| 731 | |
| 732 | template <typename Dtype> |
| 733 | void Net<Dtype>::CopyTrainedLayersFrom(const NetParameter& param) { |
| 734 | int num_source_layers = param.layer_size(); |
| 735 | for (int i = 0; i < num_source_layers; ++i) { |
| 736 | const LayerParameter& source_layer = param.layer(i); |
| 737 | const string& source_layer_name = source_layer.name(); |
| 738 | int target_layer_id = 0; |
| 739 | while (target_layer_id != layer_names_.size() && |
| 740 | layer_names_[target_layer_id] != source_layer_name) { |
| 741 | ++target_layer_id; |
| 742 | } |
| 743 | if (target_layer_id == layer_names_.size()) { |
| 744 | LOG(INFO) << "Ignoring source layer " << source_layer_name; |
| 745 | continue; |
| 746 | } |
| 747 | DLOG(INFO) << "Copying source layer " << source_layer_name; |
| 748 | vector<shared_ptr<Blob<Dtype> > >& target_blobs = |
| 749 | layers_[target_layer_id]->blobs(); |
| 750 | CHECK_EQ(target_blobs.size(), source_layer.blobs_size()) |
| 751 | << "Incompatible number of blobs for layer " << source_layer_name; |
| 752 | for (int j = 0; j < target_blobs.size(); ++j) { |
| 753 | if (!target_blobs[j]->ShapeEquals(source_layer.blobs(j))) { |
| 754 | Blob<Dtype> source_blob; |
| 755 | const bool kReshape = true; |
| 756 | source_blob.FromProto(source_layer.blobs(j), kReshape); |
| 757 | LOG(FATAL) << "Cannot copy param " << j << " weights from layer '" |
| 758 | << source_layer_name << "'; shape mismatch. Source param shape is " |
| 759 | << source_blob.shape_string() << "; target param shape is " |
| 760 | << target_blobs[j]->shape_string() << ". " |
| 761 | << "To learn this layer's parameters from scratch rather than " |
| 762 | << "copying from a saved net, rename the layer."; |
| 763 | } |
| 764 | const bool kReshape = false; |
| 765 | target_blobs[j]->FromProto(source_layer.blobs(j), kReshape); |
| 766 | } |
| 767 | } |
| 768 | } |
| 769 | |
| 770 | template <typename Dtype> |
| 771 | void Net<Dtype>::CopyTrainedLayersFrom(const string trained_filename) { |