// SPDX-License-Identifier: MIT // Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved. #include #include #include #include #include "profiler/profile_grouped_conv_bwd_data_impl.hpp" #include "profiler_operation_registry.hpp" namespace { enum struct ConvLayout { GNHWC_GKYXC_GNHWK, // 0 NHWGC_GKYXC_NHWGK, // 1 NGCHW_GKYXC_NGKHW, // 2 NGCHW_GKCYX_NGKHW, // 3 }; enum struct ConvDataType { F32_F32_F32, // 0 F16_F16_F16, // 1 BF16_BF16_BF16, // 2 }; #define OP_NAME "grouped_conv_bwd_data" #define OP_DESC "Grouped Convolution Backward Data" static void print_helper_msg() { std::cout // clang-format off << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n" << "arg2: data type (0: Output fp32, Weight fp32, Input fp32\n" << " 1: Output fp16, Weight fp16, Input fp16\n" << " 2: Output bf16, Weight bf16, Input bf16\n" << "arg3: tensor layout (0: Output[G, N, Ho, Wo, C], Weight[G, K, Y, X, C], Input[G, N, Hi, Wi, K]\n" << " 1: Output[N, Ho, Wo, G, C], Weight[G, K, Y, X, C], Input[N, Hi, Wi, G, K])\n" << " 2: Output[N, G, C, Ho, Wo], Weight[G, K, Y, X, C], Input[N, G, K, Hi, Wi])\n" << " 3: Output[N, G, C, Ho, Wo], Weight[G, K, C, Y, X], Input[N, G, K, Hi, Wi])\n" << "arg4: verification (0: no, 1: yes)\n" << "arg5: initialization (0: no init, 1: integer value, 2: decimal value)\n" << "arg6: print tensor value (0: no; 1: yes)\n" << "arg7: time kernel (0: no, 1: yes)\n" << ck::utils::conv::get_conv_param_parser_helper_msg() << std::endl; // clang-format on } } // namespace int profile_grouped_conv_bwd_data(int argc, char* argv[]) { // 8 for control, 1 for num_dim_spatial if(argc < 9) { print_helper_msg(); return 1; } const auto data_type = static_cast(std::stoi(argv[2])); const auto layout = static_cast(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 int num_dim_spatial = std::stoi(argv[8]); // 8 for control, 1 for num_dim_spatial, 4 for G/N/K/C, and 6 * num_dim_spatial, 1 for split-K if(argc != 8 + 1 + 4 + 6 * num_dim_spatial + 1) { print_helper_msg(); return 1; } const auto params = ck::utils::conv::parse_conv_param(num_dim_spatial, 9, argv); ck::index_t split_k = std::stoi(argv[8 + 1 + 4 + 6 * num_dim_spatial]); using F32 = float; using F16 = ck::half_t; using BF16 = ck::bhalf_t; using namespace ck::tensor_layout::convolution; constexpr auto I2 = ck::Number<2>{}; constexpr auto I3 = ck::Number<3>{}; auto profile = [&](auto num_dim_spatial_tmp, auto out_layout, auto wei_layout, auto in_layout, auto wei_type, auto out_type, auto in_type) { constexpr ck::index_t NDimSpatial = num_dim_spatial_tmp.value; using OutLayout = decltype(out_layout); using WeiLayout = decltype(wei_layout); using InLayout = decltype(in_layout); using OutDataType = decltype(out_type); using WeiDataType = decltype(wei_type); using InDataType = decltype(in_type); bool pass = ck::profiler::profile_grouped_conv_bwd_data_impl( do_verification, init_method, do_log, time_kernel, params, split_k); return pass ? 