194 lines
7.8 KiB
Common Lisp
194 lines
7.8 KiB
Common Lisp
/*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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#if defined(cl_intel_subgroups)
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#pragma OPENCL EXTENSION cl_intel_subgroups : enable
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#endif
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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(softmax_forward_slm,Dtype)(const int num, const int channels,
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const int spatial_dim,
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__global Dtype* scale,
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__global const Dtype* data,
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__global Dtype* out,
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__local Dtype *out_tmp,
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__local Dtype *scale_tmp,
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__local Dtype *group_tmp) {
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int n = get_global_id(1);
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for (int index = get_global_id(0), s = 0; index < spatial_dim * get_local_size(0); index +=
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get_global_size(0), ++s) {
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Dtype maxval = -DTYPE_MAX;
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for (int c = get_global_id(0); c < channels; c += get_global_size(0)) {
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Dtype tmp = data[(n * channels + c) * spatial_dim + s];
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maxval = max((Dtype)tmp, (Dtype)maxval);
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}
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maxval = sub_group_reduce_max(maxval);
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//if (get_sub_group_local_id() == 0)
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group_tmp[get_sub_group_id() * spatial_dim + s] = maxval;
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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for (int index = get_global_id(0); index < spatial_dim * get_max_sub_group_size(); index +=
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get_global_size(0)) {
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int s = index / get_max_sub_group_size();
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Dtype maxval = sub_group_reduce_max(group_tmp[get_sub_group_local_id() * spatial_dim + s]);
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//if (get_sub_group_local_id() == 0)
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scale_tmp[s] = maxval;
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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for (int index = get_global_id(0); index < channels * spatial_dim;
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index += get_global_size(0)) {
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int s = index % spatial_dim;
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out_tmp[index] = exp(data[n * channels * spatial_dim + index] - scale_tmp[s]);
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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for (int index = get_global_id(0), s = 0; index < spatial_dim * get_local_size(0); index +=
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get_global_size(0), ++s) {
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Dtype sum = 0;
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for (int c = get_global_id(0); c < channels; c += get_global_size(0)) {
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sum += out_tmp[c * spatial_dim + s];
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}
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sum = sub_group_reduce_add(sum);
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group_tmp[get_sub_group_id() * spatial_dim + s] = sum;
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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for (int index = get_global_id(0); index < spatial_dim * get_max_sub_group_size(); index +=
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get_global_size(0)) {
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int s = index / get_max_sub_group_size();
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Dtype sum = sub_group_reduce_add(group_tmp[get_sub_group_local_id() * spatial_dim + s]);
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//if (get_sub_group_local_id() == 0)
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scale_tmp[s] = sum;
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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for (int index = get_global_id(0); index < channels * spatial_dim;
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index += get_global_size(0)) {
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int s = index % spatial_dim;
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Dtype v = out_tmp[index] / scale_tmp[s];
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#ifdef LOG_SOFTMAX
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v = log(v);
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#endif
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out[n * channels * spatial_dim + index] = v;
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}
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}
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__kernel void TEMPLATE(softmax_forward,Dtype)(const int num, const int channels,
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const int spatial_dim,
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__global Dtype* scale,
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__global const Dtype* data,
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__global Dtype* out) {
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int n = get_global_id(1);
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__global Dtype *group_tmp = scale + spatial_dim * num + n * get_max_sub_group_size() * spatial_dim;
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for (int index = get_global_id(0), s = 0; index < spatial_dim * get_local_size(0); index +=
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get_global_size(0), ++s) {
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Dtype maxval = -DTYPE_MAX;
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for (int c = get_global_id(0); c < channels; c += get_global_size(0)) {
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Dtype tmp = data[(n * channels + c) * spatial_dim + s];
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maxval = max((Dtype)tmp, (Dtype)maxval);
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}
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maxval = sub_group_reduce_max(maxval);
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//if (get_sub_group_local_id() == 0)
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group_tmp[get_sub_group_id() * spatial_dim + s] = maxval;
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}
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barrier(CLK_GLOBAL_MEM_FENCE);
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for (int index = get_global_id(0); index < spatial_dim * get_max_sub_group_size(); index +=
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get_global_size(0)) {
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int s = index / get_max_sub_group_size();
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Dtype maxval = sub_group_reduce_max(group_tmp[get_sub_group_local_id() * spatial_dim + s]);
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//if (get_sub_group_local_id() == 0)
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scale[n * spatial_dim + s] = maxval;
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}
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barrier(CLK_GLOBAL_MEM_FENCE);
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for (int index = get_global_id(0); index < channels * spatial_dim;
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index += get_global_size(0)) {
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int s = index % spatial_dim;
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out[n * channels * spatial_dim + index] = exp(data[n * channels * spatial_dim + index] - scale[n * spatial_dim + s]);
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}
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barrier(CLK_GLOBAL_MEM_FENCE);
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for (int index = get_global_id(0), s = 0; index < spatial_dim * get_local_size(0); index +=
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get_global_size(0), ++s) {
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Dtype sum = 0;
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for (int c = get_global_id(0); c < channels; c += get_global_size(0)) {
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sum += out[n * channels * spatial_dim + c * spatial_dim + s];
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}
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sum = sub_group_reduce_add(sum);
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group_tmp[get_sub_group_id() * spatial_dim + s] = sum;
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}
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barrier(CLK_GLOBAL_MEM_FENCE);
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for (int index = get_global_id(0); index < spatial_dim * get_max_sub_group_size(); index +=
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get_global_size(0)) {
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int s = index / get_max_sub_group_size();
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Dtype sum = sub_group_reduce_add(group_tmp[get_sub_group_local_id() * spatial_dim + s]);
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//if (get_sub_group_local_id() == 0)
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scale[n * spatial_dim + s] = sum;
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}
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barrier(CLK_GLOBAL_MEM_FENCE);
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for (int index = get_global_id(0); index < channels * spatial_dim;
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index += get_global_size(0)) {
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int s = index % spatial_dim;
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Dtype v = out[n * channels * spatial_dim + index] / scale[n * spatial_dim + s];
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#ifdef LOG_SOFTMAX
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v = log(v);
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#endif
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out[n * channels * spatial_dim + index] = v;
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}
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}
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