explosion/spaCy: v2.0.11: Alpha Vietnamese support, fixes to vectors, improved errors and more

Help us improve spaCy and take the User Survey 2018! ✨ New features and improvements NEW: Alpha Vietnamese support with tokenization via Pyvi. NEW: Improved system for error messages and warnings. Errors now have unique error codes and are referenced in one place, and all unspecified asserts have been replaced with descriptive errors. See #2163 for implementation details, and let us know if you have any suggestions for errors and warnings in #2164! Improve language data for Polish. Tidy up dependencies and drop six, html5lib, ftfy and requests. Improve efficiency (and potentially accuracy) of beam-search training, by randomly using greedy updates for some sentences. This can be controlled by changing the beam_update_prob entry in nlp.parser.cfg. The default value is 0.5, so 50% of beam updates will be done as greedy updates. Bug fixes Fix issue #1554, #1752, #2159: Fix Token.ent_iob after Doc.merge(), and ensure consistency in Doc.ents. Fix issue #1660: Fix loading of multiple vector models. Fix issue #1967: Allow entity types with dashes. Fix issue #2032: Fix accidentally quadratic runtime in Vocab.set_vector. Fix issue #2050: Correct mistakes in Italian lemmatizer data. Fix issue #2073: Make Token.set_extension work as expected. Fix issue #2100, #2151, #2181: Drop six and html5lib and prevent dependency conflict with TensorFlow / Keras. Fix issue #2101: Improve error message if token text is empty string. Fix issue #2121: Fix Language.to_bytes and pickling in Thinc. Fix issue #2156: Fix hashtag example in Matcher docs. Fix issue #2177: Don't raise error in set_extension if getter and setter are specified or if default=None, and add error if setter is specified with no getter. Documentation and examples Add example for TensorBoard's standalone embedding projector. Improve example for training a new entity type. Add formal CITATION for assigning a DOI via Zenodo. Contributors Thanks to @jimregan, @justindujardin, @trungtv, @katrinleinweber and @skrcode for the pull requests and contributions