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提交 d6c620b9 编写于 作者: J Jiaying Zhao 提交者： GitHub
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support element_add in opencl fusion conv op (#1660)

上级 21d8b64b
隐藏空白更改
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Showing with 106 addition and 56 deletion
src/operators/kernel/cl/cl_kernel/conv_kernel.inc.cl
浏览文件 @ d6c620b9
......@@ -30,7 +30,7 @@ __kernel void conv_3x3(__private const int global_size_dim0,
__read_only image2d_t input_image,
__read_only image2d_t filter,
#ifdef BIASE
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
......@@ -52,6 +52,8 @@ __kernel void conv_3x3(__private const int global_size_dim0,
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);
if (out_c >= global_size_dim0 ||
out_w >= global_size_dim1 ||
......@@ -77,8 +79,10 @@ __kernel void conv_3x3(__private const int global_size_dim0,
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
#ifdef BIASE_CH
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#elif defined(BIASE_ELE)
half4 output = read_imageh(bias, sampler, output_pos);
#else
half4 output = 0.0f;
#endif
......@@ -327,7 +331,7 @@ __kernel void conv_3x3(__private const int global_size_dim0,
output = activation(output);
#endif
write_imageh(output_image, (int2)(out_c * global_size_dim1 + out_w, out_nh), output);
write_imageh(output_image, output_pos, output);
}
......@@ -338,7 +342,7 @@ __kernel void depth_conv_3x3(__private const int global_size_dim0,
__private const int global_size_dim2,
__read_only image2d_t input,
__read_only image2d_t filter,
#ifdef BIASE
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
#ifdef BATCH_NORM
......@@ -376,8 +380,10 @@ __kernel void depth_conv_3x3(__private const int global_size_dim0,
int2 in_pos_in_one_block = ouput_pos_in_one_block * stride_xy + (int2)(offset, offset);
#ifdef BIASE
#ifdef BIASE_CH
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#elif defined(BIASE_ELE)
half4 output = read_imageh(bias, sampler, output_pos);
#else
half4 output = 0.0f;
#endif
......@@ -492,7 +498,7 @@ __kernel void conv_1x1(__private const int global_size_dim0,
__private const int global_size_dim2,
__read_only image2d_t input_image,
__read_only image2d_t filter,
#ifdef BIASE
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
#ifdef BATCH_NORM
......@@ -512,6 +518,8 @@ __kernel void conv_1x1(__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;
......@@ -521,8 +529,10 @@ __kernel void conv_1x1(__private const int global_size_dim0,
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
#ifdef BIASE_CH
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#elif defined(BIASE_ELE)
half4 output = read_imageh(bias, sampler, output_pos);
#else
half4 output = 0.0f;
#endif
......@@ -557,7 +567,6 @@ __kernel void conv_1x1(__private const int global_size_dim0,
output = activation(output);
#endif
int2 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
write_imageh(output_image, output_pos, output);
}
......@@ -565,7 +574,7 @@ __kernel void conv_1x1_spl(
__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
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
#ifdef BATCH_NORM
......@@ -593,6 +602,12 @@ __kernel void conv_1x1_spl(
// int out_w1 = out_w + global_size_dim1;
// int out_w2 = out_w + global_size_dim1 * 2;
// int out_w3 = out_w + global_size_dim1 * 3;
int outpos_main = mul24(out_c , old_w);
int2 output_pos0 = (int2)(outpos_main + out_w0, out_nh);
int2 output_pos1 = (int2)(outpos_main + out_w1, out_nh);
int2 output_pos2 = (int2)(outpos_main + out_w2, out_nh);
int2 output_pos3 = (int2)(outpos_main + out_w3, out_nh);
const sampler_t sampler =
CLK_NORMALIZED_COORDS_TRUE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;
......@@ -615,15 +630,16 @@ __kernel void conv_1x1_spl(
int2 in_pos_in_one_block3 =
ouput_pos_in_one_block3 * stride_xy + (int2)(offset, offset);
#ifdef BIASE
half4 output0= read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output1 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output2 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output3 = read_imageh(bias, sampler, (int2)(out_c, 0));
// half4 output0 = 0.0f;
// half4 output1 = 0.0f;
