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Merge branch 'master' into sync/master-into-v4

Browse Source 
# Conflicts:
#	requirements.txt
#	spacy/pipeline/entity_linker.py
#	spacy/util.py
#	website/docs/api/entitylinker.mdx
This commit is contained in:
Raphael Mitsch 2023-03-02 14:25:11 +01:00
commit 1ea31552be
35 changed files with 486 additions and 136 deletions
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2
.github/workflows/autoblack.yml vendored
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@ -16,7 +16,7 @@ jobs:
with: with:
ref: ${{ github.head_ref }} ref: ${{ github.head_ref }}
- uses: actions/setup-python@v4 - uses: actions/setup-python@v4
- run: pip install black - run: pip install black -c requirements.txt
- name: Auto-format code if needed - name: Auto-format code if needed
run: black spacy run: black spacy
# We can't run black --check here because that returns a non-zero excit # We can't run black --check here because that returns a non-zero excit

5
CONTRIBUTING.md
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@ -173,6 +173,11 @@ formatting and [`flake8`](http://flake8.pycqa.org/en/latest/) for linting its
Python modules. If you've built spaCy from source, you'll already have both Python modules. If you've built spaCy from source, you'll already have both
tools installed. tools installed.
As a general rule of thumb, we use f-strings for any formatting of strings.
One exception are calls to Python's `logging` functionality.
To avoid unnecessary string conversions in these cases, we use string formatting
templates with `%s` and `%d` etc.
**⚠️ Note that formatting and linting is currently only possible for Python **⚠️ Note that formatting and linting is currently only possible for Python
modules in `.py` files, not Cython modules in `.pyx` and `.pxd` files.** modules in `.py` files, not Cython modules in `.pyx` and `.pxd` files.**

2
azure-pipelines.yml
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@ -41,7 +41,7 @@ jobs:
inputs: inputs:
versionSpec: "3.8" versionSpec: "3.8"
- script: | - script: |
pip install black==22.3.0 pip install black -c requirements.txt
python -m black spacy --check python -m black spacy --check
displayName: "black" displayName: "black"
- script: | - script: |

5
requirements.txt
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@ -30,9 +30,10 @@ pytest-timeout>=1.3.0,<2.0.0
mock>=2.0.0,<3.0.0 mock>=2.0.0,<3.0.0
flake8>=3.8.0,<6.0.0 flake8>=3.8.0,<6.0.0
hypothesis>=3.27.0,<7.0.0 hypothesis>=3.27.0,<7.0.0
mypy>=0.990,<0.1000; platform_machine != "aarch64" mypy>=0.990,<1.1.0; platform_machine != "aarch64" and python_version >= "3.7"
types-dataclasses>=0.1.3; python_version < "3.7"
types-mock>=0.1.1 types-mock>=0.1.1
types-setuptools>=57.0.0 types-setuptools>=57.0.0
types-requests types-requests
types-setuptools>=57.0.0 types-setuptools>=57.0.0
black>=22.0,<23.0 black==22.3.0

4
spacy/cli/_util.py
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@ -90,9 +90,9 @@ def parse_config_overrides(
cli_overrides = _parse_overrides(args, is_cli=True) cli_overrides = _parse_overrides(args, is_cli=True)
if cli_overrides: if cli_overrides:
keys = [k for k in cli_overrides if k not in env_overrides] keys = [k for k in cli_overrides if k not in env_overrides]
logger.debug(f"Config overrides from CLI: {keys}") logger.debug("Config overrides from CLI: %s", keys)
if env_overrides: if env_overrides:
logger.debug(f"Config overrides from env variables: {list(env_overrides)}") logger.debug("Config overrides from env variables: %s", list(env_overrides))
return {**cli_overrides, **env_overrides} return {**cli_overrides, **env_overrides}

2
spacy/cli/package.py
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@ -252,7 +252,7 @@ def get_third_party_dependencies(
raise regerr from None raise regerr from None
module_name = func_info.get("module") # type: ignore[attr-defined] module_name = func_info.get("module") # type: ignore[attr-defined]
if module_name: # the code is part of a module, not a --code file if module_name: # the code is part of a module, not a --code file
modules.add(func_info["module"].split(".")[0]) # type: ignore[index] modules.add(func_info["module"].split(".")[0]) # type: ignore[union-attr]
dependencies = [] dependencies = []
for module_name in modules: for module_name in modules:
if module_name in distributions: if module_name in distributions:

9
spacy/cli/project/pull.py
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@ -39,14 +39,17 @@ def project_pull(project_dir: Path, remote: str, *, verbose: bool = False):
# in the list. # in the list.
while commands: while commands:
for i, cmd in enumerate(list(commands)): for i, cmd in enumerate(list(commands)):
logger.debug(f"CMD: {cmd['name']}.") logger.debug("CMD: %s.", cmd["name"])
deps = [project_dir / dep for dep in cmd.get("deps", [])] deps = [project_dir / dep for dep in cmd.get("deps", [])]
if all(dep.exists() for dep in deps): if all(dep.exists() for dep in deps):
cmd_hash = get_command_hash("", "", deps, cmd["script"]) cmd_hash = get_command_hash("", "", deps, cmd["script"])
for output_path in cmd.get("outputs", []): for output_path in cmd.get("outputs", []):
url = storage.pull(output_path, command_hash=cmd_hash) url = storage.pull(output_path, command_hash=cmd_hash)
logger.debug( logger.debug(
f"URL: {url} for {output_path} with command hash {cmd_hash}" "URL: %s for %s with command hash %s",
url,
output_path,
cmd_hash,
) )
yield url, output_path yield url, output_path
@ -58,7 +61,7 @@ def project_pull(project_dir: Path, remote: str, *, verbose: bool = False):
commands.pop(i) commands.pop(i)
break break
else: else:
logger.debug(f"Dependency missing. Skipping {cmd['name']} outputs.") logger.debug("Dependency missing. Skipping %s outputs.", cmd["name"])
else: else:
# If we didn't break the for loop, break the while loop. # If we didn't break the for loop, break the while loop.
break break

8
spacy/cli/project/push.py
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@ -37,15 +37,15 @@ def project_push(project_dir: Path, remote: str):
remote = config["remotes"][remote] remote = config["remotes"][remote]
storage = RemoteStorage(project_dir, remote) storage = RemoteStorage(project_dir, remote)
for cmd in config.get("commands", []): for cmd in config.get("commands", []):
logger.debug(f"CMD: cmd['name']") logger.debug("CMD: %s", cmd["name"])
deps = [project_dir / dep for dep in cmd.get("deps", [])] deps = [project_dir / dep for dep in cmd.get("deps", [])]
if any(not dep.exists() for dep in deps): if any(not dep.exists() for dep in deps):
logger.debug(f"Dependency missing. Skipping {cmd['name']} outputs") logger.debug("Dependency missing. Skipping %s outputs", cmd["name"])
continue continue
cmd_hash = get_command_hash( cmd_hash = get_command_hash(
"", "", [project_dir / dep for dep in cmd.get("deps", [])], cmd["script"] "", "", [project_dir / dep for dep in cmd.get("deps", [])], cmd["script"]
) )
logger.debug(f"CMD_HASH: {cmd_hash}") logger.debug("CMD_HASH: %s", cmd_hash)
for output_path in cmd.get("outputs", []): for output_path in cmd.get("outputs", []):
output_loc = project_dir / output_path output_loc = project_dir / output_path
if output_loc.exists() and _is_not_empty_dir(output_loc): if output_loc.exists() and _is_not_empty_dir(output_loc):
@ -55,7 +55,7 @@ def project_push(project_dir: Path, remote: str):
content_hash=get_content_hash(output_loc), content_hash=get_content_hash(output_loc),
) )
logger.debug( logger.debug(
f"URL: {url} for output {output_path} with cmd_hash {cmd_hash}" "URL: %s for output %s with cmd_hash %s", url, output_path, cmd_hash
) )
yield output_path, url yield output_path, url

5
spacy/errors.py
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@ -437,8 +437,7 @@ class Errors(metaclass=ErrorsWithCodes):
E133 = ("The sum of prior probabilities for alias '{alias}' should not " E133 = ("The sum of prior probabilities for alias '{alias}' should not "
"exceed 1, but found {sum}.") "exceed 1, but found {sum}.")
E134 = ("Entity '{entity}' is not defined in the Knowledge Base.") E134 = ("Entity '{entity}' is not defined in the Knowledge Base.")
E139 = ("Knowledge base for component '{name}' is empty. Use the methods " E139 = ("Knowledge base for component '{name}' is empty.")
"`kb.add_entity` and `kb.add_alias` to add entries.")
E140 = ("The list of entities, prior probabilities and entity vectors " E140 = ("The list of entities, prior probabilities and entity vectors "
"should be of equal length.") "should be of equal length.")
E141 = ("Entity vectors should be of length {required} instead of the " E141 = ("Entity vectors should be of length {required} instead of the "
@ -951,7 +950,7 @@ class Errors(metaclass=ErrorsWithCodes):
E1049 = ("No available port found for displaCy on host {host}. Please specify an available port " E1049 = ("No available port found for displaCy on host {host}. Please specify an available port "
"with `displacy.serve(doc, port=port)`") "with `displacy.serve(doc, port=port)`")
E1050 = ("Port {port} is already in use. Please specify an available port with `displacy.serve(doc, port=port)` " E1050 = ("Port {port} is already in use. Please specify an available port with `displacy.serve(doc, port=port)` "
"or use `auto_switch_port=True` to pick an available port automatically.") "or use `auto_select_port=True` to pick an available port automatically.")
# v4 error strings # v4 error strings
E4000 = ("Expected a Doc as input, but got: '{type}'") E4000 = ("Expected a Doc as input, but got: '{type}'")

