GitLab

* Start cleaning examples

* Fixup

For more details, see https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate

* Update examples/ner/run_ner.py to use AutoModel

* Fix missing code and apply `make style` command

* fix n_gpu count when no_cuda flag is activated

* someone was left behind

* Added support for Albert in NER pipeline

* Added command-line options to examples/ner/run_ner.py to better control tokenization

* Added class AlbertForTokenClassification

* Changed output for NerPipeline to use .convert_ids_to_tokens(...) instead of .decode(...) to better reflect tokens

* 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>

Every other file uses this pattern.

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.

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.

gradient norm clipping should be done right before calling the optimiser - fixing run_glue and run_ner as well