* 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
* Reduce stored lexemes data, move feats to lookups
* Move non-derivable lexemes features (`norm / cluster / prob`) to
`spacy-lookups-data` as lookups
* Get/set `norm` in both lookups and `LexemeC`, serialize in lookups
* Remove `cluster` and `prob` from `LexemesC`, get/set/serialize in
lookups only
* Remove serialization of lexemes data as `vocab/lexemes.bin`
* Remove `SerializedLexemeC`
* Remove `Lexeme.to_bytes/from_bytes`
* Modify normalization exception loading:
* Always create `Vocab.lookups` table `lexeme_norm` for
normalization exceptions
* Load base exceptions from `lang.norm_exceptions`, but load
language-specific exceptions from lookups
* Set `lex_attr_getter[NORM]` including new lookups table in
`BaseDefaults.create_vocab()` and when deserializing `Vocab`
* Remove all cached lexemes when deserializing vocab to override
existing normalizations with the new normalizations (as a replacement
for the previous step that replaced all lexemes data with the
deserialized data)
* Skip English normalization test
Skip English normalization test because the data is now in
`spacy-lookups-data`.
* Remove norm exceptions
Moved to spacy-lookups-data.
* Move norm exceptions test to spacy-lookups-data
* Load extra lookups from spacy-lookups-data lazily
Load extra lookups (currently for cluster and prob) lazily from the
entry point `lg_extra` as `Vocab.lookups_extra`.
* Skip creating lexeme cache on load
To improve model loading times, do not create the full lexeme cache when
loading. The lexemes will be created on demand when processing.
* Identify numeric values in Lexeme.set_attrs()
With the removal of a special case for `PROB`, also identify `float` to
avoid trying to convert it with the `StringStore`.
* Skip lexeme cache init in from_bytes
* Unskip and update lookups tests for python3.6+
* Update vocab pickle to include lookups_extra
* Update vocab serialization tests
Check strings rather than lexemes since lexemes aren't initialized
automatically, account for addition of "_SP".
* Re-skip lookups test because of python3.5
* Skip PROB/float values in Lexeme.set_attrs
* Convert is_oov from lexeme flag to lex in vectors
Instead of storing `is_oov` as a lexeme flag, `is_oov` reports whether
the lexeme has a vector.
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* Limiting noun_chunks for specific langauges
* Limiting noun_chunks for specific languages
Contributor Agreement
* Addressing review comments
* Removed unused fixtures and imports
* Add fa_tokenizer in test suite
* Use fa_tokenizer in test
* Undo extraneous reformatting
Co-authored-by: adrianeboyd <adrianeboyd@gmail.com>
Reconstruction of the original PR #4697 by @MiniLau.
Removes unused `SENT_END` symbol and `IS_SENT_END` from `Matcher` schema
because the Matcher is only going to be able to support `IS_SENT_START`.
* Add pos and morph scoring to Scorer
Add pos, morph, and morph_per_type to `Scorer`. Report pos and morph
accuracy in `spacy evaluate`.
* Update morphologizer for v3
* switch to tagger-based morphologizer
* use `spacy.HashCharEmbedCNN` for morphologizer defaults
* add `Doc.is_morphed` flag
* Add morphologizer to train CLI
* Add basic morphologizer pipeline tests
* Add simple morphologizer training example
* Remove subword_features from CharEmbed models
Remove `subword_features` argument from `spacy.HashCharEmbedCNN.v1` and
`spacy.HashCharEmbedBiLSTM.v1` since in these cases `subword_features`
is always `False`.
* Rename setting in morphologizer example
Use `with_pos_tags` instead of `without_pos_tags`.
* Fix kwargs for spacy.HashCharEmbedBiLSTM.v1
* Remove defaults for spacy.HashCharEmbedBiLSTM.v1
Remove default `nM/nC` for `spacy.HashCharEmbedBiLSTM.v1`.
* Set random seed for textcat overfitting test
* merge_entities sets the vector in the vocab for the merged token
* add unit test
* import unicode_literals
* move code to _merge function
* only set vector if vocab has non-zero vectors
* Improve token head verification
Improve the verification for valid token heads when heads are set:
* in `Token.head`: heads come from the same document
* in `Doc.from_array()`: head indices are within the bounds of the
document
* Improve error message
* Sync Span __eq__ and __hash__
Use the same tuple for `__eq__` and `__hash__`, including all attributes
except `vector` and `vector_norm`.
* Update entity comparison in tests
Update `assert_docs_equal()` test util to compare `Span` properties for
ents rather than `Span` objects.
Modify flag settings so that `DEP` is not sufficient to set `is_parsed`
and only run `set_children_from_heads()` if `HEAD` is provided.
Then the combination `[SENT_START, DEP]` will set deps and not clobber
sent starts with a lot of one-word sentences.
