GitLab

* Add more token classification examples

* POS tagging example

* Phrase chunking example

* PR review fixes

* Add conllu to third party list (used in token classification examples)

* Replace mecab-python3 with fugashi

This replaces mecab-python3 with fugashi for Japanese tokenization. I am
the maintainer of both projects.

Both projects are MeCab wrappers, so the underlying C++ code is the
same. fugashi is the newer wrapper and doesn't use SWIG, so for basic
use of the MeCab API it's easier to use.

This code insures the use of a version of ipadic installed via pip,
which should make versioning and tracking down issues easier.

fugashi has wheels for Windows, OSX, and Linux, which will help with
issues with installing old versions of mecab-python3 on Windows.
Compared to mecab-python3, because fugashi doesn't use SWIG, it doesn't
require a C++ runtime to be installed on Windows.

In adding this change I removed some code dealing with `cursor`,
`token_start`, and `token_end` variables. These variables didn't seem to
be used for anything, it is unclear to me why they were there.

I ran the tests and they passed, though I couldn't figure out how to run
the slow tests (`--runslow` gave an error) and didn't try testing with
Tensorflow.

* Style fix

* Remove unused variable

Forgot to delete this...

* Adapt doc with install instructions

* Fix typo
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Document TF modeling utils

* Document all model utils

improve unittests for finetuning, especially w.r.t testing frozen parameters
fix freeze_embeds for T5
add streamlit setup.cfg

* finish benchmark

* fix isort

* fix setup cfg

* retab

* fix time measuring of tf graph mode

* fix tf cuda

* clean code

* better error message

* Fix: unpin flake8 and fix cs errors

* Ok we still need to quote those

Co-Authored-By: Stefan Schweter <stefan@schweter.it>

* add known 3rd party to setup.cfg

* comment

* Update CONTRIBUTING.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* initial pytorch lightning commit

* tested multigpu

* Fix learning rate schedule

* black formatting

* fix flake8

* isort

* isort

* .
Co-authored-by: Check your git settings! <chris@chris-laptop>

Take advantage of this to simplify the Circle CI configuration.

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

These libraries aren't always installed in the virtual environment where
isort is running. Declaring them properly avoids mixing these
third-party imports with local imports.

I don't want to consider it a dependency of transformers, but it's
usually there in local development and usually not there in CI.

I'll fix it later.

lines_after_imports = 2 is a matter of taste; I like it.