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未验证 提交 4a3ad97e 编写于 作者: R Ray Liu 提交者： GitHub
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Merge pull request #1173 from codeWorm2015/opencl 

add clfinish at fetch kernel
上级 cd08e4a9 624444ea
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Showing with 141 addition and 1304 deletion
src/framework/cl/cl_engine.h
浏览文件 @ 4a3ad97e
......@@ -90,7 +90,7 @@ class CLEngine {
bool BuildProgram(cl_program program) {
cl_int status;
status = clBuildProgram(program, 0, 0, "-cl-fast-relaxed-math", 0, 0);
status = clBuildProgram(program, 0, 0, "-cl-fast-relaxed-math -I cl_kernel", 0, 0);
CL_CHECK_ERRORS(status);
......
src/operators/kernel/cl/cl_kernel/conv_add_bn_relu_kernel.cl
浏览文件 @ 4a3ad97e
......@@ -17,427 +17,4 @@ limitations under the License. */
#define BATCH_NORM
#define RELU
#pragma OPENCL EXTENSION cl_khr_fp16 : enable
inline half4 activation(half4 in
#ifdef PRELU
,
half4 prelu_alpha
#endif
) {
half4 output;
#ifdef PRELU
output = select(prelu_alpha * in, in, in >= (half4)0.0);
#endif
#ifdef RELU
output = fmax(in, (half4)(0.0f));
#endif
return output;
}
__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);
if (out_c >= global_size_dim0 ||
out_w >= global_size_dim1 ||
out_nh >= global_size_dim2) {
printf(" out of range ");
return;
}
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;
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
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 = 0.0f;
#endif
half4 input[9];
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)(0.0f),
(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) << 15));
input[1] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y - dilation)),
(half4)(0.0f),
(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) << 15));
input[2] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y - dilation)),
(half4)(0.0f),
(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) << 15));
input[3] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x - dilation, pos_in.y)),
(half4)(0.0f),
(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) << 15));
input[4] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y)),
(half4)(0.0f),
(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) << 15));
input[5] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y)),
(half4)(0.0f),
(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) << 15));
input[6] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x - dilation, pos_in.y + dilation)),
(half4)(0.0f),
(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) << 15));
input[7] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y + dilation)),
(half4)(0.0f),
(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) << 15));
input[8] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y + dilation)),
(half4)(0.0f),
(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) << 15));
for (int j = 0; j < 9; ++j) {
int2 fuck;
fuck.x = i * 3 + j % 3;
fuck.y = out_c * 4 * 3 + 0 * 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 * 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 * 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 * 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);
}
__kernel void depth_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,
__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 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
const int batch_index = out_nh / output_height;
const int out_nh_in_one_batch = out_nh % output_height;
int2 stride_xy = (int2)(stride, stride);
int2 ouput_pos_in_one_block = (int2)(out_w, out_nh_in_one_batch);
int2 in_pos_in_one_block = ouput_pos_in_one_block * stride_xy + (int2)(offset, offset);
#ifdef BIASE
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#else
half4 output = 0.0f;
#endif
int2 pos_in_input_block = (int2)(out_c * input_width, batch_index * input_height);
int weight_y_to = out_c * 12;
half4 inputs[9];
inputs[0] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[1] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[2] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[3] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y >= input_height) << 15));
/*
if (output_pos.x == 112 && output_pos.y == 0) {
half4 input1 = inputs[3];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 3 - %v4hlf \n", in);
printf(" --- %d ---\n", in_pos_in_one_block.x - 1);
}
*/
inputs[4] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(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) << 15));
inputs[5] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y >= input_height) << 15));
inputs[6] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
inputs[7] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
inputs[8] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
for (int j = 0; j < 9; ++j) {