3
spacy/kb/kb_in_memory.pyx
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@ -46,6 +46,9 @@ cdef class InMemoryLookupKB(KnowledgeBase):
self._alias_index = PreshMap(nr_aliases + 1) self._alias_index = PreshMap(nr_aliases + 1)
self._aliases_table = alias_vec(nr_aliases + 1) self._aliases_table = alias_vec(nr_aliases + 1)
def is_empty(self):
return len(self) == 0
def __len__(self): def __len__(self):
return self.get_size_entities() return self.get_size_entities()

5
spacy/lang/sv/__init__.py
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@ -6,10 +6,7 @@ from .lex_attrs import LEX_ATTRS
from .syntax_iterators import SYNTAX_ITERATORS from .syntax_iterators import SYNTAX_ITERATORS
from ...language import Language, BaseDefaults from ...language import Language, BaseDefaults
from ...pipeline import Lemmatizer from ...pipeline import Lemmatizer
from .punctuation import TOKENIZER_INFIXES, TOKENIZER_SUFFIXES
# Punctuation stolen from Danish
from ..da.punctuation import TOKENIZER_INFIXES, TOKENIZER_SUFFIXES
class SwedishDefaults(BaseDefaults): class SwedishDefaults(BaseDefaults):

33
spacy/lang/sv/punctuation.py Normal file
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@ -0,0 +1,33 @@
from ..char_classes import LIST_ELLIPSES, LIST_ICONS
from ..char_classes import CONCAT_QUOTES, ALPHA, ALPHA_LOWER, ALPHA_UPPER
from ..punctuation import TOKENIZER_SUFFIXES
_quotes = CONCAT_QUOTES.replace("'", "")
_infixes = (
LIST_ELLIPSES
+ LIST_ICONS
+ [
r"(?<=[{al}])\.(?=[{au}])".format(al=ALPHA_LOWER, au=ALPHA_UPPER),
r"(?<=[{a}])[,!?](?=[{a}])".format(a=ALPHA),
r"(?<=[{a}])[<>=](?=[{a}])".format(a=ALPHA),
r"(?<=[{a}]):(?=[{a}])".format(a=ALPHA_UPPER),
r"(?<=[{a}]),(?=[{a}])".format(a=ALPHA),
r"(?<=[{a}])([{q}\)\]\(\[])(?=[{a}])".format(a=ALPHA, q=_quotes),
r"(?<=[{a}])--(?=[{a}])".format(a=ALPHA),
r"(?<=[{a}0-9])[<>=/](?=[{a}])".format(a=ALPHA),
r"(?<=[{a}0-9]):(?=[{a}])".format(a=ALPHA_UPPER),
]
)
_suffixes = [
suffix
for suffix in TOKENIZER_SUFFIXES
if suffix not in ["'s", "'S", "’s", "’S", r"\'"]
]
_suffixes += [r"(?<=[^sSxXzZ])\'"]
TOKENIZER_INFIXES = _infixes
TOKENIZER_SUFFIXES = _suffixes

4
spacy/language.py
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@ -106,7 +106,7 @@ def create_tokenizer() -> Callable[["Language"], Tokenizer]:
@registry.misc("spacy.LookupsDataLoader.v1") @registry.misc("spacy.LookupsDataLoader.v1")
def load_lookups_data(lang, tables): def load_lookups_data(lang, tables):
util.logger.debug(f"Loading lookups from spacy-lookups-data: {tables}") util.logger.debug("Loading lookups from spacy-lookups-data: %s", tables)
lookups = load_lookups(lang=lang, tables=tables) lookups = load_lookups(lang=lang, tables=tables)
return lookups return lookups
@ -2072,7 +2072,7 @@ class Language:
pipe = self.get_pipe(pipe_name) pipe = self.get_pipe(pipe_name)
pipe_cfg = self._pipe_configs[pipe_name] pipe_cfg = self._pipe_configs[pipe_name]
if listeners: if listeners:
util.logger.debug(f"Replacing listeners of component '{pipe_name}'") util.logger.debug("Replacing listeners of component '%s'", pipe_name)
if len(list(listeners)) != len(pipe_listeners): if len(list(listeners)) != len(pipe_listeners):
# The number of listeners defined in the component model doesn't # The number of listeners defined in the component model doesn't
# match the listeners to replace, so we won't be able to update # match the listeners to replace, so we won't be able to update

