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Tensorflow 2.1.0 introduce a new dependency model where pip install tensorflow would install tf with GPU support.
Before it would just install with CPU support, thus CircleCI is looking for NVidia driver version at initialization of the
tensorflow related tests but fails as their is no NVidia Driver running.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

- It appears that `tqdm` only introduced `tqdm.auto` in 4.27.
- See https://github.com/tqdm/tqdm/releases/tag/v4.27.0.
- Without the lower bound I received the following stack trace in an environment where I already had tqdm installed:
```
  File "/home/brendanr/anaconda3/envs/allennlp/lib/python3.6/site-packages/transformers/__init__.py", line 20, in <module>
    from .file_utils import (TRANSFORMERS_CACHE, PYTORCH_TRANSFORMERS_CACHE, PYTORCH_PRETRAINED_BERT_CACHE,
  File "/home/brendanr/anaconda3/envs/allennlp/lib/python3.6/site-packages/transformers/file_utils.py", line 24, in <module>
    from tqdm.auto import tqdm
ModuleNotFoundError: No module named 'tqdm.auto'
```

If a user or contributor ran `pip install -e .` on transformers < 3.0,
pip created a transformers.egg-info directory next to the transformers
directory at the root of the repository.

In transformers 3.0, the source is in a `src` subdirectory.
`pip install -e .` creates a transformers.egg-info directory there.
However, pip will still pick transformers.egg-info from the previous
location. This is a bug: https://github.com/pypa/pip/issues/5466

Users and contributors are likely to hit this problem because the
documentation for transformers 3.0 relies heavily on extra_requires
which didn't exist in earlier versions, so aren't defined in a stale
transformers.egg-info directory.

If such a directory exists, remove it. It's autogenerated, gitignored
and not supposed to contain anything of value.

It's redundant with setup.py and, also, incomplete (e.g. numpy).

Take advantage of this to simplify the Circle CI configuration.

Don't bother with tensorboardX: it's a fallback for PyTorch < 1.1.0.

On Python 3, `open is io.open`.

This prevents transformers from being importable simply because the CWD
is the root of the git repository, while not being importable from other
directories. That led to inconsistent behavior, especially in examples.

Once you fetch this commit, in your dev environment, you must run:

    $ pip uninstall transformers
    $ pip install -e .

This is the result of:

    $ isort --recursive examples templates transformers utils hubconf.py setup.py

This is the result of:

    $ black --line-length 119 examples templates transformers utils hubconf.py setup.py

There's a lot of fairly long lines in the project. As a consequence, I'm
picking the longest widely accepted line length, 119 characters.

This is also Thomas' preference, because it allows for explicit variable
names, to make the code easier to understand.

Since the file is written to the filesystem, a filesystem lock is the
way to go here. Add a dependency on the third-party filelock library to
get cross-platform functionality.

* Switch to plain unittest for skipping slow tests.

Add a RUN_SLOW environment variable for running them.

* Switch to plain unittest for PyTorch dependency.

* Switch to plain unittest for TensorFlow dependency.

* Avoid leaking open files in the test suite.

This prevents spurious warnings when running tests.

* Fix unicode warning on Python 2 when running tests.

The warning was:

    UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal

* Support running PyTorch tests on a GPU.

Reverts 27e015bd.

* Tests no longer require pytest.

* Make tests pass on cuda