v0.8.0 -> v0.9.0 #1452
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v0.8.0 -> v0.9.0 #1452
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moussaKam
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Sep 29, 2020
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: facebookresearch#1452 Differential Revision: D18798409 Pulled By: myleott fbshipit-source-id: 860a0d5aaf7377c8c9bd63cdb3b33d464f0e1727
facebook-github-bot
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Nov 20, 2020
Summary: Pull Request resolved: fairinternal/fairseq-py#1452 Test Plan: Imported from OSS Reviewed By: lematt1991 Differential Revision: D25108462 Pulled By: myleott fbshipit-source-id: 3c17a9937a4c3edb69f64130dfd866c5f42a4aaf
yzpang
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Feb 19, 2021
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: facebookresearch/fairseq#1452 Differential Revision: D18798409 Pulled By: myleott fbshipit-source-id: 860a0d5aaf7377c8c9bd63cdb3b33d464f0e1727
yzpang
pushed a commit
to yzpang/gold-off-policy-text-gen-iclr21
that referenced
this pull request
Feb 19, 2021
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: facebookresearch/fairseq#1452 Differential Revision: D18798409 Pulled By: myleott fbshipit-source-id: 860a0d5aaf7377c8c9bd63cdb3b33d464f0e1727
sshleifer
pushed a commit
that referenced
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Apr 7, 2021
Summary: Pull Request resolved: fairinternal/fairseq-py#1452 Test Plan: Imported from OSS Reviewed By: lematt1991 Differential Revision: D25108462 Pulled By: myleott fbshipit-source-id: 3c17a9937a4c3edb69f64130dfd866c5f42a4aaf
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Possibly breaking changes:
in_proj_weightinto separate k, v, q projections in MultiheadAttention (fdf4c3e)New features:
--fast-stat-syncoption (e1ba32a)--empty-cache-freqoption (315c463)New papers:
Speed improvements: