mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-14 13:47:13 +03:00
53c0fb7431
* 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
430 lines
18 KiB
Cython
430 lines
18 KiB
Cython
# coding: utf8
|
|
# cython: infer_types=True
|
|
# cython: bounds_check=False
|
|
# cython: profile=True
|
|
from __future__ import unicode_literals
|
|
|
|
from libc.string cimport memcpy, memset
|
|
from libc.stdlib cimport malloc, free
|
|
from cymem.cymem cimport Pool
|
|
from thinc.neural.util import get_array_module
|
|
|
|
import numpy
|
|
|
|
from .doc cimport Doc, set_children_from_heads, token_by_start, token_by_end
|
|
from .span cimport Span
|
|
from .token cimport Token
|
|
from ..lexeme cimport Lexeme, EMPTY_LEXEME
|
|
from ..structs cimport LexemeC, TokenC
|
|
from ..attrs cimport TAG, NORM
|
|
|
|
from .underscore import is_writable_attr
|
|
from ..attrs import intify_attrs
|
|
from ..util import SimpleFrozenDict
|
|
from ..errors import Errors
|
|
from ..strings import get_string_id
|
|
|
|
|
|
cdef class Retokenizer:
|
|
"""Helper class for doc.retokenize() context manager.
|
|
|
|
DOCS: https://spacy.io/api/doc#retokenize
|
|
USAGE: https://spacy.io/usage/linguistic-features#retokenization
|
|
"""
|
|
cdef Doc doc
|
|
cdef list merges
|
|
cdef list splits
|
|
cdef set tokens_to_merge
|
|
cdef list _spans_to_merge
|
|
|
|
def __init__(self, doc):
|
|
self.doc = doc
|
|
self.merges = []
|
|
self.splits = []
|
|
self.tokens_to_merge = set()
|
|
self._spans_to_merge = [] # keep a record to filter out duplicates
|
|
|
|
def merge(self, Span span, attrs=SimpleFrozenDict()):
|
|
"""Mark a span for merging. The attrs will be applied to the resulting
|
|
token.
|
|
|
|
span (Span): The span to merge.
|
|
attrs (dict): Attributes to set on the merged token.
|
|
|
|
DOCS: https://spacy.io/api/doc#retokenizer.merge
|
|
"""
|
|
if (span.start, span.end) in self._spans_to_merge:
|
|
return
|
|
if span.end - span.start <= 0:
|
|
raise ValueError(Errors.E199.format(start=span.start, end=span.end))
|
|
for token in span:
|
|
if token.i in self.tokens_to_merge:
|
|
raise ValueError(Errors.E102.format(token=repr(token)))
|
|
self.tokens_to_merge.add(token.i)
|
|
self._spans_to_merge.append((span.start, span.end))
|
|
if "_" in attrs: # Extension attributes
|
|
extensions = attrs["_"]
|
|
_validate_extensions(extensions)
|
|
attrs = {key: value for key, value in attrs.items() if key != "_"}
|
|
attrs = intify_attrs(attrs, strings_map=self.doc.vocab.strings)
|
|
attrs["_"] = extensions
|
|
else:
|
|
attrs = intify_attrs(attrs, strings_map=self.doc.vocab.strings)
|
|
self.merges.append((span, attrs))
|
|
|
|
def split(self, Token token, orths, heads, attrs=SimpleFrozenDict()):
|
|
"""Mark a Token for splitting, into the specified orths. The attrs
|
|
will be applied to each subtoken.
|
|
|
|
token (Token): The token to split.
|
|
orths (list): The verbatim text of the split tokens. Needs to match the
|
|
text of the original token.
|
|
heads (list): List of token or `(token, subtoken)` tuples specifying the
|
|
tokens to attach the newly split subtokens to.
|
|
attrs (dict): Attributes to set on all split tokens. Attribute names
|
|
mapped to list of per-token attribute values.