half4 input = inputs[j];
half4 weight0 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + j / 3));
half4 weight1 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 3 + j / 3));
half4 weight2 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 6 + j / 3));
half4 weight3 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 9 + j / 3));
output.x += input.x * weight0.x;
output.y += input.y * weight1.x;
output.z += input.z * weight2.x;
output.w += input.w * weight3.x;
}
#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
/*
if (output_pos.x == 112 && output_pos.y == 0) {
for (int i = 0; i < 9; ++i) {
half4 input1 = inputs[i];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 %d - %v4hlf \n", i, in);
}
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" depth wise output output4 = %v4hlf \n", out);
printf(" pos_in_input_block -x %d \n ", pos_in_input_block.x);
printf(" pos_in_input_block -y %d \n ", pos_in_input_block.y);
printf(" in_pos_in_one_block - x %d \n", in_pos_in_one_block.x);
printf(" in_pos_in_one_block - y %d \n", in_pos_in_one_block.y);
}
*/
write_imageh(output_image, output_pos, output);
}
__kernel void conv_1x1(__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);
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
const uint kernelHXW = 1;
int2 stride_xy = (int2)(stride, stride);
int2 ouput_pos_in_one_block = (int2)(out_w, out_nh);
int2 in_pos_in_one_block = ouput_pos_in_one_block * stride_xy + (int2)(offset, offset);
#ifdef BIASE
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#else
half4 output = 0.0f;
#endif
int out_c_p = 0, out_w_p = 0, out_nh_p = 0;
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after bias output4 = %v4hlf \n", out);
}
*/
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);
half4 input = read_imageh(input_image, sampler, pos_in);
half4 weight_x = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 0));
output.x += dot(input, weight_x);
half4 weight_y = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 1));
output.y += dot(input, weight_y);
half4 weight_z = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 2));
output.z += dot(input, weight_z);
half4 weight_w = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 3));
output.w += dot(input, weight_w);
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
printf("x - %d \n", pos_in.x);
printf("y - %d \n", pos_in.y);
float4 in = (float4)(input.x, input.y, input.z, input.w);
printf("input4 = %v4hlf \n", in);
float4 w = (float4)(weight_x.x, weight_x.y, weight_x.z, weight_x.w);
printf("weight4 = %v4hlf \n", w);
}
*/
}
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf("output4 = %v4hlf \n", out);
}
*/
#ifdef BATCH_NORM
output = output * read_imageh(new_scale, sampler, (int2)(out_c, 0)) + read_imageh(new_biase, sampler, (int2)(out_c, 0));
#endif
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after batch output4 = %v4hlf \n", out);
}
*/
#ifdef RELU
output = activation(output);
#endif
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after relu output4 = %v4hlf \n", out);
}
*/
int2 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
write_imageh(output_image, output_pos, output);
}
#include "conv_kernel.inc.cl"
src/operators/kernel/cl/cl_kernel/conv_add_kernel.cl
浏览文件 @ 4a3ad97e
......@@ -15,427 +15,4 @@ limitations under the License. */
#define BIASE
#pragma OPENCL EXTENSION cl_khr_fp16 : enable
inline half4 activation(half4 in
#ifdef PRELU
,
half4 prelu_alpha
#endif
) {
half4 output;
#ifdef PRELU
output = select(prelu_alpha * in, in, in >= (half4)0.0);
#endif
#ifdef RELU
output = fmax(in, (half4)(0.0f));
#endif
return output;
}
__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);
if (out_c >= global_size_dim0 ||
out_w >= global_size_dim1 ||
out_nh >= global_size_dim2) {
printf(" out of range ");
return;
}
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;
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
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 = 0.0f;
#endif
half4 input[9];
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)(0.0f),
(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) << 15));
input[1] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y - dilation)),
(half4)(0.0f),
(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) << 15));
input[2] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y - dilation)),
(half4)(0.0f),
(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) << 15));
input[3] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x - dilation, pos_in.y)),
(half4)(0.0f),
(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) << 15));
input[4] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y)),
(half4)(0.0f),
(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) << 15));
input[5] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y)),
(half4)(0.0f),
