/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2017, Intel Corporation, all rights reserved. // Copyright (c) 2016-2017 Fabian David Tschopp, all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's 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. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // 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 Intel Corporation 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. // //M*/ #define CONCAT(A,B) A##_##B #define TEMPLATE(name,type) CONCAT(name,type) #if defined(cl_intel_subgroups) #pragma OPENCL EXTENSION cl_intel_subgroups : enable #endif #if defined(cl_khr_fp16) #pragma OPENCL EXTENSION cl_khr_fp16 : enable #endif __kernel void TEMPLATE(softmax_forward_slm,Dtype)(const int num, const int channels, const int spatial_dim, __global Dtype* scale, __global const Dtype* data, __global Dtype* out, __local Dtype *out_tmp, __local Dtype *scale_tmp, __local Dtype *group_tmp) { int n = get_global_id(1); for (int index = get_global_id(0), s = 0; index < spatial_dim * get_local_size(0); index += get_global_size(0), ++s) { Dtype maxval = -DTYPE_MAX; for (int c = get_global_id(0); c < channels; c += get_global_size(0)) { Dtype tmp = data[(n * channels + c) * spatial_dim + s]; maxval = max((Dtype)tmp, (Dtype)maxval); } maxval = sub_group_reduce_max(maxval); //if (get_sub_group_local_id() == 0) group_tmp[get_sub_group_id() * spatial_dim + s] = maxval; } barrier(CLK_LOCAL_MEM_FENCE); for (int index = get_global_id(0); index < spatial_dim * get_max_sub_group_size(); index += get_global_size(0)) { int s = index / get_max_sub_group_size(); Dtype maxval = sub_group_reduce_max(group_tmp[get_sub_group_local_id() * spatial_dim + s]); //if (get_sub_group_local_id() == 0) scale_tmp[s] = maxval; } barrier(CLK_LOCAL_MEM_FENCE); for (int index = get_global_id(0); index < channels * spatial_dim; index += get_global_size(0)) { int s = index % spatial_dim; out_tmp[index] = exp(data[n * channels * spatial_dim + index] - scale_tmp[s]); } barrier(CLK_LOCAL_MEM_FENCE); for (int index = get_global_id(0), s = 0; index < spatial_dim * get_local_size(0); index += get_global_size(0), ++s) { Dtype sum = 0; for (int c = get_global_id(0); c < channels; c += get_global_size(0)) { sum += out_tmp[c * spatial_dim + s]; } sum = sub_group_reduce_add(sum); group_tmp[get_sub_group_id() * spatial_dim + s] = sum; } barrier(CLK_LOCAL_MEM_FENCE); for (int index = get_global_id(0); index < spatial_dim * get_max_sub_group_size(); index += get_global_size(0)) { int s = index / get_max_sub_group_size(); Dtype sum = sub_group_reduce_add(group_tmp[get_sub_group_local_id() * spatial_dim + s]); //if (get_sub_group_local_id() == 0) scale_tmp[s] = sum; } barrier(CLK_LOCAL_MEM_FENCE); for (int index = get_global_id(0); index < channels * spatial_dim; index += get_global_size(0)) { int s = index % spatial_dim; Dtype v = out_tmp[index] / scale_tmp[s]; #ifdef LOG_SOFTMAX v = log(v); #endif out[n * channels * spatial_dim + index] = v; } } __kernel void TEMPLATE(softmax_forward,Dtype)(const int num, const int channels, const int spatial_dim, __global Dtype* scale, __global const Dtype* data, __global Dtype* out) { int n = get_global_id(1); __global Dtype *group_tmp = scale + spatial_dim * num + n * get_max_sub_group_size() * spatial_dim; for (int index = get_global_id(0), s = 0; index < spatial_dim * get_local_size(0); index += get_global_size(0), ++s) { Dtype maxval = -DTYPE_MAX; for (int c = get_global_id(0); c < channels; c += get_global_size(0)) { Dtype tmp = data[(n * channels + c) * spatial_dim + s]; maxval = max((Dtype)tmp, (Dtype)maxval); } maxval = sub_group_reduce_max(maxval); //if (get_sub_group_local_id() == 0) group_tmp[get_sub_group_id() * spatial_dim + s] = maxval; } barrier(CLK_GLOBAL_MEM_FENCE); for (int index = get_global_id(0); index < spatial_dim * get_max_sub_group_size(); index += get_global_size(0)) { int s = index / get_max_sub_group_size(); Dtype maxval = sub_group_reduce_max(group_tmp[get_sub_group_local_id() * spatial_dim + s]); //if (get_sub_group_local_id() == 0) scale[n * spatial_dim + s] = maxval; } barrier(CLK_GLOBAL_MEM_FENCE); for (int index = get_global_id(0); index < channels * spatial_dim; index += get_global_size(0)) { int s = index % spatial_dim; out[n * channels * spatial_dim + index] = exp(data[n * channels * spatial_dim + index] - scale[n * spatial_dim + s]); } barrier(CLK_GLOBAL_MEM_FENCE); for (int index = get_global_id(0), s = 0; index < spatial_dim * get_local_size(0); index += get_global_size(0), ++s) { Dtype sum = 0; for (int c = get_global_id(0); c < channels; c += get_global_size(0)) { sum += out[n * channels * spatial_dim + c * spatial_dim + s]; } sum = sub_group_reduce_add(sum); group_tmp[get_sub_group_id() * spatial_dim + s] = sum; } barrier(CLK_GLOBAL_MEM_FENCE); for (int index = get_global_id(0); index < spatial_dim * get_max_sub_group_size(); index += get_global_size(0)) { int s = index / get_max_sub_group_size(); Dtype sum = sub_group_reduce_add(group_tmp[get_sub_group_local_id() * spatial_dim + s]); //if (get_sub_group_local_id() == 0) scale[n * spatial_dim + s] = sum; } barrier(CLK_GLOBAL_MEM_FENCE); for (int index = get_global_id(0); index < channels * spatial_dim; index += get_global_size(0)) { int s = index % spatial_dim; Dtype v = out[n * channels * spatial_dim + index] / scale[n * spatial_dim + s]; #ifdef LOG_SOFTMAX v = log(v); #endif out[n * channels * spatial_dim + index] = v; } }