// half4 output2 = 0.0f;
// half4 output3 = 0.0f;
#ifdef BIASE_CH
half4 output0 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output1 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output2 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output3 = read_imageh(bias, sampler, (int2)(out_c, 0));
#elif defined(BIASE_ELE)
half4 output0 = read_imageh(bias, sampler, output_pos0);
half4 output1 = read_imageh(bias, sampler, output_pos1);
half4 output2 = read_imageh(bias, sampler, output_pos2);
half4 output3 = read_imageh(bias, sampler, output_pos3);
#else
half4 output0 = 0.0f;
......@@ -712,23 +728,19 @@ __kernel void conv_1x1_spl(
output2 = activation(output2);
output3 = activation(output3);
#endif
int outpos_main = mul24(out_c , old_w);
int2 output_pos0 = (int2)(outpos_main + out_w0, out_nh);
if (out_w0 < old_w) {
write_imageh(output_image, output_pos0, output0);
}
int2 output_pos1 = (int2)(outpos_main + out_w1, out_nh);
if (out_w1 < old_w){
write_imageh(output_image, output_pos1, output1);
}
int2 output_pos2 = (int2)(outpos_main + out_w2, out_nh);
if (out_w2 < old_w){
write_imageh(output_image, output_pos2, output2);
}
int2 output_pos3 = (int2)(outpos_main + out_w3, out_nh);
if (out_w3 < old_w){
write_imageh(output_image, output_pos3, output3);
}
......@@ -1549,7 +1561,7 @@ __kernel void conv_7x7(__private const int global_size_dim0,
__read_only image2d_t input_image,
__read_only image2d_t filter_image,
#ifdef BIASE
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
......@@ -1571,6 +1583,8 @@ __kernel void conv_7x7(__private const int global_size_dim0,
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);
if (out_c >= global_size_dim0 ||
out_w >= global_size_dim1 ||
......@@ -1599,8 +1613,10 @@ __kernel void conv_7x7(__private const int global_size_dim0,
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
#ifdef BIASE_CH
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#elif defined(BIASE_ELE)
half4 output = read_imageh(bias, sampler, output_pos);
#else
half4 output = 0.0f;
#endif
......@@ -1656,7 +1672,7 @@ __kernel void conv_7x7(__private const int global_size_dim0,
output = activation(output);
#endif
write_imageh(output_image, (int2)(out_c * global_size_dim1 + out_w, out_nh), output);
write_imageh(output_image, output_pos, output);
}
__kernel void conv_5x5(__private const int global_size_dim0,
......@@ -1665,7 +1681,7 @@ __kernel void conv_5x5(__private const int global_size_dim0,
__read_only image2d_t input_image,
__read_only image2d_t filter_image,
#ifdef BIASE
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
......@@ -1687,6 +1703,8 @@ __kernel void conv_5x5(__private const int global_size_dim0,
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);
if (out_c >= global_size_dim0 ||
out_w >= global_size_dim1 ||
......@@ -1715,8 +1733,10 @@ __kernel void conv_5x5(__private const int global_size_dim0,
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
#ifdef BIASE_CH
half4 output = read_imageh(bias, sampler, (int2)(out_c, 0));
#elif defined(BIASE_ELE)
half4 output = read_imageh(bias, sampler, output_pos);
#else
half4 output = 0.0f;
#endif
......@@ -1772,7 +1792,7 @@ __kernel void conv_5x5(__private const int global_size_dim0,
output = activation(output);
#endif
write_imageh(output_image, (int2)(out_c * global_size_dim1 + out_w, out_nh), output);
write_imageh(output_image, output_pos, output);
}
__kernel void convBNAdd_3x3(__private const int global_size_dim0,
......@@ -1781,7 +1801,7 @@ __kernel void convBNAdd_3x3(__private const int global_size_dim0,
__read_only image2d_t input_image,
__read_only image2d_t filter,
#ifdef BIASE
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
......@@ -1803,6 +1823,8 @@ __kernel void convBNAdd_3x3(__private const int global_size_dim0,
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);
if (out_c >= global_size_dim0 ||
out_w >= global_size_dim1 ||
......@@ -2071,15 +2093,17 @@ __kernel void convBNAdd_3x3(__private const int global_size_dim0,
output = output * read_imageh(new_scale, sampler, (int2)(out_c, 0)) + read_imageh(new_biase, sampler, (int2)(out_c, 0));
#endif
#ifdef BIASE
output += read_imageh(bias, sampler, (int2)(out_c * global_size_dim1 + out_w, out_nh));