(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) << 15));
input[6] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x - dilation, pos_in.y + dilation)),
(half4)(0.0f),
(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) << 15));
input[7] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y + dilation)),
(half4)(0.0f),
(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) << 15));
input[8] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y + dilation)),
(half4)(0.0f),
(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) << 15));
for (int j = 0; j < 9; ++j) {
int2 fuck;
fuck.x = i * 3 + j % 3;
fuck.y = out_c * 4 * 3 + 0 * 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 * 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 * 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 * 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);
}
__kernel void depth_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,
__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 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
const int batch_index = out_nh / output_height;
const int out_nh_in_one_batch = out_nh % output_height;
int2 stride_xy = (int2)(stride, stride);
int2 ouput_pos_in_one_block = (int2)(out_w, out_nh_in_one_batch);
int2 in_pos_in_one_block = ouput_pos_in_one_block * stride_xy + (int2)(offset, offset);
#ifdef BIASE
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#else
half4 output = 0.0f;
#endif
int2 pos_in_input_block = (int2)(out_c * input_width, batch_index * input_height);
int weight_y_to = out_c * 12;
half4 inputs[9];
inputs[0] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[1] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[2] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[3] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y >= input_height) << 15));
/*
if (output_pos.x == 112 && output_pos.y == 0) {
half4 input1 = inputs[3];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 3 - %v4hlf \n", in);
printf(" --- %d ---\n", in_pos_in_one_block.x - 1);
}
*/
inputs[4] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(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) << 15));
inputs[5] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y >= input_height) << 15));
inputs[6] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
inputs[7] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
inputs[8] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
for (int j = 0; j < 9; ++j) {
half4 input = inputs[j];
half4 weight0 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + j / 3));
half4 weight1 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 3 + j / 3));
half4 weight2 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 6 + j / 3));
half4 weight3 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 9 + j / 3));
output.x += input.x * weight0.x;
output.y += input.y * weight1.x;
output.z += input.z * weight2.x;
output.w += input.w * weight3.x;
}
#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
/*
if (output_pos.x == 112 && output_pos.y == 0) {
for (int i = 0; i < 9; ++i) {
half4 input1 = inputs[i];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 %d - %v4hlf \n", i, in);
}
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" depth wise output output4 = %v4hlf \n", out);
printf(" pos_in_input_block -x %d \n ", pos_in_input_block.x);
printf(" pos_in_input_block -y %d \n ", pos_in_input_block.y);
printf(" in_pos_in_one_block - x %d \n", in_pos_in_one_block.x);
printf(" in_pos_in_one_block - y %d \n", in_pos_in_one_block.y);
}
*/
write_imageh(output_image, output_pos, output);
}
__kernel void conv_1x1(__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);
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
const uint kernelHXW = 1;
int2 stride_xy = (int2)(stride, stride);
int2 ouput_pos_in_one_block = (int2)(out_w, out_nh);
int2 in_pos_in_one_block = ouput_pos_in_one_block * stride_xy + (int2)(offset, offset);
#ifdef BIASE
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#else
half4 output = 0.0f;
#endif
int out_c_p = 0, out_w_p = 0, out_nh_p = 0;
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after bias output4 = %v4hlf \n", out);
}
*/
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);
half4 input = read_imageh(input_image, sampler, pos_in);
half4 weight_x = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 0));
output.x += dot(input, weight_x);
half4 weight_y = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 1));
output.y += dot(input, weight_y);
half4 weight_z = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 2));
output.z += dot(input, weight_z);
half4 weight_w = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 3));
output.w += dot(input, weight_w);
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
printf("x - %d \n", pos_in.x);
