Simplify warnings

This commit is contained in:
Ines Montani 2020-02-28 12:20:23 +01:00
parent 5da3ad682a
commit 37691e6d5d
21 changed files with 82 additions and 133 deletions

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@ -11,7 +11,7 @@ from . import pipeline
from .cli.info import info as cli_info
from .glossary import explain
from .about import __version__
from .errors import Errors, Warnings, deprecation_warning
from .errors import Errors, Warnings
from . import util
from .util import registry
from .language import component
@ -27,7 +27,7 @@ config = registry
def load(name, **overrides):
depr_path = overrides.get("path")
if depr_path not in (True, False, None):
deprecation_warning(Warnings.W001.format(path=depr_path))
warnings.warn(Warnings.W001.format(path=depr_path), DeprecationWarning)
return util.load_model(name, **overrides)

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@ -1,7 +1,8 @@
from wasabi import Printer
import warnings
from .tokens import Doc, Token, Span
from .errors import Errors, Warnings, user_warning
from .errors import Errors, Warnings
def analyze_pipes(pipeline, name, pipe, index, warn=True):
@ -30,7 +31,7 @@ def analyze_pipes(pipeline, name, pipe, index, warn=True):
if not fulfilled:
problems.append(annot)
if warn:
user_warning(Warnings.W025.format(name=name, attr=annot))
warnings.warn(Warnings.W025.format(name=name, attr=annot))
return problems

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@ -9,9 +9,10 @@ import gzip
import zipfile
import srsly
from wasabi import msg
import warnings
from ..vectors import Vectors
from ..errors import Errors, Warnings, user_warning
from ..errors import Errors, Warnings
from ..util import ensure_path, get_lang_class
try:
@ -227,7 +228,7 @@ def read_freqs(freqs_loc, max_length=100, min_doc_freq=5, min_freq=50):
def read_clusters(clusters_loc):
clusters = {}
if ftfy is None:
user_warning(Warnings.W004)
warnings.warn(Warnings.W004)
with clusters_loc.open() as f:
for line in tqdm(f):
try:

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@ -4,9 +4,11 @@ spaCy's built in visualization suite for dependencies and named entities.
DOCS: https://spacy.io/api/top-level#displacy
USAGE: https://spacy.io/usage/visualizers
"""
import warnings
from .render import DependencyRenderer, EntityRenderer
from ..tokens import Doc, Span
from ..errors import Errors, Warnings, user_warning
from ..errors import Errors, Warnings
from ..util import is_in_jupyter
@ -85,7 +87,7 @@ def serve(
from wsgiref import simple_server
if is_in_jupyter():
user_warning(Warnings.W011)
warnings.warn(Warnings.W011)
render(docs, style=style, page=page, minify=minify, options=options, manual=manual)
httpd = simple_server.make_server(host, port, app)
@ -115,7 +117,7 @@ def parse_deps(orig_doc, options={}):
"""
doc = Doc(orig_doc.vocab).from_bytes(orig_doc.to_bytes(exclude=["user_data"]))
if not doc.is_parsed:
user_warning(Warnings.W005)
warnings.warn(Warnings.W005)
if options.get("collapse_phrases", False):
with doc.retokenize() as retokenizer:
for np in list(doc.noun_chunks):
@ -173,7 +175,7 @@ def parse_ents(doc, options={}):
for ent in doc.ents
]
if not ents:
user_warning(Warnings.W006)
warnings.warn(Warnings.W006)
title = doc.user_data.get("title", None) if hasattr(doc, "user_data") else None
settings = get_doc_settings(doc)
return {"text": doc.text, "ents": ents, "title": title, "settings": settings}

