mirror of
https://github.com/facebookresearch/fairseq.git
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1082ba352c
- 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 |
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| .. | ||
| _static | ||
| command_line_tools.rst | ||
| conf.py | ||
| criterions.rst | ||
| data.rst | ||
| docutils.conf | ||
| getting_started.rst | ||
| index.rst | ||
| lr_scheduler.rst | ||
| make.bat | ||
| Makefile | ||
| models.rst | ||
| modules.rst | ||
| optim.rst | ||
| overview.rst | ||
| requirements.txt | ||
| tasks.rst | ||
| tutorial_classifying_names.rst | ||
| tutorial_simple_lstm.rst | ||