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| author | Ali Labbene <ali.labbene@st.com> | 2019-12-11 08:59:21 +0100 |
|---|---|---|
| committer | Ali Labbene <ali.labbene@st.com> | 2019-12-16 16:35:24 +0100 |
| commit | 9f95ff5b6ba01db09552b84a0ab79607060a2666 (patch) | |
| tree | 8a6e0dda832555c692307869aed49d07ee7facfe /docs/NN/html/group__NNConv.html | |
| parent | 76177aa280494bb36d7a0bcbda1078d4db717020 (diff) | |
| download | st-cmsis-core-lowfat-9f95ff5b6ba01db09552b84a0ab79607060a2666.tar.gz st-cmsis-core-lowfat-9f95ff5b6ba01db09552b84a0ab79607060a2666.tar.bz2 st-cmsis-core-lowfat-9f95ff5b6ba01db09552b84a0ab79607060a2666.zip | |
Official ARM version: v5.4.0
Add CMSIS V5.4.0, please refer to index.html available under \docs folder.
Note: content of \CMSIS\Core\Include has been copied under \Include to keep the same structure
used in existing projects, and thus avoid projects mass update
Note: the following components have been removed from ARM original delivery (as not used in ST packages)
- CMSIS_EW2018.pdf
- .gitattributes
- .gitignore
- \Device
- \CMSIS
- \CoreValidation
- \DAP
- \Documentation
- \DoxyGen
- \Driver
- \Pack
- \RTOS\CMSIS_RTOS_Tutorial.pdf
- \RTOS\RTX
- \RTOS\Template
- \RTOS2\RTX
- \Utilities
- All ARM/GCC projects files are deleted from \DSP, \RTOS and \RTOS2
Change-Id: Ia026c3f0f0d016627a4fb5a9032852c33d24b4d3
Diffstat (limited to 'docs/NN/html/group__NNConv.html')
| -rw-r--r-- | docs/NN/html/group__NNConv.html | 1796 |
1 files changed, 1796 insertions, 0 deletions
diff --git a/docs/NN/html/group__NNConv.html b/docs/NN/html/group__NNConv.html new file mode 100644 index 0000000..b7f1ff6 --- /dev/null +++ b/docs/NN/html/group__NNConv.html @@ -0,0 +1,1796 @@ +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<title>Neural Network Convolution Functions</title> +<title>CMSIS-NN: Neural Network Convolution Functions</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<link href="cmsis.css" rel="stylesheet" type="text/css" /> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<script type="text/javascript" src="printComponentTabs.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script 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onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Data Structures</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span 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class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> +Functions</h2></td></tr> +<tr class="memitem:ga110adcfdaab356c750c6270aa5e05f29"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga110adcfdaab356c750c6270aa5e05f29">arm_convolve_1x1_HWC_q7_fast_nonsquare</a> (const q7_t *Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q7_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q7_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t *Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:ga110adcfdaab356c750c6270aa5e05f29"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q7 version of 1x1 convolution (non-sqaure shape) <a href="#ga110adcfdaab356c750c6270aa5e05f29">More...</a><br/></td></tr> +<tr class="separator:ga110adcfdaab356c750c6270aa5e05f29"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ga55701f213b198084b52eab53097f1f58"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga55701f213b198084b52eab53097f1f58">arm_convolve_HWC_q15_basic</a> (const q15_t *Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q15_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q15_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q15_t *Im_out, const uint16_t dim_im_out, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:ga55701f213b198084b52eab53097f1f58"><td class="mdescLeft"> </td><td class="mdescRight">Basic Q15 convolution function. <a href="#ga55701f213b198084b52eab53097f1f58">More...</a><br/></td></tr> +<tr class="separator:ga55701f213b198084b52eab53097f1f58"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ga4efb1ccbbaa7dd936961989dcb443f50"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga4efb1ccbbaa7dd936961989dcb443f50">arm_convolve_HWC_q15_fast</a> (const q15_t *Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q15_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q15_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q15_t *Im_out, const uint16_t dim_im_out, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:ga4efb1ccbbaa7dd936961989dcb443f50"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q15 convolution function. <a href="#ga4efb1ccbbaa7dd936961989dcb443f50">More...</a><br/></td></tr> +<tr class="separator:ga4efb1ccbbaa7dd936961989dcb443f50"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ga614ec3b71eb96e29952ec3f09e7b9c3c"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga614ec3b71eb96e29952ec3f09e7b9c3c">arm_convolve_HWC_q15_fast_nonsquare</a> (const q15_t *Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q15_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q15_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q15_t *Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:ga614ec3b71eb96e29952ec3f09e7b9c3c"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q15 convolution function (non-sqaure shape) <a href="#ga614ec3b71eb96e29952ec3f09e7b9c3c">More...