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#ifndef CAFFE_BATCHREINDEX_LAYER_HPP_
#define CAFFE_BATCHREINDEX_LAYER_HPP_
#include <utility>
#include <vector>
#include "caffe/blob.hpp"
#include "caffe/layer.hpp"
#include "caffe/proto/caffe.pb.h"
namespace caffe {
/**
* @brief Index into the input blob along its first axis.
*
* This layer can be used to select, reorder, and even replicate examples in a
* batch. The second blob is cast to int and treated as an index into the
* first axis of the first blob.
*/
template <typename Dtype>
class BatchReindexLayer : public Layer<Dtype> {
public:
explicit BatchReindexLayer(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 "BatchReindex"; }
virtual inline int ExactNumBottomBlobs() const { return 2; }
virtual inline int ExactNumTopBlobs() const { return 1; }
protected:
/**
* @param bottom input Blob vector (length 2+)
* -# @f$ (N \times ...) @f$
* the inputs @f$ x_1 @f$
* -# @f$ (M) @f$
* the inputs @f$ x_2 @f$
* @param top output Blob vector (length 1)
* -# @f$ (M \times ...) @f$:
* the reindexed array @f$
* y = x_1[x_2]
* @f$
*/
virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
/**
* @brief Computes the error gradient w.r.t. the reordered input.
*
* @param top output Blob vector (length 1), providing the error gradient
* with respect to the outputs
* -# @f$ (M \times ...) @f$:
* containing error gradients @f$ \frac{\partial E}{\partial y} @f$
* with respect to concatenated outputs @f$ y @f$
* @param propagate_down see Layer::Backward.
* @param bottom input Blob vector (length 2):
* - @f$ \frac{\partial E}{\partial y} @f$ is de-indexed (summing where
* required) back to the input x_1
* - This layer cannot backprop to x_2, i.e. propagate_down[1] must be
* false.
*/
virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,
const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
virtual void Backward_gpu(const vector<Blob<Dtype>*>& top,
const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
private:
struct pair_sort_first {
bool operator()(const std::pair<int, int> &left,
const std::pair<int, int> &right) {
return left.first < right.first;
}
};
void check_batch_reindex(int initial_num, int final_num,
const Dtype* ridx_data);
};
} // namespace caffe
#endif // CAFFE_BATCHREINDEX_LAYER_HPP_
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