GitLab

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/846

Reviewed By: jcai1

Differential Revision: D17845996

Pulled By: okhonko

fbshipit-source-id: 3826fd9a4418496916bf1835c319dd85c89945cc

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/884

Differential Revision: D17774515

Pulled By: alexeib

fbshipit-source-id: d1ffe8ab723fa284c69b067bbd43d699eaa2f02f

Implementation of the paper "Jointly Learning to Align and Translate with Transformer Models" (#877)

Summary:
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/877

This PR implements guided alignment training described in  "Jointly Learning to Align and Translate with Transformer Models (https://arxiv.org/abs/1909.02074)".

In summary, it allows for training selected heads of the Transformer Model with external alignments computed by Statistical Alignment Toolkits. During inference, attention probabilities from the trained heads can be used to extract reliable alignments. In our work, we did not see any regressions in the translation performance because of guided alignment training.
Pull Request resolved: https://github.com/pytorch/fairseq/pull/1095

Differential Revision: D17170337

Pulled By: myleott

fbshipit-source-id: daa418bef70324d7088dbb30aa2adf9f95774859

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1200

Differential Revision: D17659658

Pulled By: myleott

fbshipit-source-id: 1863e6d60a439dbb7e71e5da68817c9d53649737

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1197

Differential Revision: D17651374

Pulled By: myleott

fbshipit-source-id: 5feb986de1e682eb83c4479f419ad51325718572

Summary:
For batched predictions in Roberta, the README was giving an example that was pretty unclear. After a thorough discussion with ngoyal2707 in issue https://github.com/pytorch/fairseq/issues/1167 he gave a clear example of how batched predictions were supposed to be done. Since I spent a lot of time on this inconsistency, I thought that it might benefit the community if his solution was in the official README 😄 !

For for details, see issue https://github.com/pytorch/fairseq/issues/1167
Pull Request resolved: https://github.com/pytorch/fairseq/pull/1195

Differential Revision: D17639354

Pulled By: myleott

fbshipit-source-id: 3eb60c5804a6481f533b19073da7880dfd0d522d

Summary:
Code for our NeurIPS paper [Levenshtein Transformer](https://arxiv.org/abs/1905.11006)
* Added Levenshtein Transformer model, task and criterion class
* Added iterative NAT Transformer, insertion Transformer and CMLM Transformer model class for baselines
* Add an option for prepending BOS to dictionary class and translation task class

Reviewed By: myleott

Differential Revision: D17297372

fbshipit-source-id: 54eca60831ae95dc721c2c34e882e1810ee575c7

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1174

Differential Revision: D17627767

Pulled By: myleott

fbshipit-source-id: 7b5f77146b8776a5967699e430136039c066c851

Summary:
This is to make this instructions a little more generalizable, since in some systems, bash will parse the spaces within quotes

Addressing https://github.com/pytorch/fairseq/issues/1146
Pull Request resolved: https://github.com/pytorch/fairseq/pull/1165

Differential Revision: D17547810

Pulled By: myleott

fbshipit-source-id: 5a026d42f678126b5ca8bc4477ba8f26ea549dcd

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1155

Differential Revision: D17509762

Pulled By: myleott

fbshipit-source-id: 4de535289c1f35abff0d8142d8580f3ede039f47

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1125

Differential Revision: D17431557

Pulled By: myleott

fbshipit-source-id: f712e5355d8dbb0a8f1170674d62e2b6880295b4

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1140

Differential Revision: D17431506

Pulled By: myleott

fbshipit-source-id: b47dae303d7e76daa5b49795476b5e48d7b090ad

Summary:
Added the `predicted_token` to each `topk` filled output item

Updated RoBERTa filling mask example in README.md

Reviewed By: myleott

Differential Revision: D17188810

fbshipit-source-id: 5fdc57ff2c13239dabf13a8dad43ae9a55e8931c

Summary:
When I try to reproduce the experiment in  _Hierarchical Neural Story Generation_, I found the command about generation cannot be executed.

It said that **fairseq-generate: error: unrecognized arguments: --sampling-temperature 0.8**
In the document, I find:
```
--temperature   temperature for generation
Default: 1.0
```
And I don't find a parameter named `--sampling-temperature`, so I think the parameter `--sampling-temperature` should be changed to `--temperature`
Pull Request resolved: https://github.com/pytorch/fairseq/pull/1099

Differential Revision: D17163065

Pulled By: myleott

fbshipit-source-id: 25c430eeee4703f8ec30353825ffec4bb973da0d

Summary:
With this white space, the command might fail.
```
fairseq-preprocess: error: unrecognized arguments:
zsh: command not found: --destdir
```
Pull Request resolved: https://github.com/pytorch/fairseq/pull/1063

Differential Revision: D17072516

Pulled By: myleott

fbshipit-source-id: 68bb9d05b40b215b18aceac2bff3f5ec1ef2f537

Summary:
2018->2019
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/842

Differential Revision: D16973530

Pulled By: nng555

fbshipit-source-id: 00207b79821ac0257a53a0581a84582130e1bff5

Summary:
Add links to pre-trained cuda models in pay less attention
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/828

