1 // Copyright Yangqing Jia 2013
3 #include <map>
4 #include <set>
5 #include <string>
6 #include <vector>
8 #include "caffe/proto/caffe.pb.h"
9 #include "caffe/layer_factory.hpp"
10 #include "caffe/net.hpp"
12 using std::pair;
13 using std::map;
14 using std::set;
16 namespace caffe {
18 template <typename Dtype>
19 Net<Dtype>::Net(const NetParameter& param,
20 const vector<Blob<Dtype>* >& bottom) {
21 // Basically, build all the layers and set up its connections.
22 name_ = param.name();
23 map<string, int> blob_name_to_idx;
24 set<string> available_blobs;
25 int num_layers = param.layers_size();
26 CHECK_EQ(bottom.size(), param.input_size())
27 << "Incorrect bottom blob size.";
28 // set the input blobs
29 for (int i = 0; i < param.input_size(); ++i) {
30 const string& blob_name = param.input(i);
31 CHECK_GT(bottom[i]->count(), 0);
32 shared_ptr<Blob<Dtype> > blob_pointer(
33 new Blob<Dtype>(bottom[i]->num(), bottom[i]->channels(),
34 bottom[i]->height(), bottom[i]->width()));
35 blobs_.push_back(blob_pointer);
36 blob_names_.push_back(blob_name);
37 net_input_blob_indices_.push_back(i);
38 blob_name_to_idx[blob_name] = i;
39 available_blobs.insert(blob_name);
40 }
41 // For each layer, set up their input and output
42 bottom_vecs_.resize(param.layers_size());
43 top_vecs_.resize(param.layers_size());
44 bottom_id_vecs_.resize(param.layers_size());
45 top_id_vecs_.resize(param.layers_size());
46 for (int i = 0; i < param.layers_size(); ++i) {
47 const LayerConnection& layer_connection = param.layers(i);
48 const LayerParameter& layer_param = layer_connection.layer();
49 layers_.push_back(shared_ptr<Layer<Dtype> >(GetLayer<Dtype>(layer_param)));
50 layer_names_.push_back(layer_param.name());
51 LOG(INFO) << "Creating Layer " << layer_param.name();
52 // Figure out this layer's input and output
53 for (int j = 0; j < layer_connection.bottom_size(); ++j) {
54 const string& blob_name = layer_connection.bottom(j);
55 if (available_blobs.find(blob_name) == available_blobs.end()) {
56 LOG(FATAL) << "Unknown blob input " << blob_name <<
57 " to layer" << j;
58 }
59 LOG(INFO) << layer_param.name() << " <- " << blob_name;
60 bottom_vecs_[i].push_back(
61 blobs_[blob_name_to_idx[blob_name]].get());
62 bottom_id_vecs_[i].push_back(blob_name_to_idx[blob_name]);
63 available_blobs.erase(blob_name);
64 }
65 for (int j = 0; j < layer_connection.top_size(); ++j) {
66 const string& blob_name = layer_connection.top(j);
67 if (blob_name_to_idx.find(blob_name) != blob_name_to_idx.end()) {
68 LOG(FATAL) << "Duplicate blobs produced by multiple sources.";
69 }
70 LOG(INFO) << layer_param.name() << " -> " << blob_name;
71 shared_ptr<Blob<Dtype> > blob_pointer(new Blob<Dtype>());
72 blobs_.push_back(blob_pointer);
73 blob_names_.push_back(blob_name);
74 blob_name_to_idx[blob_name] = blob_names_.size() - 1;
75 available_blobs.insert(blob_name);
76 top_vecs_[i].push_back(blobs_[blob_names_.size() - 1].get());
77 top_id_vecs_[i].push_back(blob_names_.size() - 1);
78 }
79 }
80 // In the end, all remaining blobs are considered output blobs.
