You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
67 lines
2.4 KiB
67 lines
2.4 KiB
/* Copyright (c) 2016 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/fluid/framework/eigen.h"
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
using Tensor = framework::Tensor;
|
|
template <typename T, int MajorType = Eigen::RowMajor,
|
|
typename IndexType = Eigen::DenseIndex>
|
|
using EigenScalar = framework::EigenScalar<T, MajorType, IndexType>;
|
|
template <typename T, int MajorType = Eigen::RowMajor,
|
|
typename IndexType = Eigen::DenseIndex>
|
|
using EigenVector = framework::EigenVector<T, MajorType, IndexType>;
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class MeanKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
auto* input = context.Input<Tensor>("X");
|
|
auto* output = context.Output<Tensor>("Out");
|
|
|
|
output->mutable_data<T>(context.GetPlace());
|
|
|
|
auto X = EigenVector<T>::Flatten(*input);
|
|
auto y = EigenScalar<T>::From(*output);
|
|
auto& place =
|
|
*context.template device_context<DeviceContext>().eigen_device();
|
|
|
|
y.device(place) = X.mean();
|
|
}
|
|
};
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class MeanGradKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
auto OG = context.Input<Tensor>(framework::GradVarName("Out"));
|
|
PADDLE_ENFORCE(OG->numel() == 1, "Mean Gradient should be scalar");
|
|
auto IG = context.Output<Tensor>(framework::GradVarName("X"));
|
|
IG->mutable_data<T>(context.GetPlace());
|
|
|
|
T ig_size = static_cast<T>(IG->numel());
|
|
Eigen::DSizes<int, 1> bcast(static_cast<int>(ig_size));
|
|
EigenVector<T>::Flatten(*IG).device(
|
|
*context.template device_context<DeviceContext>().eigen_device()) =
|
|
(EigenVector<T>::From(*OG) / ig_size).broadcast(bcast);
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|