Summary:
Preliminaries for data2vec release, include some minor improvements and bug fixes
Most important change is that we now default to raising an exception when fields in config do not have a corresponding field in the model dataclass
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/2929
Reviewed By: wnhsu
Differential Revision: D33649708
Pulled By: alexeib
fbshipit-source-id: 629bdb4c361550740b451c570c2005bb956c6fcb
Summary:
# Before submitting
- [ ] Was this discussed/approved via a Github issue? (no need for typos, doc improvements)
- [ ] Did you read the [contributor guideline](https://github.com/pytorch/fairseq/blob/main/CONTRIBUTING.md)?
- [ ] Did you make sure to update the docs?
- [ ] Did you write any new necessary tests?
## What does this PR do?
Fixes # (issue).
## PR review
Anyone in the community is free to review the PR once the tests have passed.
If we didn't discuss your PR in Github issues there's a high chance it will not be merged.
## Did you have fun?
Make sure you had fun coding �
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/2678
Reviewed By: Mortimerp9
Differential Revision: D32653381
Pulled By: dianaml0
fbshipit-source-id: 2810d14867cd7d64f4d340740e2b590b82de47fe
Summary:
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/1666
Context: the checkpoint saving call stack has become a bit convoluted:
```
train.py
+ checkpoint_utils.save_checkpoint
+ trainer.save_checkpoint
+ checkpoint_utils.save_state
+ checkpoint_utils.torch_persistent_save
```
This diff slightly simplifies the checkpoint saving logic by exposing a `state_dict` method inside the Trainer. This simplifies the call stack to:
```
train.py
+ checkpoint_utils.save_checkpoint
+ trainer.save_checkpoint
+ checkpoint_utils.torch_persistent_save
```
This new structure is important for the FullyShardedDataParallel diff (next diff in the stack), since it enables the Trainer to save multiple checkpoints for the different optimizer state shards.
Test Plan:
- unit tests
- trained WMT En-De models; confirmed checkpoints save/load properly, resuming from a checkpoint gives identical results
- `buck test fblearner/flow/projects/langtech/translation:tests` (2 failures are in trunk too): https://www.internalfb.com/intern/testinfra/testconsole/testrun/2533274840914654/
Reviewed By: zhengwy888
Differential Revision: D26771146
Pulled By: myleott
fbshipit-source-id: 10f91979cd42205c1d8abcaa9ab56f63eba31e93