</a><br/></td></tr> +<tr class="separator:ga614ec3b71eb96e29952ec3f09e7b9c3c"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ga210ae8d8fc1d12ee15b41f1fa6947681"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga210ae8d8fc1d12ee15b41f1fa6947681">arm_convolve_HWC_q7_basic</a> (const q7_t *Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q7_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q7_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t *Im_out, const uint16_t dim_im_out, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:ga210ae8d8fc1d12ee15b41f1fa6947681"><td class="mdescLeft"> </td><td class="mdescRight">Basic Q7 convolution function. <a href="#ga210ae8d8fc1d12ee15b41f1fa6947681">More...</a><br/></td></tr> +<tr class="separator:ga210ae8d8fc1d12ee15b41f1fa6947681"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ga4501fa22c0836002aa47ccc313dce252"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga4501fa22c0836002aa47ccc313dce252">arm_convolve_HWC_q7_basic_nonsquare</a> (const q7_t *Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q7_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q7_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t *Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:ga4501fa22c0836002aa47ccc313dce252"><td class="mdescLeft"> </td><td class="mdescRight">Basic Q7 convolution function (non-sqaure shape) <a href="#ga4501fa22c0836002aa47ccc313dce252">More...</a><br/></td></tr> +<tr class="separator:ga4501fa22c0836002aa47ccc313dce252"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:gae00d3c1285907d59657369fc98bcc83f"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#gae00d3c1285907d59657369fc98bcc83f">arm_convolve_HWC_q7_fast</a> (const q7_t *Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q7_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q7_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t *Im_out, const uint16_t dim_im_out, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:gae00d3c1285907d59657369fc98bcc83f"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q7 convolution function. <a href="#gae00d3c1285907d59657369fc98bcc83f">More...</a><br/></td></tr> +<tr class="separator:gae00d3c1285907d59657369fc98bcc83f"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:gabc6d6b991024e9e5c5cdbd7489de88ef"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#gabc6d6b991024e9e5c5cdbd7489de88ef">arm_convolve_HWC_q7_fast_nonsquare</a> (const q7_t *Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q7_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q7_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t *Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:gabc6d6b991024e9e5c5cdbd7489de88ef"><td class="mdescLeft"> </td><td class="mdescRight">Fast Q7 convolution function (non-sqaure shape) <a href="#gabc6d6b991024e9e5c5cdbd7489de88ef">More...</a><br/></td></tr> +<tr class="separator:gabc6d6b991024e9e5c5cdbd7489de88ef"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ga98f2ead67d7cbdf558b0cd8a3b8fc148"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga98f2ead67d7cbdf558b0cd8a3b8fc148">arm_convolve_HWC_q7_RGB</a> (const q7_t *Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q7_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q7_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t *Im_out, const uint16_t dim_im_out, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:ga98f2ead67d7cbdf558b0cd8a3b8fc148"><td class="mdescLeft"> </td><td class="mdescRight">Q7 convolution function for RGB image. <a href="#ga98f2ead67d7cbdf558b0cd8a3b8fc148">More...</a><br/></td></tr> +<tr class="separator:ga98f2ead67d7cbdf558b0cd8a3b8fc148"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:gad3d21b3bc6dbd6f3b97d01104349cb0a"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#gad3d21b3bc6dbd6f3b97d01104349cb0a">arm_depthwise_separable_conv_HWC_q7</a> (const q7_t *Im_in, const uint16_t dim_im_in, const uint16_t ch_im_in, const q7_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel, const uint16_t padding, const uint16_t stride, const q7_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t *Im_out, const uint16_t dim_im_out, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:gad3d21b3bc6dbd6f3b97d01104349cb0a"><td class="mdescLeft"> </td><td class="mdescRight">Q7 depthwise separable convolution function. <a href="#gad3d21b3bc6dbd6f3b97d01104349cb0a">More...</a><br/></td></tr> +<tr class="separator:gad3d21b3bc6dbd6f3b97d01104349cb0a"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ga32ac508c5467813a84f74f96655dc697"><td class="memItemLeft" align="right" valign="top">arm_status </td><td class="memItemRight" valign="bottom"><a class="el" href="group__NNConv.html#ga32ac508c5467813a84f74f96655dc697">arm_depthwise_separable_conv_HWC_q7_nonsquare</a> (const q7_t *Im_in, const uint16_t dim_im_in_x, const uint16_t dim_im_in_y, const uint16_t ch_im_in, const q7_t *wt, const uint16_t ch_im_out, const uint16_t dim_kernel_x, const uint16_t dim_kernel_y, const uint16_t padding_x, const uint16_t padding_y, const uint16_t stride_x, const uint16_t stride_y, const q7_t *bias, const uint16_t bias_shift, const uint16_t out_shift, q7_t *Im_out, const uint16_t dim_im_out_x, const uint16_t dim_im_out_y, q15_t *bufferA, q7_t *bufferB)</td></tr> +<tr class="memdesc:ga32ac508c5467813a84f74f96655dc697"><td class="mdescLeft"> </td><td class="mdescRight">Q7 depthwise separable convolution function (non-square shape) <a href="#ga32ac508c5467813a84f74f96655dc697">More...