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https://github.com/ROCm/composable_kernel.git
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128 lines
4.9 KiB
C++
128 lines
4.9 KiB
C++
#include <algorithm>
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#include <cstdlib>
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#include <half.hpp>
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#include <iostream>
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#include <numeric>
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#include <tuple>
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#include <vector>
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#include "cgemm_util.hpp"
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#include "config.hpp"
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#include "print.hpp"
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#include "device.hpp"
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#include "device_tensor.hpp"
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#include "device_cgemm_4gemm_xdl_cshuffle.hpp"
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#include "element_wise_operation.hpp"
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#include "gemm_specialization.hpp"
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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using DeviceCGemmNoOpPtr =
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ck::tensor_operation::device::DeviceCGemmPtr<ck::tensor_operation::element_wise::PassThrough,
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ck::tensor_operation::element_wise::PassThrough,
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ck::tensor_operation::element_wise::PassThrough>;
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namespace ck {
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namespace tensor_operation {
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namespace device {
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namespace device_cgemm_instance {
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void add_device_cgemm_4gemm_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(
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std::vector<DeviceCGemmNoOpPtr>&);
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void add_device_cgemm_4gemm_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(
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std::vector<DeviceCGemmNoOpPtr>&);
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void add_device_cgemm_4gemm_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(
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std::vector<DeviceCGemmNoOpPtr>&);
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void add_device_cgemm_4gemm_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(
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std::vector<DeviceCGemmNoOpPtr>&);
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} // namespace device_cgemm_instance
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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int main()
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{
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using ADataType = ck::half_t;
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using BDataType = ck::half_t;
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using CDataType = ck::half_t;
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using RowMajor = ck::tensor_layout::gemm::RowMajor;
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using ColumnMajor = ck::tensor_layout::gemm::ColumnMajor;
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bool res = true;
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std::vector<DeviceCGemmNoOpPtr> cgemmPtrs;
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ck::tensor_operation::device::device_cgemm_instance::
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add_device_cgemm_4gemm_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(cgemmPtrs);
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for(auto& cgemmPtr : cgemmPtrs)
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{
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res &= ck::cgemm_util::TestCGemm<DeviceCGemmNoOpPtr,
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ADataType,
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BDataType,
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CDataType,
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ColumnMajor,
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RowMajor,
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RowMajor,
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PassThrough,
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PassThrough,
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PassThrough>{}(cgemmPtr);
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}
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cgemmPtrs.clear();
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ck::tensor_operation::device::device_cgemm_instance::
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add_device_cgemm_4gemm_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(cgemmPtrs);
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for(auto& cgemmPtr : cgemmPtrs)
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{
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res &= ck::cgemm_util::TestCGemm<DeviceCGemmNoOpPtr,
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ADataType,
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BDataType,
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CDataType,
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ColumnMajor,
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ColumnMajor,
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RowMajor,
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PassThrough,
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PassThrough,
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PassThrough>{}(cgemmPtr);
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}
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cgemmPtrs.clear();
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ck::tensor_operation::device::device_cgemm_instance::
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add_device_cgemm_4gemm_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(cgemmPtrs);
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for(auto& cgemmPtr : cgemmPtrs)
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{
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res &= ck::cgemm_util::TestCGemm<DeviceCGemmNoOpPtr,
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ADataType,
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BDataType,
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CDataType,
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RowMajor,
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RowMajor,
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RowMajor,
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PassThrough,
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PassThrough,
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PassThrough>{}(cgemmPtr);
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}
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cgemmPtrs.clear();
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ck::tensor_operation::device::device_cgemm_instance::
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add_device_cgemm_4gemm_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(cgemmPtrs);
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for(auto& cgemmPtr : cgemmPtrs)
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{
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res &= ck::cgemm_util::TestCGemm<DeviceCGemmNoOpPtr,
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ADataType,
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BDataType,
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CDataType,
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RowMajor,
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ColumnMajor,
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RowMajor,
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PassThrough,
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PassThrough,
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PassThrough>{}(cgemmPtr);
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}
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std::cout << "TestCGemm ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
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return res ? 0 : 1;
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}
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