#include "ck/tensor_operation/gpu/device/tensor_layout.hpp" #include "profiler/profile_grouped_conv_fwd_outelementop_impl.hpp" #include "ck/utility/data_type.hpp" #include "profiler_operation_registry.hpp" #include enum struct ConvLayout { GNHWC_GKYXC_GNHWK = 0, NHWGC_GKYXC_NHWGK = 1 }; enum struct OutElementOp { ConvScale = 0, ConvInvScale = 1 }; enum struct ConvDataType { F8_F8_F8 = 0, BF8_BF8_F8 = 1, F8_BF8_F8 = 2, BF8_F8_F8 = 3 }; #define OP_NAME "grouped_conv_fwd_outelementop" #define OP_DESC "Grouped Convolution Forward+Elementwise Operation" static void print_helper_msg() { // clang-format off std::cout << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n" << "arg2: data type (0: Input fp8, Weight fp8, Output fp8\n" << " 1: Input bf8, Weight bf8, Output fp8\n" << " 2: Input fp8, Weight bf8, Output fp8\n" << " 3: Input bf8, Weight fp8, Output fp8)\n" << "arg3: element-wise operation (0: ConvScale\n" << " 1: ConvInvScale)\n" << "arg4: tensor layout (0: Input[G, N, Hi, Wi, C], Weight[G, K, Y, X, C], Output[G, N, Ho, Wo, K]\n" << " 1: Input[N, Hi, Wi, G, C], Weight[G, K, Y, X, C], Output[N, Ho, Wo, G, K])\n" << "arg5: verification (0: no, 1: yes)\n" << "arg6: initialization (0: no init, 1: integer value, 2: decimal value)\n" << "arg7: print tensor value (0: no; 1: yes)\n" << "arg8: time kernel (0: no, 1: yes)\n" << ck::utils::conv::get_conv_param_parser_helper_msg() << std::endl; // clang-format on } int grouped_conv_fwd_outelementop(int argc, char* argv[]) { // 9 total, 1 for num_dim_spatial if(argc < 10) { print_helper_msg(); return 1; } const auto data_type = static_cast(std::stoi(argv[2])); const auto op = static_cast(std::stoi(argv[3])); const auto layout = static_cast(std::stoi(argv[4])); const bool do_verification = std::stoi(argv[5]); const int init_method = std::stoi(argv[6]); const bool do_log = std::stoi(argv[7]); const bool time_kernel = std::stoi(argv[8]); const int num_dim_spatial = std::stoi(argv[9]); // 8 for control, 1 for num_dim_spatial, 4 for G/N/K/C, and 6 * num_dim_spatial + 1 for argv[0] 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, 10, argv); using F8 = ck::f8_t; using BF8 = ck::bf8_t; using GKZYXC = ck::tensor_layout::convolution::GKZYXC; using NDHWGC = ck::tensor_layout::convolution::NDHWGC; using NDHWGK = ck::tensor_layout::convolution::NDHWGK; using ConvScale = ck::tensor_operation::element_wise::ConvScale; using ConvInvScale = ck::tensor_operation::element_wise::ConvInvscale; constexpr auto I3 = ck::Number<3>{}; auto profile = [&](auto num_dim_spatial_tmp, auto in_layout, auto wei_layout, auto out_layout, auto in_type, auto wei_type, auto out_type, auto out_element_op, auto a_compute_type, auto b_compute_type) { constexpr ck::index_t NDimSpatial = num_dim_spatial_tmp.value; using InLayout = decltype(in_layout); using WeiLayout = decltype(wei_layout); using OutLayout = decltype(out_layout); using InDataType = decltype(in_type); using WeiDataType = decltype(wei_type); using OutDataType = decltype(out_type); using OutElementOp = decltype(out_element_op); using AComputeType = decltype(a_compute_type); using BComputeType = decltype(b_compute_type); bool pass = ck::profiler::profile_grouped_conv_fwd_outelementop_impl( do_verification, init_method, do_log, time_kernel, params); return pass ? 0 : 1; }; if(num_dim_spatial == 3 && layout == ConvLayout::NHWGC_GKYXC_NHWGK) { if(op == OutElementOp::ConvScale) { if(data_type == ConvDataType::F8_F8_F8) { return profile( I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F8{}, F8{}, F8{}, ConvScale{}, F8{}, F8{}); } else if(data_type == ConvDataType::BF8_BF8_F8) { return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF8{}, BF8{}, F8{}, ConvScale{}, BF8{}, BF8{}); } else if(data_type == ConvDataType::F8_BF8_F8) { return profile( I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F8{}, BF8{}, F8{}, ConvScale{}, F8{}, BF8{}); } else if(data_type == ConvDataType::BF8_F8_F8) { return profile( I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF8{}, F8{}, F8{}, ConvScale{}, BF8{}, F8{}); } } else if(op == OutElementOp::ConvInvScale) { if(data_type == ConvDataType::F8_F8_F8) { return profile( I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F8{}, F8{}, F8{}, ConvInvScale{}, F8{}, F8{}); } else if(data_type == ConvDataType::BF8_BF8_F8) { return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF8{}, BF8{}, F8{}, ConvInvScale{}, BF8{}, BF8{}); } else if(data_type == ConvDataType::F8_BF8_F8) { return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F8{}, BF8{}, F8{}, ConvInvScale{}, F8{}, BF8{}); } else if(data_type == ConvDataType::BF8_F8_F8) { return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF8{}, F8{}, F8{}, ConvInvScale{}, BF8{}, F8{}); } } } std::cout << "this data_type & layout is not implemented" << std::endl; return 1; } REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, grouped_conv_fwd_outelementop);