26
spacy/matcher/dependencymatcher.pyx
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@ -82,8 +82,12 @@ cdef class DependencyMatcher:
"$-": self._imm_left_sib, "$-": self._imm_left_sib,
"$++": self._right_sib, "$++": self._right_sib,
"$--": self._left_sib, "$--": self._left_sib,
">+": self._imm_right_child,
">-": self._imm_left_child,
">++": self._right_child, ">++": self._right_child,
">--": self._left_child, ">--": self._left_child,
"<+": self._imm_right_parent,
"<-": self._imm_left_parent,
"<++": self._right_parent, "<++": self._right_parent,
"<--": self._left_parent, "<--": self._left_parent,
} }
@ -427,12 +431,34 @@ cdef class DependencyMatcher:
def _left_sib(self, doc, node): def _left_sib(self, doc, node):
return [doc[child.i] for child in doc[node].head.children if child.i < node] return [doc[child.i] for child in doc[node].head.children if child.i < node]
def _imm_right_child(self, doc, node):
for child in doc[node].children:
if child.i == node + 1:
return [doc[child.i]]
return []
def _imm_left_child(self, doc, node):
for child in doc[node].children:
if child.i == node - 1:
return [doc[child.i]]
return []
def _right_child(self, doc, node): def _right_child(self, doc, node):
return [doc[child.i] for child in doc[node].children if child.i > node] return [doc[child.i] for child in doc[node].children if child.i > node]
def _left_child(self, doc, node): def _left_child(self, doc, node):
return [doc[child.i] for child in doc[node].children if child.i < node] return [doc[child.i] for child in doc[node].children if child.i < node]
def _imm_right_parent(self, doc, node):
if doc[node].head.i == node + 1:
return [doc[node].head]
return []
def _imm_left_parent(self, doc, node):
if doc[node].head.i == node - 1:
return [doc[node].head]
return []
def _right_parent(self, doc, node): def _right_parent(self, doc, node):
if doc[node].head.i > node: if doc[node].head.i > node:
return [doc[node].head] return [doc[node].head]

15
spacy/matcher/matcher.pyx
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@ -829,6 +829,11 @@ def _get_attr_values(spec, string_store):
return attr_values return attr_values
def _predicate_cache_key(attr, predicate, value, *, regex=False, fuzzy=None):
# tuple order affects performance
return (attr, regex, fuzzy, predicate, srsly.json_dumps(value, sort_keys=True))
# These predicate helper classes are used to match the REGEX, IN, >= etc # These predicate helper classes are used to match the REGEX, IN, >= etc
# extensions to the matcher introduced in #3173. # extensions to the matcher introduced in #3173.
@ -848,7 +853,7 @@ class _FuzzyPredicate:
fuzz = self.predicate[len("FUZZY"):] # number after prefix fuzz = self.predicate[len("FUZZY"):] # number after prefix
self.fuzzy = int(fuzz) if fuzz else -1 self.fuzzy = int(fuzz) if fuzz else -1
self.fuzzy_compare = fuzzy_compare self.fuzzy_compare = fuzzy_compare
self.key = (self.attr, self.fuzzy, self.predicate, srsly.json_dumps(value, sort_keys=True)) self.key = _predicate_cache_key(self.attr, self.predicate, value, fuzzy=self.fuzzy)
def __call__(self, Token token): def __call__(self, Token token):
if self.is_extension: if self.is_extension:
@ -870,7 +875,7 @@ class _RegexPredicate:
self.value = re.compile(value) self.value = re.compile(value)
self.predicate = predicate self.predicate = predicate
self.is_extension = is_extension self.is_extension = is_extension
self.key = (self.attr, self.predicate, srsly.json_dumps(value, sort_keys=True)) self.key = _predicate_cache_key(self.attr, self.predicate, value)
if self.predicate not in self.operators: if self.predicate not in self.operators:
raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate)) raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate))
@ -906,7 +911,7 @@ class _SetPredicate:
self.value = set(get_string_id(v) for v in value) self.value = set(get_string_id(v) for v in value)
self.predicate = predicate self.predicate = predicate
self.is_extension = is_extension self.is_extension = is_extension
self.key = (self.attr, self.regex, self.fuzzy, self.predicate, srsly.json_dumps(value, sort_keys=True)) self.key = _predicate_cache_key(self.attr, self.predicate, value, regex=self.regex, fuzzy=self.fuzzy)
if self.predicate not in self.operators: if self.predicate not in self.operators:
raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate)) raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate))
@ -978,7 +983,7 @@ class _ComparisonPredicate:
self.value = value self.value = value
self.predicate = predicate self.predicate = predicate
self.is_extension = is_extension self.is_extension = is_extension
self.key = (self.attr, self.predicate, srsly.json_dumps(value, sort_keys=True)) self.key = _predicate_cache_key(self.attr, self.predicate, value)
if self.predicate not in self.operators: if self.predicate not in self.operators:
raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate)) raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate))
@ -1093,7 +1098,7 @@ def _get_extension_extra_predicates(spec, extra_predicates, predicate_types,
if isinstance(value, dict): if isinstance(value, dict):
for type_, cls in predicate_types.items(): for type_, cls in predicate_types.items():
if type_ in value: if type_ in value:
key = (attr, type_, srsly.json_dumps(value[type_], sort_keys=True)) key = _predicate_cache_key(attr, type_, value[type_])
if key in seen_predicates: if key in seen_predicates:
output.append(seen_predicates[key]) output.append(seen_predicates[key])
else: else:

8
spacy/ml/models/entity_linker.py
View File

@ -89,6 +89,14 @@ def load_kb(
return kb_from_file return kb_from_file
@registry.misc("spacy.EmptyKB.v2")
def empty_kb_for_config() -> Callable[[Vocab, int], KnowledgeBase]:
def empty_kb_factory(vocab: Vocab, entity_vector_length: int):
return InMemoryLookupKB(vocab=vocab, entity_vector_length=entity_vector_length)
return empty_kb_factory
@registry.misc("spacy.EmptyKB.v1") @registry.misc("spacy.EmptyKB.v1")
def empty_kb( def empty_kb(
entity_vector_length: int, entity_vector_length: int,

14
spacy/pipeline/entity_linker.py
View File

@ -58,6 +58,7 @@ DEFAULT_NEL_MODEL = Config().from_str(default_model_config)["model"]
"get_candidates": {"@misc": "spacy.CandidateGenerator.v1"}, "get_candidates": {"@misc": "spacy.CandidateGenerator.v1"},
"get_candidates_batch": {"@misc": "spacy.CandidateBatchGenerator.v1"}, "get_candidates_batch": {"@misc": "spacy.CandidateBatchGenerator.v1"},
"overwrite": False, "overwrite": False,
"generate_empty_kb": {"@misc": "spacy.EmptyKB.v2"},
"scorer": {"@scorers": "spacy.entity_linker_scorer.v1"}, "scorer": {"@scorers": "spacy.entity_linker_scorer.v1"},
"use_gold_ents": True, "use_gold_ents": True,
"candidates_batch_size": 1, "candidates_batch_size": 1,
@ -84,6 +85,7 @@ def make_entity_linker(
get_candidates_batch: Callable[ get_candidates_batch: Callable[
[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]] [KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]
], ],
generate_empty_kb: Callable[[Vocab, int], KnowledgeBase],
overwrite: bool, overwrite: bool,
scorer: Optional[Callable], scorer: Optional[Callable],
use_gold_ents: bool, use_gold_ents: bool,
@ -106,6 +108,7 @@ def make_entity_linker(
get_candidates_batch ( get_candidates_batch (
Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]], Iterable[Candidate]] Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]], Iterable[Candidate]]
): Function that produces a list of candidates, given a certain knowledge base and several textual mentions. ): Function that produces a list of candidates, given a certain knowledge base and several textual mentions.
generate_empty_kb (Callable[[Vocab, int], KnowledgeBase]): Callable returning empty KnowledgeBase.
scorer (Optional[Callable]): The scoring method. scorer (Optional[Callable]): The scoring method.
use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another
component must provide entity annotations. component must provide entity annotations.
@ -147,6 +150,7 @@ def make_entity_linker(
entity_vector_length=entity_vector_length, entity_vector_length=entity_vector_length,
get_candidates=get_candidates, get_candidates=get_candidates,
get_candidates_batch=get_candidates_batch, get_candidates_batch=get_candidates_batch,
generate_empty_kb=generate_empty_kb,
overwrite=overwrite, overwrite=overwrite,
scorer=scorer, scorer=scorer,
use_gold_ents=use_gold_ents, use_gold_ents=use_gold_ents,
@ -188,6 +192,7 @@ class EntityLinker(TrainablePipe):
get_candidates_batch: Callable[ get_candidates_batch: Callable[
[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]] [KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]
], ],
generate_empty_kb: Callable[[Vocab, int], KnowledgeBase],
overwrite: bool = False, overwrite: bool = False,
scorer: Optional[Callable] = entity_linker_score, scorer: Optional[Callable] = entity_linker_score,
use_gold_ents: bool, use_gold_ents: bool,
@ -212,6 +217,7 @@ class EntityLinker(TrainablePipe):
Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]], Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]],
Iterable[Candidate]] Iterable[Candidate]]
): Function that produces a list of candidates, given a certain knowledge base and several textual mentions. ): Function that produces a list of candidates, given a certain knowledge base and several textual mentions.
generate_empty_kb (Callable[[Vocab, int], KnowledgeBase]): Callable returning empty KnowledgeBase.
overwrite (bool): Whether to overwrite existing non-empty annotations. overwrite (bool): Whether to overwrite existing non-empty annotations.
scorer (Optional[Callable]): The scoring method. Defaults to Scorer.score_links. scorer (Optional[Callable]): The scoring method. Defaults to Scorer.score_links.
use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another
@ -219,6 +225,7 @@ class EntityLinker(TrainablePipe):
candidates_batch_size (int): Size of batches for entity candidate generation. candidates_batch_size (int): Size of batches for entity candidate generation.
threshold (Optional[float]): Confidence threshold for entity predictions. If confidence is below the threshold (Optional[float]): Confidence threshold for entity predictions. If confidence is below the
threshold, prediction is discarded. If None, predictions are not filtered by any threshold. threshold, prediction is discarded. If None, predictions are not filtered by any threshold.
save_activations (bool): save model activations in Doc when annotating.
DOCS: https://spacy.io/api/entitylinker#init DOCS: https://spacy.io/api/entitylinker#init
""" """
@ -235,6 +242,7 @@ class EntityLinker(TrainablePipe):
self.model = model self.model = model
self.name = name self.name = name
self.labels_discard = list(labels_discard) self.labels_discard = list(labels_discard)
# how many neighbour sentences to take into account
self.n_sents = n_sents self.n_sents = n_sents
self.incl_prior = incl_prior self.incl_prior = incl_prior
self.incl_context = incl_context self.incl_context = incl_context
@ -242,9 +250,7 @@ class EntityLinker(TrainablePipe):
self.get_candidates_batch = get_candidates_batch self.get_candidates_batch = get_candidates_batch
self.cfg: Dict[str, Any] = {"overwrite": overwrite} self.cfg: Dict[str, Any] = {"overwrite": overwrite}
self.distance = CosineDistance(normalize=False) self.distance = CosineDistance(normalize=False)
# how many neighbour sentences to take into account self.kb = generate_empty_kb(self.vocab, entity_vector_length)
# create an empty KB by default
self.kb = empty_kb(entity_vector_length)(self.vocab)
self.scorer = scorer self.scorer = scorer
self.use_gold_ents = use_gold_ents self.use_gold_ents = use_gold_ents
self.candidates_batch_size = candidates_batch_size self.candidates_batch_size = candidates_batch_size
@ -266,7 +272,7 @@ class EntityLinker(TrainablePipe):
# Raise an error if the knowledge base is not initialized. # Raise an error if the knowledge base is not initialized.
if self.kb is None: if self.kb is None:
raise ValueError(Errors.E1018.format(name=self.name)) raise ValueError(Errors.E1018.format(name=self.name))
if len(self.kb) == 0: if hasattr(self.kb, "is_empty") and self.kb.is_empty():
raise ValueError(Errors.E139.format(name=self.name)) raise ValueError(Errors.E139.format(name=self.name))
def initialize( def initialize(

