mirror of
https://github.com/explosion/spaCy.git
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5bebbf7550
In order to support Python 3.13, we had to migrate to Cython 3.0. This caused some tricky interaction with our Pydantic usage, because Cython 3 uses the from __future__ import annotations semantics, which causes type annotations to be saved as strings. The end result is that we can't have Language.factory decorated functions in Cython modules anymore, as the Language.factory decorator expects to inspect the signature of the functions and build a Pydantic model. If the function is implemented in Cython, an error is raised because the type is not resolved. To address this I've moved the factory functions into a new module, spacy.pipeline.factories. I've added __getattr__ importlib hooks to the previous locations, in case anyone was importing these functions directly. The change should have no backwards compatibility implications. Along the way I've also refactored the registration of functions for the config. Previously these ran as import-time side-effects, using the registry decorator. I've created instead a new module spacy.registrations. When the registry is accessed it calls a function ensure_populated(), which cases the registrations to occur. I've made a similar change to the Language.factory registrations in the new spacy.pipeline.factories module. I want to remove these import-time side-effects so that we can speed up the loading time of the library, which can be especially painful on the CLI. I also find that I'm often working to track down the implementations of functions referenced by strings in the config. Having the registrations all happen in one place will make this easier. With these changes I've fortunately avoided the need to migrate to Pydantic v2 properly --- we're still using the v1 compatibility shim. We might not be able to hold out forever though: Pydantic (reasonably) aren't actively supporting the v1 shims. I put a lot of work into v2 migration when investigating the 3.13 support, and it's definitely challenging. In any case, it's a relief that we don't have to do the v2 migration at the same time as the Cython 3.0/Python 3.13 support.
557 lines
16 KiB
Cython
557 lines
16 KiB
Cython
# cython: embedsignature=True
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# cython: profile=False
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# Compiler crashes on memory view coercion without this. Should report bug.
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cimport numpy as np
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from libc.string cimport memset
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np.import_array()
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import warnings
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import numpy
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from thinc.api import get_array_module
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from .attrs cimport (
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IS_ALPHA,
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IS_ASCII,
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IS_BRACKET,
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IS_CURRENCY,
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IS_DIGIT,
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IS_LEFT_PUNCT,
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IS_LOWER,
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IS_PUNCT,
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IS_QUOTE,
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IS_RIGHT_PUNCT,
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IS_SPACE,
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IS_STOP,
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IS_TITLE,
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IS_UPPER,
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LIKE_EMAIL,
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LIKE_NUM,
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LIKE_URL,
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)
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from .typedefs cimport attr_t, flags_t
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from .attrs import intify_attrs
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from .errors import Errors, Warnings
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OOV_RANK = 0xffffffffffffffff # UINT64_MAX
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memset(&EMPTY_LEXEME, 0, sizeof(LexemeC))
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EMPTY_LEXEME.id = OOV_RANK
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cdef class Lexeme:
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"""An entry in the vocabulary. A `Lexeme` has no string context – it's a
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word-type, as opposed to a word token. It therefore has no part-of-speech
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tag, dependency parse, or lemma (lemmatization depends on the
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part-of-speech tag).
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DOCS: https://spacy.io/api/lexeme
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"""
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def __init__(self, Vocab vocab, attr_t orth):
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"""Create a Lexeme object.
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vocab (Vocab): The parent vocabulary
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orth (uint64): The orth id of the lexeme.
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Returns (Lexeme): The newly constructd object.