printf("y - %d \n", pos_in.y);
float4 in = (float4)(input.x, input.y, input.z, input.w);
printf("input4 = %v4hlf \n", in);
float4 w = (float4)(weight_x.x, weight_x.y, weight_x.z, weight_x.w);
printf("weight4 = %v4hlf \n", w);
}
*/
}
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf("output4 = %v4hlf \n", out);
}
*/
#ifdef BATCH_NORM
output = output * read_imageh(new_scale, sampler, (int2)(out_c, 0)) + read_imageh(new_biase, sampler, (int2)(out_c, 0));
#endif
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after batch output4 = %v4hlf \n", out);
}
*/
#ifdef RELU
output = activation(output);
#endif
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after relu output4 = %v4hlf \n", out);
}
*/
int2 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
write_imageh(output_image, output_pos, output);
}
#include "conv_kernel.inc.cl"
src/operators/kernel/cl/cl_kernel/conv_kernel.cl
浏览文件 @ 4a3ad97e
......@@ -12,412 +12,4 @@ 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);
if (out_c >= global_size_dim0 ||
out_w >= global_size_dim1 ||
out_nh >= global_size_dim2) {
printf(" out of range ");
return;
}
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;
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
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 = 0.0f;
#endif
half4 input[9];
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)(0.0f),
(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) << 15));
input[1] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y - dilation)),
(half4)(0.0f),
(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) << 15));
input[2] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y - dilation)),
(half4)(0.0f),
(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) << 15));
input[3] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x - dilation, pos_in.y)),
(half4)(0.0f),
(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) << 15));
input[4] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y)),
(half4)(0.0f),
(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) << 15));
input[5] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y)),
(half4)(0.0f),
(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) << 15));
input[6] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x - dilation, pos_in.y + dilation)),
(half4)(0.0f),
(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) << 15));
input[7] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y + dilation)),
(half4)(0.0f),
(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) << 15));
input[8] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y + dilation)),
(half4)(0.0f),
(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) << 15));
for (int j = 0; j < 9; ++j) {
int2 fuck;
fuck.x = i * 3 + j % 3;
fuck.y = out_c * 4 * 3 + 0 * 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 * 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 * 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 * 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);
}
__kernel void depth_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,
__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 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
const int batch_index = out_nh / output_height;
const int out_nh_in_one_batch = out_nh % output_height;
int2 stride_xy = (int2)(stride, stride);
int2 ouput_pos_in_one_block = (int2)(out_w, out_nh_in_one_batch);
int2 in_pos_in_one_block = ouput_pos_in_one_block * stride_xy + (int2)(offset, offset);
#ifdef BIASE
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#else
half4 output = 0.0f;
#endif
int2 pos_in_input_block = (int2)(out_c * input_width, batch_index * input_height);
int weight_y_to = out_c * 12;
half4 inputs[9];
inputs[0] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[1] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[2] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[3] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y >= input_height) << 15));
/*
if (output_pos.x == 112 && output_pos.y == 0) {
half4 input1 = inputs[3];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 3 - %v4hlf \n", in);
printf(" --- %d ---\n", in_pos_in_one_block.x - 1);
}
*/
inputs[4] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(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) << 15));
inputs[5] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y >= input_height) << 15));
inputs[6] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
inputs[7] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
inputs[8] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
for (int j = 0; j < 9; ++j) {
half4 input = inputs[j];
half4 weight0 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + j / 3));
half4 weight1 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 3 + j / 3));
