) Constant value to use for borders if border_mode is set to CONSTANT. </td></tr>
</table>
</dd>
</dl>
<p>Referenced by <a class="el" href="cl__convolution_8cpp_source.xhtml#l00056">main_cl_convolution()</a>.</p>
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<td class="memname">void run </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
<td></td>
</tr>
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</td>
<td class="mlabels-right">
<span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td>
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</div><div class="memdoc">
<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></dl>
<p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p>
<p>Referenced by <a class="el" href="cl__convolution_8cpp_source.xhtml#l00056">main_cl_convolution()</a>.</p>
</div>
</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li>arm_compute/runtime/CL/functions/<a class="el" href="_c_l_convolution_8h_source.xhtml">CLConvolution.h</a></li>
</ul>
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