net.hpp

#ifndef CAFFE_NET_HPP_
#define CAFFE_NET_HPP_

#include <map>
#include <set>
#include <string>
#include <utility>
#include <vector>

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

namespace caffe {

template <typename Dtype>
class Net {
 public:
  explicit Net(const NetParameter& param);
  explicit Net(const string& param_file, Phase phase,
      const int level = 0, const vector<string>* stages = NULL);
  virtual ~Net() {}

  void Init(const NetParameter& param);

  const vector<Blob<Dtype>*>& Forward(Dtype* loss = NULL);
  const vector<Blob<Dtype>*>& ForwardPrefilled(Dtype* loss = NULL) {
    LOG_EVERY_N(WARNING, 1000) << "DEPRECATED: ForwardPrefilled() "
        << "will be removed in a future version. Use Forward().";
    return Forward(loss);
  }

  Dtype ForwardFromTo(int start, int end);
  Dtype ForwardFrom(int start);
  Dtype ForwardTo(int end);
  const vector<Blob<Dtype>*>& Forward(const vector<Blob<Dtype>* > & bottom,
      Dtype* loss = NULL);

  void ClearParamDiffs();

  void Backward();
  void BackwardFromTo(int start, int end);
  void BackwardFrom(int start);
  void BackwardTo(int end);

  void Reshape();

  Dtype ForwardBackward() {
    Dtype loss;
    Forward(&loss);
    Backward();
    return loss;
  }

  void Update();
  void ShareWeights();

  void ShareTrainedLayersWith(const Net* other);
  // For an already initialized net, CopyTrainedLayersFrom() copies the already
  // trained layers from another net parameter instance.
  void CopyTrainedLayersFrom(const NetParameter& param);
  void CopyTrainedLayersFrom(const string trained_filename);
  void CopyTrainedLayersFromBinaryProto(const string trained_filename);
  void CopyTrainedLayersFromHDF5(const string trained_filename);
  void ToProto(NetParameter* param, bool write_diff = false) const;
  void ToHDF5(const string& filename, bool write_diff = false) const;

  inline const string& name() const { return name_; }
  inline const vector<string>& layer_names() const { return layer_names_; }
  inline const vector<string>& blob_names() const { return blob_names_; }
  inline const vector<shared_ptr<Blob<Dtype> > >& blobs() const {
    return blobs_;
  }
  inline const vector<shared_ptr<Layer<Dtype> > >& layers() const {
    return layers_;
  }
  inline Phase phase() const { return phase_; }
  inline const vector<vector<Blob<Dtype>*> >& bottom_vecs() const {
    return bottom_vecs_;
  }
  inline const vector<vector<Blob<Dtype>*> >& top_vecs() const {
    return top_vecs_;
  }
  inline const vector<int> & top_ids(int i) const {
    CHECK_GE(i, 0) << "Invalid layer id";
    CHECK_LT(i, top_id_vecs_.size()) << "Invalid layer id";
    return top_id_vecs_[i];
  }
  inline const vector<int> & bottom_ids(int i) const {
    CHECK_GE(i, 0) << "Invalid layer id";
    CHECK_LT(i, bottom_id_vecs_.size()) << "Invalid layer id";
    return bottom_id_vecs_[i];
  }
  inline const vector<vector<bool> >& bottom_need_backward() const {
    return bottom_need_backward_;
  }
  inline const vector<Dtype>& blob_loss_weights() const {
    return blob_loss_weights_;
  }
  inline const vector<bool>& layer_need_backward() const {
    return layer_need_backward_;
  }
  inline const vector<shared_ptr<Blob<Dtype> > >& params() const {
    return params_;
  }
  inline const vector<Blob<Dtype>*>& learnable_params() const {
    return learnable_params_;
  }
  inline const vector<float>& params_lr() const { return params_lr_; }
  inline const vector<bool>& has_params_lr() const { return has_params_lr_; }
  inline const vector<float>& params_weight_decay() const {
    return params_weight_decay_;
  }
  inline const vector<bool>& has_params_decay() const {
    return has_params_decay_;
  }
  const map<string, int>& param_names_index() const {
    return param_names_index_;
  }
  inline const vector<int>& param_owners() const { return param_owners_; }
  inline const vector<string>& param_display_names() const {
    return param_display_names_;
  }
  inline int num_inputs() const { return net_input_blobs_.size(); }
  inline int num_outputs() const { return net_output_blobs_.size(); }
  inline const vector<Blob<Dtype>*>& input_blobs() const {
    return net_input_blobs_;
  }
  inline const vector<Blob<Dtype>*>& output_blobs() const {
    return net_output_blobs_;
  }
  inline const vector<int>& input_blob_indices() const {
    return net_input_blob_indices_;
  }
  inline const vector<int>& output_blob_indices() const {
    return net_output_blob_indices_;
  }
  bool has_blob(const string& blob_name) const;
  const shared_ptr<Blob<Dtype> > blob_by_name(const string& blob_name) const;
  bool has_layer(const string& layer_name) const;
  const shared_ptr<Layer<Dtype> > layer_by_name(const string& layer_name) const;

