Spacy-transformers

* Downgrade version pin of `importlib_metadata` to prevent conflict.
* Fix issue 92: Fix index error when calculating `doc.tensor`.

Thanks to ssavvi for the pull request!

> ⚠️ This release requires downloading new models. Also note the new model names that specify `trf` (transformers) instead of `pytt` (PyTorch transformers).

* Rename package from `spacy-pytorch-transformers` to `spacy-transformers`.
* Update to `spacy>=2.2.0`.
* Upgrade to latest `transformers`.
* Improve code and repo organization.

* Fix serialization.
* Update `pytorch-transformers` to support [DistilBERT](https://medium.com/huggingface/distilbert-8cf3380435b5).
* Add pre-packed [DistilBERT model](https://github.com/explosion/spacy-models/releases/tag/en_pytt_distilbertbaseuncased_lg-2.1.0).

* Add out-of-the-box support for [RoBERTa](https://github.com/pytorch/fairseq/tree/master/examples/roberta).
* Add pre-packaged [RoBERTa model](https://github.com/explosion/spacy-models/releases/tag/en_pytt_robertabase_lg-2.1.0).
* Update to `pytorch-transformers` v1.1.
* Fix serialization when model was saved from GPU.

* Add support for [GLUE benchmark tasks](examples/tasks).
* Support text-pair classification. The specifics of this are likely to change, but you can see [`run_glue.py`](examples/tasks/run_glue.py) for current usage.
* Improve reliability of tokenization and alignment.
* Add support for segment IDs to the `PyTT_Wrapper` class. These can now be passed in as a second column of the `RaggedArray` input. See the [`model_registry.get_word_pieces`](spacy_pytorch_transformers/model_registry.py) function for example usage.
* Set default maximum sequence length to 128.
* Fix bug that caused settings not to be passed into `PyTT_TextCategorizer` on model initialization.
* Fix serialization of XLNet model.

* Handle unaligned tokens in extension attributes.