mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-15 02:27:57 +00:00
236f946292
* convnd_fwd fp16 example
* update example
* update example
* update instance
* updating refernce conv
* update reference conv
* update conv fwd profiler
* update conv 1d and 3d instance
* update include path
* clean
* update profiler for conv bwd data and weight
* update conv bwd weight
* clean
* update conv example
* update profiler for conv bwd weight
* update ckprofiler for conv bwd data
* fix reference conv bwd data bug; update conv bwd data test
* update examples
* fix initialization issue
* update test for conv fwd
* clean
* clean
* remove test case too sensitive to error threshhold
* fix test
* clean
* fix build
* adding conv multiple d
* adding conv multiple D
* add matrix padder
* add gemm padding to convnd
* adding group conv
* update gemm multi-d
* refactor
* refactor
* refactor
* clean
* clean
* refactor
* refactor
* reorg
* add ds
* add bias
* clean
* add G
* adding group
* adding group
* adding group
* update Tensor
* clean
* update example
* update DeviceGemmMultipleD_Xdl_CShuffle
* update conv bwd-data and bwd-weight
* upate contraction example
* update gemm and batch gemm with e permute
* fix example build
* instance for grouped conv1d
* update example
* adding group conv instance
* update gemm bilinear instance
* update gemm+add+add+fastgelu instance
* update profiler
* update profiler
* update test
* update test and client example
* clean
* add grouped conv into profiler
* update profiler
* clean
* add test grouped conv, update all conv test to gtest
* update test
[ROCm/composable_kernel commit: 500fa99512]
164 lines
8.1 KiB
C++
164 lines
8.1 KiB
C++
// SPDX-License-Identifier: MIT
|
|
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
|
|
|
|
#include <iostream>
|
|
#include <numeric>
|
|
#include <initializer_list>
|
|
#include <cstdlib>
|
|
|
|
#include "profiler/include/profile_grouped_gemm_impl.hpp"
|
|
|
|
enum struct GemmMatrixLayout
|
|
{
|
|
MK_KN_MN, // 0
|
|
MK_NK_MN, // 1
|
|
KM_KN_MN, // 2
|
|
KM_NK_MN, // 3
|
|
MK_KN_NM, // 4
|
|
MK_NK_NM, // 5
|
|
KM_KN_NM, // 6
|
|
KM_NK_NM, // 7
|
|
};
|
|
|
|
enum struct GemmDataType
|
|
{
|
|
F32_F32_F32, // 0
|
|
F16_F16_F16, // 1
|
|
BF16_BF16_BF16, // 2
|
|
INT8_INT8_INT8, // 3
|
|
};
|
|
|
|
std::vector<int> argToIntArray(char* input)
|
|
{
|
|
std::vector<int> out;
|
|
|
|
std::istringstream in(input);
|
|
|
|
std::string item;
|
|
|
|
while(std::getline(in, item, ','))
|
|
{
|
|
out.push_back(std::stoi(item));
|
|
}
|
|
|
|
return out;
|
|
}
|
|
|
|
int profile_grouped_gemm(int argc, char* argv[])
|
|
{
|
|
if(!(argc == 14))
|
|
{
|
|
printf("arg1: tensor operation (grouped_gemm: Grouped GEMM)\n");
|
|
printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
|
|
printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
|
|
printf(" 1: A[m, k] * B[n, k] = C[m, n];\n");
|
|
printf(" 2: A[k, m] * B[k, n] = C[m, n];\n");
|
|