</a><br/></td></tr> +<tr class="separator:ga32ac508c5467813a84f74f96655dc697"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<a name="details" id="details"></a><h2 class="groupheader">Description</h2> +<p>Perform convolution layer</p> +<p>The convolution is implemented in 2 steps: im2col and GEMM</p> +<p>im2col is a process of converting each patch of image data into a column. After im2col, the convolution is computed as matrix-matrix multiplication.</p> +<p>To reduce the memory footprint, the im2col is performed partially. Each iteration, only a few column (i.e., patches) are generated and computed with GEMM kernels similar to CMSIS-DSP arm_mat_mult functions. </p> +<h2 class="groupheader">Function Documentation</h2> +<a class="anchor" id="ga110adcfdaab356c750c6270aa5e05f29"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_convolve_1x1_HWC_q7_fast_nonsquare </td> + <td>(</td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_y</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">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">q7_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding size x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding size y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> + </table> + </dd> +</dl> +<dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> +<p>This function is optimized for convolution with 1x1 kernel size (i.e., dim_kernel_x=1 and dim_kernel_y=1). It can be used for the second half of MobileNets [1] after depthwise separable convolution.</p> +<p>This function is the version with full list of optimization tricks, but with some contraints: ch_im_in is multiple of 4 ch_im_out is multiple of 2</p> +<p>[1] MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications <a href="https://arxiv.org/abs/1704.04861">https://arxiv.org/abs/1704.04861</a> </p> + +<p>References <a class="el" href="arm__nnfunctions_8h.html#aefe9c7ce9a65060a244b06dffe74c4b3">arm_nn_mat_mult_kernel_q7_q15_reordered()</a>, <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> + +</div> +</div> +<a class="anchor" id="ga55701f213b198084b52eab53097f1f58"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_convolve_HWC_q15_basic </td> + <td>(</td> + <td class="paramtype">const q15_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q15_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride</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">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">q15_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </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>bufferA size: ch_im_in*dim_kernel*dim_kernel</p> +<p>bufferB size: 0</p> +<p>This basic version is designed to work for any input tensor and weight dimension. </p> + +<p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> + +</div> +</div> +<a class="anchor" id="ga4efb1ccbbaa7dd936961989dcb443f50"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_convolve_HWC_q15_fast </td> + <td>(</td> + <td class="paramtype">const q15_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q15_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride</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">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">q15_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> + </table> + </dd> +</dl> +<dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> +<p><b>Buffer size:</b></p> +<p>bufferA size: 2*ch_im_in*dim_kernel*dim_kernel</p> +<p>bufferB size: 0</p> +<p><b>Input dimension constraints:</b></p> +<p>ch_im_in is multiple of 2</p> +<p>ch_im_out is multipe of 2 </p> + +<p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> + +</div> +</div> +<a class="anchor" id="ga614ec3b71eb96e29952ec3f09e7b9c3c"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_convolve_HWC_q15_fast_nonsquare </td> + <td>(</td> + <td class="paramtype">const q15_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q15_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_y</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">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">q15_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding size x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding size y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> + </table> + </dd> +</dl> +<dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> +<p><b>Buffer size:</b></p> +<p>bufferA size: 2*ch_im_in*dim_kernel*dim_kernel</p> +<p>bufferB size: 0</p> +<p><b>Input dimension constraints:</b></p> +<p>ch_im_in is multiple of 2</p> +<p>ch_im_out is multipe of 2 </p> + +<p>References <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> + +</div> +</div> +<a class="anchor" id="ga210ae8d8fc1d12ee15b41f1fa6947681"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_convolve_HWC_q7_basic </td> + <td>(</td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride</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">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">q7_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </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>bufferA size: 2*ch_im_in*dim_kernel*dim_kernel</p> +<p>bufferB size: 0</p> +<p>This basic version is designed to work for any input tensor and weight dimension. </p> + +<p>References <a class="el" href="arm__nnfunctions_8h.html#abc4fb258cfe8500ee68e812a293a80a3">arm_nn_mat_mult_kernel_q7_q15()</a>, <a