/************************************************************************************* * Copyright (c) 2015, Advanced Micro Devices, Inc. * All rights reserved. * * Redistribution and use in source and binary forms, with or without modification, * are permitted provided that the following conditions are met: * * 1. Redistributions of source code must retain the above copyright notice, this * list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright notice, * this list of conditions and the following disclaimer in the documentation and/or * other materials provided with the distribution. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. * IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, * INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, * OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, * WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE * POSSIBILITY OF SUCH DAMAGE. **************************************************************************************/ __kernel void LRNComputeOutput(const int nthreads, __global T* in, __global T* scale, const T negative_beta, __global T* out) { int index = get_global_id(0); int tmp = get_global_size(0); for(index; index < nthreads; index += tmp) out[index] = in[index] * pow(scale[index], negative_beta); } __kernel void LRNFillScale(const int nthreads, __global T* in, const int num, const int channels, const int height, const int width, const int size, const T alpha_over_size, const T k, __global T* scale) { int index = get_global_id(0); int tmp = get_global_size(0); for(index; index < nthreads; index += tmp) { // find out the local offset const int w = index % width; const int h = (index / width) % height; const int n = index / width / height; const int offset = (n * channels * height + h) * width + w; const int step = height * width; in = in + offset; scale = scale + offset; int head = 0; const int pre_pad = (size - 1) / 2; const int post_pad = size - pre_pad - 1; T accum_scale = 0; // fill the scale at [n, :, h, w] // accumulate values while (head < post_pad && head < channels) { accum_scale += in[head * step] * in[head * step]; ++head; } // both add and subtract while (head < channels) { accum_scale += in[head * step] * in[head * step]; if (head - size >= 0) { accum_scale -= in[(head - size) * step] * in[(head - size) * step]; } scale[(head - post_pad) * step] = k + accum_scale * alpha_over_size; ++head; } // subtract only while (head < channels + post_pad) { if (head - size >= 0) { accum_scale -= in[(head - size) * step] * in[(head - size) * step]; } scale[(head - post_pad) * step] = k + accum_scale * alpha_over_size; ++head; } } }