conv_op.cpp

/* Copyright (c) 2016 Baidu, Inc. All Rights Reserved.
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==============================================================================*/

#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();

  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);