0 : 1; }; if(num_dim_spatial == 2) { if(layout == ConvLayout::GNHWC_GKYXC_GNHWK) { if(data_type == ConvDataType::F32_F32_F32) { return profile(I2, GNHWK{}, GKYXC{}, GNHWC{}, F32{}, F32{}, F32{}); } else if(data_type == ConvDataType::F16_F16_F16) { return profile(I2, GNHWK{}, GKYXC{}, GNHWC{}, F16{}, F16{}, F16{}); } else if(data_type == ConvDataType::BF16_BF16_BF16) { return profile(I2, GNHWK{}, GKYXC{}, GNHWC{}, BF16{}, BF16{}, BF16{}); } } else if(layout == ConvLayout::NHWGC_GKYXC_NHWGK) { if(data_type == ConvDataType::F32_F32_F32) { return profile(I2, NHWGK{}, GKYXC{}, NHWGC{}, F32{}, F32{}, F32{}); } else if(data_type == ConvDataType::F16_F16_F16) { return profile(I2, NHWGK{}, GKYXC{}, NHWGC{}, F16{}, F16{}, F16{}); } else if(data_type == ConvDataType::BF16_BF16_BF16) { return profile(I2, NHWGK{}, GKYXC{}, NHWGC{}, BF16{}, BF16{}, BF16{}); } } else if(layout == ConvLayout::NGCHW_GKYXC_NGKHW) { if(data_type == ConvDataType::F32_F32_F32) { return profile(I2, NGKHW{}, GKYXC{}, NGCHW{}, F32{}, F32{}, F32{}); } else if(data_type == ConvDataType::F16_F16_F16) { return profile(I2, NGKHW{}, GKYXC{}, NGCHW{}, F16{}, F16{}, F16{}); } else if(data_type == ConvDataType::BF16_BF16_BF16) { return profile(I2, NGKHW{}, GKYXC{}, NGCHW{}, BF16{}, BF16{}, BF16{}); } } else if(layout == ConvLayout::NGCHW_GKCYX_NGKHW) { if(data_type == ConvDataType::F32_F32_F32) { return profile(I2, NGKHW{}, GKCYX{}, NGCHW{}, F32{}, F32{}, F32{}); } else if(data_type == ConvDataType::F16_F16_F16) { return profile(I2, NGKHW{}, GKCYX{}, NGCHW{}, F16{}, F16{}, F16{}); } else if(data_type == ConvDataType::BF16_BF16_BF16) { return profile(I2, NGKHW{}, GKCYX{}, NGCHW{}, BF16{}, BF16{}, BF16{}); } } } else if(num_dim_spatial == 3) { if(layout == ConvLayout::GNHWC_GKYXC_GNHWK) { if(data_type == ConvDataType::F32_F32_F32) { return profile(I3, GNDHWK{}, GKZYXC{}, GNDHWC{}, F32{}, F32{}, F32{}); } else if(data_type == ConvDataType::F16_F16_F16) { return profile(I3, GNDHWK{}, GKZYXC{}, GNDHWC{}, F16{}, F16{}, F16{}); } else if(data_type == ConvDataType::BF16_BF16_BF16) { return profile(I3, GNDHWK{}, GKZYXC{}, GNDHWC{}, BF16{}, BF16{}, BF16{}); } } else if(layout == ConvLayout::NHWGC_GKYXC_NHWGK) { if(data_type == ConvDataType::F32_F32_F32) { return profile(I3, NDHWGK{}, GKZYXC{}, NDHWGC{}, F32{}, F32{}, F32{}); } else if(data_type == ConvDataType::F16_F16_F16) { return profile(I3, NDHWGK{}, GKZYXC{}, NDHWGC{}, F16{}, F16{}, F16{}); } else if(data_type == ConvDataType::BF16_BF16_BF16) { return profile(I3, NDHWGK{}, GKZYXC{}, NDHWGC{}, BF16{}, BF16{}, BF16{}); } } else if(layout == ConvLayout::NGCHW_GKYXC_NGKHW) { if(data_type == ConvDataType::F32_F32_F32) { return profile(I3, NGKDHW{}, GKZYXC{}, NGCDHW{}, F32{}, F32{}, F32{}); } else if(data_type == ConvDataType::F16_F16_F16) { return profile(I3, NGKDHW{}, GKZYXC{}, NGCDHW{}, F16{}, F16{}, F16{}); } else if(data_type == ConvDataType::BF16_BF16_BF16) { return profile(I3, NGKDHW{}, GKZYXC{}, NGCDHW{}, BF16{}, BF16{}, BF16{}); } } else if(layout == ConvLayout::NGCHW_GKYXC_NGKHW) { if(data_type == ConvDataType::F32_F32_F32) { return profile(I3, NGKDHW{}, GKCZYX{}, NGCDHW{}, F32{}, F32{}, F32{}); } else if(data_type == ConvDataType::F16_F16_F16) { return profile(I3, NGKDHW{}, GKCZYX{}, NGCDHW{}, F16{}, F16{}, F16{}); } else if(data_type == ConvDataType::BF16_BF16_BF16) { return profile(I3, NGKDHW{}, GKCZYX{}, NGCDHW{}, BF16{}, BF16{}, BF16{}); } } } std::cout << "this data_type & layout is not implemented" << std::endl; return 1; } REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_grouped_conv_bwd_data);