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#ifndef CAFFE_FLATTEN_LAYER_HPP_
#define CAFFE_FLATTEN_LAYER_HPP_
#include <vector>
#include "caffe/blob.hpp"
#include "caffe/layer.hpp"
#include "caffe/proto/caffe.pb.h"
namespace caffe {
/**
* @brief Reshapes the input Blob into flat vectors.
*
* Note: because this layer does not change the input values -- merely the
* dimensions -- it can simply copy the input. The copy happens "virtually"
* (thus taking effectively 0 real time) by setting, in Forward, the data
* pointer of the top Blob to that of the bottom Blob (see Blob::ShareData),
* and in Backward, the diff pointer of the bottom Blob to that of the top Blob
* (see Blob::ShareDiff).
*/
template <typename Dtype>
class FlattenLayer : public Layer<Dtype> {
public:
explicit FlattenLayer(const LayerParameter& param)
: Layer<Dtype>(param) {}
virtual void Reshape(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
virtual inline const char* type() const { return "Flatten"; }
virtual inline int ExactNumBottomBlobs() const { return 1; }
virtual inline int ExactNumTopBlobs() const { return 1; }
protected:
/**
* @param bottom input Blob vector (length 2+)
* -# @f$ (N \times C \times H \times W) @f$
* the inputs
* @param top output Blob vector (length 1)
* -# @f$ (N \times CHW \times 1 \times 1) @f$
* the outputs -- i.e., the (virtually) copied, flattened inputs
*/
virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
/**
* @brief Computes the error gradient w.r.t. the concatenate inputs.
*
* @param top output Blob vector (length 1), providing the error gradient with
* respect to the outputs
* @param propagate_down see Layer::Backward.
* @param bottom input Blob vector (length K), into which the top error
* gradient is (virtually) copied
*/
virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,
const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
};
} // namespace caffe
#endif // CAFFE_FLATTEN_LAYER_HPP_
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