7
spacy/tests/lang/sv/test_prefix_suffix_infix.py
View File

@ -32,3 +32,10 @@ def test_tokenizer_splits_comma_infix(sv_tokenizer, text):
def test_tokenizer_splits_ellipsis_infix(sv_tokenizer, text): def test_tokenizer_splits_ellipsis_infix(sv_tokenizer, text):
tokens = sv_tokenizer(text) tokens = sv_tokenizer(text)
assert len(tokens) == 3 assert len(tokens) == 3
@pytest.mark.issue(12311)
@pytest.mark.parametrize("text", ["99:e", "c:a", "EU:s", "Maj:t"])
def test_sv_tokenizer_handles_colon(sv_tokenizer, text):
tokens = sv_tokenizer(text)
assert len(tokens) == 1

16
spacy/tests/matcher/test_dependency_matcher.py
View File

@ -316,16 +316,32 @@ def test_dependency_matcher_precedence_ops(en_vocab, op, num_matches):
("the", "brown", "$--", 0), ("the", "brown", "$--", 0),
("brown", "the", "$--", 1), ("brown", "the", "$--", 1),
("brown", "brown", "$--", 0), ("brown", "brown", "$--", 0),
("over", "jumped", "<+", 0),
("quick", "fox", "<+", 0),
("the", "quick", "<+", 0),
("brown", "fox", "<+", 1),
("quick", "fox", "<++", 1), ("quick", "fox", "<++", 1),
("quick", "over", "<++", 0), ("quick", "over", "<++", 0),
("over", "jumped", "<++", 0), ("over", "jumped", "<++", 0),
("the", "fox", "<++", 2), ("the", "fox", "<++", 2),
("brown", "fox", "<-", 0),
("fox", "over", "<-", 0),
("the", "over", "<-", 0),
("over", "jumped", "<-", 1),
("brown", "fox", "<--", 0), ("brown", "fox", "<--", 0),
("fox", "jumped", "<--", 0), ("fox", "jumped", "<--", 0),
("fox", "over", "<--", 1), ("fox", "over", "<--", 1),
("fox", "brown", ">+", 0),
("over", "fox", ">+", 0),
("over", "the", ">+", 0),
("jumped", "over", ">+", 1),
("jumped", "over", ">++", 1), ("jumped", "over", ">++", 1),
("fox", "lazy", ">++", 0), ("fox", "lazy", ">++", 0),
("over", "the", ">++", 0), ("over", "the", ">++", 0),
("jumped", "over", ">-", 0),
("fox", "quick", ">-", 0),
("brown", "quick", ">-", 0),
("fox", "brown", ">-", 1),
("brown", "fox", ">--", 0), ("brown", "fox", ">--", 0),
("fox", "brown", ">--", 1), ("fox", "brown", ">--", 1),
("jumped", "fox", ">--", 1), ("jumped", "fox", ">--", 1),

