mirror of
https://github.com/facebookresearch/fairseq.git
synced 2024-09-11 17:25:31 +03:00
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
47 lines
1.1 KiB
Python
47 lines
1.1 KiB
Python
#!/usr/bin/env python3
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# Copyright (c) 2017-present, Facebook, Inc.
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# All rights reserved.
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#
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# This source code is licensed under the license found in the LICENSE file in
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# the root directory of this source tree. An additional grant of patent rights
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# can be found in the PATENTS file in the same directory.
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from setuptools import setup, find_packages, Extension
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import sys
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if sys.version_info < (3,):
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sys.exit('Sorry, Python3 is required for fairseq.')
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with open('README.md') as f:
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readme = f.read()
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with open('LICENSE') as f:
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license = f.read()
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with open('requirements.txt') as f:
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reqs = f.read()
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bleu = Extension(
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'fairseq.libbleu',
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sources=[
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'fairseq/clib/libbleu/libbleu.cpp',
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'fairseq/clib/libbleu/module.cpp',
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],
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extra_compile_args=['-std=c++11'],
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)
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setup(
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name='fairseq',
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version='0.6.0',
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description='Facebook AI Research Sequence-to-Sequence Toolkit',
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long_description=readme,
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license=license,
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install_requires=reqs.strip().split('\n'),
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packages=find_packages(),
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ext_modules=[bleu],
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test_suite='tests',
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)
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