Summary:
- Make arrow iterator able to read from jsonl files, the entropies are omitted in this case
- Make the data/checkpoint code fsspec compatible
- Fix issues with all reduce with non-bf16 in dist_sum and norm computation.
- Minimal fixes to get eval to run, it is slow currently
- Add bpb numbers during training
Test Plan:
Run
```
torchrun --nproc-per-node 8 -m bytelatent.train config=internal/configs/entropy_model.yaml eval=null max_steps=10100
```
Summary:
- Refactor local model configs to be separate and clearer
- Add attention arguments and correct which attention is used in local models
- Preparation for being able to have an entropy train script
- Fix failing unit tests
Test Plan:
Summary:
For compatibility with either local/nfs or S3 datasets, swap to fsspec.
Add a tool to compare local and remote filesystems
Test Plan:
- Ran regular train script
- Ran with config with data in S3
