// SPDX-License-Identifier: MIT // Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved. #pragma once #include #include #include #include "ck/ck.hpp" #include "ck/ck.hpp" #include "ck/tensor_operation/gpu/device/device_conv_fwd.hpp" #include "ck/tensor_operation/gpu/device/tensor_layout.hpp" #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp" #include "ck/library/tensor_operation_instance/gpu/convolution_backward_weight.hpp" #include "ck/library/reference_tensor_operation/cpu/reference_conv_bwd_weight.hpp" #include "ck/library/utility/check_err.hpp" #include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp" #include "ck/library/utility/convolution_parameter.hpp" #include "ck/library/utility/device_memory.hpp" #include "ck/library/utility/host_tensor.hpp" #include "ck/library/utility/host_tensor_generator.hpp" namespace ck { namespace profiler { template void show_data_nhwc_layout(Tensor& nhwc) { std::cout << "["; for(int n = 0; n < ck::type_convert(nhwc.GetLengths()[0]); n++) { std::cout << "["; for(int hi = 0; hi < ck::type_convert(nhwc.GetLengths()[2]); hi++) { std::cout << "["; for(int wi = 0; wi < ck::type_convert(nhwc.GetLengths()[3]); wi++) { std::cout << "["; for(int c = 0; c < ck::type_convert(nhwc.GetLengths()[1]); c++) { std::cout << static_cast(nhwc(n, c, hi, wi)) << " "; } std::cout << "]"; } std::cout << "]"; } std::cout << "]"; } std::cout << "]"; } template bool profile_conv_bwd_weight_impl(int do_verification, int init_method, bool do_log, bool time_kernel, const ck::utils::conv::ConvParam& conv_param, ck::index_t split_k) { using InElementOp = ck::tensor_operation::element_wise::PassThrough; using WeiElementOp = ck::tensor_operation::element_wise::PassThrough; using OutElementOp = ck::tensor_operation::element_wise::PassThrough; const auto in_element_op = InElementOp{}; const auto wei_element_op = WeiElementOp{}; const auto out_element_op = OutElementOp{}; const auto in_g_n_c_wis_desc = ck::utils::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed(conv_param); const auto wei_g_k_c_xs_desc = ck::utils::conv::make_weight_host_tensor_descriptor_g_k_c_xs_packed(conv_param); const auto out_g_n_k_wos_desc = ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed(conv_param); Tensor input(in_g_n_c_wis_desc); Tensor weight_host_result(wei_g_k_c_xs_desc); Tensor weight_device_result(wei_g_k_c_xs_desc); Tensor output(out_g_n_k_wos_desc); std::cout << "input: " << input.GetDesc() << std::endl; std::cout << "weight: " << weight_host_result.GetDesc() << std::endl; std::cout << "output: " << output.GetDesc() << std::endl; switch(init_method) { case 0: break; case 1: input.GenerateTensorValue(GeneratorTensor_2{-5, 5}); output.GenerateTensorValue(GeneratorTensor_2{-5, 5}); break; default: input.GenerateTensorValue(GeneratorTensor_3{0.0, 1.0}); output.GenerateTensorValue(GeneratorTensor_3{-0.5, 0.5}); } DeviceMem in_device_buf(input.GetMemorySize()); DeviceMem wei_device_buf(weight_device_result.GetMemorySize()); DeviceMem out_device_buf(output.GetMemorySize()); in_device_buf.ToDevice(input.data()); out_device_buf.ToDevice(output.data()); if(do_verification) { auto ref_conv = ck::tensor_operation::host::ReferenceConvBwdWeight{}; auto ref_invoker = ref_conv.MakeInvoker(); auto ref_argument = ref_conv.MakeArgument(input, weight_host_result, output, conv_param.conv_filter_strides_, conv_param.conv_filter_dilations_, conv_param.input_left_pads_, conv_param.input_right_pads_, in_element_op, wei_element_op, out_element_op); ref_invoker.Run(ref_argument); } using DeviceOp = ck::tensor_operation::device::DeviceConvBwdWeight; // get device op instances const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory< DeviceOp>::GetInstances(); std::cout << "found " << op_ptrs.size() << " instances" << std::endl; std::string best_op_name; float best_avg_time = 0; float best_tflops = 0; float best_gb_per_sec = 0; // profile device Conv instances bool all_pass = true; for(auto& op_ptr : op_ptrs) { auto argument_ptr = op_ptr->MakeArgumentPointer(in_device_buf.GetDeviceBuffer(), wei_device_buf.GetDeviceBuffer(), out_device_buf.GetDeviceBuffer(), conv_param.N_, conv_param.K_, conv_param.C_, conv_param.input_spatial_lengths_, conv_param.filter_spatial_lengths_, conv_param.output_spatial_lengths_, conv_param.conv_filter_strides_, conv_param.conv_filter_dilations_, conv_param.input_left_pads_, conv_param.input_right_pads_, in_element_op, wei_element_op, out_element_op, split_k); if(op_ptr->IsSupportedArgument(argument_ptr.get())) { // using atomic add, so need to reset input wei_device_buf.SetZero(); std::string op_name = op_ptr->GetTypeString(); auto invoker_ptr = op_ptr->MakeInvokerPointer(); float avg_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, time_kernel}); std::size_t flop = conv_param.GetFlops(); std::size_t num_btype = conv_param.GetByte(); float tflops = static_cast(flop) / 1.E9 / avg_time; float gb_per_sec = num_btype / 1.E6 / avg_time; std::cout << "Perf: " << std::setw(10) << avg_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, " << op_name << std::endl; if(tflops > best_tflops) { best_op_name = op_name; best_tflops = tflops; best_avg_time = avg_time; best_gb_per_sec = gb_per_sec; } if(do_verification) { wei_device_buf.FromDevice(weight_device_result.data()); bool pass = ck::utils::check_err(weight_host_result, weight_device_result); if(!pass) { std::cout << "Fail info:" << op_ptr->GetTypeString() << std::endl; } all_pass &= pass; if(do_log) { std::cout << "in : "; show_data_nhwc_layout(output); std::cout << std::endl; std::cout << "wei: "; show_data_nhwc_layout(weight_host_result); std::cout << std::endl; std::cout << "out : "; show_data_nhwc_layout(input); std::cout << std::endl; std::cout << "wei_device: "; show_data_nhwc_layout(weight_device_result); std::cout << std::endl; } } } else { std::cout << op_ptr->GetTypeString() << " does not support this problem" << std::endl; } } std::cout << "Best configuration parameters:" << "\nname: " << best_op_name << "\navg_time: " << best_avg_time << "\ntflops: " << best_tflops << "\nGB/s: " << best_gb_per_sec << std::endl; return all_pass; } } // namespace profiler } // namespace ck