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"""
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self.vocab = vocab
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self.orth = orth
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self.c = <LexemeC*><void*>vocab.get_by_orth(vocab.mem, orth)
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if self.c.orth != orth:
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raise ValueError(Errors.E071.format(orth=orth, vocab_orth=self.c.orth))
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def __richcmp__(self, other, int op):
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if other is None:
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if op == 0 or op == 1 or op == 2:
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return False
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else:
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return True
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if isinstance(other, Lexeme):
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a = self.orth
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b = other.orth
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elif isinstance(other, int):
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a = self.orth
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b = other
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elif isinstance(other, str):
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a = self.orth_
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b = other
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else:
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a = 0
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b = 1
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if op == 2: # ==
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return a == b
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elif op == 3: # !=
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return a != b
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elif op == 0: # <
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return a < b
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elif op == 1: # <=
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return a <= b
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elif op == 4: # >
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return a > b
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elif op == 5: # >=
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return a >= b
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else:
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raise NotImplementedError(op)
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def __hash__(self):
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return self.c.orth
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def set_attrs(self, **attrs):
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cdef attr_id_t attr
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attrs = intify_attrs(attrs)
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for attr, value in attrs.items():
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# skip PROB, e.g. from lexemes.jsonl
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if isinstance(value, float):
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continue
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elif isinstance(value, int):
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Lexeme.set_struct_attr(self.c, attr, value)
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else:
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Lexeme.set_struct_attr(self.c, attr, self.vocab.strings.add(value))
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def set_flag(self, attr_id_t flag_id, bint value):
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"""Change the value of a boolean flag.
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flag_id (int): The attribute ID of the flag to set.
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value (bool): The new value of the flag.
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"""
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Lexeme.c_set_flag(self.c, flag_id, value)
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def check_flag(self, attr_id_t flag_id):
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"""Check the value of a boolean flag.
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flag_id (int): The attribute ID of the flag to query.
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RETURNS (bool): The value of the flag.
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"""
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return True if Lexeme.c_check_flag(self.c, flag_id) else False
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def similarity(self, other):
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"""Compute a semantic similarity estimate. Defaults to cosine over
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vectors.
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other (object): The object to compare with. By default, accepts `Doc`,
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`Span`, `Token` and `Lexeme` objects.
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RETURNS (float): A scalar similarity score. Higher is more similar.
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"""
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# Return 1.0 similarity for matches
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if hasattr(other, "orth"):
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if self.c.orth == other.orth:
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return 1.0
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elif (
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hasattr(other, "__len__") and len(other) == 1
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and hasattr(other[0], "orth")
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and self.c.orth == other[0].orth
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):
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return 1.0
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if self.vector_norm == 0 or other.vector_norm == 0:
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warnings.warn(Warnings.W008.format(obj="Lexeme"))
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return 0.0
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vector = self.vector
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xp = get_array_module(vector)
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result = xp.dot(vector, other.vector) / (self.vector_norm * other.vector_norm)
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# ensure we get a scalar back (numpy does this automatically but cupy doesn't)
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return result.item()
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@property
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def has_vector(self):
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"""RETURNS (bool): Whether a word vector is associated with the object.
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"""
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return self.vocab.has_vector(self.c.orth)
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@property
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def vector_norm(self):
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"""RETURNS (float): The L2 norm of the vector representation."""
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vector = self.vector
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return numpy.sqrt((vector**2).sum())
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@property
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def vector(self):
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"""A real-valued meaning representation.
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RETURNS (numpy.ndarray[ndim=1, dtype='float32']): A 1D numpy array
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representing the lexeme's semantics.
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"""
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cdef int length = self.vocab.vectors_length
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if length == 0:
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raise ValueError(Errors.E010)
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return self.vocab.get_vector(self.c.orth)
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@vector.setter
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def vector(self, vector):
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if len(vector) != self.vocab.vectors_length:
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raise ValueError(Errors.E073.format(new_length=len(vector),
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length=self.vocab.vectors_length))
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self.vocab.set_vector(self.c.orth, vector)
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@property
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def rank(self):
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"""RETURNS (str): Sequential ID of the lexeme's lexical type, used
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to index into tables, e.g. for word vectors."""
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return self.c.id
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@rank.setter
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def rank(self, value):
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self.c.id = value
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@property
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def sentiment(self):
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"""RETURNS (float): A scalar value indicating the positivity or
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negativity of the lexeme."""