|
|
|
|
DOCS: https://spacy.io/api/doc#retokenizer.split
|
|
"""
|
|
if ''.join(orths) != token.text:
|
|
raise ValueError(Errors.E117.format(new=''.join(orths), old=token.text))
|
|
if "_" in attrs: # Extension attributes
|
|
extensions = attrs["_"]
|
|
for extension in extensions:
|
|
_validate_extensions(extension)
|
|
attrs = {key: value for key, value in attrs.items() if key != "_"}
|
|
# NB: Since we support {"KEY": [value, value]} syntax here, this
|
|
# will only "intify" the keys, not the values
|
|
attrs = intify_attrs(attrs, strings_map=self.doc.vocab.strings)
|
|
attrs["_"] = extensions
|
|
else:
|
|
# NB: Since we support {"KEY": [value, value]} syntax here, this
|
|
# will only "intify" the keys, not the values
|
|
attrs = intify_attrs(attrs, strings_map=self.doc.vocab.strings)
|
|
head_offsets = []
|
|
for head in heads:
|
|
if isinstance(head, Token):
|
|
head_offsets.append((head.idx, 0))
|
|
else:
|
|
head_offsets.append((head[0].idx, head[1]))
|
|
self.splits.append((token.idx, orths, head_offsets, attrs))
|
|
|
|
def __enter__(self):
|
|
self.merges = []
|
|
self.splits = []
|
|
return self
|
|
|
|
def __exit__(self, *args):
|
|
# Do the actual merging here
|
|
if len(self.merges) >= 1:
|
|
_merge(self.doc, self.merges)
|
|
# Iterate in order, to keep things simple.
|
|
for start_char, orths, heads, attrs in sorted(self.splits):
|
|
# Resolve token index
|
|
token_index = token_by_start(self.doc.c, self.doc.length, start_char)
|
|
# Check we're still able to find tokens starting at the character offsets
|
|
# referred to in the splits. If we merged these tokens previously, we
|
|
# have to raise an error
|
|
if token_index == -1:
|
|
raise IndexError(Errors.E122)
|
|
head_indices = []
|
|
for head_char, subtoken in heads:
|
|
head_index = token_by_start(self.doc.c, self.doc.length, head_char)
|
|
if head_index == -1:
|
|
raise IndexError(Errors.E123)
|
|
# We want to refer to the token index of the head *after* the
|
|
# mergery. We need to account for the extra tokens introduced.
|
|
# e.g., let's say we have [ab, c] and we want a and b to depend
|
|
# on c. The correct index for c will be 2, not 1.
|
|
if head_index > token_index:
|
|
head_index += len(orths)-1
|
|
head_indices.append(head_index+subtoken)
|
|
_split(self.doc, token_index, orths, head_indices, attrs)
|
|
|
|
|
|
def _merge(Doc doc, merges):
|
|
"""Retokenize the document, such that the spans described in 'merges'
|
|
are merged into a single token. This method assumes that the merges
|
|
are in the same order at which they appear in the doc, and that merges
|
|
do not intersect each other in any way.
|
|
|
|
merges: Tokens to merge, and corresponding attributes to assign to the
|
|
merged token. By default, attributes are inherited from the
|
|
syntactic root of the span.
|
|
RETURNS (Token): The first newly merged token.