81 for (set<string>::iterator it = available_blobs.begin();
82 it != available_blobs.end(); ++it) {
83 LOG(ERROR) << "This network produces output " << *it;
84 net_output_blob_indices_.push_back(blob_name_to_idx[*it]);
85 net_output_blobs_.push_back(blobs_[blob_name_to_idx[*it]].get());
86 }
88 LOG(ERROR) << "Setting up the layers.";
89 for (int i = 0; i < layers_.size(); ++i) {
90 LOG(INFO) << "Setting up " << layer_names_[i];
91 layers_[i]->SetUp(bottom_vecs_[i], &top_vecs_[i]);
92 vector<shared_ptr<Blob<Dtype> > >& layer_params = layers_[i]->params();
93 for (int j = 0; j < layer_params.size(); ++j) {
94 params_.push_back(layer_params[j]);
95 }
96 }
98 LOG(ERROR) << "Network initialization done.";
99 }
101 template <typename Dtype>
102 const vector<Blob<Dtype>*>& Net<Dtype>::Forward(
103 const vector<Blob<Dtype>*> & bottom) {
104 // Copy bottom to internal bottom
105 for (int i = 0; i < bottom.size(); ++i) {
106 blobs_[net_input_blob_indices_[i]]->CopyFrom(*bottom[i]);
107 }
108 for (int i = 0; i < layers_.size(); ++i) {
109 //LOG(ERROR) << "Forwarding " << layer_names_[i];
110 layers_[i]->Forward(bottom_vecs_[i], &top_vecs_[i]);
111 }
112 return net_output_blobs_;
113 }
115 template <typename Dtype>
116 Dtype Net<Dtype>::Backward() {
117 Dtype loss = 0;
118 // TODO(Yangqing): figure out those layers that do not need backward.
119 for (int i = layers_.size() - 1; i >= 0; --i) {
120 Dtype layer_loss = layers_[i]->Backward(
121 top_vecs_[i], true, &bottom_vecs_[i]);
122 loss += layer_loss;
123 }
124 return loss;
125 }
127 template <typename Dtype>
128 void Net<Dtype>::CopyTrainedLayersFrom(const NetParameter& param) {
129 int num_source_layers = param.layers_size();
130 for (int i = 0; i < num_source_layers; ++i) {
131 const LayerParameter& source_layer = param.layers(i).layer();
132 const string& source_layer_name = source_layer.name();
133 int target_layer_id = 0;
134 while (target_layer_id != layer_names_.size() &&
135 layer_names_[target_layer_id] != source_layer_name) {
136 ++target_layer_id;
137 }
138 if (target_layer_id == layer_names_.size()) {
139 LOG(INFO) << "Ignoring source layer " << source_layer_name;
140 continue;
141 }
142 LOG(INFO) << "Loading source layer " << source_layer_name;
143 vector<shared_ptr<Blob<Dtype> > >& target_blobs =
144 layers_[target_layer_id]->params();
145 CHECK_EQ(target_blobs.size(), source_layer.blobs_size())
146 << "Incompatible number of blobs for layer " << source_layer_name;
147 for (int j = 0; j < target_blobs.size(); ++j) {
148 target_blobs[j]->FromProto(source_layer.blobs(j));
149 }
150 }
151 }
153 template <typename Dtype>
154 void Net<Dtype>::ToProto(NetParameter* param, bool write_diff) {
155 param->Clear();
156 param->set_name(name_);
157 // Add bottom and top
158 for (int i = 0; i < net_input_blob_indices_.size(); ++i) {
159 param->add_input(blob_names_[net_input_blob_indices_[i]]);
160 }
161 LOG(INFO) << "Serializing " << layers_.size() << " layers";
162 for (int i = 0; i < layers_.size(); ++i) {
163 LayerConnection* layer_connection = param->add_layers();
164 for (int j = 0; j < bottom_id_vecs_[i].size(); ++j) {
165 layer_connection->add_bottom(blob_names_[bottom_id_vecs_[i][j]]);
166 }
167 for (int j = 0; j < top_id_vecs_[i].size(); ++j) {
168 layer_connection->add_top(blob_names_[top_id_vecs_[i][j]]);
169 }
170 LayerParameter* layer_parameter = layer_connection->mutable_layer();
171 layers_[i]->ToProto(layer_parameter);
172 }
173 }
175 template <typename Dtype>
176 void Net<Dtype>::Update() {
177 for (int i = 0; i < params_.size(); ++i) {
178 params_[i]->Update();
179 }
180 }
182 INSTANTIATE_CLASS(Net);
184 } // namespace caffe