// SPDX-License-Identifier: MIT // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. #pragma once #include #include "ck/ck.hpp" #include "ck/utility/reduction_enums.hpp" #include "ck/utility/reduction_functions_accumulate.hpp" #include "ck/tensor_operation/gpu/device/reduction_operator_mapping.hpp" #include "ck/tensor_operation/gpu/device/impl/device_pool2d_fwd_nhwc_nhwc.hpp" #include "ck/tensor_operation/gpu/device/impl/device_index_pool_bwd_impl.hpp" #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp" #include "ck/library/utility/check_err.hpp" #include "ck/library/utility/device_memory.hpp" #include "ck/library/utility/host_tensor.hpp" #include "ck/library/utility/host_tensor_generator.hpp" #include "ck/library/utility/literals.hpp" #include "ck/library/reference_tensor_operation/cpu/reference_pool_fwd.hpp" #include "ck/library/reference_tensor_operation/cpu/reference_maxpool_bwd.hpp" template bool maxpool_bwd_test(bool do_verification, bool time_kernel, ck::index_t N, ck::index_t C, ck::index_t Y, ck::index_t X, ck::index_t Hi, ck::index_t Wi, ck::index_t window_stride_h, ck::index_t window_stride_w, ck::index_t in_left_pad_h, ck::index_t in_left_pad_w, ck::index_t in_right_pad_h, ck::index_t in_right_pad_w) { using PassThrough = ck::tensor_operation::element_wise::PassThrough; using DevicePoolFwdInstance = ck::tensor_operation::device::DevicePool2dFwd_Input_N_Hi_Wi_C_Output_N_Ho_Wo_C< InDataType, // InDataType OutDataType, // OutDataType IndexDataType, // IndexDataType ComputeDataType, // ComputeDataType ck::ReduceTensorOp::MAX, true, // OutputIndex 64, // BlockSize 64, // ReduceMThreadClusterSize 1, // ReduceKThreadClusterSize 4, // ReduceMThreadSliceSize 1, // ReduceKThreadSliceSize 1>; // InSrcOutDstVectorSize using DeviceMaxPoolBwdInstance = ck::tensor_operation::device:: DeviceIndexPoolBwdImpl; const ck::index_t Ho = (Hi + in_left_pad_h + in_right_pad_h - Y) / window_stride_h + 1; const ck::index_t Wo = (Wi + in_left_pad_w + in_right_pad_w - X) / window_stride_w + 1; const std::vector window_spatial_lengths{Y, X}; const std::vector window_strides{window_stride_h, window_stride_w}; const std::vector input_left_pads{in_left_pad_h, in_left_pad_w}; const std::vector input_right_pads{in_right_pad_h, in_right_pad_w}; // tensor layout auto f_host_tensor_descriptor = [](std::size_t N_, std::size_t C_, std::size_t H, std::size_t W, auto layout) { using namespace ck::literals; if constexpr(ck::is_same::value) { return HostTensorDescriptor({N_, C_, H, W}, {C_ * H * W, H * W, W, 1_uz}); } else if constexpr(ck::is_same::value) { return HostTensorDescriptor({N_, C_, H, W}, {C_ * H * W, 1_uz, W * C_, C_}); } }; // in Tensor in_n_c_hi_wi(f_host_tensor_descriptor(N, C, Hi, Wi, InLayout{})); // out Tensor out_n_c_ho_wo_host(f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{})); Tensor out_n_c_ho_wo_device(f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{})); // indices Tensor indices_n_c_ho_wo_device( f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{})); Tensor indices_n_c_ho_wo_host( f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{})); // dout Tensor dout_n_c_ho_wo(f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{})); // din Tensor din_n_c_hi_wi_host(f_host_tensor_descriptor(N, C, Hi, Wi, InLayout{})); Tensor din_n_c_hi_wi_device(f_host_tensor_descriptor(N, C, Hi, Wi, InLayout{})); std::cout << "in_n_c_hi_wi: " << in_n_c_hi_wi.mDesc << std::endl; std::cout << "out_n_c_ho_wo: " << out_n_c_ho_wo_host.mDesc << std::endl; std::cout << "indices_n_c_ho_wo: " << indices_n_c_ho_wo_host.mDesc << std::endl; std::cout << "dout_n_c_ho_wo: " << dout_n_c_ho_wo.mDesc << std::endl; std::cout << "din_n_c_hi_wi: " << din_n_c_hi_wi_host.mDesc << std::endl; in_n_c_hi_wi.GenerateTensorValue(GeneratorTensor_3{-1.0, 