GitLab

* nlp -> datasets

* More nlp -> datasets

* Woopsie

* More nlp -> datasets

* One last

* Cache Github Actions CI

* Remove useless file

* Pin to 1.5.0

* Patch XLM GPU test

* Upgrade pip when doing CI

* Don't forget Github CI

* Distributed eval: SequentialDistributedSampler + gather all results

* For consistency only write to disk from world_master

Close https://github.com/huggingface/transformers/issues/4272

* Working distributed eval

* Hook into scripts

* Fix #3721 again

* TPU.mesh_reduce: stay in tensor space

Thanks @jysohn23

* Just a small comment

* whitespace

* torch.hub: pip install packaging

* Add test scenarii

while looking for fix to https://twitter.com/julien_c/status/1237864185821708291

* debug env

* Restrict TF GPU memory

* Fixup

* One more test

* rm debug logs

* Fixup

see https://www.tensorflow.org/guide/gpu#limiting_gpu_memory_growth

Co-Authored-By: Funtowicz Morgan <mfuntowicz@users.noreply.github.com>
Co-Authored-By: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

* Create self-hosted.yml

* Update self-hosted.yml

* Update self-hosted.yml

* Update self-hosted.yml

* Update self-hosted.yml

* Update self-hosted.yml

* do not run slow tests, for now

* [ci] For comparison with circleci, let's also run CPU-tests

* [ci] reorganize

* clearer filenames

* [ci] Final tweaks before merging

* rm slow tests on circle ci

* Trigger CI

* On GPU this concurrency was way too high