3
spacy/tests/pipeline/test_entity_linker.py
View File

@ -353,6 +353,9 @@ def test_kb_default(nlp):
"""Test that the default (empty) KB is loaded upon construction""" """Test that the default (empty) KB is loaded upon construction"""
entity_linker = nlp.add_pipe("entity_linker", config={}) entity_linker = nlp.add_pipe("entity_linker", config={})
assert len(entity_linker.kb) == 0 assert len(entity_linker.kb) == 0
with pytest.raises(ValueError, match="E139"):
# this raises an error because the KB is empty
entity_linker.validate_kb()
assert entity_linker.kb.get_size_entities() == 0 assert entity_linker.kb.get_size_entities() == 0
assert entity_linker.kb.get_size_aliases() == 0 assert entity_linker.kb.get_size_aliases() == 0
# 64 is the default value from pipeline.entity_linker # 64 is the default value from pipeline.entity_linker

71
spacy/tests/serialize/test_serialize_kb.py
View File

@ -1,7 +1,10 @@
from typing import Callable from pathlib import Path
from typing import Callable, Iterable, Any, Dict
from spacy import util import srsly
from spacy.util import ensure_path, registry, load_model_from_config
from spacy import util, Errors
from spacy.util import ensure_path, registry, load_model_from_config, SimpleFrozenList
from spacy.kb.kb_in_memory import InMemoryLookupKB from spacy.kb.kb_in_memory import InMemoryLookupKB
from spacy.vocab import Vocab from spacy.vocab import Vocab
from thinc.api import Config from thinc.api import Config
@ -91,7 +94,10 @@ def test_serialize_subclassed_kb():
[components.entity_linker] [components.entity_linker]
factory = "entity_linker" factory = "entity_linker"
[components.entity_linker.generate_empty_kb]
@misc = "kb_test.CustomEmptyKB.v1"
[initialize] [initialize]
[initialize.components] [initialize.components]
@ -99,7 +105,7 @@ def test_serialize_subclassed_kb():
[initialize.components.entity_linker] [initialize.components.entity_linker]
[initialize.components.entity_linker.kb_loader] [initialize.components.entity_linker.kb_loader]
@misc = "spacy.CustomKB.v1" @misc = "kb_test.CustomKB.v1"
entity_vector_length = 342 entity_vector_length = 342
custom_field = 666 custom_field = 666
""" """
@ -109,10 +115,57 @@ def test_serialize_subclassed_kb():
super().__init__(vocab, entity_vector_length) super().__init__(vocab, entity_vector_length)
self.custom_field = custom_field self.custom_field = custom_field
@registry.misc("spacy.CustomKB.v1") def to_disk(self, path, exclude: Iterable[str] = SimpleFrozenList()):
"""We overwrite InMemoryLookupKB.to_disk() to ensure that self.custom_field is stored as well."""
path = ensure_path(path)
if not path.exists():
path.mkdir(parents=True)
if not path.is_dir():
raise ValueError(Errors.E928.format(loc=path))
def serialize_custom_fields(file_path: Path) -> None:
srsly.write_json(file_path, {"custom_field": self.custom_field})
serialize = {
"contents": lambda p: self.write_contents(p),
"strings.json": lambda p: self.vocab.strings.to_disk(p),
"custom_fields": lambda p: serialize_custom_fields(p),
}
util.to_disk(path, serialize, exclude)
def from_disk(self, path, exclude: Iterable[str] = SimpleFrozenList()):
"""We overwrite InMemoryLookupKB.from_disk() to ensure that self.custom_field is loaded as well."""
path = ensure_path(path)
if not path.exists():
raise ValueError(Errors.E929.format(loc=path))
if not path.is_dir():
raise ValueError(Errors.E928.format(loc=path))
def deserialize_custom_fields(file_path: Path) -> None:
self.custom_field = srsly.read_json(file_path)["custom_field"]
deserialize: Dict[str, Callable[[Any], Any]] = {
"contents": lambda p: self.read_contents(p),
"strings.json": lambda p: self.vocab.strings.from_disk(p),
"custom_fields": lambda p: deserialize_custom_fields(p),
}
util.from_disk(path, deserialize, exclude)
@registry.misc("kb_test.CustomEmptyKB.v1")
def empty_custom_kb() -> Callable[[Vocab, int], SubInMemoryLookupKB]:
def empty_kb_factory(vocab: Vocab, entity_vector_length: int):
return SubInMemoryLookupKB(
vocab=vocab,
entity_vector_length=entity_vector_length,
custom_field=0,
)
return empty_kb_factory
@registry.misc("kb_test.CustomKB.v1")
def custom_kb( def custom_kb(
entity_vector_length: int, custom_field: int entity_vector_length: int, custom_field: int
) -> Callable[[Vocab], InMemoryLookupKB]: ) -> Callable[[Vocab], SubInMemoryLookupKB]:
def custom_kb_factory(vocab): def custom_kb_factory(vocab):
kb = SubInMemoryLookupKB( kb = SubInMemoryLookupKB(
vocab=vocab, vocab=vocab,
@ -139,6 +192,6 @@ def test_serialize_subclassed_kb():
nlp2 = util.load_model_from_path(tmp_dir) nlp2 = util.load_model_from_path(tmp_dir)
entity_linker2 = nlp2.get_pipe("entity_linker") entity_linker2 = nlp2.get_pipe("entity_linker")
# After IO, the KB is the standard one # After IO, the KB is the standard one
assert type(entity_linker2.kb) == InMemoryLookupKB assert type(entity_linker2.kb) == SubInMemoryLookupKB
assert entity_linker2.kb.entity_vector_length == 342 assert entity_linker2.kb.entity_vector_length == 342
assert not hasattr(entity_linker2.kb, "custom_field") assert entity_linker2.kb.custom_field == 666

