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[XLNet] Fix mems behavior (#8567)

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* fix mems in xlnet

* fix use_mems

* fix use_mem_len

* fix use mems

* clean docs

* fix tf typo

* make xlnet tf for generation work

* fix tf test

* refactor use cache

* add use cache for missing models

* correct use_cache in generate

* correct use cache in tf generate

* fix tf

* correct getattr typo

* make sylvain happy

* change in docs as well

* do not apply to cookie cutter statements

* fix tf test

* make pytorch model fully backward compatible
This commit is contained in:
Patrick von Platen
2020-11-25 22:54:59 +01:00
committed by GitHub
parent 369f1d77b4
commit 2a6fbe6a40
47 changed files with 259 additions and 134 deletions
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docs/source/model_doc/bertgeneration.rst
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@@ -10,7 +10,7 @@ Tasks <https://arxiv.org/abs/1907.12461>`__ by Sascha Rothe, Shashi Narayan, Ali
The abstract from the paper is the following:
*Unsupervised pre-training of large neural models has recently revolutionized Natural Language Processing. By
*Unsupervised pretraining of large neural models has recently revolutionized Natural Language Processing. By
warm-starting from the publicly released checkpoints, NLP practitioners have pushed the state-of-the-art on multiple
benchmarks while saving significant amounts of compute time. So far the focus has been mainly on the Natural Language
Understanding tasks. In this paper, we demonstrate the efficacy of pre-trained checkpoints for Sequence Generation. We