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  1. 03 Dec, 2019 1 commit
    • Myle Ott's avatar
      v0.8.0 -> v0.9.0 (#1452) · df2f84ce
      Myle Ott authored 
      Summary:
Possibly breaking changes:
- Set global numpy seed (4a7cd582)
- Split `in_proj_weight` into separate k, v, q projections in MultiheadAttention (fdf4c3e9)
- TransformerEncoder returns namedtuples instead of dict (27568a7e)

New features:
- Add `--fast-stat-sync` option (e1ba32aa)
- Add `--empty-cache-freq` option (315c463d)
- Support criterions with parameters (ba5f829f)

New papers:
- Simple and Effective Noisy Channel Modeling for Neural Machine Translation (49177c99)
- Levenshtein Transformer (86857a58, ...)
- Cross+Self-Attention for Transformer Models (4ac2c5f2)
- Jointly Learning to Align and Translate with Transformer Models (1c667929)
- Reducing Transformer Depth on Demand with Structured Dropout (dabbef46)
- Unsupervised Cross-lingual Representation Learning at Scale (XLM-RoBERTa) (e23e5eaa)
- BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension (a92bcdad)
- CamemBERT: a French BERT (b31849aa)

Speed improvements:
- Add CUDA kernels for LightConv and DynamicConv (f840564d)
- Cythonization of various dataloading components (4fc39538, ...)
- Don't project mask tokens for MLM training (718677eb)
Pull Request resolved: https://github.com/pytorch/fairseq/pull/1452

Differential Revision: D18798409

Pulled By: myleott

fbshipit-source-id: 860a0d5aaf7377c8c9bd63cdb3b33d464f0e1727
      df2f84ce
  3. 07 Nov, 2019 1 commit
  5. 02 Nov, 2019 1 commit
  7. 27 Sep, 2019 1 commit
    • Zhanghao Wu's avatar
      Update getting_started.rst (#1188) · 2314979e
      Zhanghao Wu authored 
      Summary:
Hi,

I think there is a minor mistake in the doc. `--distributed-no-spawn` argument is needed for distributed training on multiple machines without `slurm`. Otherwise, the program will start 8 jobs on each GPU, when `nproc_per_node=8`.
Pull Request resolved: https://github.com/pytorch/fairseq/pull/1188

Differential Revision: D17627778

Pulled By: myleott

fbshipit-source-id: 35ab6b650dc1132d7cb2d150e80d2ebf0caf3e69
      2314979e
  9. 23 Sep, 2019 1 commit
  11. 14 Aug, 2019 1 commit
    • Myle Ott's avatar
      v0.7.2 -> v0.8.0 (#1017) · ffffe04e
      Myle Ott authored 
      Summary:
Changelog:
- Relicensed under MIT license
- Add RoBERTa
- Add wav2vec
- Add WMT'19 models
- Add initial ASR code
- Changed torch.hub interface (`generate` renamed to `translate`)
- Add `--tokenizer` and `--bpe`
- f812e529: Renamed data.transforms -> data.encoders
- 654affc0: New Dataset API (optional)
- `47fd9852`: Deprecate old Masked LM components
- `5f78106a`: Set mmap as default dataset format and infer format automatically
- Misc fixes for sampling
- Misc fixes to support PyTorch 1.2
Pull Request resolved: https://github.com/pytorch/fairseq/pull/1017

Differential Revision: D16799880

Pulled By: myleott

fbshipit-source-id: 45ad8bc531724a53063cbc24ca1c93f715cdc5a7
      ffffe04e
  13. 25 Jul, 2019 1 commit
  15. 19 Jul, 2019 2 commits
  17. 20 Jun, 2019 2 commits
    • Myle Ott's avatar
      v0.7.1: fix PyPI setup and tests · 881381cf
      Myle Ott authored 
      Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/818

