wehub-resource-sync
119 lines
3.5 KiB
C++
119 lines
3.5 KiB
C++
/* 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 <memory>
|
|
#include <string>
|
|
#include <unordered_map>
|
|
#include <vector>
|
|
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
|
|
#if !defined(PADDLE_WITH_XPU_KP) || defined(__xpu_on_host__)
|
|
#include "unsupported/Eigen/CXX11/Tensor"
|
|
#endif
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
using DataLayout = phi::DataLayout;
|
|
|
|
template <typename T>
|
|
using EigenArrayMap =
|
|
Eigen::Map<Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
|
|
template <typename T>
|
|
using ConstEigenArrayMap =
|
|
Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
|
|
template <typename T>
|
|
using EigenVectorArrayMap = Eigen::Map<Eigen::Array<T, Eigen::Dynamic, 1>>;
|
|
template <typename T>
|
|
using ConstEigenVectorArrayMap =
|
|
Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, 1>>;
|
|
|
|
class BatchNormOp : public framework::OperatorWithKernel {
|
|
public:
|
|
using framework::OperatorWithKernel::OperatorWithKernel;
|
|
void InferShape(framework::InferShapeContext* ctx) const override;
|
|
|
|
protected:
|
|
phi::KernelKey GetExpectedKernelType(
|
|
const framework::ExecutionContext& ctx) const override;
|
|
|
|
phi::KernelKey GetKernelTypeForVar(
|
|
const std::string& var_name,
|
|
const phi::DenseTensor& tensor,
|
|
const phi::KernelKey& expected_kernel_type) const override;
|
|
};
|
|
|
|
class BatchNormGradOp : public framework::OperatorWithKernel {
|
|
public:
|
|
using framework::OperatorWithKernel::OperatorWithKernel;
|
|
void InferShape(framework::InferShapeContext* ctx) const override;
|
|
|
|
protected:
|
|
phi::KernelKey GetExpectedKernelType(
|
|
const framework::ExecutionContext& ctx) const override;
|
|
|
|
phi::KernelKey GetKernelTypeForVar(
|
|
const std::string& var_name,
|
|
const phi::DenseTensor& tensor,
|
|
const phi::KernelKey& expected_kernel_type) const override;
|
|
};
|
|
|
|
class BatchNormDoubleGradOp : public framework::OperatorWithKernel {
|
|
public:
|
|
using framework::OperatorWithKernel::OperatorWithKernel;
|
|
void InferShape(framework::InferShapeContext* ctx) const override;
|
|
|
|
protected:
|
|
phi::KernelKey GetExpectedKernelType(
|
|
const framework::ExecutionContext& ctx) const override;
|
|
};
|
|
|
|
class BatchNormOpMaker : public framework::OpProtoAndCheckerMaker {
|
|
public:
|
|
void Make() override;
|
|
};
|
|
|
|
template <typename T>
|
|
class BatchNormGradMaker : public framework::SingleGradOpMaker<T> {
|
|
public:
|
|
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
|
|
|
|
protected:
|
|
void Apply(GradOpPtr<T> op) const override;
|
|
};
|
|
|
|
template <typename T>
|
|
class BatchNormDoubleGradMaker : public framework::SingleGradOpMaker<T> {
|
|
public:
|
|
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
|
|
|
|
protected:
|
|
void Apply(GradOpPtr<T> op) const override;
|
|
};
|
|
|
|
class BatchNormOpInferVarType
|
|
: public framework::PassInDtypeAndVarTypeToOutput {
|
|
protected:
|
|
std::unordered_map<std::string, std::string>& GetInputOutputWithSameType()
|
|
const override {
|
|
static std::unordered_map<std::string, std::string> m{{"X", /*->*/ "Y"}};
|
|
return m;
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|