activation_kernel.cl

/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#include <cl_common.h>


__kernel void relu(__read_only image2d_t input,
                   __write_only image2d_t output,
                   __private const float threshold,
                   __private const float scale) {

  const int x = get_global_id(0); // image_width
  const int y = get_global_id(1); // image_height

  const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
                            CLK_ADDRESS_CLAMP |
                            CLK_FILTER_NEAREST;

  CL_DTYPE4 in = READ_IMG_TYPE(CL_DTYPE_CHAR, input, sampler, (int2)(x, y));
  in = max((CL_DTYPE4)(0.0f), in);
  WRITE_IMG_TYPE(CL_DTYPE_CHAR, output, (int2)(x, y), in);
}


__kernel void relu6(__read_only image2d_t input,
                    __write_only image2d_t output,
                    __private const float threshold,
                   __private const float scale){

  const int x = get_global_id(0);
  const int y = get_global_id(1);

  const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
                            CLK_ADDRESS_CLAMP |
                            CLK_FILTER_NEAREST;

  CL_DTYPE4 in = READ_IMG_TYPE(CL_DTYPE_CHAR, input, sampler, (int2)(x, y));
  in = max((CL_DTYPE4)(0.0f, 0.0f, 0.0f, 0.0f), in);
  in = min((CL_DTYPE4)(threshold, threshold, threshold, threshold), in);
  WRITE_IMG_TYPE(CL_DTYPE_CHAR, output, (int2)(x, y), in);
}


__kernel void sigmoid(__read_only image2d_t input,
                      __write_only image2d_t output,
                      __private const float threshold,
                      __private const float scale) {
  const int x = get_global_id(0);  // image_width
  const int y = get_global_id(1);  // image_height

  const sampler_t sampler =
      CLK_NORMALIZED_COORDS_TRUE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;

  CL_DTYPE4 in = READ_IMG_TYPE(CL_DTYPE_CHAR, input, sampler, (int2)(x, y));
  CL_DTYPE4 out;
  out.x = 1.0 / (1.0 + pow(2.71828182, -1.0 * (float)(in.x)));
  out.y = 1.0 / (1.0 + pow(2.71828182, -1.0 * (float)(in.y)));
  out.z = 1.0 / (1.0 + pow(2.71828182, -1.0 * (float)(in.z)));
  out.w = 1.0 / (1.0 + pow(2.71828182, -1.0 * (float)(in.w)));

  WRITE_IMG_TYPE(CL_DTYPE_CHAR, output, (int2)(x, y), out);
}

__kernel void leaky_relu(__read_only image2d_t input,
                      __write_only image2d_t output,
                      __private const float threshold,
                      __private const float scale) {
  const int x = get_global_id(0);
  const int y = get_global_id(1);

  const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
                            CLK_ADDRESS_CLAMP |
                            CLK_FILTER_NEAREST;

  CL_DTYPE4 in = READ_IMG_TYPE(CL_DTYPE_CHAR, input, sampler, (int2)(x, y));
  CL_DTYPE4 s_val = CONVERT_TYPE_TO(scale, CL_DTYPE) * in;
  if (in.x < 0.0f){
    in.x = s_val.x;
  }
  if (in.y < 0.0f){
    in.y = s_val.y;
  }
  if (in.z < 0.0f){
    in.z = s_val.z;
  }
  if (in.w < 0.0f){
    in.w = s_val.w;
  }
  WRITE_IMG_TYPE(CL_DTYPE_CHAR, output, (int2)(x, y), in);
}

__kernel void tanh_act(__read_only image2d_t input,
                      __write_only image2d_t output,
                      __private const float threshold,
                      __private const float scale) {

  const int x = get_global_id(0); // image_width
  const int y = get_global_id(1); // image_height

  const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
                            CLK_ADDRESS_CLAMP |
                            CLK_FILTER_NEAREST;

  CL_DTYPE4 in = READ_IMG_TYPE(CL_DTYPE_CHAR, input, sampler, (int2)(x, y));
  CL_DTYPE4 out= (exp(in) - exp(-in))/ (exp(in) + exp(-in));
  WRITE_IMG_TYPE(CL_DTYPE_CHAR, output, (int2)(x, y), out);
}

__kernel void exp_act(__read_only image2d_t input,
                      __write_only image2d_t output,
                      __private const float threshold,
                   __private const float scale) {

  const int x = get_global_id(0); // image_width
  const int y = get_global_id(1); // image_height

  const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
                            CLK_ADDRESS_CLAMP |
                            CLK_FILTER_NEAREST;

  CL_DTYPE4 in = READ_IMG_TYPE(CL_DTYPE_CHAR, input, sampler, (int2)(x, y));
  CL_DTYPE4 out = exp(in);
  WRITE_IMG_TYPE(CL_DTYPE_CHAR, output, (int2)(x, y), out);
}

__kernel void swish(__read_only image2d_t input,
                      __write_only image2d_t output,
                      __private const float threshold,
                   __private const float scale) {

  const int x = get_global_id(0); // image_width
  const int y = get_global_id(1); // image_height

  const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
                            CLK_ADDRESS_CLAMP |
                            CLK_FILTER_NEAREST;

  CL_DTYPE4 in = READ_IMG_TYPE(CL_DTYPE_CHAR, input, sampler, (int2)(x, y));
  CL_DTYPE4 out = in / (1 + exp(-(CL_DTYPE)scale * in));
  WRITE_IMG_TYPE(CL_DTYPE_CHAR, output, (int2)(x, y), out);
}