Differential Revision: D15916265

Pulled By: myleott

fbshipit-source-id: c66c0bd988d3472c4150226952f34ee8d4c3db86
      881381cf
    • Myle Ott's avatar
      v0.7.0 (#817) · bd710e75
      Myle Ott authored 
      Summary:
Notable (possibly breaking) changes:
- d45db804: Remove checkpoint utility functions from utils.py into checkpoint_utils.py
- f2563c21: Move LM definitions into separate files
- dffb1674: Updates to model API:
  - `FairseqModel` -> `FairseqEncoderDecoderModel`
  - add `FairseqDecoder.extract_features` and `FairseqDecoder.output_layer`
  - `encoder_out_dict` -> `encoder_out`
  - rm unused `remove_head` functions
- 34726d56: Move `distributed_init` into `DistributedFairseqModel`
- cf17068a: Simplify distributed launch by automatically launching multiprocessing on each node for all visible GPUs (allows launching just one job per node instead of one per GPU)
- d45db804: Change default LR scheduler from `reduce_lr_on_plateau` to `fixed`
- 96ac28d3: Rename `--sampling-temperature` -> `--temperature`
- fc1a19a3: Deprecate dummy batches
- a1c997bd: Add memory mapped datasets
- 0add50c2: Allow cycling over multiple datasets, where each one becomes an "epoch"

Plus many additional features and bugfixes
Pull Request resolved: https://github.com/pytorch/fairseq/pull/817

Differential Revision: D15913844

Pulled By: myleott

fbshipit-source-id: d5b5d678efdd9dd3e4d7ca848ddcf1ec2b21bf6b
      bd710e75
  19. 15 May, 2019 1 commit
    • Myle Ott's avatar
      Updates to model API (#561) · dffb1674
      Myle Ott authored 
      Summary:
- `FairseqModel` -> `FairseqEncoderDecoderModel`
- add `FairseqDecoder.extract_features` and `FairseqDecoder.output_layer`
- `encoder_out_dict` -> `encoder_out`
- rm unused `remove_head` functions
- update docs
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/561

Differential Revision: D15271142

Pulled By: myleott

fbshipit-source-id: 8e8864e399336020f0271c780598e968ff51a264
      dffb1674
  21. 12 May, 2019 1 commit
  23. 30 Apr, 2019 1 commit
  25. 15 Mar, 2019 1 commit
    • Myle Ott's avatar
      0.6.1 -> 0.6.2 (#577) · e6422528
      Myle Ott authored 
      Summary:
Changelog:
- 998ba4f: Add language models from Baevski & Auli (2018)
- 4294c4f6: Add mixture of experts code from Shen et al. (2019)
- 00493490: Add example for multilingual training
- 48d9afbe: Speed improvements, including fused operators from apex
- 44d27e64: Add Tensorboard support
- d17fa851: Add Adadelta optimizer
- 9e1c880f: Add `FairseqEncoderModel`
- b65c579b: Add `FairseqTask.inference_step` to modularize generate.py
- 2ad1178e: Add back `--curriculum`
- Misc bug fixes and other features

Pull Request resolved: https://github.com/pytorch/fairseq/pull/577

Differential Revision: D14481233

Pulled By: myleott

fbshipit-source-id: 4ff8625ef1c0b24273fc65df7c5658e3c932e8b7
      e6422528
  27. 28 Feb, 2019 1 commit
  29. 09 Feb, 2019 1 commit
    • Myle Ott's avatar
      Add fairseq to PyPI (#495) · fbd4cef9
      Myle Ott authored 
      Summary:
- fairseq can now be installed via pip: `pip install fairseq`
- command-line tools are globally accessible: `fairseq-preprocess`, `fairseq-train`, `fairseq-generate`, etc.
Pull Request resolved: https://github.com/pytorch/fairseq/pull/495

Differential Revision: D14017761

Pulled By: myleott

fbshipit-source-id: 10c9f6634a3056074eac2f33324b4f1f404d4235
      fbd4cef9
  31. 25 Jan, 2019 1 commit
  33. 15 Jan, 2019 1 commit
  35. 07 Jan, 2019 1 commit
  37. 05 Jan, 2019 1 commit
  39. 25 Sep, 2018 1 commit
    • Sergey Edunov's avatar
      Switch to DistributedDataParallelC10d and bump version 0.5.0 -> 0.6.0 · 1082ba35
      Sergey Edunov authored 
      - no more FP16Trainer, we just have an FP16Optimizer wrapper
- most of the distributed code is moved to a new wrapper class called DistributedFairseqModel, which behaves like DistributedDataParallel and a FairseqModel at the same time
- Trainer now requires an extra dummy_batch argument at initialization, which we do fwd/bwd on when there's an uneven number of batches per worker. We hide the gradients from these dummy batches by multiplying the loss by 0
- Trainer.train_step now takes a list of samples, which will allow cleaner --update-freq
      1082ba35
  41. 18 Sep, 2018 1 commit
  43. 04 Sep, 2018 1 commit
  45. 03 Sep, 2018 1 commit