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sentiment_table = self.vocab.lookups.get_table("lexeme_sentiment", {})
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return sentiment_table.get(self.c.orth, 0.0)
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@sentiment.setter
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def sentiment(self, float x):
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if "lexeme_sentiment" not in self.vocab.lookups:
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self.vocab.lookups.add_table("lexeme_sentiment")
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sentiment_table = self.vocab.lookups.get_table("lexeme_sentiment")
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sentiment_table[self.c.orth] = x
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@property
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def orth_(self):
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"""RETURNS (str): The original verbatim text of the lexeme
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(identical to `Lexeme.text`). Exists mostly for consistency with
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the other attributes."""
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return self.vocab.strings[self.c.orth]
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@property
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def text(self):
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"""RETURNS (str): The original verbatim text of the lexeme."""
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return self.orth_
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@property
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def lower(self):
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"""RETURNS (uint64): Lowercase form of the lexeme."""
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return self.c.lower
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@lower.setter
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def lower(self, attr_t x):
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self.c.lower = x
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@property
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def norm(self):
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"""RETURNS (uint64): The lexeme's norm, i.e. a normalised form of the
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lexeme text.
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"""
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return self.c.norm
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@norm.setter
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def norm(self, attr_t x):
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if "lexeme_norm" not in self.vocab.lookups:
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self.vocab.lookups.add_table("lexeme_norm")
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norm_table = self.vocab.lookups.get_table("lexeme_norm")
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norm_table[self.c.orth] = self.vocab.strings[x]
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self.c.norm = x
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@property
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def shape(self):
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"""RETURNS (uint64): Transform of the word's string, to show
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orthographic features.
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"""
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return self.c.shape
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@shape.setter
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def shape(self, attr_t x):
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self.c.shape = x
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@property
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def prefix(self):
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"""RETURNS (uint64): Length-N substring from the start of the word.
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Defaults to `N=1`.
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"""
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return self.c.prefix
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@prefix.setter
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def prefix(self, attr_t x):
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self.c.prefix = x
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@property
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def suffix(self):
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"""RETURNS (uint64): Length-N substring from the end of the word.
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Defaults to `N=3`.
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"""
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return self.c.suffix
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@suffix.setter
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def suffix(self, attr_t x):
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self.c.suffix = x
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@property
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def cluster(self):
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"""RETURNS (int): Brown cluster ID."""
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cluster_table = self.vocab.lookups.get_table("lexeme_cluster", {})
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return cluster_table.get(self.c.orth, 0)
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@cluster.setter
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def cluster(self, int x):
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cluster_table = self.vocab.lookups.get_table("lexeme_cluster", {})
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cluster_table[self.c.orth] = x
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@property
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def lang(self):
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"""RETURNS (uint64): Language of the parent vocabulary."""
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return self.c.lang
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@lang.setter
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def lang(self, attr_t x):
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self.c.lang = x
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@property
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def prob(self):
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"""RETURNS (float): Smoothed log probability estimate of the lexeme's
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type."""
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prob_table = self.vocab.lookups.get_table("lexeme_prob", {})
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settings_table = self.vocab.lookups.get_table("lexeme_settings", {})
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default_oov_prob = settings_table.get("oov_prob", -20.0)
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return prob_table.get(self.c.orth, default_oov_prob)
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@prob.setter
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def prob(self, float x):
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prob_table = self.vocab.lookups.get_table("lexeme_prob", {})
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prob_table[self.c.orth] = x
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@property
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def lower_(self):
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"""RETURNS (str): Lowercase form of the word."""
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return self.vocab.strings[self.c.lower]
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@lower_.setter
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def lower_(self, str x):
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self.c.lower = self.vocab.strings.add(x)
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@property
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def norm_(self):
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"""RETURNS (str): The lexeme's norm, i.e. a normalised form of the
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lexeme text.
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"""
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return self.vocab.strings[self.c.norm]
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@norm_.setter
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def norm_(self, str x):
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self.norm = self.vocab.strings.add(x)
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@property
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def shape_(self):
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"""RETURNS (str): Transform of the word's string, to show
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orthographic features.
