Main v0 release
Module updates
- Fused LSTM kernels in mLSTM module with
fuse_lstm
flags
Model updates - improved model serialization size and options
- no saving of gradients
- saving optimizer is optional
- reloading weights trained with weight norm is more stable
Weight Norm/Reparameterization update
- modified hooks to work with fused LSTM kernel
Data updates - Parses dataset types (csv, json, etc) automatically. Only need to specify supervised vs unsupervised
- Added loose json functionality
- Tested csv datasets more thoroughly
- Save Names of processed results fixed so that original file's name stays the same now.
- Fixed DataParallel/DistributedDP batching of evaluation datasets
- Made it easier to specify validation/test datasets
- Made it easier to specify dataset shards
- Added negative sequence lengths for datasets.