qijun
8 years ago
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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/framework/eigen.h"
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#include "paddle/framework/tensor.h"
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namespace paddle {
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namespace operators {
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namespace math {
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template <typename Place, typename T>
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struct Sigmoid {
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void operator()(const platform::DeviceContext& device_context,
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const framework::Tensor& X, framework::Tensor* Y) {
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auto x = framework::EigenVector<T>::Flatten(X);
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auto y = framework::EigenVector<T>::Flatten(*Y);
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auto* place = device_context.template get_eigen_device<Place>();
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y.device(*place) = 1. / (1. + (-x).exp());
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}
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};
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template <typename Place, typename T>
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struct SigmoidGrad {
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void operator()(const platform::DeviceContext& device_context,
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const framework::Tensor& X, const framework::Tensor& Y,
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const framework::Tensor& dY, framework::Tensor* dX) {
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auto dx = framework::EigenVector<T>::Flatten(*dX);
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auto y = framework::EigenVector<T>::Flatten(Y);
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auto dy = framework::EigenVector<T>::Flatten(dY);
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auto* place = device_context.template get_eigen_device<Place>();
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dx.device(*place) = dy * y * (1. - y);
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}
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};
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template <typename Place, typename T>
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struct Exp {
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void operator()(const platform::DeviceContext& device_context,
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const framework::Tensor& input, framework::Tensor* output) {
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auto x = framework::EigenVector<T>::Flatten(input);
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auto y = framework::EigenVector<T>::Flatten(*output);
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auto* place = device_context.template get_eigen_device<Place>();
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y.device(*place) = x.exp();
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}
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};
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template <typename Place, typename T>
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struct ExpGrad {
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void operator()(const platform::DeviceContext& device_context,
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const framework::Tensor& X, const framework::Tensor& Y,
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const framework::Tensor& dY, framework::Tensor* dX) {
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auto dx = framework::EigenVector<T>::Flatten(*dX);
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auto y = framework::EigenVector<T>::Flatten(Y);
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auto* place = device_context.template get_eigen_device<Place>();
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dx.device(*place) = y;
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}
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};
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template <typename Place, typename T>
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struct Relu {
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void operator()(const platform::DeviceContext& device_context,
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const framework::Tensor& input, framework::Tensor* output) {
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auto x = framework::EigenVector<T>::Flatten(input);
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auto y = framework::EigenVector<T>::Flatten(*output);
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auto* place = device_context.template get_eigen_device<Place>();
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y.device(*place) = x.cwiseMax(static_cast<T>(0));
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}
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};
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template <typename Place, typename T>
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struct ReluGrad {
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void operator()(const platform::DeviceContext& device_context,
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const framework::Tensor& X, const framework::Tensor& Y,
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const framework::Tensor& dY, framework::Tensor* dX) {
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auto dx = framework::EigenVector<T>::Flatten(*dX);
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auto dy = framework::EigenVector<T>::Flatten(dY);
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auto x = framework::EigenVector<T>::Flatten(X);
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auto* place = device_context.template get_eigen_device<Place>();
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dx.device(*place) = dy * (x > static_cast<T>(0)).template cast<T>();
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}
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};
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} // namespace math
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} // namespace operators
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} // namespace paddle
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