half4 weight2 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 6 + j / 3));
half4 weight3 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 9 + j / 3));
output.x += input.x * weight0.x;
output.y += input.y * weight1.x;
output.z += input.z * weight2.x;
output.w += input.w * weight3.x;
}
#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
/*
if (output_pos.x == 112 && output_pos.y == 0) {
for (int i = 0; i < 9; ++i) {
half4 input1 = inputs[i];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 %d - %v4hlf \n", i, in);
}
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" depth wise output output4 = %v4hlf \n", out);
printf(" pos_in_input_block -x %d \n ", pos_in_input_block.x);
printf(" pos_in_input_block -y %d \n ", pos_in_input_block.y);
printf(" in_pos_in_one_block - x %d \n", in_pos_in_one_block.x);
printf(" in_pos_in_one_block - y %d \n", in_pos_in_one_block.y);
}
*/
write_imageh(output_image, output_pos, output);
}
__kernel void conv_1x1(__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);
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
const uint kernelHXW = 1;
int2 stride_xy = (int2)(stride, stride);
int2 ouput_pos_in_one_block = (int2)(out_w, out_nh);
int2 in_pos_in_one_block = ouput_pos_in_one_block * stride_xy + (int2)(offset, offset);
#ifdef BIASE
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#else
half4 output = 0.0f;
#endif
int out_c_p = 0, out_w_p = 0, out_nh_p = 0;
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after bias output4 = %v4hlf \n", out);
}
*/
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);
half4 input = read_imageh(input_image, sampler, pos_in);
half4 weight_x = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 0));
output.x += dot(input, weight_x);
half4 weight_y = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 1));
output.y += dot(input, weight_y);
half4 weight_z = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 2));
output.z += dot(input, weight_z);
half4 weight_w = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 3));
output.w += dot(input, weight_w);
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
printf("x - %d \n", pos_in.x);
printf("y - %d \n", pos_in.y);
float4 in = (float4)(input.x, input.y, input.z, input.w);
printf("input4 = %v4hlf \n", in);
float4 w = (float4)(weight_x.x, weight_x.y, weight_x.z, weight_x.w);
printf("weight4 = %v4hlf \n", w);
}
*/
}
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf("output4 = %v4hlf \n", out);
}
*/
#ifdef BATCH_NORM
output = output * read_imageh(new_scale, sampler, (int2)(out_c, 0)) + read_imageh(new_biase, sampler, (int2)(out_c, 0));
#endif
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after batch output4 = %v4hlf \n", out);
}
*/
#ifdef RELU
output = activation(output);
#endif
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after relu output4 = %v4hlf \n", out);
}
*/
int2 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
write_imageh(output_image, output_pos, output);
}
#include "conv_kernel.inc.cl"
src/operators/kernel/cl/cl_kernel/conv_kernel.inc.cl
浏览文件 @ 4a3ad97e
......@@ -20,10 +20,9 @@ conv_relu
conv_bn_relu
conv_add_relu
conv_add_bn_relu
*/
#include "cl_kernel/cl_common.h"
#include "cl_common.h"
__kernel void conv_3x3(__private const int global_size_dim0,
__private const int global_size_dim1,
......@@ -92,47 +91,47 @@ __kernel void conv_3x3(__private const int global_size_dim0,
input[0] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x - dilation, pos_in.y - dilation)),
(half4)(0.0f),
(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));
(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) << 15));
input[1] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y - dilation)),
(half4)(0.0f),
(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));
(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) << 15));
input[2] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y - dilation)),
(half4)(0.0f),
(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));
(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) << 15));
input[3] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x - dilation, pos_in.y)),
(half4)(0.0f),
(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));
(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) << 15));
input[4] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y)),
(half4)(0.0f),
(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));
(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) << 15));
input[5] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y)),
(half4)(0.0f),
(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));
(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) << 15));
input[6] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x - dilation, pos_in.y + dilation)),
(half4)(0.0f),
