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<a href="#func-members">Functions</a> </div>
<div class="headertitle">
<div class="title">Fully-connected Layer Functions<div class="ingroups"><a class="el" href="group__groupNN.html">Neural Network Functions</a></div></div> </div>
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
Functions</h2></td></tr>
<tr class="memitem:ga4a1521e7532a1e62d71f3b12762016e2"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#ga4a1521e7532a1e62d71f3b12762016e2">arm_fully_connected_mat_q7_vec_q15</a> (const q15_t *pV, const q7_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t *bias, q15_t *pOut, q15_t *vec_buffer)</td></tr>
<tr class="memdesc:ga4a1521e7532a1e62d71f3b12762016e2"><td class="mdescLeft"> </td><td class="mdescRight">Mixed Q15-Q7 fully-connected layer function. <a href="#ga4a1521e7532a1e62d71f3b12762016e2">More...</a><br/></td></tr>
<tr class="separator:ga4a1521e7532a1e62d71f3b12762016e2"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:gae3857bb6375692e81dde8cbd70adec08"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#gae3857bb6375692e81dde8cbd70adec08">arm_fully_connected_mat_q7_vec_q15_opt</a> (const q15_t *pV, const q7_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t *bias, q15_t *pOut, q15_t *vec_buffer)</td></tr>
<tr class="memdesc:gae3857bb6375692e81dde8cbd70adec08"><td class="mdescLeft"> </td><td class="mdescRight">Mixed Q15-Q7 opt fully-connected layer function. <a href="#gae3857bb6375692e81dde8cbd70adec08">More...</a><br/></td></tr>
<tr class="separator:gae3857bb6375692e81dde8cbd70adec08"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:gaac666c212b209e636c2369dd5c75d0dc"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#gaac666c212b209e636c2369dd5c75d0dc">arm_fully_connected_q15</a> (const q15_t *pV, const q15_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q15_t *bias, q15_t *pOut, q15_t *vec_buffer)</td></tr>
<tr class="memdesc:gaac666c212b209e636c2369dd5c75d0dc"><td class="mdescLeft"> </td><td class="mdescRight">Q15 opt fully-connected layer function. <a href="#gaac666c212b209e636c2369dd5c75d0dc">More...</a><br/></td></tr>
<tr class="separator:gaac666c212b209e636c2369dd5c75d0dc"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ga062912078da113f5dd2004fd919a0ff2"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#ga062912078da113f5dd2004fd919a0ff2">arm_fully_connected_q15_opt</a> (const q15_t *pV, const q15_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q15_t *bias, q15_t *pOut, q15_t *vec_buffer)</td></tr>
<tr class="memdesc:ga062912078da113f5dd2004fd919a0ff2"><td class="mdescLeft"> </td><td class="mdescRight">Q15 opt fully-connected layer function. <a href="#ga062912078da113f5dd2004fd919a0ff2">More...</a><br/></td></tr>
<tr class="separator:ga062912078da113f5dd2004fd919a0ff2"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ga8b7e0c2e989e8c75f0dc789f3115323d"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#ga8b7e0c2e989e8c75f0dc789f3115323d">arm_fully_connected_q7</a> (const q7_t *pV, const q7_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t *bias, q7_t *pOut, q15_t *vec_buffer)</td></tr>
<tr class="memdesc:ga8b7e0c2e989e8c75f0dc789f3115323d"><td class="mdescLeft"> </td><td class="mdescRight">Q7 basic fully-connected layer function. <a href="#ga8b7e0c2e989e8c75f0dc789f3115323d">More...</a><br/></td></tr>
<tr class="separator:ga8b7e0c2e989e8c75f0dc789f3115323d"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:gaf82b71ef472a38f8fc9ac414d9d07e67"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__FC.html#gaf82b71ef472a38f8fc9ac414d9d07e67">arm_fully_connected_q7_opt</a> (const q7_t *pV, const q7_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t *bias, q7_t *pOut, q15_t *vec_buffer)</td></tr>
<tr class="memdesc:gaf82b71ef472a38f8fc9ac414d9d07e67"><td class="mdescLeft"> </td><td class="mdescRight">Q7 opt fully-connected layer function. <a href="#gaf82b71ef472a38f8fc9ac414d9d07e67">More...</a><br/></td></tr>
<tr class="separator:gaf82b71ef472a38f8fc9ac414d9d07e67"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Description</h2>
<p>Perform fully-connected layer</p>
<p>Fully-connected layer is basically a matrix-vector multiplication with bias. The matrix is the weights and the input/output vectors are the activation values. Supported {weight, activation} precisions include {8-bit, 8-bit}, {16-bit, 16-bit}, and {8-bit, 16-bit}.</p>
<p>Here we have two types of kernel functions. The basic function implements the function using regular GEMV approach. The opt functions operates with weights in interleaved formats. </p>
<h2 class="groupheader">Function Documentation</h2>
<a class="anchor" id="ga4a1521e7532a1e62d71f3b12762016e2"></a>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">arm_status arm_fully_connected_mat_q7_vec_q15 </td>
<td>(</td>
<td class="paramtype">const q15_t * </td>
<td class="paramname"><em>pV</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>pM</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>dim_vec</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>num_of_rows</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>bias_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>out_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>bias</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>pOut</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>vec_buffer</em> </td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl>
