- 30 Sep, 2019 1 commit
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Sarthak Garg authored
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
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- 30 Jul, 2019 1 commit
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Myle Ott authored
Summary: The previous BSD+PATENTS license was controversial. We have been approved to relicense fairseq under the MIT license. Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/786 Differential Revision: D16560654 Pulled By: myleott fbshipit-source-id: f78b1beb4f2895dd7b9bfc79f5f952a2bfb94034
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- 21 Jul, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/747 Differential Revision: D16403464 Pulled By: myleott fbshipit-source-id: ee3b4184f129a02be833c7bdc00685978b4de883
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- 19 Jul, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/734 Differential Revision: D16377044 Pulled By: myleott fbshipit-source-id: 37d5553d76aa7c653113fec089f59710281c31d7
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- 10 Jun, 2019 1 commit
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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
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- 08 May, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/720 Differential Revision: D15259091 Pulled By: myleott fbshipit-source-id: 06a35996c06ccddb49fdc9e01e348ff3c9da334e
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- 30 Apr, 2019 1 commit
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Myle Ott authored
Summary: - Add --add-bos-token option to LM task - Cleanup utils.py and options.py Pull Request resolved: https://github.com/pytorch/fairseq/pull/654 Differential Revision: D15041794 Pulled By: myleott fbshipit-source-id: 3ad00007769d5f48308052cfd40de39c5ffa1a6e
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- 29 Mar, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/606 Differential Revision: D14680968 Pulled By: myleott fbshipit-source-id: 8044d828a8167199c10f2aee24f7e611feb91802
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- 19 Mar, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/587 Differential Revision: D14517597 Pulled By: myleott fbshipit-source-id: 4831ea5a9da1c2e207529a4ab3c4d0b070f5f34e
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- 28 Feb, 2019 1 commit
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Vladimir Karpukhin authored
Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/541 Just a combo of a stacked pair D14057943 & D14176011, Made this as a separete diff cause there seems to be some issue with porting a stacked change into github repo Differential Revision: D14251048 fbshipit-source-id: 0a47f534a69d6ab2ebe035fba40fd51748cccfb8
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- 26 Feb, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/528 Differential Revision: D14218377 Pulled By: myleott fbshipit-source-id: facb0a32f6aebf56a4fea7259080394ad2d2d846
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- 22 Feb, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/pytorch/translate/pull/351 This makes it easier for tasks to plugin to generate.py/interactive.py Pull Request resolved: https://github.com/pytorch/fairseq/pull/520 Differential Revision: D14183881 Pulled By: myleott fbshipit-source-id: ede5e53ddc1215ed3b12b8f1eba048c946913c33
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- 16 Feb, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/505 Differential Revision: D14110201 Pulled By: myleott fbshipit-source-id: 099ce61fa386c016f3a1d1815c6fe1a9a6c9005d
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- 05 Feb, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/489 Differential Revision: D13956810 Pulled By: myleott fbshipit-source-id: 61ace179d1d3790226c38b3f3e47f5452b5ec514
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- 30 Jan, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/484 Differential Revision: D13880636 Pulled By: myleott fbshipit-source-id: 984b2e1c3b281c28243102eb971ea45ec891d94e
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- 16 Jan, 2019 1 commit
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Davide Caroselli authored
Summary: On a multi-gpu training scenario, the `train.py` script spawns new processes with `torch.multiprocessing.spawn`. Unfortunately those child processes don't inherit the modules imported with `--user-dir`. This pull request fixes this problem: custom module import in now explicit on every `main()` function. Pull Request resolved: https://github.com/pytorch/fairseq/pull/449 Differential Revision: D13676922 Pulled By: myleott fbshipit-source-id: 520358d66155697885b878a37e7d0484bddbc1c6
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- 05 Jan, 2019 1 commit
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Myle Ott authored
Summary: Pull Request resolved: https://github.com/pytorch/translate/pull/283 Pull Request resolved: https://github.com/pytorch/fairseq/pull/428 Differential Revision: D13564190 Pulled By: myleott fbshipit-source-id: 3b62282d7069c288f5bdd1dd2c120788cee4abb5
