/*
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Copyright (c) 2014, 2015, The Regents of the University of California (Regents)
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Copyright (c) 2014, 2015, the respective contributors
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For the list of contributors go to https://github.com/BVLC/caffe/blob/master/CONTRIBUTORS.md


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    * Redistributions of source code must retain the above copyright notice,
      this list of conditions and the following disclaimer.
    * Redistributions in binary form must reproduce the above copyright
      notice, this list of conditions and the following disclaimer in the
      documentation and/or other materials provided with the distribution.
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      may be used to endorse or promote products derived from this software
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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*/

#ifndef CAFFE_CROP_LAYER_HPP_
#define CAFFE_CROP_LAYER_HPP_

#include <utility>
#include <vector>

#include "caffe/blob.hpp"
#include "caffe/layer.hpp"
#include "caffe/proto/caffe.pb.h"

namespace caffe {

/**
 * @brief Takes a Blob and crop it, to the shape specified by the second input
 *  Blob, across all dimensions after the specified axis.
 *
 * TODO(dox): thorough documentation for Forward, Backward, and proto params.
 */

template <typename Dtype>
class CropLayer : public Layer<Dtype> {
 public:
  explicit CropLayer(const LayerParameter& param)
      : Layer<Dtype>(param) {}
  virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom,
      const vector<Blob<Dtype>*>& top);
  virtual void Reshape(const vector<Blob<Dtype>*>& bottom,
      const vector<Blob<Dtype>*>& top);

  virtual inline const char* type() const { return "Crop"; }
  virtual inline int ExactNumBottomBlobs() const { return 2; }
  virtual inline int ExactNumTopBlobs() const { return 1; }

 protected:
  virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
      const vector<Blob<Dtype>*>& top);
  virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,
      const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
  virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
      const vector<Blob<Dtype>*>& top);
  virtual void Backward_gpu(const vector<Blob<Dtype>*>& top,
      const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);

  vector<int> offsets;

 private:
  template<bool is_forward>
  void crop_copy(const vector<Blob<Dtype>*>& bottom,
               const vector<Blob<Dtype>*>& top,
               const vector<int>& offsets,
               const Dtype* src_data,
               Dtype* dest_data);

  // Copy function: this is similar to crop_copy() but loops over all
  // but the last two dimensions to allow for ND cropping while still relying on
  // a CUDA kernel for the innermost two dimensions for performance reasons.  An
  // alterantive implementation could rely on the kernel more by passing
  // offsets, but this is problematic because of its variable length.
  // Since in the standard (N,C,W,H) case N,C are usually not cropped a speedup
  // could be achieved by not looping the application of the copy_kernel around
  // these dimensions.
  void crop_copy_gpu(const vector<Blob<Dtype>*>& bottom,
                const vector<Blob<Dtype>*>& top,
                const vector<int>& offsets,
                vector<int> indices,
                int cur_dim,
                const Dtype* src_data,
                Dtype* dest_data,
                bool is_forward);
};
}  // namespace caffe

#endif  // CAFFE_CROP_LAYER_HPP_
