// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #pragma once #include "paddle/phi/kernels/funcs/eigen/common.h" #include "paddle/phi/kernels/funcs/eigen/eigen_function.h" namespace phi { template void HingeLossKernel(const Context& dev_ctx, const DenseTensor& logits, const DenseTensor& labels, DenseTensor* loss) { auto* pred = &logits; auto* label = &labels; auto& place = *dev_ctx.eigen_device(); auto x = EigenVector::Flatten(*pred); auto y = EigenVector::Flatten(*label); dev_ctx.template Alloc(loss); auto l = EigenVector::Flatten(*loss); funcs::EigenHingeLoss, T>::Eval(place, l, x, y); } template void HingeLossGradKernel(const Context& dev_ctx, const DenseTensor& logits, const DenseTensor& labels, const DenseTensor& loss_grad, DenseTensor* logits_grad) { auto* pred = &logits; auto* label = &labels; auto* dloss = &loss_grad; auto* dpred = logits_grad; auto& place = *dev_ctx.eigen_device(); auto x = EigenVector::Flatten(*pred); auto y = EigenVector::Flatten(*label); auto dl = EigenVector::Flatten(*dloss); if (dpred) { dev_ctx.template Alloc(dpred); auto dx = EigenVector::Flatten(*dpred); funcs::EigenHingeLossGrad, T>::Eval( place, dx, dl, x, y); } } } // namespace phi