explosion/spaCy: v2.1.7: Improved evaluation, better language factories and bug fixes

✨ New features and improvements

• Add Token.tensor and Span.tensor attributes.
• Support simple training format of (text, annotations) instead of only (doc, gold) for nlp.evaluate.
• Add support for "lang_factory" setting in model meta.json (see #4031).
• Also support "requirements" in meta.json to define packages for setup's install_requires.
• Improve Pipe base class methods and make them less presumptuous.
• Improve Danish and Korean tokenization.
• Improve error messages when deserializing model fails.

• Fix issue #3669, #3962: Fix dependency copy in Span.as_doc that could cause segfault.
• Fix issue #3968: Fix bug in per-entity scores.
• Fix issue #4000: Improve entity linking API.
• Fix issue #4022: Fix error when Korean text contains special characters.
• Fix issue #4030: Handle edge case when calling TextCategorizer.predict with empty Doc.
• Fix issue #4045: Correct Span.sent docs.
• Fix issue #4048: Fix init-model command if there's no vocab.
• Fix issue #4052: Improve per-type scoring of NER.
• Fix issue #4054: Ensure the lang of nlp and nlp.vocab stay consistent.
• Fix bugs in Token.similarity and Span.similarity when called via hook.

• Add documentation for gold.align helper.
• Add more explicit section on processing text.
• Improve documentation on disabling pipeline components.
• Fix various typos and inconsistencies.

Thanks to @sorenlind, @pmbaumgartner, @svlandeg, @FallakAsad, @BreakBB, @adrianeboyd, @polm, @b1uec0in, @mdaudali and @ejarkm for the pull requests and contributions.