// 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_transpose_grad_kernel.h"
#include "paddle/phi/kernels/impl/conv_transpose_grad_kernel_impl.h"

#include "paddle/phi/core/kernel_registry.h"

namespace phi {

template <typename T, typename Context>
void DepthwiseConv2dTransposeGradKernel(const Context& ctx,
                                        const DenseTensor& x,
                                        const DenseTensor& filter,
                                        const DenseTensor& dout,
                                        const std::vector<int>& strides,
                                        const std::vector<int>& paddings,
                                        const std::vector<int>& output_padding,
                                        const std::vector<int>& output_size,
                                        const std::string& padding_algorithm,
                                        int groups,
                                        const std::vector<int>& dilations,
                                        const std::string& data_format,
                                        DenseTensor* dx,
                                        DenseTensor* dfilter) {
  ConvTransposeGradRawKernel<T, Context>(ctx,
                                         x,
                                         filter,
                                         dout,
                                         strides,
                                         paddings,
                                         padding_algorithm,
                                         groups,
                                         dilations,
                                         data_format,
                                         dx,
                                         dfilter);
}

}  // namespace phi

PD_REGISTER_KERNEL(conv2d_transpose_grad,
                   CPU,
                   ALL_LAYOUT,
                   phi::Conv2dTransposeGradKernel,
                   float,
                   double) {}
PD_REGISTER_KERNEL(conv3d_transpose_grad,
                   CPU,
                   ALL_LAYOUT,
                   phi::Conv3dTransposeGradKernel,
                   float,
                   double) {}
PD_REGISTER_KERNEL(depthwise_conv2d_transpose_grad,
                   CPU,
                   ALL_LAYOUT,
                   phi::DepthwiseConv2dTransposeGradKernel,
                   float,
                   double) {}