<p><b>Buffer size:</b></p>
<p>vec_buffer size: 0</p>
<p>Q7_Q15 version of the fully connected layer</p>
<p>Weights are in q7_t and Activations are in q15_t </p>
<p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p>
<p>Referenced by <a class="el" href="arm__nnexamples__gru_8cpp.html#ac71a806472c7c0c284a2253e71a6a27b">gru_example()</a>.</p>
</div>
</div>
<a class="anchor" id="gae3857bb6375692e81dde8cbd70adec08"></a>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">arm_status arm_fully_connected_mat_q7_vec_q15_opt </td>
<td>(</td>
<td class="paramtype">const q15_t * </td>
<td class="paramname"><em>pV</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>pM</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>dim_vec</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>num_of_rows</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>bias_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>out_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>bias</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>pOut</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>vec_buffer</em> </td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl>
<p><b>Buffer size:</b></p>
<p>vec_buffer size: 0</p>
<p>Q7_Q15 version of the fully connected layer</p>
<p>Weights are in q7_t and Activations are in q15_t</p>
<p>Limitation: x4 version requires weight reordering to work</p>
<p>Here we use only one pointer to read 4 rows in the weight matrix. So if the original q7_t matrix looks like this:</p>
<p>| a11 | a12 | a13 | a14 | a15 | a16 | a17 |</p>
<p>| a21 | a22 | a23 | a24 | a25 | a26 | a27 |</p>
<p>| a31 | a32 | a33 | a34 | a35 | a36 | a37 |</p>
<p>| a41 | a42 | a43 | a44 | a45 | a46 | a47 |</p>
<p>| a51 | a52 | a53 | a54 | a55 | a56 | a57 |</p>
<p>| a61 | a62 | a63 | a64 | a65 | a66 | a67 |</p>
<p>We operates on multiple-of-4 rows, so the first four rows becomes</p>
<p>| a11 | a21 | a12 | a22 | a31 | a41 | a32 | a42 |</p>
<p>| a13 | a23 | a14 | a24 | a33 | a43 | a34 | a44 |</p>
<p>| a15 | a25 | a16 | a26 | a35 | a45 | a36 | a46 |</p>
<p>The column left over will be in-order. which is: | a17 | a27 | a37 | a47 |</p>
<p>For the left-over rows, we do 1x1 computation, so the data remains as its original order.</p>
<p>So the stored weight matrix looks like this:</p>
<p>| a11 | a21 | a12 | a22 | a31 | a41 |</p>
<p>| a32 | a42 | a13 | a23 | a14 | a24 |</p>
<p>| a33 | a43 | a34 | a44 | a15 | a25 |</p>
<p>| a16 | a26 | a35 | a45 | a36 | a46 |</p>
<p>| a17 | a27 | a37 | a47 | a51 | a52 |</p>
<p>| a53 | a54 | a55 | a56 | a57 | a61 |</p>
<p>| a62 | a63 | a64 | a65 | a66 | a67 | </p>
<p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p>
<p>Referenced by <a class="el" href="arm__nnexamples__gru_8cpp.html#ac71a806472c7c0c284a2253e71a6a27b">gru_example()</a>.</p>
</div>
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<a class="anchor" id="gaac666c212b209e636c2369dd5c75d0dc"></a>
<div class="memitem">
<div class="memproto">
<table class="memname">
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<td class="memname">arm_status arm_fully_connected_q15 </td>
<td>(</td>
<td class="paramtype">const q15_t * </td>
<td class="paramname"><em>pV</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q15_t * </td>
<td class="paramname"><em>pM</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>dim_vec</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>num_of_rows</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>bias_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>out_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q15_t * </td>
<td class="paramname"><em>bias</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>pOut</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>vec_buffer</em> </td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Q15 basic fully-connected layer function.</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl>
<p><b>Buffer size:</b></p>
<p>vec_buffer size: 0 </p>
<p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p>
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<td class="memname">arm_status arm_fully_connected_q15_opt </td>
<td>(</td>
<td class="paramtype">const q15_t * </td>
<td class="paramname"><em>pV</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q15_t * </td>
<td class="paramname"><em>pM</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>dim_vec</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>num_of_rows</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>bias_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>out_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q15_t * </td>
<td class="paramname"><em>bias</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>pOut</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>vec_buffer</em> </td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl>
<p><b>Buffer size:</b></p>
<p>vec_buffer size: 0</p>
<p>Here we use only one pointer to read 4 rows in the weight matrix. So if the original matrix looks like this:</p>
<p>| a11 | a12 | a13 |</p>
<p>| a21 | a22 | a23 |</p>
<p>| a31 | a32 | a33 |</p>
<p>| a41 | a42 | a43 |</p>
<p>| a51 | a52 | a53 |</p>
<p>| a61 | a62 | a63 |</p>
<p>We operates on multiple-of-4 rows, so the first four rows becomes</p>
<p>| a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |</p>