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"""
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return self.vocab.strings[self.c.shape]
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@shape_.setter
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def shape_(self, str x):
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self.c.shape = self.vocab.strings.add(x)
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@property
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def prefix_(self):
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"""RETURNS (str): Length-N substring from the start of the word.
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Defaults to `N=1`.
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"""
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return self.vocab.strings[self.c.prefix]
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@prefix_.setter
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def prefix_(self, str x):
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self.c.prefix = self.vocab.strings.add(x)
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@property
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def suffix_(self):
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"""RETURNS (str): Length-N substring from the end of the word.
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Defaults to `N=3`.
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"""
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return self.vocab.strings[self.c.suffix]
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@suffix_.setter
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def suffix_(self, str x):
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self.c.suffix = self.vocab.strings.add(x)
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@property
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def lang_(self):
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"""RETURNS (str): Language of the parent vocabulary."""
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return self.vocab.strings[self.c.lang]
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@lang_.setter
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def lang_(self, str x):
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self.c.lang = self.vocab.strings.add(x)
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@property
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def flags(self):
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"""RETURNS (uint64): Container of the lexeme's binary flags."""
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return self.c.flags
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@flags.setter
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def flags(self, flags_t x):
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self.c.flags = x
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@property
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def is_oov(self):
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"""RETURNS (bool): Whether the lexeme is out-of-vocabulary."""
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return self.orth not in self.vocab.vectors
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@property
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def is_stop(self):
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"""RETURNS (bool): Whether the lexeme is a stop word."""
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return Lexeme.c_check_flag(self.c, IS_STOP)
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@is_stop.setter
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def is_stop(self, bint x):
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Lexeme.c_set_flag(self.c, IS_STOP, x)
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@property
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def is_alpha(self):
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"""RETURNS (bool): Whether the lexeme consists of alphabetic
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characters. Equivalent to `lexeme.text.isalpha()`.
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"""
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return Lexeme.c_check_flag(self.c, IS_ALPHA)
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@is_alpha.setter
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def is_alpha(self, bint x):
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Lexeme.c_set_flag(self.c, IS_ALPHA, x)
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@property
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def is_ascii(self):
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"""RETURNS (bool): Whether the lexeme consists of ASCII characters.
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Equivalent to `[any(ord(c) >= 128 for c in lexeme.text)]`.
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"""
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return Lexeme.c_check_flag(self.c, IS_ASCII)
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@is_ascii.setter
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def is_ascii(self, bint x):
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Lexeme.c_set_flag(self.c, IS_ASCII, x)
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@property
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def is_digit(self):
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"""RETURNS (bool): Whether the lexeme consists of digits. Equivalent
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to `lexeme.text.isdigit()`.
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"""
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return Lexeme.c_check_flag(self.c, IS_DIGIT)
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@is_digit.setter
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def is_digit(self, bint x):
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Lexeme.c_set_flag(self.c, IS_DIGIT, x)
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@property
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def is_lower(self):
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"""RETURNS (bool): Whether the lexeme is in lowercase. Equivalent to
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`lexeme.text.islower()`.
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"""
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return Lexeme.c_check_flag(self.c, IS_LOWER)
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@is_lower.setter
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def is_lower(self, bint x):
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Lexeme.c_set_flag(self.c, IS_LOWER, x)
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@property
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def is_upper(self):
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"""RETURNS (bool): Whether the lexeme is in uppercase. Equivalent to
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`lexeme.text.isupper()`.
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"""
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return Lexeme.c_check_flag(self.c, IS_UPPER)
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@is_upper.setter
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def is_upper(self, bint x):
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Lexeme.c_set_flag(self.c, IS_UPPER, x)
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@property
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def is_title(self):
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"""RETURNS (bool): Whether the lexeme is in titlecase. Equivalent to
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`lexeme.text.istitle()`.
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"""
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return Lexeme.c_check_flag(self.c, IS_TITLE)
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@is_title.setter
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def is_title(self, bint x):
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Lexeme.c_set_flag(self.c, IS_TITLE, x)
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@property
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def is_punct(self):
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"""RETURNS (bool): Whether the lexeme is punctuation."""
