v0.8.0 -> v0.9.0 (facebookresearch#1452)

Summary:
Possibly breaking changes:
- Set global numpy seed (4a7cd58)
- Split `in_proj_weight` into separate k, v, q projections in MultiheadAttention (fdf4c3e)
- TransformerEncoder returns namedtuples instead of dict (27568a7)

New features:
- Add `--fast-stat-sync` option (e1ba32a)
- Add `--empty-cache-freq` option (315c463)
- Support criterions with parameters (ba5f829)

New papers:
- Simple and Effective Noisy Channel Modeling for Neural Machine Translation (49177c9)
- Levenshtein Transformer (86857a5, ...)
- Cross+Self-Attention for Transformer Models (4ac2c5f)
- Jointly Learning to Align and Translate with Transformer Models (1c66792)
- Reducing Transformer Depth on Demand with Structured Dropout (dabbef4)
- Unsupervised Cross-lingual Representation Learning at Scale (XLM-RoBERTa) (e23e5ea)
- BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension (a92bcda)
- CamemBERT: a French BERT (b31849a)

Speed improvements:
- Add CUDA kernels for LightConv and DynamicConv (f840564)
- Cythonization of various dataloading components (4fc3953, ...)
- Don't project mask tokens for MLM training (718677e)
Pull Request resolved: facebookresearch#1452

Differential Revision: D18798409

Pulled By: myleott

fbshipit-source-id: 860a0d5aaf7377c8c9bd63cdb3b33d464f0e1727

v0.7.2 -> v0.8.0 (facebookresearch#1017)

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`
- f812e52: Renamed data.transforms -> data.encoders
- 654affc: New Dataset API (optional)
- `47fd985`: Deprecate old Masked LM components
- `5f78106`: Set mmap as default dataset format and infer format automatically
- Misc fixes for sampling
- Misc fixes to support PyTorch 1.2
Pull Request resolved: facebookresearch#1017

Differential Revision: D16799880

Pulled By: myleott

fbshipit-source-id: 45ad8bc531724a53063cbc24ca1c93f715cdc5a7

v0.7.1 -> v0.7.2 (facebookresearch#891)

Summary:
No major API changes since the last release. Cutting a new release since we'll be merging significant (possibly breaking) changes to logging, data loading and the masked LM implementation soon.
Pull Request resolved: facebookresearch#891

Differential Revision: D16377132

Pulled By: myleott

fbshipit-source-id: f1cb88e671ccd510e53334d0f449fe18585268c7

v0.7.1: fix PyPI setup and tests

Summary: Pull Request resolved: facebookresearch#818

Differential Revision: D15916265

Pulled By: myleott

fbshipit-source-id: c66c0bd988d3472c4150226952f34ee8d4c3db86

v0.7.0 (facebookresearch#817)

Summary:
Notable (possibly breaking) changes:
- d45db80: Remove checkpoint utility functions from utils.py into checkpoint_utils.py
- f2563c2: Move LM definitions into separate files
- dffb167: Updates to model API:
  - `FairseqModel` -> `FairseqEncoderDecoderModel`
  - add `FairseqDecoder.extract_features` and `FairseqDecoder.output_layer`
  - `encoder_out_dict` -> `encoder_out`
  - rm unused `remove_head` functions
- 34726d5: Move `distributed_init` into `DistributedFairseqModel`
- cf17068: 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)
- d45db80: Change default LR scheduler from `reduce_lr_on_plateau` to `fixed`
- 96ac28d: Rename `--sampling-temperature` -> `--temperature`
- fc1a19a: Deprecate dummy batches
- a1c997b: Add memory mapped datasets
- 0add50c: Allow cycling over multiple datasets, where each one becomes an "epoch"

Plus many additional features and bugfixes
Pull Request resolved: facebookresearch#817

Differential Revision: D15913844

Pulled By: myleott

fbshipit-source-id: d5b5d678efdd9dd3e4d7ca848ddcf1ec2b21bf6b

0.6.1 -> 0.6.2 (facebookresearch#577)

Summary:
Changelog:
- 998ba4f: Add language models from Baevski & Auli (2018)
- 4294c4f: Add mixture of experts code from Shen et al. (2019)
- 0049349: Add example for multilingual training
- 48d9afb: Speed improvements, including fused operators from apex
- 44d27e6: Add Tensorboard support
- d17fa85: Add Adadelta optimizer
- 9e1c880: Add `FairseqEncoderModel`
- b65c579: Add `FairseqTask.inference_step` to modularize generate.py
- 2ad1178: Add back `--curriculum`
- Misc bug fixes and other features

Pull Request resolved: facebookresearch#577

Differential Revision: D14481233

Pulled By: myleott

fbshipit-source-id: 4ff8625ef1c0b24273fc65df7c5658e3c932e8b7

Add fairseq to PyPI (facebookresearch#495)

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: facebookresearch#495

Differential Revision: D14017761

Pulled By: myleott

fbshipit-source-id: 10c9f6634a3056074eac2f33324b4f1f404d4235

Online backtranslation module

Co-authored-by: liezl200 <[email protected]>

0.4.0 -> 0.5.0

Changelog:
- 97b58b4: add Transformer model from Vaswani et al. (2017)
- b2374e5: faster Transformer inference with improved caching
- 2d27ae0: simulate large mini-batch training with delayed updates (`--update-freq`)
- 7ee1d28: add FP16 training support (`--fp16`)
- 2a84f46: faster inference by removing completed sentences from the batch
- 663fd80: batched interactive generation
- 4c2ef2d: add language modeling / gated convolutional model from Dauphin et al. (2017)
- b59815b: add Hierarchical Neural Story Generation model from Fan et al. (2018)
- ff68a9e: add FairseqTask to modularize task definitions (e.g., translation, language modeling)

Merge internal changes (facebookresearch#163)