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Myle Ottfacebook-github-bot
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v0.8.0 -> v0.9.0 (#1452)
Summary: Possibly breaking changes: - Set global numpy seed (4a7cd58) - Split `in_proj_weight` into separate k, v, q projections in MultiheadAttention (fdf4c3e) - TransformerEncoder returns namedtuples instead of dict (27568a7) New features: - Add `--fast-stat-sync` option (e1ba32a) - Add `--empty-cache-freq` option (315c463) - Support criterions with parameters (ba5f829) New papers: - Simple and Effective Noisy Channel Modeling for Neural Machine Translation (49177c9) - Levenshtein Transformer (86857a5, ...) - Cross+Self-Attention for Transformer Models (4ac2c5f) - Jointly Learning to Align and Translate with Transformer Models (1c66792) - Reducing Transformer Depth on Demand with Structured Dropout (dabbef4) - Unsupervised Cross-lingual Representation Learning at Scale (XLM-RoBERTa) (e23e5ea) - BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension (a92bcda) - CamemBERT: a French BERT (b31849a) Speed improvements: - Add CUDA kernels for LightConv and DynamicConv (f840564) - Cythonization of various dataloading components (4fc3953, ...) - Don't project mask tokens for MLM training (718677e) Pull Request resolved: #1452 Differential Revision: D18798409 Pulled By: myleott fbshipit-source-id: 860a0d5aaf7377c8c9bd63cdb3b33d464f0e1727
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docs/conf.py

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# built documents.
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#
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# The short X.Y version.
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version = '0.8.0'
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version = '0.9.0'
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# The full version, including alpha/beta/rc tags.
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release = '0.8.0'
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release = '0.9.0'
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# The language for content autogenerated by Sphinx. Refer to documentation
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# for a list of supported languages.

examples/__init__.py

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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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__version__ = '0.8.0'
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__version__ = '0.9.0'
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import examples.noisychannel # noqa

fairseq/__init__.py

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# LICENSE file in the root directory of this source tree.
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__all__ = ['pdb']
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__version__ = '0.8.0'
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__version__ = '0.9.0'
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import fairseq.criterions # noqa
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import fairseq.models # noqa

setup.py

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setup(
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name='fairseq',
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version='0.8.0',
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version='0.9.0',
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description='Facebook AI Research Sequence-to-Sequence Toolkit',
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url='https://github.com/pytorch/fairseq',
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classifiers=[

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