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.
72 lines
3.2 KiB
72 lines
3.2 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License");
|
|
you may not use this file except in compliance with the License.
|
|
Indicesou 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/framework/op_registry.h"
|
|
#include "paddle/operators/math/math_function.h"
|
|
#include "paddle/operators/math/unpooling.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
template <typename DeviceContext, typename T>
|
|
class UnpoolKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
const framework::Tensor* in_x = context.Input<framework::Tensor>("X");
|
|
const framework::Tensor* in_y = context.Input<framework::Tensor>("Indices");
|
|
auto* out = context.Output<framework::Tensor>("Out");
|
|
std::string unpooling_type = context.Attr<std::string>("unpooling_type");
|
|
std::vector<int> ksize = context.Attr<std::vector<int>>("ksize");
|
|
std::vector<int> strides = context.Attr<std::vector<int>>("strides");
|
|
std::vector<int> paddings = context.Attr<std::vector<int>>("paddings");
|
|
T* output_data = out->mutable_data<T>(context.GetPlace());
|
|
auto& dev_ctx = context.template device_context<DeviceContext>();
|
|
if (output_data) {
|
|
math::SetConstant<DeviceContext, T> set_zero;
|
|
set_zero(dev_ctx, out, static_cast<T>(0));
|
|
}
|
|
math::Unpool2dMaxFunctor<DeviceContext, T> unpool2d_max_forward;
|
|
unpool2d_max_forward(dev_ctx, *in_x, *in_y, out);
|
|
}
|
|
};
|
|
template <typename DeviceContext, typename T>
|
|
class UnpoolGradKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
const framework::Tensor* in_x = context.Input<framework::Tensor>("X");
|
|
const framework::Tensor* in_y = context.Input<framework::Tensor>("Indices");
|
|
const framework::Tensor* out = context.Input<framework::Tensor>("Out");
|
|
const framework::Tensor* out_grad =
|
|
context.Input<framework::Tensor>(framework::GradVarName("Out"));
|
|
framework::Tensor* in_x_grad =
|
|
context.Output<framework::Tensor>(framework::GradVarName("X"));
|
|
std::string unpooling_type = context.Attr<std::string>("unpooling_type");
|
|
std::vector<int> ksize = context.Attr<std::vector<int>>("ksize");
|
|
std::vector<int> strides = context.Attr<std::vector<int>>("strides");
|
|
std::vector<int> paddings = context.Attr<std::vector<int>>("paddings");
|
|
|
|
auto& device_ctx = context.template device_context<DeviceContext>();
|
|
math::SetConstant<DeviceContext, T> zero;
|
|
if (in_x_grad) {
|
|
in_x_grad->mutable_data<T>(context.GetPlace());
|
|
zero(device_ctx, in_x_grad, static_cast<T>(0));
|
|
}
|
|
math::Unpool2dMaxGradFunctor<DeviceContext, T> unpool2d_max_backward;
|
|
unpool2d_max_backward(device_ctx, *in_x, *in_y, *out, *out_grad, in_x_grad);
|
|
}
|
|
};
|
|
} // namespace operators
|
|
} // namespace paddle
|