|
|
"""
|
|
cdef int i, merge_index, start, end, token_index, current_span_index, current_offset, offset, span_index
|
|
cdef Span span
|
|
cdef const LexemeC* lex
|
|
cdef TokenC* token
|
|
cdef Pool mem = Pool()
|
|
cdef int merged_iob = 0
|
|
|
|
# merges should not be empty, but make sure to avoid zero-length mem alloc
|
|
assert len(merges) > 0
|
|
tokens = <TokenC**>mem.alloc(len(merges), sizeof(TokenC))
|
|
spans = []
|
|
|
|
def _get_start(merge):
|
|
return merge[0].start
|
|
|
|
merges.sort(key=_get_start)
|
|
for merge_index, (span, attributes) in enumerate(merges):
|
|
start = span.start
|
|
end = span.end
|
|
spans.append(span)
|
|
# House the new merged token where it starts
|
|
token = &doc.c[start]
|
|
start_ent_iob = doc.c[start].ent_iob
|
|
start_ent_type = doc.c[start].ent_type
|
|
# Initially set attributes to attributes of span root
|
|
token.tag = doc.c[span.root.i].tag
|
|
token.pos = doc.c[span.root.i].pos
|
|
token.morph = doc.c[span.root.i].morph
|
|
token.ent_iob = doc.c[span.root.i].ent_iob
|
|
token.ent_type = doc.c[span.root.i].ent_type
|
|
merged_iob = token.ent_iob
|
|
# If span root is part of an entity, merged token is B-ENT
|
|
if token.ent_iob in (1, 3):
|
|
merged_iob = 3
|
|
# If start token is I-ENT and previous token is of the same
|
|
# type, then I-ENT (could check I-ENT from start to span root)
|
|
if start_ent_iob == 1 and start > 0 \
|
|
and start_ent_type == token.ent_type \
|
|
and doc.c[start - 1].ent_type == token.ent_type:
|
|
merged_iob = 1
|
|
token.ent_iob = merged_iob
|
|
# Unset attributes that don't match new token
|
|
token.lemma = 0
|
|
token.norm = 0
|
|
tokens[merge_index] = token
|
|
# Resize the doc.tensor, if it's set. Let the last row for each token stand
|
|
# for the merged region. To do this, we create a boolean array indicating
|
|
# whether the row is to be deleted, then use numpy.delete
|
|
if doc.tensor is not None and doc.tensor.size != 0:
|
|
doc.tensor = _resize_tensor(doc.tensor,
|
|
[(m[0].start, m[0].end) for m in merges])
|
|
# Memorize span roots and sets dependencies of the newly merged
|
|
# tokens to the dependencies of their roots.
|
|
span_roots = []
|
|
for i, span in enumerate(spans):
|
|
span_roots.append(span.root.i)
|
|
tokens[i].dep = span.root.dep
|
|
# We update token.lex after keeping span root and dep, since
|
|
# setting token.lex will change span.start and span.end properties
|
|
# as it modifies the character offsets in the doc
|
|
for token_index, (span, attributes) in enumerate(merges):
|
|
new_orth = ''.join([t.text_with_ws for t in spans[token_index]])
|
|
if spans[token_index][-1].whitespace_:
|
|
new_orth = new_orth[:-len(spans[token_index][-1].whitespace_)]
|
|
# add the vector of the (merged) entity to the vocab
|
|
if not doc.vocab.get_vector(new_orth).any():
|
|
if doc.vocab.vectors_length > 0:
|
|
doc.vocab.set_vector(new_orth, span.vector)
|
|
token = tokens[token_index]
|
|
lex = doc.vocab.get(doc.mem, new_orth)
|
|
token.lex = lex
|
|
# We set trailing space here too
|
|
token.spacy = doc.c[spans[token_index].end-1].spacy
|
|
py_token = span[0]
|
|
# Assign attributes
|
|
for attr_name, attr_value in attributes.items():
|
|
if attr_name == "_": # Set extension attributes
|
|
for ext_attr_key, ext_attr_value in attr_value.items():
|
|
py_token._.set(ext_attr_key, ext_attr_value)
|
|
elif attr_name == TAG:
|
|
doc.vocab.morphology.assign_tag(token, attr_value)
|
|
else:
|
|
# Set attributes on both token and lexeme to take care of token
|
|
# attribute vs. lexical attribute without having to enumerate
|
|
# them. If an attribute name is not valid, set_struct_attr will
|
|
# ignore it. Exception: set NORM only on tokens.
|
|
Token.set_struct_attr(token, attr_name, attr_value)
|
|
if attr_name != NORM:
|
|
Lexeme.set_struct_attr(<LexemeC*>lex, attr_name, attr_value)
