Fix the adjusted token index / lca matrix index ranges for
`_get_lca_matrix` for spans.
* The range for `k` should correspond to the adjusted indices in
`lca_matrix` with the `start` indexed at `0`
* Only set NORM on Token in retokenizer
Instead of setting `NORM` on both the token and lexeme, set `NORM` only
on the token.
The retokenizer tries to set all possible attributes with
`Token/Lexeme.set_struct_attr` so that it doesn't have to enumerate
which attributes are available for each. `NORM` is the only attribute
that's stored on both and for most cases it doesn't make sense to set
the global norms based on a individual retokenization. For lexeme-only
attributes like `IS_STOP` there's no way to avoid the global side
effects, but I think that `NORM` would be better only on the token.
* Fix test
* Allow Doc.char_span to snap to token boundaries
Add a `mode` option to allow `Doc.char_span` to snap to token
boundaries. The `mode` options:
* `strict`: character offsets must match token boundaries (default, same as
before)
* `inside`: all tokens completely within the character span
* `outside`: all tokens at least partially covered by the character span
Add a new helper function `token_by_char` that returns the token
corresponding to a character position in the text. Update
`token_by_start` and `token_by_end` to use `token_by_char` for more
efficient searching.
* Remove unused import
* Rename mode to alignment_mode
Rename `mode` to `alignment_mode` with the options
`strict`/`contract`/`expand`. Any unrecognized modes are silently
converted to `strict`.
* 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`.
* 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.
* expand serialization test for custom token attribute
* add failing test for issue 4849
* define ENT_ID as attr and use in doc serialization
* fix few typos
* Include Doc.cats in to_bytes()
* Include Doc.cats in DocBin serialization
* Add tests for serialization of cats
Test serialization of cats for Doc and DocBin.
Iterate over lr_edges until all heads are within the current sentence.
Instead of iterating over them for a fixed number of iterations, check
whether the sentence boundaries are correct for the heads and stop when
all are correct. Stop after a maximum of 10 iterations, providing a
warning in this case since the sentence boundaries may not be correct.
* raise specific error when removing a matcher rule that doesn't exist
* rephrasing
* goldparse init: allocate fields only if doc is not empty
* avoid zero length alloc in saving tokenizer cache
* avoid allocating zero length mem in matcher
* asserts to avoid allocating zero length mem
* fix zero-length allocation in matcher
* bump cymem version
* revert cymem version bump
* remove duplicate unit test
* unit test (currently failing) for issue 4267
* bugfix: ensure doc.ents preserves kb_id annotations
* fix in setting doc.ents with empty label
* rename
* test for presetting an entity to a certain type
* allow overwriting Outside + blocking presets
* fix actions when previous label needs to be kept
* fix default ent_iob in set entities
* cleaner solution with U- action
* remove debugging print statements
* unit tests with explicit transitions and is_valid testing
* remove U- from move_names explicitly
* remove unit tests with pre-trained models that don't work
* remove (working) unit tests with pre-trained models
* clean up unit tests
* move unit tests
* small fixes
* remove two TODO's from doc.ents comments
* make merge more efficient
* fix offsets
* merge works with relative indices
* remove printing
* Add the SCA
* fix SCA date
* more cythonize _retokenize.pyx
* more cythonize _retokenize.pyx
* fix only declaration in _retokenize.pyx
* switch back to absolute head
* switch back to absolute head
* fix comment
* merge from origin repo
