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  1. 11 Dec, 2018 1 commit
  3. 08 Dec, 2018 1 commit
  5. 07 Dec, 2018 2 commits
    • Myle Ott's avatar
      Add --fp16-scale-tolerance (#397) · 03ef3ab8
      Myle Ott authored 
      Summary:
Let's only decrease the loss scale if a large enough percentage of batches overflow.
Pull Request resolved: https://github.com/pytorch/fairseq/pull/397

Differential Revision: D13355159

Pulled By: myleott

fbshipit-source-id: e17dde73d34a639519b4348c013fdd19d2b314e6
      03ef3ab8
    • Halil Akin's avatar
      Take a dummy train step under OOM to keep multiprocessing in sync · 6c006a34
      Halil Akin authored 
      Summary: This is not a guaranteed solution (since processes may still get out of sync if OOM happens after an all_gather/all_reduce has been done) - but should still make multiprocessing training more robust in practice since it seems we usually OOM early enough.

Reviewed By: myleott

Differential Revision: D13086018

fbshipit-source-id: feb1b01c2eb8818797cfdabc0faac8056ba1b4ee
      6c006a34
  7. 06 Dec, 2018 4 commits
  9. 04 Dec, 2018 1 commit
  11. 30 Nov, 2018 1 commit
  13. 29 Nov, 2018 2 commits
  15. 27 Nov, 2018 2 commits
  17. 26 Nov, 2018 2 commits
  19. 19 Nov, 2018 1 commit
    • Halil Akin's avatar
      Protect against failures in case of OOMs · a442244d
      Halil Akin authored 
      Summary: Fixing some distributed failures that happen when OOMs are observed.

Reviewed By: myleott

Differential Revision: D13121054

fbshipit-source-id: f71a0a695332acbaa1797e89887b8b7c7ddaa727
      a442244d
  21. 18 Nov, 2018 2 commits
  23. 17 Nov, 2018 1 commit
  25. 16 Nov, 2018 1 commit
    • Haoran Li's avatar
      make dictionary optional · a4e34985
      Haoran Li authored 
      Reviewed By: jingfeidu

Differential Revision: D13104360

fbshipit-source-id: 9636f5ee2721818f98b33af559fa24292534a72f
      a4e34985
  27. 14 Nov, 2018 1 commit
  29. 13 Nov, 2018 1 commit
  31. 10 Nov, 2018 1 commit
    • Ruty Rinott's avatar
      pipeline for LM training · 880e7cd4
      Ruty Rinott authored 
      Summary:
step 2 of pipeline for LM training
assumes tokenized text data as input. Splits it into train/validation/test, and runs binarization
(step a_ii in https://fb.quip.com/kazzAxvZHBj9)

Reviewed By: borguz

Differential Revision: D10454705

fbshipit-source-id: 74e8679041f5507c4e404c1b719547c2ae9ed983
      880e7cd4
  33. 08 Nov, 2018 1 commit
    • Peng-Jen Chen's avatar
      Fix error when training multilingual_translation task with multi-GPU · 189fcabf
      Peng-Jen Chen authored 
      Summary:
D10052908 introduce multilingual_translation task, but it raises exception when training with multiple-GPUs: P60202593

With Myle's help, we found that it is because of improperly handled dummy batch data type, and it causes optimizer.backward() is not executed same number of times cross different GPUs.

Reviewed By: xianxl

Differential Revision: D12964263

fbshipit-source-id: 4991039030bf373f0c484e131acc4736487be4d8
      189fcabf
  35. 07 Nov, 2018 2 commits
    • Myle Ott's avatar
      Merge internal changes · 8eb232ce
      Myle Ott authored 
      Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/352

Differential Revision: D12956930

Pulled By: myleott

fbshipit-source-id: 39334a79544bac570feb04be9103269d7c1563f9
      8eb232ce
    • Liezl Puzon's avatar
      Support BPE end of word marker suffix in fairseq noising module · 2b13f3c0
      Liezl Puzon authored 
      Summary:
There are 2 ways to implement BPE:
1. use a continuation marker suffix to indicate that there is at least one more subtoken left in the word
2. use a end of word marker suffix to indicate that there is no more subtokens left in the word

This adds some logic to account for either kind of BPE marker suffix. This diff adds a corresponding test. I also refactored the test setup to reduce the number of boolean args when setting up test data.

Reviewed By: xianxl

Differential Revision: D12919428

fbshipit-source-id: 405e9f346dce6e736c1305288721dfc7b63e872a
      2b13f3c0
  37. 02 Nov, 2018 2 commits
  39. 01 Nov, 2018 6 commits
  41. 30 Oct, 2018 1 commit
    • James Cross's avatar
      transformer onnx trace: skip no-op transpose (#333) · 672977c1
      James Cross authored 
      Summary:
Pull Request resolved: https://github.com/pytorch/fairseq/pull/333

A tiny hack to speed up inference slightly for transformer beam search after export to graph mode. Specifically, there is no need to transpose a dimension with size 1 (the sequence length of a single decoder time step during beam search) with its neighbor immediately before a view/reshape.

Reviewed By: jmp84

Differential Revision: D12833011

fbshipit-source-id: f9c344a9ad595e6e48a8a65b31cf2b1392f9b938
      672977c1
  43. 27 Oct, 2018 1 commit
    • Xian Li's avatar
      Extend WordShuffle noising function to apply to non-bpe tokens · 90c01b3a
      Xian Li authored 
      Summary:
We'd like to resue the noising functions and DenoisingDataset in
adversarial training. However, current noising functions assume the input are
subword tokens. The goal of this diff is to extend it so the noising can be
applied to word tokens. Since we're mostly interested in the word shuffle
noising, so I only modified the WordShuffle class.

Reviewed By: liezl200

Differential Revision: D10523177

fbshipit-source-id: 1e5d27362850675010e73cd38850c890d42652ab
      90c01b3a
  45. 26 Oct, 2018 1 commit
    • Wei Ho's avatar
      Fix print & add more informative logging · 6117f827
      Wei Ho authored 
      Summary: Fix fairseq's `force` option for disabling print suppression (otherwise, `print(..., force=True)` fails on master since the force kwarg gets passed to the builtin print).

Reviewed By: dpacgopinath

Differential Revision: D10522058

fbshipit-source-id: bbc10c021a7d21396ebfbb1bf007f6b9b162f4fd
      6117f827
  47. 25 Oct, 2018 2 commits