(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));
(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) << 15));
input[7] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x, pos_in.y + dilation)),
(half4)(0.0f),
(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));
(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) << 15));
input[8] = select(read_imageh(input_image, sampler,
(int2)(pos_in.x + dilation, pos_in.y + dilation)),
(half4)(0.0f),
(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));
(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) << 15));
for (int j = 0; j < 9; ++j) {
int2 fuck;
......@@ -166,6 +165,9 @@ __kernel void conv_3x3(__private const int global_size_dim0,
write_imageh(output_image, (int2)(out_c * global_size_dim1 + out_w, out_nh), output);
}
__kernel void depth_conv_3x3(__private const int global_size_dim0,
__private const int global_size_dim1,
__private const int global_size_dim2,
......@@ -192,6 +194,9 @@ __kernel void depth_conv_3x3(__private const int global_size_dim0,
const int out_w = get_global_id(1);
const int out_nh = get_global_id(2);
int2 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST;
......@@ -200,7 +205,6 @@ __kernel void depth_conv_3x3(__private const int global_size_dim0,
const int out_nh_in_one_batch = out_nh % output_height;
const uint kernelHXW = 1;
int2 stride_xy = (int2)(stride, stride);
int2 ouput_pos_in_one_block = (int2)(out_w, out_nh_in_one_batch);
......@@ -214,53 +218,65 @@ __kernel void depth_conv_3x3(__private const int global_size_dim0,
#endif
int2 pos_in_input_block = (int2)(out_c * input_width, batch_index * input_height);
int weight_x_to = out_c * 3;
int weight_y_to = out_c * 12;
half4 inputs[9];
inputs[0] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)(in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height));
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[1] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)(in_pos_in_one_block.x < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y - 1 >= input_height));
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[2] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(half4)(0.0f),
(ushort4)(in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height));
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y - 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y - 1 >= input_height) << 15));
inputs[3] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(ushort4)(in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y >= input_height));
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y >= input_height) << 15));
/*
if (output_pos.x == 112 && output_pos.y == 0) {
half4 input1 = inputs[3];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 3 - %v4hlf \n", in);
printf(" --- %d ---\n", in_pos_in_one_block.x - 1);
}
*/
inputs[4] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(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));
(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) << 15));
inputs[5] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y)),
(half4)(0.0f),
(ushort4)(in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y >= input_height));
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y >= input_height) << 15));
inputs[6] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)(in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height));
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x - 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
inputs[7] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)(in_pos_in_one_block.x < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y + 1 >= input_height));
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
inputs[8] = select(read_imageh(input, sampler, (int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1, pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(half4)(0.0f),
(ushort4)(in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height));
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y + 1 < 0 || in_pos_in_one_block.x + 1 >= input_width || in_pos_in_one_block.y + 1 >= input_height) << 15));
for (int j = 0; j < 9; ++j) {
half4 input = inputs[j];
half4 weight = read_imageh(filter, sampler, (int2)(weight_x_to + j % 3, j / 3));
output.x += input.x * weight.x;
output.y += input.y * weight.y;
output.z += input.z * weight.z;
output.w += input.w * weight.w;
half4 weight0 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + j / 3));
half4 weight1 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 3 + j / 3));
half4 weight2 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 6 + j / 3));
half4 weight3 = read_imageh(filter, sampler, (int2)(j % 3, weight_y_to + 9 + j / 3));
output.x += input.x * weight0.x;
output.y += input.y * weight1.x;
output.z += input.z * weight2.x;
output.w += input.w * weight3.x;