<p>| a13 | a23 | a33 | a43 |</p>
<p>Remaining rows are kept the same original order.</p>
<p>So the stored weight matrix looks like this:</p>
<p>| a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |</p>
<p>| a13 | a23 | a33 | a43 | a51 | a52 | a53 | a61 |</p>
<p>| a62 | a63 | </p>
<p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p>
</div>
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<a class="anchor" id="ga8b7e0c2e989e8c75f0dc789f3115323d"></a>
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<td class="memname">arm_status arm_fully_connected_q7 </td>
<td>(</td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>pV</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>pM</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>dim_vec</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>num_of_rows</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>bias_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>out_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>bias</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q7_t * </td>
<td class="paramname"><em>pOut</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>vec_buffer</em> </td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl>
<p><b>Buffer size:</b></p>
<p>vec_buffer size: dim_vec</p>
<p>This basic function is designed to work with regular weight matrix without interleaving. </p>
<p>References <a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_q7_to_q15_reordered_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p>
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<td class="memname">arm_status arm_fully_connected_q7_opt </td>
<td>(</td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>pV</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>pM</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>dim_vec</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>num_of_rows</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>bias_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const uint16_t </td>
<td class="paramname"><em>out_shift</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const q7_t * </td>
<td class="paramname"><em>bias</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q7_t * </td>
<td class="paramname"><em>pOut</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">q15_t * </td>
<td class="paramname"><em>vec_buffer</em> </td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">pV</td><td>pointer to input vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">pM</td><td>pointer to matrix weights </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">dim_vec</td><td>length of the vector </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">num_of_rows</td><td>number of rows in weight matrix </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias_shift</td><td>amount of left-shift for bias </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">out_shift</td><td>amount of right-shift for output </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">pOut</td><td>pointer to output vector </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">vec_buffer</td><td>pointer to buffer space for input </td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code></dd></dl>
<p><b>Buffer size:</b></p>
<p>vec_buffer size: dim_vec</p>
<p>This opt function is designed to work with interleaved weight matrix. The vector input is assumed in q7_t format, we call arm_q7_to_q15_no_shift_shuffle function to expand into q15_t format with certain weight re-ordering, refer to the function comments for more details. Here we use only one pointer to read 4 rows in the weight matrix. So if the original q7_t matrix looks like this:</p>
<p>| a11 | a12 | a13 | a14 | a15 | a16 | a17 |</p>
<p>| a21 | a22 | a23 | a24 | a25 | a26 | a27 |</p>
<p>| a31 | a32 | a33 | a34 | a35 | a36 | a37 |</p>
<p>| a41 | a42 | a43 | a44 | a45 | a46 | a47 |</p>
<p>| a51 | a52 | a53 | a54 | a55 | a56 | a57 |</p>
<p>| a61 | a62 | a63 | a64 | a65 | a66 | a67 |</p>
<p>We operates on multiple-of-4 rows, so the first four rows becomes</p>
<p>| a11 | a21 | a13 | a23 | a31 | a41 | a33 | a43 |</p>
<p>| a12 | a22 | a14 | a24 | a32 | a42 | a34 | a44 |</p>
<p>| a15 | a25 | a35 | a45 | a16 | a26 | a36 | a46 |</p>
<p>So within the kernel, we first read the re-ordered vector in as:</p>
<p>| b1 | b3 | and | b2 | b4 |</p>
<p>the four q31_t weights will look like</p>
<p>| a11 | a13 |, | a21 | a23 |, | a31 | a33 |, | a41 | a43 |</p>
<p>| a12 | a14 |, | a22 | a24 |, | a32 | a34 |, | a42 | a44 |</p>
<p>The column left over will be in-order. which is:</p>
<p>| a17 | a27 | a37 | a47 |</p>
<p>For the left-over rows, we do 1x1 computation, so the data remains as its original order.</p>
<p>So the stored weight matrix looks like this:</p>
<p>| a11 | a21 | a13 | a23 | a31 | a41 |</p>
<p>| a33 | a43 | a12 | a22 | a14 | a24 |</p>
<p>| a32 | a42 | a34 | a44 | a15 | a25 |</p>
<p>| a35 | a45 | a16 | a26 | a36 | a46 |</p>
<p>| a17 | a27 | a37 | a47 | a51 | a52 |</p>
<p>| a53 | a54 | a55 | a56 | a57 | a61 |</p>
<p>| a62 | a63 | a64 | a65 | a66 | a67 | </p>
<p>References <a class="el" href="group__nndata__convert.html#gaba8fd446d5f54760b406ee63b25d1aee">arm_q7_to_q15_reordered_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p>
<p>Referenced by <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main()</a>.</p>
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