// SPDX-License-Identifier: MIT // Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved. #include #include #include #include #include "profiler/include/profile_batched_gemm_gemm_impl.hpp" using F16 = ck::half_t; using F32 = float; using Row = ck::tensor_layout::gemm::RowMajor; using Col = ck::tensor_layout::gemm::ColumnMajor; int profile_batched_gemm_gemm(int argc, char* argv[]) { enum struct GemmMatrixLayout { MK_NK_NO_MO, // 0 MK_NK_ON_MO, // 0 }; enum struct GemmDataType { F32_F32_F32_F32, // 0 F16_F16_F16_F16, // 1 }; GemmDataType data_type = GemmDataType::F16_F16_F16_F16; GemmMatrixLayout layout = GemmMatrixLayout::MK_NK_NO_MO; bool do_verification = true; int init_method = 1; bool do_log = 0; bool time_kernel = false; // GEMM shape ck::index_t M = 1024; ck::index_t N = 1024; ck::index_t K = 64; ck::index_t O = 128; ck::index_t BatchCount = 4; ck::index_t StrideA0 = -1; ck::index_t StrideB0 = -1; ck::index_t StrideB1 = -1; ck::index_t StrideE1 = -1; ck::index_t BatchStrideA0 = -1; ck::index_t BatchStrideB0 = -1; ck::index_t BatchStrideB1 = -1; ck::index_t BatchStrideE1 = -1; if(argc == 8) { data_type = static_cast(std::stoi(argv[2])); layout = static_cast(std::stoi(argv[3])); do_verification = std::stoi(argv[4]); init_method = std::stoi(argv[5]); do_log = std::stoi(argv[6]); time_kernel = std::stoi(argv[7]); } else if(argc == 13) { data_type = static_cast(std::stoi(argv[2])); layout = static_cast(std::stoi(argv[3])); do_verification = std::stoi(argv[4]); init_method = std::stoi(argv[5]); do_log = std::stoi(argv[6]); time_kernel = std::stoi(argv[7]); M = std::stoi(argv[8]); N = std::stoi(argv[9]); K = std::stoi(argv[10]); O = std::stoi(argv[11]); BatchCount = std::stoi(argv[12]); } else if(argc == 21) { data_type = static_cast(std::stoi(argv[2])); layout = static_cast(std::stoi(argv[3])); do_verification = std::stoi(argv[4]); init_method = std::stoi(argv[5]); do_log = std::stoi(argv[6]); time_kernel = std::stoi(argv[7]); M = std::stoi(argv[8]); N = std::stoi(argv[9]); K = std::stoi(argv[10]); O = std::stoi(argv[11]); BatchCount = std::stoi(argv[12]); StrideA0 = std::stoi(argv[13]); StrideB0 = std::stoi(argv[14]); StrideB1 = std::stoi(argv[15]); StrideE1 = std::stoi(argv[16]); BatchStrideA0 = std::stoi(argv[17]); BatchStrideB0 = std::stoi(argv[18]); BatchStrideB1 = std::stoi(argv[19]); BatchStrideE1 = std::stoi(argv[20]); } else { printf("arg1: tensor operation (batched_gemm_gemm: Batched_GEMM+Gemm)\n"); printf("arg2: data type (1: fp16)\n"); printf("arg3: matrix layout (0: Relu(A0[m, k] * B0[n, k] + D0[m, n]) * B1[n, o] + D1[m, o] " "= E1[m, o]; 1: Relu(A0[m, k] * B0[n, k] + D0[m, n]) * B1[o, n] + D1[m, o] = E1[m, " "o];)\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=no, 1=yes)\n"); printf("arg8 to 12: M, N, K, O, Batch\n"); printf("arg13 to 16: StrideA0, StrideB0, StrideB1, StrideE1\n"); printf("arg17 to 20: BatchStrideA0, BatchStrideB0, BatchStrideB1, BatchStrideE1 \n"); exit(1); } if(data_type == GemmDataType::F16_F16_F16_F16 && layout == GemmMatrixLayout::MK_NK_NO_MO) { ck::profiler::profile_batched_gemm_gemm_impl // E1Layout, (do_verification, init_method, do_log, time_kernel, M, N, K, O, BatchCount, StrideA0, StrideB0, StrideB1, StrideE1, BatchStrideA0, BatchStrideB0, BatchStrideB1, BatchStrideE1); } else if(data_type == GemmDataType::F16_F16_F16_F16 && layout == GemmMatrixLayout::MK_NK_ON_MO) { ck::profiler::profile_batched_gemm_gemm_impl // E1Layout, (do_verification, init_method, do_log, time_kernel, M, N, K, O, BatchCount, StrideA0, StrideB0, StrideB1, StrideE1, BatchStrideA0, BatchStrideB0, BatchStrideB1, BatchStrideE1); } else { throw std::runtime_error("wrong! this data_type & layout is not implemented"); } return 0; }