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- 26 Dec, 2018 1 commit
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Myle Ott authored
Summary: - 04cc608: Add `--match-source-len` option to generate.py to for sequence-tagging tasks - 19f1a40: Add `--no-repeat-ngram-size` option to generate.py for ngram blocking Pull Request resolved: https://github.com/pytorch/fairseq/pull/422 Differential Revision: D13548445 Pulled By: myleott fbshipit-source-id: 26d1ae83993e428fcb020dac5ae358b0e36233d9
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- 25 Sep, 2018 1 commit
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Stephen Roller authored
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- 03 Sep, 2018 3 commits
- 25 Jul, 2018 2 commits
- 19 Jul, 2018 1 commit
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Sergey Edunov authored
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- 08 Jul, 2018 1 commit
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Angela Fan authored
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- 25 Jun, 2018 1 commit
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Myle Ott authored
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- 21 Jun, 2018 1 commit
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Myle Ott authored
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- 15 Jun, 2018 7 commits
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Myle Ott authored
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Myle Ott authored
A Task defines the data format, stores shared state (e.g., dictionaries) and provides helpers for building the model/criterion and calculating the loss. Changes: - Add TranslationTask and LanguageModelingTask. New tasks can be registered with @register_task decorator. - Add EpochBatchIterator to encapsulate batching and saving/restoring dataloader position - Remove LEFT_PAD_* constants and make them configurable per task
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Myle Ott authored
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Angela Fan authored
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alexeib authored
This implements convolutional language model from https://arxiv.org/pdf/1612.08083.pdf There are 3 modes for constructing batches: - token block: fill each sample with a specified number of tokens without regard for sentence delimiters - this is what was used for training in the paper - complete: fill each sample with a specified number of tokens but make sure it contains only complete sentences (i.e. if next sentence goes over token block limit, move it to the next sample) - this was used for evaluation in the paper - eos: one sentence per sample (skip blank lines) some results: GCNN-13 - GBW - 37.46 GCNN-14B - GBW - 33.88 GCNN-8 - Wiki103 - 43.76 GCNN-14 - Wiki103 - 35.66 train: python train.py /private/home/abaevski/data/wiki103 --save-dir /tmp --fp16 --max-epoch 35 --save-interval 1 --save-interval-updates 1000 --keep-interval-updates 25 --arch fconv_lm --optimizer nag --lr 1.0 --lr-scheduler reduce_lr_on_plateau --lr-shrink 0.5 --decoder-embed-dim 280 --decoder-layers '[(850, 6)] * 3 + [(850,1)] + [(850,5)] * 4 + [(850,1)] + [(850,4)] * 3 + [(1024,4)] + [(2048, 4)]' --clip-norm 0.1 --dropout 0.2 --weight-decay 5e-06 --criterion cross_entropy --max-tokens 1024 --max-target-positions 1024 --seed 1 --log-format json --log-interval 500 eval: python eval_lm.py ~abaevski/data/wiki103 --path '/checkpoint02/abaevski/2018-04-27/lm_wiki.fp16.mxup300000.fconv.adam.lrs=reduce_lr_on_plateau.emb280.layers(850,6)*3+(850,1)+(850,5)*4+(850,1)+(850,4)*3+(1024,1)+(2048,4).lr0.0005.clp0.1.drp0.3.wd0.0.crt=cross_entropy.mxtk2048.smptk256.seed1.ngpu8/checkpoint_last.pt'
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Alexei Baevski authored
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Sergey Edunov authored
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- 01 May, 2018 2 commits
- 02 Apr, 2018 1 commit
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Myle Ott authored
Changes: - 7d19e36: Add `--sampling` flag to generate.py to sample instead of doing beam search - c777340: Add `scripts/average_checkpoints.py` to average multiple checkpoints into a combined model - 3ea882c: Add `--max-update` option to train.py to stop training after a given number of updates - small bugfixes for distributed training, LSTM, inverse square root LR scheduler
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- 27 Feb, 2018 2 commits
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Myle Ott authored
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Myle Ott authored
This PR includes breaking API changes to modularize fairseq-py and adds support for distributed training across multiple nodes. Changes: - c7033ef: add support for distributed training! See updated README for usage. - e016299: modularize fairseq-py, adding support for register_model, register_criterion, register_optimizer, etc. - 154e440: update LSTM implementation to use PackedSequence objects in the encoder, better following best practices and improving perf - 90c2973 and 1da6265: improve unit test coverage
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