// 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.

#include "paddle/phi/kernels/conv_grad_kernel.h"

#include "paddle/common/flags.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/conv_grad_kernel_impl.h"
#include "paddle/phi/kernels/impl/slow_conv_kernel_impl.cuh"

COMMON_DECLARE_bool(use_accuracy_compatible_kernel);

namespace phi {

template <typename T, typename Context>
void SlowConv3DDilatedGradKernel(const Context& dev_ctx,
                                 const DenseTensor& input,
                                 const DenseTensor& filter,
                                 const paddle::optional<DenseTensor>& bias,
                                 const DenseTensor& out_grad,
                                 const std::vector<int>& strides,
                                 const std::vector<int>& paddings,
                                 const std::string& padding_algorithm,
                                 int groups,
                                 const std::vector<int>& dilations,
                                 const std::string& data_format,
                                 DenseTensor* input_grad,
                                 DenseTensor* filter_grad,
                                 DenseTensor* bias_grad) {
  SlowConvBackward<T, Context, 3>(dev_ctx,
                                  input,
                                  filter,
                                  out_grad,
                                  strides,
                                  paddings,
                                  padding_algorithm,
                                  dilations,
                                  groups,
                                  data_format,
                                  input_grad,
                                  filter_grad,
                                  bias_grad);
}

template <typename T, typename Context>
void SlowConvDilatedGradKernel(const Context& dev_ctx,
                               const DenseTensor& input,
                               const DenseTensor& filter,
                               const paddle::optional<DenseTensor>& bias,
                               const DenseTensor& output_grad,
                               const std::vector<int>& strides,
                               const std::vector<int>& paddings,
                               const std::string& padding_algorithm,
                               const std::vector<int>& dilations,
                               int groups,
                               const std::string& data_format,
                               DenseTensor* input_grad,
                               DenseTensor* filter_grad,
                               DenseTensor* bias_grad) {
  SlowConvBackward<T, Context, 2>(dev_ctx,
                                  input,
                                  filter,
                                  output_grad,
                                  strides,
                                  paddings,
                                  padding_algorithm,
                                  dilations,
                                  groups,
                                  data_format,
                                  input_grad,
                                  filter_grad,
                                  bias_grad);
}

template <typename T, typename Context>
void Conv3DGradKernel(const Context& dev_ctx,
                      const DenseTensor& input,
                      const DenseTensor& filter,
                      const DenseTensor& out_grad,
                      const std::vector<int>& strides,
                      const std::vector<int>& paddings,
                      const std::string& padding_algorithm,
                      int groups,
                      const std::vector<int>& dilations,
                      const std::string& data_format,
                      DenseTensor* input_grad,
                      DenseTensor* filter_grad) {
  ConvGradKernel<T>(dev_ctx,
                    input,
                    filter,
                    out_grad,
                    strides,
                    paddings,
                    padding_algorithm,
                    dilations,
                    groups,
                    data_format,
                    input_grad,
                    filter_grad);
}

}  // namespace phi

PD_REGISTER_KERNEL(conv2d_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::ConvGradKernel,
                   float,
                   double,
                   phi::float16,
                   phi::bfloat16) {}

PD_REGISTER_KERNEL(conv3d_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::Conv3DGradKernel,
                   float,
                   double,
                   phi::float16,
                   phi::bfloat16) {}

PD_REGISTER_KERNEL(slow_conv2d_dilated_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::SlowConvDilatedGradKernel,
                   float,
                   double,
                   phi::float16,
                   phi::bfloat16) {}

PD_REGISTER_KERNEL(slow_conv3d_dilated_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::SlowConv3DDilatedGradKernel,
                   float,
                   double,
                   phi::float16,
                   phi::bfloat16) {}

PD_REGISTER_KERNEL(conv2d_double_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::ConvGradGradKernel,
                   float,
                   double) {}