#ifdef BIASE_CH
output += read_imageh(bias, sampler, (int2)(out_c, 0));
#elif defined(BIASE_ELE)
output += read_imageh(bias, sampler, output_pos);
#endif
#ifdef RELU
output = activation(output);
#endif
write_imageh(output_image, (int2)(out_c * global_size_dim1 + out_w, out_nh), output);
write_imageh(output_image, output_pos, output);
}
__kernel void convBNAdd_1x1(__private const int global_size_dim0,
......@@ -2087,7 +2111,7 @@ __kernel void convBNAdd_1x1(__private const int global_size_dim0,
__private const int global_size_dim2,
__read_only image2d_t input_image,
__read_only image2d_t filter,
#ifdef BIASE
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
#ifdef BATCH_NORM
......@@ -2107,6 +2131,8 @@ __kernel void convBNAdd_1x1(__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;
......@@ -2145,15 +2171,16 @@ __kernel void convBNAdd_1x1(__private const int global_size_dim0,
output = output * read_imageh(new_scale, sampler, (int2)(out_c, 0)) + read_imageh(new_biase, sampler, (int2)(out_c, 0));
#endif
#ifdef BIASE
output += read_imageh(bias, sampler, (int2)(out_c * global_size_dim1 + out_w, out_nh));
#ifdef BIASE_CH
output += read_imageh(bias, sampler, (int2)(out_c, 0));
#elif defined(BIASE_ELE)
output += read_imageh(bias, sampler, output_pos);
#endif
#ifdef RELU
output = activation(output);
#endif
int2 output_pos = (int2)(out_c * global_size_dim1 + out_w, out_nh);
write_imageh(output_image, output_pos, output);
}
......@@ -2161,7 +2188,7 @@ __kernel void convBNAdd_1x1_spl(
__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
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
#ifdef BATCH_NORM
......@@ -2186,9 +2213,11 @@ __kernel void convBNAdd_1x1_spl(
int out_w2 = out_w + global_size_dim1 * 2;
int out_w3 = out_w + global_size_dim1 * 3;
// int out_w1 = out_w + global_size_dim1;
// int out_w2 = out_w + global_size_dim1 * 2;
// int out_w3 = out_w + global_size_dim1 * 3;
int outpos_main = mul24(out_c , old_w);
int2 output_pos0 = (int2)(outpos_main + out_w0, out_nh);
int2 output_pos1 = (int2)(outpos_main + out_w1, out_nh);
int2 output_pos2 = (int2)(outpos_main + out_w2, out_nh);
int2 output_pos3 = (int2)(outpos_main + out_w3, out_nh);
const sampler_t sampler =
CLK_NORMALIZED_COORDS_TRUE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;
......@@ -2279,7 +2308,7 @@ __kernel void convBNAdd_1x1_spl(
}
#ifdef BATCH_NORM
output0 = output0 * read_imageh(new_scale, sampler, (int2)(out_c, 0)) +
output0 = output0 * read_imageh(new_scale, sampler, (int2)(out_c, 0)) +
read_imageh(new_biase, sampler, (int2)(out_c, 0));
output1 = output1 * read_imageh(new_scale, sampler, (int2)(out_c, 0)) +
......@@ -2292,11 +2321,16 @@ __kernel void convBNAdd_1x1_spl(
read_imageh(new_biase, sampler, (int2)(out_c, 0));
#endif
#ifdef BIASE
output0= read_imageh(bias, sampler, (int2)(out_c, 0));
output1 = read_imageh(bias, sampler, (int2)(out_c, 0));
output2 = read_imageh(bias, sampler, (int2)(out_c, 0));
output3 = read_imageh(bias, sampler, (int2)(out_c, 0));
#ifdef BIASE_CH
output0 += read_imageh(bias, sampler, (int2)(out_c, 0));
output1 += read_imageh(bias, sampler, (int2)(out_c, 0));
output2 += read_imageh(bias, sampler, (int2)(out_c, 0));
output3 += read_imageh(bias, sampler, (int2)(out_c, 0));
#elif defined(BIASE_ELE)
output0 += read_imageh(bias, sampler, output_pos0);
output1 += read_imageh(bias, sampler, output_pos1);
output2 += read_imageh(bias, sampler, output_pos2);
output3 += read_imageh(bias, sampler, output_pos3);
#endif
#ifdef RELU
......@@ -2305,23 +2339,19 @@ __kernel void convBNAdd_1x1_spl(
output2 = activation(output2);
output3 = activation(output3);
#endif
int outpos_main = mul24(out_c , old_w);
int2 output_pos0 = (int2)(outpos_main + out_w0, out_nh);
if (out_w0 < old_w) {
write_imageh(output_image, output_pos0, output0);
}
int2 output_pos1 = (int2)(outpos_main + out_w1, out_nh);
if (out_w1 < old_w){
write_imageh(output_image, output_pos1, output1);
}
int2 output_pos2 = (int2)(outpos_main + out_w2, out_nh);
if (out_w2 < old_w){
write_imageh(output_image, output_pos2, output2);
}
int2 output_pos3 = (int2)(outpos_main + out_w3, out_nh);
if (out_w3 < old_w){
write_imageh(output_image, output_pos3, output3);
}
......
