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72 lines
2.7 KiB
72 lines
2.7 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/fluid/framework/eigen.h"
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T, typename AttrType = T>
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class HingeLossKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* pred = context.Input<framework::Tensor>("Logits");
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auto* label = context.Input<framework::Tensor>("Labels");
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auto* loss = context.Output<framework::Tensor>("Loss");
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auto& place =
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*context.template device_context<DeviceContext>().eigen_device();
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auto x = framework::EigenVector<T>::Flatten(*pred);
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auto y = framework::EigenVector<T>::Flatten(*label);
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loss->mutable_data<T>(context.GetPlace());
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auto l = framework::EigenVector<T>::Flatten(*loss);
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l.device(place) =
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(static_cast<T>(1) - x * (static_cast<T>(2) * y - static_cast<T>(1)))
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.cwiseMax(static_cast<T>(0));
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}
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};
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template <typename DeviceContext, typename T, typename AttrType = T>
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class HingeLossGradKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* pred = context.Input<framework::Tensor>("Logits");
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auto* label = context.Input<framework::Tensor>("Labels");
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auto* dloss =
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context.Input<framework::Tensor>(framework::GradVarName("Loss"));
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auto* dpred =
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context.Output<framework::Tensor>(framework::GradVarName("Logits"));
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auto& place =
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*context.template device_context<DeviceContext>().eigen_device();
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auto x = framework::EigenVector<T>::Flatten(*pred);
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auto y = framework::EigenVector<T>::Flatten(*label);
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auto dl = framework::EigenVector<T>::Flatten(*dloss);
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if (dpred) {
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dpred->mutable_data<T>(context.GetPlace());
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auto dx = framework::EigenVector<T>::Flatten(*dpred);
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auto alt_labels = static_cast<T>(2) * y - static_cast<T>(1);
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dx.device(place) =
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dl * ((x * alt_labels) < static_cast<T>(1)).template cast<T>() *
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(-alt_labels);
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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