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a5cd203284
* 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>
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| .. | ||
| cli | ||
| data | ||
| displacy | ||
| lang | ||
| matcher | ||
| ml | ||
| pipeline | ||
| syntax | ||
| tests | ||
| tokens | ||
| __init__.pxd | ||
| __init__.py | ||
| __main__.py | ||
| _ml.py | ||
| about.py | ||
| analysis.py | ||
| attrs.pxd | ||
| attrs.pyx | ||
| compat.py | ||
| errors.py | ||
| glossary.py | ||
| gold.pxd | ||
| gold.pyx | ||
| kb.pxd | ||
| kb.pyx | ||
| language.py | ||
| lemmatizer.py | ||
| lexeme.pxd | ||
| lexeme.pyx | ||
| lookups.py | ||
| morphology.pxd | ||
| morphology.pyx | ||
| parts_of_speech.pxd | ||
| parts_of_speech.pyx | ||
| scorer.py | ||
| strings.pxd | ||
| strings.pyx | ||
| structs.pxd | ||
| symbols.pxd | ||
| symbols.pyx | ||
| tokenizer.pxd | ||
| tokenizer.pyx | ||
| typedefs.pxd | ||
| typedefs.pyx | ||
| util.py | ||
| vectors.pyx | ||
| vocab.pxd | ||
| vocab.pyx | ||