5 Commits

Author	SHA1	Message	Date
Jerry Ma	3f4fc50163	Miscellaneous documentation improvements: (#868) ... Summary: - More clearly document the correspondence between FairseqAdam and torch.optim.AdamW - Add ResamplingDataset to Sphinx docs Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/868 Differential Revision: D17523244 Pulled By: jma127 fbshipit-source-id: 8e7b34b24889b2c8f70b09a52a625d2af135734b	2019-09-23 12:27:12 -07:00
Myle Ott	fbd4cef9a5	Add fairseq to PyPI (#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: 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	7633129ba8	Merge internal changes (#283) ... 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 ... - 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
Myle Ott	6381cc977f	Add documentation	2018-09-03 19:15:23 -04:00