printf(" 3: A[k, m] * B[n, k] = C[m, n])\n");
|
|
printf("arg4: verification (0: no; 1: yes)\n");
|
|
printf("arg5: initialization (0: no init; 1: integer value; 2: decimal value)\n");
|
|
printf("arg6: print tensor value (0: no; 1: yes)\n");
|
|
printf("arg7: time kernel (0=n0, 1=yes)\n");
|
|
printf("arg8 to 13: Ms, Ns, Ks, StrideAs, StrideBs, StrideCs (e.g., 256,256 128,128 64,64 "
|
|
"64,64 64,64 128,128)\n");
|
|
exit(1);
|
|
}
|
|
|
|
const auto data_type = static_cast<GemmDataType>(std::stoi(argv[2]));
|
|
const auto layout = static_cast<GemmMatrixLayout>(std::stoi(argv[3]));
|
|
const bool do_verification = std::stoi(argv[4]);
|
|
const int init_method = std::stoi(argv[5]);
|
|
const bool do_log = std::stoi(argv[6]);
|
|
const bool time_kernel = std::stoi(argv[7]);
|
|
|
|
const auto Ms = argToIntArray(argv[8]);
|
|
const auto Ns = argToIntArray(argv[9]);
|
|
const auto Ks = argToIntArray(argv[10]);
|
|
|
|
const auto StrideAs = argToIntArray(argv[11]);
|
|
const auto StrideBs = argToIntArray(argv[12]);
|
|
const auto StrideCs = argToIntArray(argv[13]);
|
|
|
|
if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::MK_KN_MN)
|
|
{
|
|
ck::profiler::profile_grouped_gemm_impl<ck::half_t,
|
|
ck::half_t,
|
|
ck::half_t,
|
|
float,
|
|
ck::tensor_layout::gemm::RowMajor,
|
|
ck::tensor_layout::gemm::RowMajor,
|
|
ck::tensor_layout::gemm::RowMajor>(do_verification,
|
|
init_method,
|
|
do_log,
|
|
time_kernel,
|
|
Ms,
|
|
Ns,
|
|
Ks,
|
|
StrideAs,
|
|
StrideBs,
|
|
StrideCs);
|
|
}
|
|
else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::MK_NK_MN)
|
|
{
|
|
ck::profiler::profile_grouped_gemm_impl<ck::half_t,
|
|
ck::half_t,
|
|
ck::half_t,
|
|
float,
|
|
ck::tensor_layout::gemm::RowMajor,
|
|
ck::tensor_layout::gemm::ColumnMajor,
|
|
ck::tensor_layout::gemm::RowMajor>(do_verification,
|
|
init_method,
|
|
do_log,
|
|
time_kernel,
|
|
Ms,
|
|
Ns,
|
|
Ks,
|
|
StrideAs,
|
|
StrideBs,
|
|
StrideCs);
|
|
}
|
|
else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::KM_KN_MN)
|
|
{
|
|
ck::profiler::profile_grouped_gemm_impl<ck::half_t,
|
|
ck::half_t,
|
|
ck::half_t,
|
|
float,
|
|
ck::tensor_layout::gemm::ColumnMajor,
|
|
ck::tensor_layout::gemm::RowMajor,
|
|
ck::tensor_layout::gemm::RowMajor>(do_verification,
|
|
init_method,
|
|
do_log,
|
|
time_kernel,
|
|
Ms,
|
|
Ns,
|
|
Ks,
|
|
StrideAs,
|
|
StrideBs,
|
|
StrideCs);
|
|
}
|
|
else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::KM_NK_MN)
|
|
{
|
|
ck::profiler::profile_grouped_gemm_impl<ck::half_t,
|
|
ck::half_t,
|
|
ck::half_t,
|
|
float,
|
|
ck::tensor_layout::gemm::ColumnMajor,
|
|
ck::tensor_layout::gemm::ColumnMajor,
|
|
ck::tensor_layout::gemm::RowMajor>(do_verification,
|
|
init_method,
|
|
do_log,
|
|
time_kernel,
|
|
Ms,
|
|
Ns,
|
|
Ks,
|
|
StrideAs,
|
|
StrideBs,
|
|
StrideCs);
|
|
}
|
|
else
|
|
{
|
|
throw std::runtime_error("wrong! this GEMM data_type & layout is not implemented");
|
|
}
|
|
|
|
return 0;
|
|
}
|