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@ -1,8 +1,3 @@
import os
import warnings
import inspect
def add_codes(err_cls):
"""Add error codes to string messages via class attribute names."""
@ -583,64 +578,3 @@ class MatchPatternError(ValueError):
class AlignmentError(ValueError):
pass
class ModelsWarning(UserWarning):
pass
WARNINGS = {
"user": UserWarning,
"deprecation": DeprecationWarning,
"models": ModelsWarning,
}
def _get_warn_types(arg):
if arg == "": # don't show any warnings
return []
if not arg or arg == "all": # show all available warnings
return WARNINGS.keys()
return [w_type.strip() for w_type in arg.split(",") if w_type.strip() in WARNINGS]
def _get_warn_excl(arg):
if not arg:
return []
return [w_id.strip() for w_id in arg.split(",")]
SPACY_WARNING_FILTER = os.environ.get("SPACY_WARNING_FILTER")
SPACY_WARNING_TYPES = _get_warn_types(os.environ.get("SPACY_WARNING_TYPES"))
SPACY_WARNING_IGNORE = _get_warn_excl(os.environ.get("SPACY_WARNING_IGNORE"))
def user_warning(message):
_warn(message, "user")
def deprecation_warning(message):
_warn(message, "deprecation")
def models_warning(message):
_warn(message, "models")
def _warn(message, warn_type="user"):
"""
message (unicode): The message to display.
category (Warning): The Warning to show.
"""
if message.startswith("["):
w_id = message.split("[", 1)[1].split("]", 1)[0] # get ID from string
else:
w_id = None
ignore_warning = w_id and w_id in SPACY_WARNING_IGNORE
if warn_type in SPACY_WARNING_TYPES and not ignore_warning:
category = WARNINGS[warn_type]
stack = inspect.stack()[-1]
with warnings.catch_warnings():
if SPACY_WARNING_FILTER:
warnings.simplefilter(SPACY_WARNING_FILTER, category)
warnings.warn_explicit(message, category, stack[1], stack[2])

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@ -7,10 +7,11 @@ import shutil
import itertools
from pathlib import Path
import srsly
import warnings
from .syntax import nonproj
from .tokens import Doc, Span
from .errors import Errors, AlignmentError, user_warning, Warnings
from .errors import Errors, AlignmentError, Warnings
from . import util
@ -550,7 +551,7 @@ def _json_iterate(loc):
py_raw = file_.read()
cdef long file_length = len(py_raw)
if file_length > 2 ** 30:
user_warning(Warnings.W027.format(size=file_length))
warnings.warn(Warnings.W027.format(size=file_length))
raw = <char*>py_raw
cdef int square_depth = 0

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@ -1,16 +1,18 @@
# cython: infer_types=True
# cython: profile=True
from pathlib import Path
from cymem.cymem cimport Pool
from preshed.maps cimport PreshMap
from cpython.exc cimport PyErr_SetFromErrno
from libc.stdio cimport fopen, fclose, fread, fwrite, feof, fseek
from libc.stdint cimport int32_t, int64_t
from os import path
from libcpp.vector cimport vector
from pathlib import Path
import warnings
from os import path
from .typedefs cimport hash_t
from .errors import Errors, Warnings, user_warning
from .errors import Errors, Warnings
cdef class Candidate:
@ -110,7 +112,7 @@ cdef class KnowledgeBase:
# Return if this entity was added before
if entity_hash in self._entry_index:
user_warning(Warnings.W018.format(entity=entity))
warnings.warn(Warnings.W018.format(entity=entity))
return
# Raise an error if the provided entity vector is not of the correct length
@ -142,7 +144,7 @@ cdef class KnowledgeBase:
# only process this entity if its unique ID hadn't been added before
entity_hash = self.vocab.strings.add(entity_list[i])
if entity_hash in self._entry_index:
user_warning(Warnings.W018.format(entity=entity_list[i]))
warnings.warn(Warnings.W018.format(entity=entity_list[i]))
else:
entity_vector = vector_list[i]
@ -190,7 +192,7 @@ cdef class KnowledgeBase:
# Check whether this alias was added before
if alias_hash in self._alias_index:
user_warning(Warnings.W017.format(alias=alias))
warnings.warn(Warnings.W017.format(alias=alias))
return
cdef vector[int64_t] entry_indices
@ -247,7 +249,7 @@ cdef class KnowledgeBase:
if is_present:
if not ignore_warnings:
user_warning(Warnings.W024.format(entity=entity, alias=alias))
warnings.warn(Warnings.W024.format(entity=entity, alias=alias))
else:
entry_indices.push_back(int(entry_index))
alias_entry.entry_indices = entry_indices

