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  1. 11 Jun, 2019 6 commits
  3. 10 Jun, 2019 2 commits
    • Myle Ott's avatar
      More generator features for demo (#791) · 4868c182
      Myle Ott authored 
      Summary:
- make it possible to load file_utils.py without the dependencies
- add some more demo features
Pull Request resolved: https://github.com/pytorch/fairseq/pull/791

Differential Revision: D15739950

Pulled By: myleott

fbshipit-source-id: 38df5209973a6fe2e3651575b97134e096aaf5bf
      4868c182
    • freewym's avatar
      fix log printing in progress bar (#778) · a58c1127
      freewym authored 
      Summary:
In the current progress bar, the counter for log_interval will always start from 0, which is not correct if  reloading from a checkpoint in the middle of an epoch. This fix obtains the offset from the iterator to set the counter correctly.
Pull Request resolved: https://github.com/pytorch/fairseq/pull/778

Differential Revision: D15739953

Pulled By: myleott

fbshipit-source-id: a1d13403ec5783b22e01d7cb63874fd8dea7f8b0
      a58c1127
  5. 07 Jun, 2019 1 commit
  7. 06 Jun, 2019 1 commit
  9. 04 Jun, 2019 4 commits
  11. 03 Jun, 2019 2 commits
  13. 02 Jun, 2019 2 commits
  15. 01 Jun, 2019 1 commit
  17. 31 May, 2019 1 commit
  19. 30 May, 2019 7 commits
  21. 29 May, 2019 7 commits
  23. 28 May, 2019 1 commit
  25. 24 May, 2019 2 commits
  27. 23 May, 2019 3 commits
    • Jason Fried's avatar
      collections.abc python 3.8 · 6b3a516f
      Jason Fried authored 
      Summary:
In python 3.7 collections.abc warns when importing abc classes from `collections`
In 3.8 this will not work at all.

This changes all code using abc's from collections to attempt to import from `collections.abc`

I am not fixing existing lint's don't ask, if `arc lint` auto-fixed I accepted, except for spelling in code.

Reviewed By: lisroach

Differential Revision: D15461049

fbshipit-source-id: ac2bf2ec8cffacd8ba5572882b0832bbf99a1646
      6b3a516f
    • Myle Ott's avatar
      Fix gating for find_unused_parameters · 128f4bea
      Myle Ott authored 
      Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/600

Differential Revision: D15469322

Pulled By: myleott

fbshipit-source-id: fdefa8efbb10e48b2a04a6bc10404fd2f3f21ecf
      128f4bea
    • Kritika Singh's avatar
      Allow unused params in distributed training · 72a5487c
      Kritika Singh authored 
      Summary:
Context from https://fb.workplace.com/groups/1405155842844877/permalink/2785095451517569/:

I am adding a model to pyspeech (formerly fairspeq) with the following `forward`:
```
def forward(self, src_tokens, src_lengths, prev_output_tokens, name):
    encoder_out = self.encoder(src_tokens, src_lengths)
    if name == Dataset.d1:
        decoder_out = self.decoder1(prev_output_tokens, encoder_out)
    elif name == Dataset.d2:
        decoder_out = self.decoder2(encoder_out)
    return decoder_out
```
When I run distributed training on this model, I get the following error:

```
RuntimeError: Expected to have finished reduction in the prior iteration before starting a
new one. This error indicates that your module has parameters that were not used in
producing loss. You can enable unused parameter detection by (1) passing the keyword
argument `find_unused_parameters=True` to `torch.nn.parallel.DistributedDataParallel`; (2)
making sure all `forward` function outputs participate in calculating loss. If you already have
done the above two steps, then the distributed data parallel module wasn't able to locate the
output tensors in the return value of your module's `forward` function. Please include the loss
function and the structure of the return value of `forward` of your module when reporting this
issue (e.g. list, dict, iterable). (prepare_for_backward at
caffe2/torch/csrc/distributed/c10d/reducer.cpp:410)
```

The recommended fix is to pass find_unused_parameters=True to DistributedDataParallel's initialization

Reviewed By: myleott

Differential Revision: D15439726

fbshipit-source-id: 7fd80d4a3f49ac90182dec723b49b14e6689406a
      72a5487c