conv_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. */

#pragma OPENCL EXTENSION cl_khr_fp16 : enable

__kernel void conv_3x3(__private const int global_size_dim0,
                                              __private const int global_size_dim1,
                                              __private const int global_size_dim2,
                                              __read_only image2d_t input_image,
                                              __read_only image2d_t filter,
#ifdef BIASE
                                              __read_only image2d_t bias,
#endif

#ifdef BATCH_NORM
                                              __read_only image2d_t new_scale,
                                              __read_only image2d_t new_biase,
#endif

                                              __write_only image2d_t output_image,
                                              __private const int stride,
                                              __private const int offset,
                                              __private const int input_c,
                                              __private const int dilation,
                                              __private const int input_width,/* of one block */
                                              __private const int input_height,/* of one block */
                                              __private const int output_width,
                                              __private const int output_height) {

    const int out_c = get_global_id(0);
    const int out_w = get_global_id(1);
    const int out_nh = get_global_id(2);

    int2 stride_xy;
    stride_xy.x = stride;
    stride_xy.y = stride;

    int2 ouput_pos_in_one_block;
    ouput_pos_in_one_block.x = out_w;
    ouput_pos_in_one_block.y = out_nh;

    int2 in_pos_in_one_block;
    in_pos_in_one_block.x = ouput_pos_in_one_block.x * stride + offset;
    in_pos_in_one_block.y = ouput_pos_in_one_block.y * stride + offset;

 #ifdef BIASE
    half4 output = read_imageh(bias, sampler, int2(out_c, 0));
#else
    half4 output = 0.0;
#endif

   half4 input[9];

   const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
                              CLK_ADDRESS_CLAMP         |
                              CLK_FILTER_NEAREST;

   for (int i = 0; i < input_c; ++i) {
        int2 pos_in = (int2)(i * input_width + in_pos_in_one_block.x, in_pos_in_one_block.y);
        input[0] = select(read_imageh(input_image, sampler,
                            (int2)(pos_in.x - dilation, pos_in.y - dilation)),
                            (half4)(0.0),
                            (ushort4)(in_pos_in_one_block.x - dilation < 0 || in_pos_in_one_block.y - dilation < 0 || in_pos_in_one_block.x - dilation >= input_width || in_pos_in_one_block.y - dilation >= input_height));

        input[1] = select(read_imageh(input_image, sampler,
                          (int2)(pos_in.x, pos_in.y - dilation)),
                          (half4)(0.0),
                          (ushort4)(in_pos_in_one_block.x < 0 || in_pos_in_one_block.y - dilation < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y - dilation >= input_height));

        input[2] = select(read_imageh(input_image, sampler,
                          (int2)(pos_in.x + dilation, pos_in.y - dilation)),
                          (half4)(0.0),
                          (ushort4)(in_pos_in_one_block.x + dilation < 0 || in_pos_in_one_block.y - dilation < 0 || in_pos_in_one_block.x + dilation >= input_width || in_pos_in_one_block.y - dilation >= input_height));

        input[3] = select(read_imageh(input_image, sampler,
                          (int2)(pos_in.x - dilation, pos_in.y)),
                          (half4)(0.0),
                          (ushort4)(in_pos_in_one_block.x - dilation < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x - dilation >= input_width || in_pos_in_one_block.y >= input_height));

        input[4] = select(read_imageh(input_image, sampler,
                          (int2)(pos_in.x, pos_in.y)),
                          (half4)(0.0),
                          (ushort4)(in_pos_in_one_block.x < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y >= input_height));

        input[5] = select(read_imageh(input_image, sampler,
                          (int2)(pos_in.x + dilation, pos_in.y)),
                          (half4)(0.0),
                          (ushort4)(in_pos_in_one_block.x + dilation < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x + dilation >= input_width || in_pos_in_one_block.y >= input_height));

        input[6] = select(read_imageh(input_image, sampler,
                          (int2)(pos_in.x - dilation, pos_in.y + dilation)),
                          (half4)(0.0),
                          (ushort4)(in_pos_in_one_block.x - dilation < 0 || in_pos_in_one_block.y + dilation < 0 || in_pos_in_one_block.x - dilation >= input_width || in_pos_in_one_block.y + dilation >= input_height));

        input[7] = select(read_imageh(input_image, sampler,
                          (int2)(pos_in.x, pos_in.y + dilation)),
                          (half4)(0.0),
                          (ushort4)(in_pos_in_one_block.x < 0 || in_pos_in_one_block.y + dilation < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y + dilation >= input_height));

        input[8] = select(read_imageh(input_image, sampler,
                          (int2)(pos_in.x + dilation, pos_in.y + dilation)),
                          (half4)(0.0),
                          (ushort4)(pos_in.x + dilation < 0 || in_pos_in_one_block.y + dilation < 0 || pos_in.x + dilation >= input_width || in_pos_in_one_block.y + dilation >= input_height));

        for (int j = 0; j < 9; ++j) {
            int2 fuck;
            fuck.x = i * 3 + j % 3;
            fuck.y = out_c * 4 * 3 + 0 * out_c * 3 + j / 3;
            half4 weight_x = read_imageh(filter, sampler, fuck);
            output.x += dot(input[j], weight_x);

            fuck.y = out_c * 4 * 3 + 1 * out_c * 3 + j / 3;
            half4 weight_y = read_imageh(filter, sampler, fuck);
            output.y += dot(input[j], weight_y);

            fuck.y = out_c * 4 * 3 + 2 * out_c * 3 + j / 3;
            half4 weight_z = read_imageh(filter, sampler, fuck);
            output.z += dot(input[j], weight_z);

            fuck.y = out_c * 4 * 3 + 3 * out_c * 3 + j / 3;
            half4 weight_w = read_imageh(filter, sampler, fuck);
            output.w += dot(input[j], weight_w);
        }
    }

#ifdef BATCH_NORM
    output = output * read_imageh(new_scale, sampler, int2(out_c, 0)) + read_imageh(new_biase, sampler, int2(out_c, 0))
#endif

#ifdef RELU
    output = activation(output);
#endif

    write_imageh(output_image, (int2)(out_c * global_size_dim1 + out_w, out_nh), output);
}