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@ -5,6 +5,7 @@ import functools
from contextlib import contextmanager
from copy import copy, deepcopy
from pathlib import Path
import warnings
from thinc.api import get_current_ops, Config
import srsly
@ -26,7 +27,7 @@ from .lang.tokenizer_exceptions import TOKEN_MATCH
from .lang.tag_map import TAG_MAP
from .tokens import Doc
from .lang.lex_attrs import LEX_ATTRS, is_stop
from .errors import Errors, Warnings, deprecation_warning, user_warning
from .errors import Errors, Warnings
from . import util
from . import about
@ -340,11 +341,11 @@ class Language(object):
if "model" in config:
model_cfg = config["model"]
if not isinstance(model_cfg, dict):
user_warning(Warnings.W099.format(type=type(model_cfg), pipe=name))
warnings.warn(Warnings.W099.format(type=type(model_cfg), pipe=name))
model_cfg = None
del config["model"]
if model_cfg is None and default_config is not None:
user_warning(Warnings.W098.format(name=name))
warnings.warn(Warnings.W098.format(name=name))
model_cfg = default_config["model"]
model = None
if model_cfg is not None:
@ -779,7 +780,7 @@ class Language(object):
# raw_texts will be used later to stop iterator.
texts, raw_texts = itertools.tee(texts)
if n_threads != -1:
deprecation_warning(Warnings.W016)
warnings.warn(Warnings.W016, DeprecationWarning)
if n_process == -1:
n_process = mp.cpu_count()
if as_tuples:
@ -915,7 +916,7 @@ class Language(object):
DOCS: https://spacy.io/api/language#to_disk
"""
if disable is not None:
deprecation_warning(Warnings.W014)
warnings.warn(Warnings.W014, DeprecationWarning)
exclude = disable
path = util.ensure_path(path)
serializers = {}
@ -949,7 +950,7 @@ class Language(object):
DOCS: https://spacy.io/api/language#from_disk
"""
if disable is not None:
deprecation_warning(Warnings.W014)
warnings.warn(Warnings.W014, DeprecationWarning)
exclude = disable
path = util.ensure_path(path)
deserializers = {}
@ -987,7 +988,7 @@ class Language(object):
DOCS: https://spacy.io/api/language#to_bytes
"""
if disable is not None:
deprecation_warning(Warnings.W014)
warnings.warn(Warnings.W014, DeprecationWarning)
exclude = disable
serializers = {}
serializers["vocab"] = lambda: self.vocab.to_bytes()
@ -1013,7 +1014,7 @@ class Language(object):
DOCS: https://spacy.io/api/language#from_bytes
"""
if disable is not None:
deprecation_warning(Warnings.W014)
warnings.warn(Warnings.W014, DeprecationWarning)
exclude = disable
deserializers = {}
deserializers["config.cfg"] = lambda b: self.config.from_bytes(b)

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@ -7,6 +7,7 @@ np.import_array()
import numpy
from thinc.api import get_array_module
import warnings
from .typedefs cimport attr_t, flags_t
from .attrs cimport IS_ALPHA, IS_ASCII, IS_DIGIT, IS_LOWER, IS_PUNCT, IS_SPACE
@ -15,7 +16,7 @@ from .attrs cimport IS_BRACKET, IS_QUOTE, IS_LEFT_PUNCT, IS_RIGHT_PUNCT
from .attrs cimport IS_CURRENCY, IS_OOV, PROB
from .attrs import intify_attrs
from .errors import Errors, Warnings, user_warning
from .errors import Errors, Warnings
memset(&EMPTY_LEXEME, 0, sizeof(LexemeC))
@ -124,7 +125,7 @@ cdef class Lexeme:
if self.c.orth == other[0].orth:
return 1.0
if self.vector_norm == 0 or other.vector_norm == 0:
user_warning(Warnings.W008.format(obj="Lexeme"))
warnings.warn(Warnings.W008.format(obj="Lexeme"))
return 0.0
vector = self.vector
xp = get_array_module(vector)

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@ -7,6 +7,7 @@ from murmurhash.mrmr cimport hash64
import re
import srsly
import warnings
from ..typedefs cimport attr_t
from ..structs cimport TokenC
@ -16,7 +17,7 @@ from ..tokens.token cimport Token
from ..attrs cimport ID, attr_id_t, NULL_ATTR, ORTH, POS, TAG, DEP, LEMMA
from ..schemas import validate_token_pattern
from ..errors import Errors, MatchPatternError, Warnings, deprecation_warning
from ..errors import Errors, MatchPatternError, Warnings
from ..strings import get_string_id
from ..attrs import IDS
@ -188,7 +189,7 @@ cdef class Matcher:
YIELDS (Doc): Documents, in order.
"""
if n_threads != -1:
deprecation_warning(Warnings.W016)
warnings.warn(Warnings.W016, DeprecationWarning)
if as_tuples:
for doc, context in docs:

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@ -1,16 +1,17 @@
# cython: infer_types=True
# cython: profile=True
from libc.stdint cimport uintptr_t
from preshed.maps cimport map_init, map_set, map_get, map_clear, map_iter
import warnings
from ..attrs cimport ORTH, POS, TAG, DEP, LEMMA
from ..structs cimport TokenC
from ..tokens.token cimport Token
from ..typedefs cimport attr_t
from ..schemas import TokenPattern
from ..errors import Errors, Warnings, deprecation_warning, user_warning
from ..errors import Errors, Warnings
cdef class PhraseMatcher:
@ -37,7 +38,7 @@ cdef class PhraseMatcher:
DOCS: https://spacy.io/api/phrasematcher#init
"""
if max_length != 0:
deprecation_warning(Warnings.W010)
warnings.warn(Warnings.W010, DeprecationWarning)
self.vocab = vocab
self._callbacks = {}
self._docs = {}
@ -193,7 +194,7 @@ cdef class PhraseMatcher:
if self._validate and (doc.is_tagged or doc.is_parsed) \
and self.attr not in (DEP, POS, TAG, LEMMA):
string_attr = self.vocab.strings[self.attr]
user_warning(Warnings.W012.format(key=key, attr=string_attr))
warnings.warn(Warnings.W012.format(key=key, attr=string_attr))
keyword = self._convert_to_array(doc)
else:
keyword = doc
@ -202,7 +203,7 @@ cdef class PhraseMatcher:
current_node = self.c_map
for token in keyword:
if token == self._terminal_hash:
user_warning(Warnings.W021)
warnings.warn(Warnings.W021)
break
result = <MapStruct*>map_get(current_node, token)
if not result:
@ -304,7 +305,7 @@ cdef class PhraseMatcher:
DOCS: https://spacy.io/api/phrasematcher#pipe
"""
if n_threads != -1:
deprecation_warning(Warnings.W016)
warnings.warn(Warnings.W016, DeprecationWarning)
if as_tuples:
for doc, context in stream:
matches = self(doc)

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@ -3,6 +3,7 @@ from libc.string cimport memset
import srsly
from collections import Counter
import numpy
import warnings
from .strings import get_string_id
from . import symbols
@ -11,7 +12,7 @@ from .attrs import LEMMA, intify_attrs
from .parts_of_speech cimport SPACE
from .parts_of_speech import IDS as POS_IDS
from .lexeme cimport Lexeme
from .errors import Errors, Warnings, user_warning
from .errors import Errors, Warnings
from .util import ensure_path
@ -39,7 +40,7 @@ def _normalize_props(props):
elif isinstance(key, (int, str)) and isinstance(value, (int, str)):
out[key] = value
else:
user_warning(Warnings.W028.format(feature={key: value}))
warnings.warn(Warnings.W028.format(feature={key: value}))
return out
@ -109,7 +110,7 @@ cdef class Morphology:
return tag_ptr.key
features = self.feats_to_dict(features)
if not isinstance(features, dict):
user_warning(Warnings.W028.format(feature=features))
warnings.warn(Warnings.W028.format(feature=features))
features = {}
features = _normalize_props(features)
string_features = {self.strings.as_string(field): self.strings.as_string(values) for field, values in features.items()}

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@ -5,6 +5,7 @@ import srsly
import random
from thinc.api import CosineDistance, to_categorical, get_array_module
from thinc.api import set_dropout_rate
import warnings
from ..tokens.doc cimport Doc
from ..syntax.nn_parser cimport Parser
@ -21,7 +22,7 @@ from ..attrs import POS, ID
from ..util import link_vectors_to_models, create_default_optimizer
from ..parts_of_speech import X
from ..kb import KnowledgeBase
from ..errors import Errors, TempErrors, user_warning, Warnings
from ..errors import Errors, TempErrors, Warnings
from .. import util
@ -525,7 +526,7 @@ class Tagger(Pipe):
**kwargs):
lemma_tables = ["lemma_rules", "lemma_index", "lemma_exc", "lemma_lookup"]
if not any(table in self.vocab.lookups for table in lemma_tables):
user_warning(Warnings.W022)
warnings.warn(Warnings.W022)
orig_tag_map = dict(self.vocab.morphology.tag_map)
new_tag_map = {}
for example in get_examples():