class="el" href="group__nndata__convert.html#gae349de4dba8d253c89d45794ccf05680">arm_q7_to_q15_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> + +</div> +</div> +<a class="anchor" id="ga4501fa22c0836002aa47ccc313dce252"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_convolve_HWC_q7_basic_nonsquare </td> + <td>(</td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_y</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">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">q7_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding size x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding size y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> + </table> + </dd> +</dl> +<dl class="section return"><dt>Returns</dt><dd>The function returns <code>ARM_MATH_SUCCESS</code> </dd></dl> + +<p>References <a class="el" href="arm__nnfunctions_8h.html#abc4fb258cfe8500ee68e812a293a80a3">arm_nn_mat_mult_kernel_q7_q15()</a>, <a class="el" href="group__nndata__convert.html#gae349de4dba8d253c89d45794ccf05680">arm_q7_to_q15_no_shift()</a>, and <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>.</p> + +</div> +</div> +<a class="anchor" id="gae00d3c1285907d59657369fc98bcc83f"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_convolve_HWC_q7_fast </td> + <td>(</td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride</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">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">q7_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> + </table> + </dd> +</dl> +<dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> +<p><b>Buffer size:</b></p> +<p>bufferA size: 2*ch_im_in*dim_kernel*dim_kernel</p> +<p>bufferB size: 0</p> +<p><b>Input dimension constraints:</b></p> +<p>ch_im_in is multiple of 4 ( because of the SIMD32 read and swap )</p> +<p>ch_im_out is multipe of 2 ( bacause 2x2 mat_mult kernel )</p> +<p>The im2col converts the Q7 tensor input into Q15 column, which is stored in bufferA. There is reordering happenning during this im2col process with arm_q7_to_q15_reordered_no_shift. For every four elements, the second and third elements are swapped.</p> +<p>The computation kernel arm_nn_mat_mult_kernel_q7_q15_reordered does the GEMM computation with the reordered columns.</p> +<p>To speed-up the determination of the padding condition, we split the computation into 3x3 parts, i.e., {top, mid, bottom} X {left, mid, right}. This reduces the total number of boundary condition checks and improves the data copying performance. </p> + +<p>References <a class="el" href="arm__nnfunctions_8h.html#aefe9c7ce9a65060a244b06dffe74c4b3">arm_nn_mat_mult_kernel_q7_q15_reordered()</a>, <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> + +</div> +</div> +<a class="anchor" id="gabc6d6b991024e9e5c5cdbd7489de88ef"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_convolve_HWC_q7_fast_nonsquare </td> + <td>(</td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_y</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">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">q7_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding size x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding size y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> + </table> + </dd> +</dl> +<dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> +<p>This function is the version with full list of optimization tricks, but with some contraints: ch_im_in is multiple of 4 ch_im_out is multiple of 2 </p> + +<p>References <a class="el" href="arm__nnfunctions_8h.html#aefe9c7ce9a65060a244b06dffe74c4b3">arm_nn_mat_mult_kernel_q7_q15_reordered()</a>, <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> + +</div> +</div> +<a class="anchor" id="ga98f2ead67d7cbdf558b0cd8a3b8fc148"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_convolve_HWC_q7_RGB </td> + <td>(</td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride</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">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">q7_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> +<p>Q7 version of convolution for RGB image.</p> +<dl class="params"><dt>Parameters</dt><dd> + <table class="params"> + <tr><td class="paramdir">[in]</td><td class="paramname">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> + </table> + </dd> +</dl> +<dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> +<p><b>Buffer size:</b></p> +<p>bufferA size: 2*ch_im_in*dim_kernel*dim_kernel</p> +<p>bufferB size: 0</p> +<p><b>Input dimension constraints:</b></p> +<p>ch_im_in equals 3</p> +<p>This kernel is written exclusively for convolution with ch_im_in equals 3. This applies on the first layer of CNNs which has input image with RGB format. </p> + +<p>References <a class="el" href="arm__nnfunctions_8h.html#abc4fb258cfe8500ee68e812a293a80a3">arm_nn_mat_mult_kernel_q7_q15()</a>, <a class="el" href="unionarm__nnword.html#a9b5e49e4e2c4b7203e07b305386bb2ba">arm_nnword::half_words</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>, and <a class="el" href="unionarm__nnword.html#a35c7b2ae25e35e0ddcd9ec0a1a6f8d18">arm_nnword::word</a>.</p> + +<p>Referenced by <a class="el" href="arm__nnexamples__cifar10_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main()</a>.