wehub-resource-sync
140 lines
5.1 KiB
C++
140 lines
5.1 KiB
C++
/* Copyright (c) 2022 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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#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
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namespace phi::funcs {
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template <typename T>
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struct EigenRankLoss<Eigen::DefaultDevice, T> {
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using InType =
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Eigen::TensorMap<Eigen::Tensor<const T, 1, Eigen::RowMajor, int64_t>>;
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using OutType =
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Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, int64_t>>;
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static void Eval(const Eigen::DefaultDevice& dev,
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OutType out,
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const InType& label,
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const InType& left,
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const InType& right) {
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out.device(dev) =
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(1.0f + (left - right).exp()).log() - label * (left - right);
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}
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};
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template <typename T>
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struct EigenRankLossGrad<Eigen::DefaultDevice, T> {
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using InType =
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Eigen::TensorMap<Eigen::Tensor<const T, 1, Eigen::RowMajor, int64_t>>;
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using OutType =
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Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, int64_t>>;
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static void EvalLeft(const Eigen::DefaultDevice& dev,
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OutType dleft,
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const InType& dout,
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const InType& label,
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const InType& left,
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const InType& right) {
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dleft.device(dev) = dout * (1.0f / (1.0f + (right - left).exp()) - label);
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}
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static void EvalRight(const Eigen::DefaultDevice& dev,
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OutType dright,
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const InType& dout,
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const InType& label,
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const InType& left,
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const InType& right) {
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dright.device(dev) = -dout * (1.0f / (1.0f + (right - left).exp()) - label);
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}
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};
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template struct EigenRankLoss<Eigen::DefaultDevice, float>;
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template struct EigenRankLossGrad<Eigen::DefaultDevice, float>;
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template <typename T>
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struct EigenLogLoss<Eigen::DefaultDevice, T> {
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using InType =
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Eigen::TensorMap<Eigen::Tensor<const T, 1, Eigen::RowMajor, int64_t>>;
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using OutType =
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Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, int64_t>>;
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static void Eval(const Eigen::DefaultDevice& dev,
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OutType out,
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const InType& pred,
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const InType& label,
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const T& epsilon) {
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out.device(dev) = (-(label * (pred + epsilon).log()) -
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((static_cast<T>(1) - label) *
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(static_cast<T>(1) - pred + epsilon).log()));
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}
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};
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template <typename T>
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struct EigenLogLossGrad<Eigen::DefaultDevice, T> {
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using InType =
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Eigen::TensorMap<Eigen::Tensor<const T, 1, Eigen::RowMajor, int64_t>>;
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using OutType =
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Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, int64_t>>;
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static void Eval(const Eigen::DefaultDevice& dev,
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OutType dpred,
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const InType& dloss,
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const InType& pred,
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const InType& label,
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const T& epsilon) {
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dpred.device(dev) =
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dloss *
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(-(label / (pred + epsilon)) +
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((static_cast<T>(1) - label) / (static_cast<T>(1) - pred + epsilon)));
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}
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};
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template struct EigenLogLoss<Eigen::DefaultDevice, float>;
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template struct EigenLogLossGrad<Eigen::DefaultDevice, float>;
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template <typename T>
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struct EigenHingeLoss<Eigen::DefaultDevice, T> {
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using InType =
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Eigen::TensorMap<Eigen::Tensor<const T, 1, Eigen::RowMajor, int64_t>>;
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using OutType =
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Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, int64_t>>;
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static void Eval(const Eigen::DefaultDevice& dev,
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OutType loss,
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const InType& pred,
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const InType& label) {
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loss.device(dev) = (static_cast<T>(1) -
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pred * (static_cast<T>(2) * label - 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 T>
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struct EigenHingeLossGrad<Eigen::DefaultDevice, T> {
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using InType =
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Eigen::TensorMap<Eigen::Tensor<const T, 1, Eigen::RowMajor, int64_t>>;
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using OutType =
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Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, int64_t>>;
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static void Eval(const Eigen::DefaultDevice& dev,
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OutType dpred,
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const InType& dloss,
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const InType& pred,
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const InType& label) {
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auto alt_labels = static_cast<T>(2) * label - static_cast<T>(1);
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dpred.device(dev) =
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dloss * ((pred * 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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template struct EigenHingeLoss<Eigen::DefaultDevice, float>;
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template struct EigenHingeLossGrad<Eigen::DefaultDevice, float>;
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} // namespace phi::funcs
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