/* Copyright (c) 2018 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 "operators/conv_op.h"
#include <vector>
#include "framework/data_type.h"
#include "framework/op_proto_maker.h"
#include "framework/op_registry.h"

namespace paddle_mobile {
namespace operators {

int ConvOutputSize(int input_size, int filter_size, int dilation, int padding,
                   int stride) {
  const int dkernel = dilation * (filter_size - 1) + 1;
  int output_size = (input_size + 2 * padding - dkernel) / stride + 1;
  return output_size;
}

template <typename Dtype, typename T>
void ConvOp<Dtype, T>::InferShape() const {
  //  std::cout << " begin get dims: " << std::endl;

  auto in_dims = param_.Input()->dims();

  //  std::cout << " end get in dims: " << std::endl;

  //  std::cout << " in_dims: " << in_dims << std::endl;

  //  std::cout << " begin get Filter " << std::endl;

  auto filter_dims = param_.Filter()->dims();

  //  std::cout << " end get Filter " << std::endl;

  //  std::cout << " begin get Attrs " << std::endl;

  const std::vector<int> &strides = param_.Strides();

  //  std::cout << " end get Attrs " << strides[0] << std::endl;

  std::vector<int> paddings = param_.Paddings();

  int groups = param_.Groups();

  std::vector<int> dilations = param_.Dilations();

  PADDLE_MOBILE_ENFORCE((in_dims.size() == filter_dims.size() &&
                         dilations.size() == paddings.size() &&
                         paddings.size() == strides.size()),
                        "ConvParam is not suitable");

  std::vector<int64_t> output_shape({in_dims[0], filter_dims[0]});
  for (size_t i = 0; i < strides.size(); ++i) {
    output_shape.push_back(ConvOutputSize(in_dims[i + 2], filter_dims[i + 2],
                                          dilations[i], paddings[i],
                                          strides[i]));
  }

  framework::DDim ddim = framework::make_ddim(output_shape);
  param_.Output()->Resize(ddim);
}

template class ConvOp<CPU, float>;

}  // namespace operators
}  // namespace paddle_mobile

namespace ops = paddle_mobile::operators;
USE_OP(conv2d);
REGISTER_OPERATOR(conv2d, ops::ConvOp);