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<a href="#func-members">Functions</a> </div>
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<div class="title">Neural Network Pooling Functions<div class="ingroups"><a class="el" href="group__groupNN.html">Neural Network Functions</a></div></div> </div>
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</div><!--header-->
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<div class="contents">
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<table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
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Functions</h2></td></tr>
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<tr class="memitem:ga99afcdcc61eaf429ab3ee823702e44ce"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__Pooling.html#ga99afcdcc61eaf429ab3ee823702e44ce">arm_maxpool_q7_HWC</a> (q7_t *Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const uint16_t dim_im_out, q7_t *bufferA, q7_t *Im_out)</td></tr>
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<tr class="memdesc:ga99afcdcc61eaf429ab3ee823702e44ce"><td class="mdescLeft"> </td><td class="mdescRight">Q7 max pooling function. <a href="#ga99afcdcc61eaf429ab3ee823702e44ce">More...</a><br/></td></tr>
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<tr class="separator:ga99afcdcc61eaf429ab3ee823702e44ce"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:gae4a7b07f97ec4313524c9fb9fbcb1f6a"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="group__Pooling.html#gae4a7b07f97ec4313524c9fb9fbcb1f6a">arm_avepool_q7_HWC</a> (q7_t *Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const uint16_t dim_im_out, q7_t *bufferA, q7_t *Im_out)</td></tr>
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<tr class="memdesc:gae4a7b07f97ec4313524c9fb9fbcb1f6a"><td class="mdescLeft"> </td><td class="mdescRight">Q7 average pooling function. <a href="#gae4a7b07f97ec4313524c9fb9fbcb1f6a">More...</a><br/></td></tr>
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<tr class="separator:gae4a7b07f97ec4313524c9fb9fbcb1f6a"><td class="memSeparator" colspan="2"> </td></tr>
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</table>
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<a name="details" id="details"></a><h2 class="groupheader">Description</h2>
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<p>Perform pooling functions, including max pooling and average pooling </p>
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<h2 class="groupheader">Function Documentation</h2>
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<a class="anchor" id="gae4a7b07f97ec4313524c9fb9fbcb1f6a"></a>
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<div class="memitem">
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<div class="memproto">
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<table class="memname">
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<tr>
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<td class="memname">void arm_avepool_q7_HWC </td>
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<td>(</td>
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<td class="paramtype">q7_t * </td>
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<td class="paramname"><em>Im_in</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>dim_im_in</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>ch_im_in</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>dim_kernel</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>padding</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>stride</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>dim_im_out</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">q7_t * </td>
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<td class="paramname"><em>bufferA</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">q7_t * </td>
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<td class="paramname"><em>Im_out</em> </td>
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</tr>
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<tr>
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<td></td>
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<td>)</td>
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<td></td><td></td>
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</tr>
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</table>
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</div><div class="memdoc">
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramdir">[in,out]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr>
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<tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr>
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<tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr>
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</table>
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</dd>
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</dl>
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<dl class="section return"><dt>Returns</dt><dd>none.</dd></dl>
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<p><b>Buffer size:</b></p>
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<p>bufferA size: 2*dim_im_out*ch_im_in</p>
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<p>The pooling function is implemented as split x-pooling then y-pooling.</p>
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<p>This pooling function is input-destructive. Input data is undefined after calling this function. </p>
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<p>References <a class="el" href="group__nndata__convert.html#gae349de4dba8d253c89d45794ccf05680">arm_q7_to_q15_no_shift()</a>.</p>
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</div>
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</div>
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<a class="anchor" id="ga99afcdcc61eaf429ab3ee823702e44ce"></a>
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<div class="memitem">
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<div class="memproto">
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<table class="memname">
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<tr>
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<td class="memname">void arm_maxpool_q7_HWC </td>
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<td>(</td>
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<td class="paramtype">q7_t * </td>
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<td class="paramname"><em>Im_in</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>dim_im_in</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>ch_im_in</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>dim_kernel</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>padding</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>stride</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const uint16_t </td>
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<td class="paramname"><em>dim_im_out</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">q7_t * </td>
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<td class="paramname"><em>bufferA</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">q7_t * </td>
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<td class="paramname"><em>Im_out</em> </td>
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</tr>
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<tr>
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<td></td>
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<td>)</td>
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<td></td><td></td>
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</tr>
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</table>
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</div><div class="memdoc">
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramdir">[in,out]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr>
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<tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr>
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<tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr>
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<tr><td class="paramdir">[in,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr>
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</table>
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</dd>
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</dl>
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<dl class="section return"><dt>Returns</dt><dd>none.</dd></dl>
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<p><b>Buffer size:</b></p>
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<p>bufferA size: 0</p>
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<p>The pooling function is implemented as split x-pooling then y-pooling.</p>
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<p>This pooling function is input-destructive. Input data is undefined after calling this function. </p>
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<p>Referenced by <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main()</a>.</p>
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