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@ -19,6 +19,7 @@ from itertools import islice
import srsly
import numpy.random
import numpy
import warnings
from ..gold import Example
from ..typedefs cimport weight_t, class_t, hash_t
@ -31,7 +32,7 @@ from ..util import link_vectors_to_models, create_default_optimizer, registry
from ..compat import copy_array
from ..tokens.doc cimport Doc
from ..gold cimport GoldParse
from ..errors import Errors, user_warning, Warnings
from ..errors import Errors, Warnings
from .. import util
from .stateclass cimport StateClass
from ._state cimport StateC

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@ -2,7 +2,6 @@ import pytest
import numpy
from spacy.tokens import Doc, Span
from spacy.vocab import Vocab
from spacy.errors import ModelsWarning
from spacy.attrs import ENT_TYPE, ENT_IOB, SENT_START, HEAD, DEP
from ..util import get_doc
@ -213,7 +212,7 @@ def test_doc_api_similarity_match():
assert doc.similarity(doc[0]) == 1.0
assert doc.similarity(doc.vocab["a"]) == 1.0
doc2 = Doc(doc.vocab, words=["a", "b", "c"])
with pytest.warns(ModelsWarning):
with pytest.warns(UserWarning):
assert doc.similarity(doc2[:1]) == 1.0
assert doc.similarity(doc2) == 0.0

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@ -2,7 +2,6 @@ import pytest
from spacy.attrs import ORTH, LENGTH
from spacy.tokens import Doc, Span
from spacy.vocab import Vocab
from spacy.errors import ModelsWarning
from spacy.util import filter_spans
from ..util import get_doc
@ -121,7 +120,7 @@ def test_span_similarity_match():
doc = Doc(Vocab(), words=["a", "b", "a", "b"])
span1 = doc[:2]
span2 = doc[2:]
with pytest.warns(ModelsWarning):
with pytest.warns(UserWarning):
assert span1.similarity(span2) == 1.0
assert span1.similarity(doc) == 0.0
assert span1[:1].similarity(doc.vocab["a"]) == 1.0

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@ -11,13 +11,14 @@ from preshed.maps cimport PreshMap
cimport cython
import re
import warnings
from .tokens.doc cimport Doc
from .strings cimport hash_string
from .attrs import intify_attrs
from .symbols import ORTH
from .errors import Errors, Warnings, deprecation_warning
from .errors import Errors, Warnings
from . import util
from .attrs import intify_attrs
from .lexeme cimport EMPTY_LEXEME
@ -128,7 +129,7 @@ cdef class Tokenizer:
return (self.__class__, args, None, None)
cpdef Doc tokens_from_list(self, list strings):
deprecation_warning(Warnings.W002)
warnings.warn(Warnings.W002, DeprecationWarning)
return Doc(self.vocab, words=strings)
def __call__(self, unicode string):
@ -216,7 +217,7 @@ cdef class Tokenizer:
DOCS: https://spacy.io/api/tokenizer#pipe
"""
if n_threads != -1:
deprecation_warning(Warnings.W016)
warnings.warn(Warnings.W016, DeprecationWarning)
for text in texts:
yield self(text)

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@ -13,6 +13,7 @@ import struct
import srsly
from thinc.api import get_array_module
from thinc.util import copy_array
import warnings
from .span cimport Span
from .token cimport Token
@ -26,7 +27,6 @@ from ..parts_of_speech cimport CCONJ, PUNCT, NOUN, univ_pos_t
from ..attrs import intify_attrs, IDS
from ..util import normalize_slice
from ..compat import copy_reg, pickle
from ..errors import deprecation_warning, models_warning, user_warning
from ..errors import Errors, Warnings
from .. import util
from .underscore import Underscore, get_ext_args
@ -388,9 +388,9 @@ cdef class Doc:
else:
return 1.0
if self.vocab.vectors.n_keys == 0:
models_warning(Warnings.W007.format(obj="Doc"))
warnings.warn(Warnings.W007.format(obj="Doc"))
if self.vector_norm == 0 or other.vector_norm == 0:
user_warning(Warnings.W008.format(obj="Doc"))
warnings.warn(Warnings.W008.format(obj="Doc"))
return 0.0
vector = self.vector
xp = get_array_module(vector)
@ -1024,10 +1024,10 @@ cdef class Doc:
indices did not fall at token boundaries.
"""
cdef unicode tag, lemma, ent_type
deprecation_warning(Warnings.W013.format(obj="Doc"))
warnings.warn(Warnings.W013.format(obj="Doc"), DeprecationWarning)
# TODO: ENT_KB_ID ?
if len(args) == 3:
deprecation_warning(Warnings.W003)
warnings.warn(Warnings.W003, DeprecationWarning)
tag, lemma, ent_type = args
attributes[TAG] = tag
attributes[LEMMA] = lemma
@ -1167,7 +1167,7 @@ cdef int set_children_from_heads(TokenC* tokens, int length) except -1:
while not heads_within_sents:
heads_within_sents = _set_lr_kids_and_edges(tokens, length, loop_count)
if loop_count > 10:
user_warning(Warnings.W026)
warnings.warn(Warnings.W026)
loop_count += 1
# Set sentence starts
for i in range(length):

