Hi, this is a pretty big release of
nnForge. The most important improvement is that mode schemas are now stored in
Protobuf format. You now define the schema via plain text file. Use convert_schema action to convert from old binary format to new one. I also implemented
Overfeat functionality - this allows running inference on large input data with fine-frained results efficiently.
All the change are:
- Schema:
- Model schema is now stord in Protobuf format. Use convert_schema to convert schemas in old binary format to new one
- Input and output data normalizers are stored in protobuf format now. Use convert_input_normalizer and convert_output_normalizer to convert existing binary normalizers to new format
- Schema and data are compatible now if non-empty layers match. Now empty-data layers don't matter
- Training data:
- Improvements insupervised_image_stream_reader
- embed_data_transformer added
- Training:
- Nesterov momentum added (see --momentum_type option)
- uniform_intensity_data_transformer added
- Momentum data is kept between epochs (it is save and restored as well)
- ROC result outputs accuracy, precision, recall, and F-score now (in addition to AUC)
- Visualization:
- snapshot_invalid now saves images, including binary classifier case
- Inference:
- Overfeat functionality added (see tiling option of max subsampling layer, and untile layer)