  void set_debug_info(const bool value) { debug_info_ = value; }

  // Helpers for Init.
  static void FilterNet(const NetParameter& param,
      NetParameter* param_filtered);
  static bool StateMeetsRule(const NetState& state, const NetStateRule& rule,
      const string& layer_name);

  // Invoked at specific points during an iteration
  class Callback {
   protected:
    virtual void run(int layer) = 0;

    template <typename T>
    friend class Net;
  };
  const vector<Callback*>& before_forward() const { return before_forward_; }
  void add_before_forward(Callback* value) {
    before_forward_.push_back(value);
  }
  const vector<Callback*>& after_forward() const { return after_forward_; }
  void add_after_forward(Callback* value) {
    after_forward_.push_back(value);
  }
  const vector<Callback*>& before_backward() const { return before_backward_; }
  void add_before_backward(Callback* value) {
    before_backward_.push_back(value);
  }
  const vector<Callback*>& after_backward() const { return after_backward_; }
  void add_after_backward(Callback* value) {
    after_backward_.push_back(value);
  }

 protected:
  // Helpers for Init.
  void AppendTop(const NetParameter& param, const int layer_id,
                 const int top_id, set<string>* available_blobs,
                 map<string, int>* blob_name_to_idx);
  int AppendBottom(const NetParameter& param, const int layer_id,
                   const int bottom_id, set<string>* available_blobs,
                   map<string, int>* blob_name_to_idx);
  void AppendParam(const NetParameter& param, const int layer_id,
                   const int param_id);

  void ForwardDebugInfo(const int layer_id);
  void BackwardDebugInfo(const int layer_id);
  void UpdateDebugInfo(const int param_id);

  string name_;
  Phase phase_;
  vector<shared_ptr<Layer<Dtype> > > layers_;
  vector<string> layer_names_;
  map<string, int> layer_names_index_;
  vector<bool> layer_need_backward_;
  vector<shared_ptr<Blob<Dtype> > > blobs_;
  vector<string> blob_names_;
  map<string, int> blob_names_index_;
  vector<bool> blob_need_backward_;
  vector<vector<Blob<Dtype>*> > bottom_vecs_;
  vector<vector<int> > bottom_id_vecs_;
  vector<vector<bool> > bottom_need_backward_;
  vector<vector<Blob<Dtype>*> > top_vecs_;
  vector<vector<int> > top_id_vecs_;
  vector<Dtype> blob_loss_weights_;
  vector<vector<int> > param_id_vecs_;
  vector<int> param_owners_;
  vector<string> param_display_names_;
  vector<pair<int, int> > param_layer_indices_;
  map<string, int> param_names_index_;
  vector<int> net_input_blob_indices_;
  vector<int> net_output_blob_indices_;
  vector<Blob<Dtype>*> net_input_blobs_;
  vector<Blob<Dtype>*> net_output_blobs_;
  vector<shared_ptr<Blob<Dtype> > > params_;
  vector<Blob<Dtype>*> learnable_params_;
  vector<int> learnable_param_ids_;
  vector<float> params_lr_;
  vector<bool> has_params_lr_;
  vector<float> params_weight_decay_;
  vector<bool> has_params_decay_;
  size_t memory_used_;
  bool debug_info_;
  // Callbacks
  vector<Callback*> before_forward_;
  vector<Callback*> after_forward_;
  vector<Callback*> before_backward_;
  vector<Callback*> after_backward_;

DISABLE_COPY_AND_ASSIGN(Net);
};


}  // namespace caffe

#endif  // CAFFE_NET_HPP_