|
|
# Begin by setting all the head indices to absolute token positions
|
|
# This is easier to work with for now than the offsets
|
|
# Before thinking of something simpler, beware the case where a
|
|
# dependency bridges over the entity. Here the alignment of the
|
|
# tokens changes.
|
|
for i in range(doc.length):
|
|
doc.c[i].head += i
|
|
# Set the head of the merged token from the Span
|
|
for i in range(len(merges)):
|
|
tokens[i].head = doc.c[span_roots[i]].head
|
|
# Adjust deps before shrinking tokens
|
|
# Tokens which point into the merged token should now point to it
|
|
# Subtract the offset from all tokens which point to >= end
|
|
offsets = []
|
|
current_span_index = 0
|
|
current_offset = 0
|
|
for i in range(doc.length):
|
|
if current_span_index < len(spans) and i == spans[current_span_index].end:
|
|
# Last token was the last of the span
|
|
current_offset += (spans[current_span_index].end - spans[current_span_index].start) -1
|
|
current_span_index += 1
|
|
if current_span_index < len(spans) and \
|
|
spans[current_span_index].start <= i < spans[current_span_index].end:
|
|
offsets.append(spans[current_span_index].start - current_offset)
|
|
else:
|
|
offsets.append(i - current_offset)
|
|
for i in range(doc.length):
|
|
doc.c[i].head = offsets[doc.c[i].head]
|
|
# Now compress the token array
|
|
offset = 0
|
|
in_span = False
|
|
span_index = 0
|
|
for i in range(doc.length):
|
|
if in_span and i == spans[span_index].end:
|
|
# First token after a span
|
|
in_span = False
|
|
span_index += 1
|
|
if span_index < len(spans) and i == spans[span_index].start:
|
|
# First token in a span
|
|
doc.c[i - offset] = doc.c[i] # move token to its place
|
|
offset += (spans[span_index].end - spans[span_index].start) - 1
|
|
in_span = True
|
|
if not in_span:
|
|
doc.c[i - offset] = doc.c[i] # move token to its place
|
|
|
|
for i in range(doc.length - offset, doc.length):
|
|
memset(&doc.c[i], 0, sizeof(TokenC))
|
|
doc.c[i].lex = &EMPTY_LEXEME
|
|
doc.length -= offset
|
|
# ...And, set heads back to a relative position
|
|
for i in range(doc.length):
|
|
doc.c[i].head -= i
|
|
# Set the left/right children, left/right edges
|
|
set_children_from_heads(doc.c, doc.length)
|
|
# Make sure ent_iob remains consistent
|
|
make_iob_consistent(doc.c, doc.length)
|
|
# Return the merged Python object
|
|
return doc[spans[0].start]
|
|
|
|
|
|
def _resize_tensor(tensor, ranges):
|
|
delete = []
|
|
for start, end in ranges:
|
|
for i in range(start, end-1):
|
|
delete.append(i)
|
|
xp = get_array_module(tensor)
|
|
return xp.delete(tensor, delete, axis=0)
|
|
|
|
|
|
def _split(Doc doc, int token_index, orths, heads, attrs):
|
|
"""Retokenize the document, such that the token at
|
|
`doc[token_index]` is split into tokens with the orth 'orths'
|
|
token_index(int): token index of the token to split.
|
|
orths: IDs of the verbatim text content of the tokens to create
|
|
**attributes: Attributes to assign to each of the newly created tokens. By default,
|
|
attributes are inherited from the original token.
|
|
RETURNS (Token): The first newly created token.
|
|
"""
|
|
cdef int nb_subtokens = len(orths)
|
|
cdef const LexemeC* lex
|
|
cdef TokenC* token
|
|
cdef TokenC orig_token = doc.c[token_index]
|
|
cdef int orig_length = len(doc)
|
|
|
|
if(len(heads) != nb_subtokens):
|
|
raise ValueError(Errors.E115)
|
|
# First, make the dependencies absolutes
|
|
for i in range(doc.length):
|
|
doc.c[i].head += i
|
|
# Adjust dependencies, so they refer to post-split indexing
|
|
offset = nb_subtokens - 1
|
|
for i in range(doc.length):
|
|
if doc.c[i].head > token_index:
|
|
doc.c[i].head += offset
|
|
# Double doc.c max_length if necessary (until big enough for all new tokens)
|
|
while doc.length + nb_subtokens - 1 >= doc.max_length:
|
|
doc._realloc(doc.max_length * 2)
|
|
# Move tokens after the split to create space for the new tokens
|
|
doc.length = len(doc) + nb_subtokens -1
|
|
to_process_tensor = (doc.tensor is not None and doc.tensor.size != 0)
|
|
if to_process_tensor:
|
|
xp = get_array_module(doc.tensor)
|
|
doc.tensor = xp.append(doc.tensor, xp.zeros((nb_subtokens,doc.tensor.shape[1]), dtype="float32"), axis=0)
|
|
for token_to_move in range(orig_length - 1, token_index, -1):
|
|
doc.c[token_to_move + nb_subtokens - 1] = doc.c[token_to_move]
|
|
if to_process_tensor:
|
|
doc.tensor[token_to_move + nb_subtokens - 1] = doc.tensor[token_to_move]
|
|
# Host the tokens in the newly created space
|
|
cdef int idx_offset = 0
|
|
for i, orth in enumerate(orths):
|
|
token = &doc.c[token_index + i]
|
|
lex = doc.vocab.get(doc.mem, orth)
|
|
token.lex = lex
|
|
token.lemma = 0 # reset lemma
|
|
token.norm = 0 # reset norm
|
|
if to_process_tensor:
|
|
# setting the tensors of the split tokens to array of zeros
|
|
doc.tensor[token_index + i] = xp.zeros((1,doc.tensor.shape[1]), dtype="float32")
|
|
# Update the character offset of the subtokens
|
|
if i != 0:
|
|
token.idx = orig_token.idx + idx_offset
|
|
idx_offset += len(orth)
|
|
# Set token.spacy to False for all non-last split tokens, and
|
|
# to origToken.spacy for the last token
|
|
if (i < nb_subtokens - 1):
|
|
token.spacy = False
|
|
else:
|
|
token.spacy = orig_token.spacy
|
|
# Make IOB consistent
|
|
if (orig_token.ent_iob == 3):
|
|
if i == 0:
|
|
token.ent_iob = 3
|
|
else:
|
|
token.ent_iob = 1
|
|
else:
|
|
# In all other cases subtokens inherit iob from origToken
|
|
token.ent_iob = orig_token.ent_iob
|
|
# Apply attrs to each subtoken
|
|
for attr_name, attr_values in attrs.items():
|
|
for i, attr_value in enumerate(attr_values):
|
|
token = &doc.c[token_index + i]
|
|
if attr_name == "_":
|
|
for ext_attr_key, ext_attr_value in attr_value.items():
|
|
doc[token_index + i]._.set(ext_attr_key, ext_attr_value)
|
|
# NB: We need to call get_string_id here because only the keys are
|
|
# "intified" (since we support "KEY": [value, value] syntax here).
|
|
elif attr_name == TAG:
|
|
doc.vocab.morphology.assign_tag(token, get_string_id(attr_value))
|
|
else:
|
|
# Set attributes on both token and lexeme to take care of token
|
|
# attribute vs. lexical attribute without having to enumerate
|
|
# them. If an attribute name is not valid, set_struct_attr will
|
|
# ignore it. Exception: set NORM only on tokens.
|
|
Token.set_struct_attr(token, attr_name, get_string_id(attr_value))
|
|
if attr_name != NORM:
|
|
Lexeme.set_struct_attr(<LexemeC*>token.lex, attr_name, get_string_id(attr_value))
|
|
# Assign correct dependencies to the inner token
|
|
for i, head in enumerate(heads):
|
|
doc.c[token_index + i].head = head
|
|
# Transform the dependencies into relative ones again
|
|
for i in range(doc.length):
|
|
doc.c[i].head -= i
|
|
# set children from head
|
|
set_children_from_heads(doc.c, doc.length)
|
|
|
|
|
|
def _validate_extensions(extensions):
|
|
if not isinstance(extensions, dict):
|
|
raise ValueError(Errors.E120.format(value=repr(extensions)))
|
|
for key, value in extensions.items():
|
|
# Get the extension and make sure it's available and writable
|
|
extension = Token.get_extension(key)
|
|
if not extension: # Extension attribute doesn't exist
|
|
raise ValueError(Errors.E118.format(attr=key))
|
|
if not is_writable_attr(extension):
|
|
raise ValueError(Errors.E119.format(attr=key))
|
|
|
|
|
|
cdef make_iob_consistent(TokenC* tokens, int length):
|
|
cdef int i
|
|
if tokens[0].ent_iob == 1:
|
|
tokens[0].ent_iob = 3
|
|
for i in range(1, length):
|
|
if tokens[i].ent_iob == 1 and tokens[i - 1].ent_type != tokens[i].ent_type:
|
|
tokens[i].ent_iob = 3
|