/usr/include/caffe/layers/input_layer.hpp is in libcaffe-cpu-dev 1.0.0~rc4-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | #ifndef CAFFE_INPUT_LAYER_HPP_
#define CAFFE_INPUT_LAYER_HPP_
#include <vector>
#include "caffe/blob.hpp"
#include "caffe/layer.hpp"
#include "caffe/proto/caffe.pb.h"
namespace caffe {
/**
* @brief Provides data to the Net by assigning tops directly.
*
* This data layer is a container that merely holds the data assigned to it;
* forward, backward, and reshape are all no-ops.
*/
template <typename Dtype>
class InputLayer : public Layer<Dtype> {
public:
explicit InputLayer(const LayerParameter& param)
: Layer<Dtype>(param) {}
virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
// Data layers should be shared by multiple solvers in parallel
virtual inline bool ShareInParallel() const { return true; }
// Data layers have no bottoms, so reshaping is trivial.
virtual void Reshape(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top) {}
virtual inline const char* type() const { return "Input"; }
virtual inline int ExactNumBottomBlobs() const { return 0; }
virtual inline int MinTopBlobs() 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) {}
};
} // namespace caffe
#endif // CAFFE_INPUT_LAYER_HPP_
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