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* 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

cc @bramvanroy @stefan-it

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

* add "info" command to CLI

As a convenience, add the info directive to CLI. Running `python transformers-cli info` will return a string containing the transformers version, platform, python version, PT/TF version and GPU support

* Swap f-strings for .format

Still supporting 3.5 so can't use f-strings (sad face)

* Add reference in issue to CLI

* Add the expected fields to issue template

This way, people can still add the information manually if they want. (Though I fear they'll just ignore it.)

* Remove heading from output

* black-ify

* order of imports

Should ensure isort test passes

* use is_X_available over import..pass

* style

* fix copy-paste bug

* Rename command info -> env

Also adds the command to CONTRIBUTING.md in "Did you find a bug" section

- mostly stylistic streamlining
- removed 'additional context' sections. They seem to be rarely used and might cause confusion. If more details are needed, users can add them to the 'details' section

Motivate users to @-tag authors of models to increase visibility and expand the community

- change references to pytorch-transformers to transformers
- link to code formatting guidelines

- add 'your contribution' section
- add code formatting link to 'additional context'

Prefer that general questions are asked on Stack Overflow

Streamlines usages of pytorch-transformers and pytorch-pretrained-bert. Add link to the README for the migration guide.