Myle Ott
e6422528da
0.6.1 -> 0.6.2 ( #577 )
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Summary:
Changelog:
- 998ba4f4294c4f004934948d9afb44d27e6d17fa859e1c880b65c5792ad1178https://github.com/pytorch/fairseq/pull/577
Differential Revision: D14481233
Pulled By: myleott
fbshipit-source-id: 4ff8625ef1c0b24273fc65df7c5658e3c932e8b7
2019-03-15 10:27:01 -07:00
Vladimir Karpukhin
f296824f40
Move string line encoding logic from tokenizer to Dictionary (unified diff). ( #541 )
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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
2019-02-28 09:19:12 -08:00
Myle Ott
fbd4cef9a5
Add fairseq to PyPI ( #495 )
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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
2019-02-08 22:03:29 -08:00
Myle Ott
b41c74dc5b
Add code for "Pay Less Attention with Lightweight and Dynamic Convolutions" ( #473 )
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Summary:
Changelog:
- `e330f56`: Add code for the "Pay Less Attention with Lightweight and Dynamic Convolutions" paper
- `5e3b98c`: Add scripts for computing tokenized BLEU with compound splitting and sacrebleu
- update READMEs
- misc fixes
Pull Request resolved: https://github.com/pytorch/fairseq/pull/473
Differential Revision: D13819717
Pulled By: myleott
fbshipit-source-id: f2dc12ea89a436b950cafec3593ed1b04af808e9
2019-01-25 15:40:26 -08:00
Davide Caroselli
ebaf8c5030
'--user-dir' documentation (correct) ( #447 )
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Summary:
Command line option --user-dir documented in docs/overview.rst
Pull Request resolved: https://github.com/pytorch/fairseq/pull/447
Differential Revision: D13674744
Pulled By: myleott
fbshipit-source-id: 17049ee5c9f692f5298ef9fa7381ee583f269cde
2019-01-15 11:54:17 -08:00
Myle Ott
14bd9c62a3
Update docs for --lazy-load and torch.distributed.launch
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Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/433
Differential Revision: D13588032
Pulled By: myleott
fbshipit-source-id: 0e5ff361e27b206c4490264f0f51863367499e81
2019-01-07 15:28:09 -08:00
Myle Ott
7633129ba8
Merge internal changes ( #283 )
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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
2019-01-04 20:03:19 -08:00
Sergey Edunov
1082ba352c
Switch to DistributedDataParallelC10d and bump version 0.5.0 -> 0.6.0
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- 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
2018-09-25 17:36:43 -04:00
Sergey Edunov
fe2d1581a4
Fix docs
2018-09-17 22:34:17 -07:00
Myle Ott
4a47b88992
Update documentation
2018-09-03 20:03:37 -04:00
Myle Ott
6381cc977f
Add documentation
2018-09-03 19:15:23 -04:00