1.0}); dout_n_c_ho_wo.GenerateTensorValue(GeneratorTensor_3{-1.0, 1.0}); DeviceMem in_device_buf(sizeof(InDataType) * in_n_c_hi_wi.mDesc.GetElementSpaceSize()); DeviceMem out_device_buf(sizeof(OutDataType) * out_n_c_ho_wo_device.mDesc.GetElementSpaceSize()); DeviceMem indices_device_buf(sizeof(IndexDataType) * indices_n_c_ho_wo_device.mDesc.GetElementSpaceSize()); DeviceMem dout_device_buf(sizeof(DOutDataType) * dout_n_c_ho_wo.mDesc.GetElementSpaceSize()); DeviceMem din_device_buf(sizeof(DInDataType) * din_n_c_hi_wi_device.mDesc.GetElementSpaceSize()); in_device_buf.ToDevice(in_n_c_hi_wi.mData.data()); dout_device_buf.ToDevice(dout_n_c_ho_wo.mData.data()); din_device_buf.SetZero(); auto pool_fwd = DevicePoolFwdInstance{}; auto pool_fwd_invoker_ptr = pool_fwd.MakeInvokerPointer(); auto pool_fwd_argument_ptr = pool_fwd.MakeArgumentPointer( static_cast(in_device_buf.GetDeviceBuffer()), static_cast(out_device_buf.GetDeviceBuffer()), static_cast(indices_device_buf.GetDeviceBuffer()), {N, C, Hi, Wi}, window_spatial_lengths, {N, C, Ho, Wo}, {C * Hi * Wi, 1, Wi * C, C}, {C * Ho * Wo, 1, Wo * C, C}, {C * Ho * Wo, 1, Wo * C, C}, window_strides, input_left_pads, input_right_pads, {2, 3}); if(!pool_fwd.IsSupportedArgument(pool_fwd_argument_ptr.get())) { throw std::runtime_error("wrong! pool_fwd with the specified compilation parameters does " "not support this problem"); } float ave_time_fwd = pool_fwd_invoker_ptr->Run(pool_fwd_argument_ptr.get(), StreamConfig{nullptr, time_kernel}); auto pool_bwd = DeviceMaxPoolBwdInstance{}; auto pool_bwd_invoker_ptr = pool_bwd.MakeInvokerPointer(); auto pool_bwd_argument_ptr = pool_bwd.MakeArgumentPointer( static_cast(dout_device_buf.GetDeviceBuffer()), static_cast(indices_device_buf.GetDeviceBuffer()), static_cast(din_device_buf.GetDeviceBuffer()), dout_n_c_ho_wo.mDesc.GetElementSpaceSize(), din_n_c_hi_wi_device.mDesc.GetElementSpaceSize(), window_spatial_lengths, window_strides); if(!pool_bwd.IsSupportedArgument(pool_bwd_argument_ptr.get())) { throw std::runtime_error("wrong! pool_bwd with the specified compilation parameters does " "not support this problem"); } float ave_time_bwd = pool_bwd_invoker_ptr->Run(pool_bwd_argument_ptr.get(), StreamConfig{nullptr, time_kernel}); std::cout << "Pool fwd perf: " << ave_time_fwd << " ms" << std::endl; std::cout << "Pool bwd perf: " << ave_time_bwd << " ms" << std::endl; bool pass = true; if(do_verification) { using ReferencePoolingFwdInstance = ck::tensor_operation::host::ReferencePoolingFwd<4, 2, InDataType, OutDataType, ComputeDataType, IndexDataType, ck::ReduceTensorOp::MAX, PropagateNan, true>; auto ref_pooling_fwd = ReferencePoolingFwdInstance{}; auto ref_pooling_fwd_invoker = ref_pooling_fwd.MakeInvoker(); auto ref_pooling_fwd_argument = ref_pooling_fwd.MakeArgument(in_n_c_hi_wi, out_n_c_ho_wo_host, indices_n_c_ho_wo_host, window_spatial_lengths, window_strides, input_left_pads, input_right_pads); ref_pooling_fwd_invoker.Run(ref_pooling_fwd_argument); using ReferencePoolingBwdInstance = ck::tensor_operation::host:: ReferenceMaxPoolBwd; auto ref_pooling_bwd = ReferencePoolingBwdInstance{}; auto ref_pooling_bwd_invoker = ref_pooling_bwd.MakeInvoker(); auto ref_pooling_bwd_argument = ref_pooling_bwd.MakeArgument( dout_n_c_ho_wo, indices_n_c_ho_wo_host, din_n_c_hi_wi_host, PassThrough{}); ref_pooling_bwd_invoker.Run(ref_pooling_bwd_argument); out_device_buf.FromDevice(out_n_c_ho_wo_device.mData.data()); indices_device_buf.FromDevice(indices_n_c_ho_wo_device.mData.data()); din_device_buf.FromDevice(din_n_c_hi_wi_device.mData.data()); pass = pass && ck::utils::check_err(out_n_c_ho_wo_device, out_n_c_ho_wo_host); pass = pass && ck::utils::check_err(indices_n_c_ho_wo_device, indices_n_c_ho_wo_host); pass = pass && ck::utils::check_err(din_n_c_hi_wi_device, din_n_c_hi_wi_host); } return (pass); };