}
#ifdef BATCH_NORM
......@@ -271,7 +287,27 @@ __kernel void depth_conv_3x3(__private const int global_size_dim0,
output = activation(output);
#endif
int2 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
/*
if (output_pos.x == 112 && output_pos.y == 0) {
for (int i = 0; i < 9; ++i) {
half4 input1 = inputs[i];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 %d - %v4hlf \n", i, in);
}
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" depth wise output output4 = %v4hlf \n", out);
printf(" pos_in_input_block -x %d \n ", pos_in_input_block.x);
printf(" pos_in_input_block -y %d \n ", pos_in_input_block.y);
printf(" in_pos_in_one_block - x %d \n", in_pos_in_one_block.x);
printf(" in_pos_in_one_block - y %d \n", in_pos_in_one_block.y);
}
*/
write_imageh(output_image, output_pos, output);
}
......@@ -314,9 +350,19 @@ __kernel void conv_1x1(__private const int global_size_dim0,
half4 output = 0.0f;
#endif
int out_c_p = 0, out_w_p = 0, out_nh_p = 0;
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after bias output4 = %v4hlf \n", out);
}
*/
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);
if (pos_in.x >=0 && pos_in.y >= 0 && pos_in.x < input_width && pos_in.y < input_height) {
half4 input = read_imageh(input_image, sampler, pos_in);
half4 weight_x = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 0));
......@@ -330,20 +376,56 @@ __kernel void conv_1x1(__private const int global_size_dim0,
half4 weight_w = read_imageh(filter, sampler, (int2)(i, out_c * 4 + 3));
output.w += dot(input, weight_w);
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
printf("x - %d \n", pos_in.x);
printf("y - %d \n", pos_in.y);
float4 in = (float4)(input.x, input.y, input.z, input.w);
printf("input4 = %v4hlf \n", in);
float4 w = (float4)(weight_x.x, weight_x.y, weight_x.z, weight_x.w);
printf("weight4 = %v4hlf \n", w);
}
*/
}
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf("output4 = %v4hlf \n", out);
}
*/
#ifdef BATCH_NORM
output = output * read_imageh(new_scale, sampler, (int2)(out_c, 0)) + read_imageh(new_biase, sampler, (int2)(out_c, 0));
#endif
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after batch output4 = %v4hlf \n", out);
}
*/
#ifdef RELU
output = activation(output);
#endif
/*
if (out_c == out_c_p && out_w == out_w_p && out_nh == out_nh_p) {
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" after relu output4 = %v4hlf \n", out);
}
*/
int2 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
write_imageh(output_image, output_pos, output);
}
src/operators/kernel/cl/fetch_kernel.cpp
浏览文件 @ 4a3ad97e
......@@ -14,6 +14,8 @@ limitations under the License. */
#include "operators/kernel/fetch_kernel.h"
#include "framework/cl/cl_tensor.h"
//#include "common/common.h"
//#include <iostream>
namespace paddle_mobile {
namespace operators {
......@@ -77,11 +79,19 @@ void FetchKernel<GPU_CL, float>::Compute(const FetchParam<GPU_CL> &param) {
clEnqueueNDRangeKernel(this->cl_helper_.CLCommandQueue(), kernel, 3, NULL,
default_work_size.data(), NULL, 0, NULL, NULL);
// auto time1 = paddle_mobile::time();
// printf(" before finish \n");
// clFlsh(this->cl_helper_.CLCommandQueue());
// clFinish(this->cl_helper_.CLCommandQueue());
clFinish(this->cl_helper_.CLCommandQueue());
// printf(" after finish \n");
// auto time2 = paddle_mobile::time();
//
//
// std::cout << " finish cost :" << paddle_mobile::time_diff(time1, time2)
// << "ms" << std::endl;
memcpy(out->data<float>(), out_cl_tensor.Data<float>(), out->memory_size());
}
......
test/net/test_mobilenet_GPU.cpp
浏览文件 @ 4a3ad97e
......@@ -33,24 +33,23 @@ int main() {
std::vector<int64_t> dims{1, 3, 224, 224};
GetInput<float>(g_test_image_1x3x224x224_banana, &input, dims);
// auto time3 = paddle_mobile::time();
auto time3 = paddle_mobile::time();
auto vec_result = paddle_mobile.Predict(input, dims);
// auto time4 = paddle_mobile::time();
auto time4 = paddle_mobile::time();
for (int i = 0; i < 10; ++i) {
auto vec_result = paddle_mobile.Predict(input, dims);
}
// for (int i = 0; i < 10; ++i) {
// auto vec_result = paddle_mobile.Predict(input, dims);
// }
auto time3 = paddle_mobile::time();
// auto time3 = paddle_mobile::time();
for (int i = 0; i < 10; ++i) {
auto vec_result = paddle_mobile.Predict(input, dims);
}
// for (int i = 0; i < 10; ++i) {
// auto vec_result = paddle_mobile.Predict(input, dims);
// }
auto time4 = paddle_mobile::time();
std::cout << "predict cost :" << paddle_mobile::time_diff(time3, time4) / 10
<< "ms" << std::endl;
// auto time4 = paddle_mobile::time();
std::cout << "predict cost :" << paddle_mobile::time_diff(time3, time4) << "ms" << std::endl;
std::vector<float>::iterator biggest =
std::max_element(std::begin(vec_result), std::end(vec_result));
std::cout << " Max element is " << *biggest << " at position "
......
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