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@ -6,6 +6,7 @@ import numpy
import numpy.linalg
from thinc.api import get_array_module
from collections import defaultdict
import warnings
from .doc cimport token_by_start, token_by_end, get_token_attr, _get_lca_matrix
from .token cimport TokenC
@ -18,8 +19,7 @@ from ..lexeme cimport Lexeme
from ..symbols cimport dep
from ..util import normalize_slice
from ..errors import Errors, TempErrors, Warnings, user_warning, models_warning
from ..errors import deprecation_warning
from ..errors import Errors, TempErrors, Warnings
from .underscore import Underscore, get_ext_args
@ -287,7 +287,7 @@ cdef class Span:
attributes are inherited from the syntactic root token of the span.
RETURNS (Token): The newly merged token.
"""
deprecation_warning(Warnings.W013.format(obj="Span"))
warnings.warn(Warnings.W013.format(obj="Span"), DeprecationWarning)
return self.doc.merge(self.start_char, self.end_char, *args,
**attributes)
@ -326,9 +326,9 @@ cdef class Span:
else:
return 1.0
if self.vocab.vectors.n_keys == 0:
models_warning(Warnings.W007.format(obj="Span"))
warnings.warn(Warnings.W007.format(obj="Span"))
if self.vector_norm == 0.0 or other.vector_norm == 0.0:
user_warning(Warnings.W008.format(obj="Span"))
warnings.warn(Warnings.W008.format(obj="Span"))
return 0.0
vector = self.vector
xp = get_array_module(vector)

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@ -8,6 +8,7 @@ np.import_array()
import numpy
from thinc.api import get_array_module
import warnings
from ..typedefs cimport hash_t
from ..lexeme cimport Lexeme
@ -20,7 +21,7 @@ from ..symbols cimport conj
from .. import parts_of_speech
from .. import util
from ..errors import Errors, Warnings, user_warning, models_warning
from ..errors import Errors, Warnings
from .underscore import Underscore, get_ext_args
from .morphanalysis cimport MorphAnalysis
@ -205,9 +206,9 @@ cdef class Token:
if self.c.lex.orth == other.orth:
return 1.0
if self.vocab.vectors.n_keys == 0:
models_warning(Warnings.W007.format(obj="Token"))
warnings.warn(Warnings.W007.format(obj="Token"))
if self.vector_norm == 0 or other.vector_norm == 0:
user_warning(Warnings.W008.format(obj="Token"))
warnings.warn(Warnings.W008.format(obj="Token"))
return 0.0
vector = self.vector
xp = get_array_module(vector)

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@ -13,6 +13,7 @@ import numpy.random
import srsly
import catalogue
import sys
import warnings
try:
@ -22,7 +23,7 @@ except ImportError:
from .symbols import ORTH
from .compat import cupy, CudaStream
from .errors import Errors, Warnings, deprecation_warning, user_warning
from .errors import Errors, Warnings
_PRINT_ENV = False
@ -731,7 +732,7 @@ def get_serialization_exclude(serializers, exclude, kwargs):
options = [name.split(".")[0] for name in serializers]
for key, value in kwargs.items():
if key in ("vocab",) and value is False:
deprecation_warning(Warnings.W015.format(arg=key))
warnings.warn(Warnings.W015.format(arg=key), DeprecationWarning)
exclude.append(key)
elif key.split(".")[0] in options:
raise ValueError(Errors.E128.format(arg=key))
@ -776,7 +777,7 @@ def link_vectors_to_models(vocab):
if vectors.name is None:
vectors.name = VECTORS_KEY
if vectors.data.size != 0:
user_warning(Warnings.W020.format(shape=vectors.data.shape))
warnings.warn(Warnings.W020.format(shape=vectors.data.shape))
for word in vocab:
if word.orth in vectors.key2row:
word.rank = vectors.key2row[word.orth]