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return Lexeme.c_check_flag(self.c, IS_PUNCT)
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@is_punct.setter
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def is_punct(self, bint x):
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Lexeme.c_set_flag(self.c, IS_PUNCT, x)
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@property
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def is_space(self):
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"""RETURNS (bool): Whether the lexeme consist of whitespace characters.
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Equivalent to `lexeme.text.isspace()`.
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"""
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return Lexeme.c_check_flag(self.c, IS_SPACE)
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@is_space.setter
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def is_space(self, bint x):
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Lexeme.c_set_flag(self.c, IS_SPACE, x)
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@property
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def is_bracket(self):
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"""RETURNS (bool): Whether the lexeme is a bracket."""
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return Lexeme.c_check_flag(self.c, IS_BRACKET)
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@is_bracket.setter
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def is_bracket(self, bint x):
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Lexeme.c_set_flag(self.c, IS_BRACKET, x)
|
||
|
||
@property
|
||
def is_quote(self):
|
||
"""RETURNS (bool): Whether the lexeme is a quotation mark."""
|
||
return Lexeme.c_check_flag(self.c, IS_QUOTE)
|
||
|
||
@is_quote.setter
|
||
def is_quote(self, bint x):
|
||
Lexeme.c_set_flag(self.c, IS_QUOTE, x)
|
||
|
||
@property
|
||
def is_left_punct(self):
|
||
"""RETURNS (bool): Whether the lexeme is left punctuation, e.g. (."""
|
||
return Lexeme.c_check_flag(self.c, IS_LEFT_PUNCT)
|
||
|
||
@is_left_punct.setter
|
||
def is_left_punct(self, bint x):
|
||
Lexeme.c_set_flag(self.c, IS_LEFT_PUNCT, x)
|
||
|
||
@property
|
||
def is_right_punct(self):
|
||
"""RETURNS (bool): Whether the lexeme is right punctuation, e.g. )."""
|
||
return Lexeme.c_check_flag(self.c, IS_RIGHT_PUNCT)
|
||
|
||
@is_right_punct.setter
|
||
def is_right_punct(self, bint x):
|
||
Lexeme.c_set_flag(self.c, IS_RIGHT_PUNCT, x)
|
||
|
||
@property
|
||
def is_currency(self):
|
||
"""RETURNS (bool): Whether the lexeme is a currency symbol, e.g. $, €."""
|
||
return Lexeme.c_check_flag(self.c, IS_CURRENCY)
|
||
|
||
@is_currency.setter
|
||
def is_currency(self, bint x):
|
||
Lexeme.c_set_flag(self.c, IS_CURRENCY, x)
|
||
|
||
@property
|
||
def like_url(self):
|
||
"""RETURNS (bool): Whether the lexeme resembles a URL."""
|
||
return Lexeme.c_check_flag(self.c, LIKE_URL)
|
||
|
||
@like_url.setter
|
||
def like_url(self, bint x):
|
||
Lexeme.c_set_flag(self.c, LIKE_URL, x)
|
||
|
||
@property
|
||
def like_num(self):
|
||
"""RETURNS (bool): Whether the lexeme represents a number, e.g. "10.9",
|
||
"10", "ten", etc.
|
||
"""
|
||
return Lexeme.c_check_flag(self.c, LIKE_NUM)
|
||
|
||
@like_num.setter
|
||
def like_num(self, bint x):
|
||
Lexeme.c_set_flag(self.c, LIKE_NUM, x)
|
||
|
||
@property
|
||
def like_email(self):
|
||
"""RETURNS (bool): Whether the lexeme resembles an email address."""
|
||
return Lexeme.c_check_flag(self.c, LIKE_EMAIL)
|
||
|
||
@like_email.setter
|
||
def like_email(self, bint x):
|
||
Lexeme.c_set_flag(self.c, LIKE_EMAIL, x)
|