pool_grad_kernel.h

// Copyright (c) 2022 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 <string>
#include <vector>

#include "paddle/phi/common/int_array.h"
#include "paddle/phi/core/dense_tensor.h"

namespace phi {

template <typename T, typename Context>
void Pool2dGradKernel(const Context& ctx,
                      const DenseTensor& x,
                      const DenseTensor& out,
                      const DenseTensor& dout,
                      const IntArray& kernel_size,
                      const std::vector<int>& strides,
                      const std::vector<int>& paddings,
                      bool ceil_mode,
                      bool exclusive,
                      const std::string& data_format,
                      const std::string& pooling_type,
                      bool global_pooling,
                      bool adaptive,
                      const std::string& padding_algorithm,
                      DenseTensor* dx);

template <typename T, typename Context>
void Pool2dGradGPUDNNKernel(const Context& ctx,
                            const DenseTensor& x,
                            const DenseTensor& out,
                            const DenseTensor& dout,
                            const IntArray& kernel_size,
                            const std::vector<int>& strides,
                            const std::vector<int>& paddings,
                            bool ceil_mode,
                            bool exclusive,
                            const std::string& data_format,
                            const std::string& pooling_type,
                            bool global_pooling,
                            bool adaptive,
                            const std::string& padding_algorithm,
                            DenseTensor* dx);

template <typename T, typename Context>
void Pool2dDoubleGradKernel(const Context& ctx,
                            const DenseTensor& x,
                            const IntArray& kernel_size,
                            const std::vector<int>& strides,
                            const std::vector<int>& paddings,
                            bool ceil_mode,
                            bool exclusive,
                            const std::string& data_format,
                            const std::string& pooling_type,
                            bool global_pooling,
                            bool adaptive,
                            const std::string& padding_algorithm,
                            DenseTensor* out);

template <typename T, typename Context>
void Pool2dDoubleGradGPUDNNKernel(const Context& ctx,
                                  const DenseTensor& x,
                                  const IntArray& kernel_size,
                                  const std::vector<int>& strides,
                                  const std::vector<int>& paddings,
                                  bool ceil_mode,
                                  bool exclusive,
                                  const std::string& data_format,
                                  const std::string& pooling_type,
                                  bool global_pooling,
                                  bool adaptive,
                                  const std::string& padding_algorithm,
                                  DenseTensor* out);

template <typename T, typename Context>
void MaxPool2dWithIndexGradKernel(const Context& ctx,
                                  const DenseTensor& x,
                                  const DenseTensor& mask,
                                  const DenseTensor& dout,
                                  const std::vector<int>& kernel_size,
                                  const std::vector<int>& strides,
                                  const std::vector<int>& paddings,
                                  bool global_pooling,
                                  bool adaptive,
                                  DenseTensor* dx);

template <typename T, typename Context>
void Pool3dGradKernel(const Context& ctx,
                      const DenseTensor& x,
                      const DenseTensor& out,
                      const DenseTensor& dout,
                      const std::vector<int>& kernel_size,
                      const std::vector<int>& strides,
                      const std::vector<int>& paddings,
                      bool ceil_mode,
                      bool exclusive,
                      const std::string& data_format,
                      const std::string& pooling_type,
                      bool global_pooling,
                      bool adaptive,
                      const std::string& padding_algorithm,
                      DenseTensor* dx);

template <typename T, typename Context>
void Pool3dGradGPUDNNKernel(const Context& ctx,
                            const DenseTensor& x,
                            const DenseTensor& out,
                            const DenseTensor& dout,
                            const std::vector<int>& kernel_size,
                            const std::vector<int>& strides,
                            const std::vector<int>& paddings,
                            bool ceil_mode,
                            bool exclusive,
                            const std::string& data_format,
                            const std::string& pooling_type,
                            bool global_pooling,
                            bool adaptive,
                            const std::string& padding_algorithm,
                            DenseTensor* dx);

template <typename T, typename Context>
void MaxPool3dWithIndexGradKernel(const Context& ctx,
                                  const DenseTensor& x,
                                  const DenseTensor& mask,
                                  const DenseTensor& dout,
                                  const std::vector<int>& kernel_size,
                                  const std::vector<int>& strides,
                                  const std::vector<int>& paddings,
                                  bool global_pooling,
                                  bool adaptive,
                                  DenseTensor* dx);

}  // namespace phi