mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-12 09:16:52 +00:00
cec69bc3bc
* Add host API * manually rebase on develop * clean * manually rebase on develop * exclude tests from all target * address review comments * update client app name * fix missing lib name * clang-format update * refactor * refactor * refactor * refactor * refactor * fix test issue * refactor * refactor * refactor * upate cmake and readme Co-authored-by: Chao Liu <chao.liu2@amd.com>
78 lines
3.5 KiB
C++
78 lines
3.5 KiB
C++
#include <iostream>
|
|
#include <numeric>
|
|
#include <initializer_list>
|
|
#include <cstdlib>
|
|
#include <stdlib.h>
|
|
#include <half.hpp>
|
|
#include <vector>
|
|
|
|
#include "client_app_impl.hpp"
|
|
|
|
int main(int argc, char* argv[])
|
|
{
|
|
if(argc != 25)
|
|
{
|
|
printf("arg1: tensor operation (conv_fwd: ForwardConvolution)\n");
|
|
printf("arg2: data type (0: fp32; 1: fp16)\n");
|
|
printf("arg3: input tensor layout (0: NCHW; 1: NHWC)\n");
|
|
printf("arg4: weight tensor layout (0: KCYX; 1: KYXC)\n");
|
|
printf("arg5: output tensor layout (0: NKHW; 1: NHWK)\n");
|
|
printf("arg6: verification (0: no; 1: yes)\n");
|
|
printf("arg7: initialization (0: no init; 1: integer value; 2: decimal value)\n");
|
|
printf("arg8: print tensor value (0: no; 1: yes)\n");
|
|
printf("arg9: time kernel (0=n0, 1=yes)\n");
|
|
printf("arg10 to 24: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, "
|
|
"RightPx\n");
|
|
exit(1);
|
|
}
|
|
|
|
const ConvDataType data_type = static_cast<ConvDataType>(std::stoi(argv[2]));
|
|
const int in_layout = static_cast<ConvInputLayout>(std::stoi(argv[3]));
|
|
const int wei_layout = static_cast<ConvWeightLayout>(std::stoi(argv[4]));
|
|
const int out_layout = static_cast<ConvOutputLayout>(std::stoi(argv[5]));
|
|
const bool do_verification = std::stoi(argv[6]);
|
|
const int init_method = std::stoi(argv[7]);
|
|
const bool do_log = std::stoi(argv[8]);
|
|
const bool time_kernel = std::stoi(argv[9]);
|
|
|
|
const ck::index_t N = std::stoi(argv[10]);
|
|
const ck::index_t K = std::stoi(argv[11]);
|
|
const ck::index_t C = std::stoi(argv[12]);
|
|
const ck::index_t Y = std::stoi(argv[13]);
|
|
const ck::index_t X = std::stoi(argv[14]);
|
|
const ck::index_t Hi = std::stoi(argv[15]);
|
|
const ck::index_t Wi = std::stoi(argv[16]);
|
|
|
|
const ck::index_t conv_stride_h = std::stoi(argv[17]);
|
|
const ck::index_t conv_stride_w = std::stoi(argv[18]);
|
|
const ck::index_t conv_dilation_h = std::stoi(argv[19]);
|
|
const ck::index_t conv_dilation_w = std::stoi(argv[20]);
|
|
const ck::index_t in_left_pad_h = std::stoi(argv[21]);
|
|
const ck::index_t in_left_pad_w = std::stoi(argv[22]);
|
|
const ck::index_t in_right_pad_h = std::stoi(argv[23]);
|
|
const ck::index_t in_right_pad_w = std::stoi(argv[24]);
|
|
|
|
const ck::index_t YEff = (Y - 1) * conv_dilation_h + 1;
|
|
const ck::index_t XEff = (X - 1) * conv_dilation_w + 1;
|
|
|
|
const ck::index_t Ho = (Hi + in_left_pad_h + in_right_pad_h - YEff) / conv_stride_h + 1;
|
|
const ck::index_t Wo = (Wi + in_left_pad_w + in_right_pad_w - XEff) / conv_stride_w + 1;
|
|
|
|
ck::app::profile_conv_fwd_impl(do_verification,
|
|
init_method,
|
|
do_log,
|
|
time_kernel,
|
|
data_type,
|
|
N,
|
|
K,
|
|
C,
|
|
std::vector<ck::index_t>{Hi, Wi},
|
|
std::vector<ck::index_t>{Y, X},
|
|
std::vector<ck::index_t>{Ho, Wo},
|
|
std::vector<ck::index_t>{conv_stride_h, conv_stride_w},
|
|
std::vector<ck::index_t>{conv_dilation_h, conv_dilation_w},
|
|
std::vector<ck::index_t>{in_left_pad_h, in_left_pad_w},
|
|
std::vector<ck::index_t>{in_right_pad_h, in_right_pad_w});
|
|
return 1;
|
|
}
|