* verbose and tag_map options
* adding init_tok2vec option and only changing the tok2vec that is specified
* adding omit_extra_lookups and verifying textcat config
* wip
* pretrain bugfix
* add replace and resume options
* train_textcat fix
* raw text functionality
* improve UX when KeyError or when input data can't be parsed
* avoid unnecessary access to goldparse in TextCat pipe
* save performance information in nlp.meta
* add noise_level to config
* move nn_parser's defaults to config file
* multitask in config - doesn't work yet
* scorer offering both F and AUC options, need to be specified in config
* add textcat verification code from old train script
* small fixes to config files
* clean up
* set default config for ner/parser to allow create_pipe to work as before
* two more test fixes
* small fixes
* cleanup
* fix NER pickling + additional unit test
* create_pipe as before
* Make Example require a Doc object (previously optional)
Clarify methods in GoldCorpus
WIP refactor Example
Refactor Example.split_sents
Fix test
Fix augment
Update test
Update test
Fix import
Update test_scorer
Update Example
* Move get_parses_from_example to spacy.syntax
* Get GoldParse out of Example
* Avoid expecting GoldParse input in parser
* Add Alignment to spacy.gold.align
* Update Example object
* Add comment
* Update pipeline
* Fix imports
* Simplify gold_io
* WIP on GoldCorpus
* Update test
* Xfail some gold tests
* Remove ignore_misaligned option from GoldCorpus
* Fix Example constructor
* Update test
* Fix usage of Example
* Add deprecated_get_gold method on Example
* Patch scorer
* Fix test
* Fix test
* Update tests
* Xfail a test
* Fix passing of make_projective
* Pass make_projective by default
* Hack data format in Example.from_dict
* Update tests
* Fix example.from_dict
* Update morphologizer
* Fix entity linker
* Add get_field to TokenAnnotation
* Fix Example.get_aligned
* Update test
* Fix alignment
* Fix corpus
* Fix GoldCorpus
* Handle misaligned
* Format
* Fix missing import
Updates from #5362 and fix from #5387:
* `train`:
* if training on GPU, only run evaluation/timing on CPU in the first
iteration
* if training is aborted, exit with a non-0 exit status
