summaryrefslogtreecommitdiff
path: root/include/caffe/layers/input_layer.hpp
blob: f4472678c69750c69bb097532cb0ac3229843034 (plain)
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_