</p> + +</div> +</div> +<a class="anchor" id="gad3d21b3bc6dbd6f3b97d01104349cb0a"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_depthwise_separable_conv_HWC_q7 </td> + <td>(</td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride</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">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">q7_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in</td><td>input tensor dimention </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel</td><td>filter kernel size </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding</td><td>padding sizes </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride</td><td>convolution stride </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out</td><td>output tensor dimension </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> + </table> + </dd> +</dl> +<dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> +<p><b>Buffer size:</b></p> +<p>bufferA size: 2*ch_im_in*dim_kernel*dim_kernel</p> +<p>bufferB size: 0</p> +<p><b>Input dimension constraints:</b></p> +<p>ch_im_in equals ch_im_out</p> +<p>Implementation: There are 3 nested loop here: Inner loop: calculate each output value with MAC instruction over an accumulator Mid loop: loop over different output channel Outer loop: loop over different output (x, y) </p> + +<p>References <a class="el" href="unionarm__nnword.html#ac7cff6480a8e29d95f29b73cb1267249">arm_nnword::bytes</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>, and <a class="el" href="unionarm__nnword.html#a35c7b2ae25e35e0ddcd9ec0a1a6f8d18">arm_nnword::word</a>.</p> + +</div> +</div> +<a class="anchor" id="ga32ac508c5467813a84f74f96655dc697"></a> +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">arm_status arm_depthwise_separable_conv_HWC_q7_nonsquare </td> + <td>(</td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>Im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_in_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_in</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const q7_t * </td> + <td class="paramname"><em>wt</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>ch_im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_kernel_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>padding_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>stride_y</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">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">q7_t * </td> + <td class="paramname"><em>Im_out</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_x</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const uint16_t </td> + <td class="paramname"><em>dim_im_out_y</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q15_t * </td> + <td class="paramname"><em>bufferA</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">q7_t * </td> + <td class="paramname"><em>bufferB</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">Im_in</td><td>pointer to input tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_x</td><td>input tensor dimention x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_in_y</td><td>input tensor dimention y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_in</td><td>number of input tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">wt</td><td>pointer to kernel weights </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">ch_im_out</td><td>number of filters, i.e., output tensor channels </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_x</td><td>filter kernel size x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_kernel_y</td><td>filter kernel size y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_x</td><td>padding sizes x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">padding_y</td><td>padding sizes y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_x</td><td>convolution stride x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">stride_y</td><td>convolution stride y </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>pointer to bias </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,out]</td><td class="paramname">Im_out</td><td>pointer to output tensor </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_x</td><td>output tensor dimension x </td></tr> + <tr><td class="paramdir">[in]</td><td class="paramname">dim_im_out_y</td><td>output tensor dimension y </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferA</td><td>pointer to buffer space for input </td></tr> + <tr><td class="paramdir">[in,out]</td><td class="paramname">bufferB</td><td>pointer to buffer space for output </td></tr> + </table> + </dd> +</dl> +<dl class="section return"><dt>Returns</dt><dd>The function returns either <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.</dd></dl> +<p>This function is the version with full list of optimization tricks, but with some contraints: ch_im_in is multiple of 2 ch_im_out is multiple of 2 </p> + +<p>References <a class="el" href="unionarm__nnword.html#ac7cff6480a8e29d95f29b73cb1267249">arm_nnword::bytes</a>, <a class="el" href="arm__nnsupportfunctions_8h.html#a4cbd428a2b4a4f6b2a6e4219520c7ce0">NN_ROUND</a>, and <a class="el" href="unionarm__nnword.html#a35c7b2ae25e35e0ddcd9ec0a1a6f8d18">arm_nnword::word</a>.</p> + +</div> +</div> +</div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="footer">Generated on Wed Aug 1 2018 17:12:32 for CMSIS-NN by Arm Ltd. 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