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Open Source Computer Vision Library
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101 lines
4.3 KiB
101 lines
4.3 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2017, Intel Corporation, all rights reserved. |
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// Copyright (c) 2016-2017 Fabian David Tschopp, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#define CONCAT(A,B) A##_##B |
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#define TEMPLATE(name,type) CONCAT(name,type) |
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#define KERNEL_ARG_DTYPE float |
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#if defined(cl_khr_fp16) |
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#pragma OPENCL EXTENSION cl_khr_fp16 : enable |
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#endif |
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__kernel void TEMPLATE(lrn_full_no_scale,Dtype)(const int nthreads, __global const Dtype* in, |
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const int num, const int channels, |
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const int height, const int width, const int size, |
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const KERNEL_ARG_DTYPE alpha_over_size, const KERNEL_ARG_DTYPE k, |
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__global Dtype* const out, |
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const KERNEL_ARG_DTYPE negative_beta) { |
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for (int index = get_global_id(0); index < nthreads; |
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index += get_global_size(0)) { |
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// find out the local offset |
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const int w = index % width; |
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const int h = (index / width) % height; |
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const int n = index / width / height; |
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const int offset = (n * channels * height + h) * width + w; |
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const int step = height * width; |
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__global const Dtype* in_off = in + offset; |
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__global Dtype* out_off = out + offset; |
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int head = 0; |
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const int pre_pad = (size - 1) / 2; |
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const int post_pad = size - pre_pad - 1; |
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float accum_scale = 0; |
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// fill the scale at [n, :, h, w] |
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// accumulate values |
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while (head < post_pad && head < channels) { |
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float v = in_off[head * step]; |
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accum_scale += v * v; |
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++head; |
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} |
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// both add and subtract |
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while (head < channels) { |
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float v = in_off[head * step]; |
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accum_scale += v * v; |
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if (head - size >= 0) { |
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v = in_off[(head - size) * step]; |
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accum_scale -= v * v; |
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} |
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float scale_val = k + accum_scale * alpha_over_size; |
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out_off[(head - post_pad) * step] = (Dtype)((float)in_off[(head - post_pad) * step] * native_powr(scale_val, negative_beta)); |
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++head; |
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} |
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// subtract only |
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while (head < channels + post_pad) { |
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if (head - size >= 0) { |
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float v = in_off[(head - size) * step]; |
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accum_scale -= v * v; |
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} |
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float scale_val = k + accum_scale * alpha_over_size; |
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out_off[(head - post_pad) * step] = (Dtype)((float)in_off[(head - post_pad) * step] * native_powr(scale_val, negative_beta)); |
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++head; |
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} |
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} |
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}
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