src/operators/kernel/cl/conv_add_bn_relu_kernel.cpp
浏览文件 @ d6c620b9
......@@ -130,7 +130,12 @@ bool ConvAddBNReluKernel<GPU_CL, float>::Init(
const std::string conv_kernel_file = "conv_kernel.cl";
const std::string wino_kernel_file = "winograd_transform.cl";
const std::string build_options = "-DBIASE -DBATCH_NORM -DRELU";
std::string build_options = "-DBATCH_NORM -DRELU";
if (param->Output()->dims() == param->Bias()->dims()) {
build_options += " -DBIASE_ELE";
} else {
build_options += " -DBIASE_CH";
}
/*
if (param->Filter()->dims()[2] == 1 &&
......
src/operators/kernel/cl/conv_add_kernel.cpp
浏览文件 @ d6c620b9
......@@ -37,7 +37,12 @@ bool ConvAddKernel<GPU_CL, float>::Init(FusionConvAddParam<GPU_CL> *param) {
const std::string conv_kernel_file = "conv_kernel.cl";
const std::string wino_kernel_file = "winograd_transform.cl";
const std::string build_options = "-DBIASE";
std::string build_options;
if (param->Output()->dims() == param->Bias()->dims()) {
build_options = "-DBIASE_ELE";
} else {
build_options = "-DBIASE_CH";
}
if (param->Filter()->dims()[2] == 1 && param->Filter()->dims()[3] == 1) {
param->ExecMode() = ConvParam<GPU_CL>::EXEC_SLIDINGWINDOW1x1_FLOAT;
......
src/operators/kernel/cl/conv_add_relu_kernel.cpp
浏览文件 @ d6c620b9
......@@ -38,7 +38,12 @@ bool ConvAddReluKernel<GPU_CL, float>::Init(
const std::string conv_kernel_file = "conv_kernel.cl";
const std::string wino_kernel_file = "winograd_transform.cl";
const std::string build_options = "-DBIASE -DRELU";
std::string build_options = "-DRELU";
if (param->Output()->dims() == param->Bias()->dims()) {
build_options += " -DBIASE_ELE";
} else {
build_options += " -DBIASE_CH";
}
if (param->Filter()->dims()[2] == 1 && param->Filter()->dims()[3] == 1) {
param->ExecMode() = ConvParam<GPU_CL>::EXEC_SLIDINGWINDOW1x1_FLOAT;
......
src/operators/kernel/cl/conv_bn_add_relu_kernel.cpp
浏览文件 @ d6c620b9
......@@ -102,7 +102,12 @@ bool ConvBNAddReluKernel<GPU_CL, float>::Init(
const std::string conv_kernel_file = "conv_kernel.cl";
const std::string wino_kernel_file = "winograd_transform.cl";
const std::string build_options = "-DBIASE -DBATCH_NORM -DRELU";
std::string build_options = "-DBATCH_NORM -DRELU";
if (param->Output()->dims() == param->Bias()->dims()) {
build_options += " -DBIASE_ELE";
} else {
build_options += " -DBIASE_CH";
}
if (param->Filter()->dims()[2] == 1 && param->Filter()->dims()[3] == 1) {
param->ExecMode() = ConvParam<GPU_CL>::EXEC_SLIDINGWINDOW1x1_FLOAT;
......
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