Reviewed By: michaelauli

Differential Revision: D16833577

Pulled By: nng555

fbshipit-source-id: 1556aa77fd87ea259812de8ef65963257c370f9b

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/840

Differential Revision: D16947645

Pulled By: myleott

fbshipit-source-id: e869789bc22bbf5cb08d9adfa44f9fc09b3805af

Summary:
Training is failing sometimes because `self.collater` can be both method and property for AsrDataset
https://github.com/pytorch/fairseq/issues/1036

Reviewed By: jcai1

Differential Revision: D16919945

fbshipit-source-id: b34ba54e4dae315b7c723996610a348a8e3031af

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/835

Differential Revision: D16904038

Pulled By: myleott

fbshipit-source-id: 2c9d0b913f8d688297ac80fcabd905bd1397f66a

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1041

Differential Revision: D16904073

Pulled By: myleott

fbshipit-source-id: 22e5e25a15f7a0b6f2d827d98c953a6cec07610e

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/827

Differential Revision: D16833252

Pulled By: myleott

fbshipit-source-id: 8eded8cc651002dfd60869fc2383d305ed335d3a

Summary:
Implementation of noisy channel model reranking for release with paper
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/667

Reviewed By: michaelauli

Differential Revision: D15901665

Pulled By: nng555

fbshipit-source-id: 2de2c518be8e5828ffad72db3e741b0940623373

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/826

Differential Revision: D16830402

Pulled By: myleott

fbshipit-source-id: 25afaa6d9de7b51cc884e3f417c8e6b349f5a7bc

Summary:
1) So far getting `78%`  on winogrande validation dataset comapred to `63.5%` in the paper.
2) Will upgrade readme once everything is finalized.

Questions:

1) Should I just call `binary_wsc_task` instead of `winogrande` to be less specific to dataset and be generic?
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/825

Differential Revision: D16810159

fbshipit-source-id: cfde73561fa4caaaa63a4773c0aecd12ce1fa518

Summary:
CUDA code for light/dynamicconv kernels, including pytorch modules. Modules can be built by running setup.py in each respective folder, and can then be imported and used like any other module.
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/547

Reviewed By: myleott, shubho

Differential Revision: D15703660

Pulled By: nng555

fbshipit-source-id: e9c913753be3a1cd571965f7200df6678b644520

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/823

Differential Revision: D16804995

Pulled By: myleott

fbshipit-source-id: abac5dc0ed6b7bfe2309ba273456e54b37340b2c

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1014

Differential Revision: D16784120

Pulled By: myleott

fbshipit-source-id: 946c0e33b594f8378e4ab6482ce49efcb36e1743

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/820

Differential Revision: D16783469

fbshipit-source-id: d5af8ba6a6685608d67b72d584952b8e43eabf9f

Summary:
- remove unnecessary extra spaces in RACE data in preprocessing
- fix finetuning instructions (add `--truncate-sequence` and add `--dropout` params)
- close file handle in SentenceRankingTask
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/818

Differential Revision: D16770055

Pulled By: myleott

fbshipit-source-id: 2c80084e92cdf8692f2ea7e43f7c344c402b9e61

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1004

Differential Revision: D16751443

Pulled By: myleott

fbshipit-source-id: f70acd6c7be6d69da45b5b32fe4c4eff021539ab

Summary:
This task and loss are used for sentence ranking and multiple choice tasks such as RACE
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/809

Reviewed By: myleott

Differential Revision: D16715745

Pulled By: jingfeidu

fbshipit-source-id: cb4d1c7b26ebb3e2382449ba51af5745ef56f30f

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/815

Differential Revision: D16733633

fbshipit-source-id: 0a5029e41b6dbb9fb28e9703ad057d939d489d90

Summary:
Allow shell script to create sub directories with -p flag. Amends readme file too.
Pull Request resolved: https://github.com/pytorch/fairseq/pull/997

Differential Revision: D16710813

Pulled By: myleott

fbshipit-source-id: 89abefa27e8fac99d212fc9b7b0dbc3690043ba0

Summary:
Initial code for speech recognition task.
Right now only one ASR model added - https://arxiv.org/abs/1904.11660

unit test testing:
python -m unittest discover tests

also run model training with this code and obtained
5.0 test_clean | 13.4 test_other
on librispeech with pytorch/audio features
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/810

Reviewed By: cpuhrsch

Differential Revision: D16706659

Pulled By: okhonko

fbshipit-source-id: 89a5f9883e50bc0e548234287aa0ea73f7402514

Summary:
1) This currently works only for single `<mask>` token as multi mask, we might have to look more into order of factorization.
2) This is currently only for single BPE token
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/807

Differential Revision: D16674509

fbshipit-source-id: 0a020030ee5df6a5115e5f85d5a9ef52b1ad9e1c

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/805

Differential Revision: D16670825

Pulled By: myleott

fbshipit-source-id: 872a1a0274681a34d54bda00bfcfcda2e94144c6

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/806

Differential Revision: D16649933

fbshipit-source-id: 6eeda6e2caf8019228e3efc0c27ddfcc3c4d8674

Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/795

Differential Revision: D16620488

Pulled By: myleott

fbshipit-source-id: 1998a9ccd8816fc7f590861fb4898f910a36bc1e

Summary:
fix links to .tar.gz vs .tar.bz2
Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/796

Reviewed By: myleott

Differential Revision: D16611740

Pulled By: nng555

fbshipit-source-id: 76210484225ed917ff14ef626845680d918948f5