137
spacy/tests/test_cli_app.py
View File

@ -1,5 +1,7 @@
import os import os
from pathlib import Path from pathlib import Path
import pytest
import srsly
from typer.testing import CliRunner from typer.testing import CliRunner
from spacy.tokens import DocBin, Doc from spacy.tokens import DocBin, Doc
@ -89,3 +91,138 @@ def test_debug_data_trainable_lemmatizer_cli(en_vocab):
# Instead of checking specific wording of the output, which may change, # Instead of checking specific wording of the output, which may change,
# we'll check that this section of the debug output is present. # we'll check that this section of the debug output is present.
assert "= Trainable Lemmatizer =" in result_debug_data.stdout assert "= Trainable Lemmatizer =" in result_debug_data.stdout
# project tests
SAMPLE_PROJECT = {
"title": "Sample project",
"description": "This is a project for testing",
"assets": [
{
"dest": "assets/spacy-readme.md",
"url": "https://github.com/explosion/spaCy/raw/dec81508d28b47f09a06203c472b37f00db6c869/README.md",
"checksum": "411b2c89ccf34288fae8ed126bf652f7",
},
{
"dest": "assets/citation.cff",
"url": "https://github.com/explosion/spaCy/raw/master/CITATION.cff",
"checksum": "c996bfd80202d480eb2e592369714e5e",
"extra": True,
},
],
"commands": [
{
"name": "ok",
"help": "print ok",
"script": ["python -c \"print('okokok')\""],
},
{
"name": "create",
"help": "make a file",
"script": ["touch abc.txt"],
"outputs": ["abc.txt"],
},
{
"name": "clean",
"help": "remove test file",
"script": ["rm abc.txt"],
},
],
}
SAMPLE_PROJECT_TEXT = srsly.yaml_dumps(SAMPLE_PROJECT)
@pytest.fixture
def project_dir():
with make_tempdir() as pdir:
(pdir / "project.yml").write_text(SAMPLE_PROJECT_TEXT)
yield pdir
def test_project_document(project_dir):
readme_path = project_dir / "README.md"
assert not readme_path.exists(), "README already exists"
result = CliRunner().invoke(
app, ["project", "document", str(project_dir), "-o", str(readme_path)]
)
assert result.exit_code == 0
assert readme_path.is_file()
text = readme_path.read_text("utf-8")
assert SAMPLE_PROJECT["description"] in text
def test_project_assets(project_dir):
asset_dir = project_dir / "assets"
assert not asset_dir.exists(), "Assets dir is already present"
result = CliRunner().invoke(app, ["project", "assets", str(project_dir)])
assert result.exit_code == 0
assert (asset_dir / "spacy-readme.md").is_file(), "Assets not downloaded"
# check that extras work
result = CliRunner().invoke(app, ["project", "assets", "--extra", str(project_dir)])
assert result.exit_code == 0
assert (asset_dir / "citation.cff").is_file(), "Extras not downloaded"
def test_project_run(project_dir):
# make sure dry run works
test_file = project_dir / "abc.txt"
result = CliRunner().invoke(
app, ["project", "run", "--dry", "create", str(project_dir)]
)
assert result.exit_code == 0
assert not test_file.is_file()
result = CliRunner().invoke(app, ["project", "run", "create", str(project_dir)])
assert result.exit_code == 0
assert test_file.is_file()
result = CliRunner().invoke(app, ["project", "run", "ok", str(project_dir)])
assert result.exit_code == 0
assert "okokok" in result.stdout
@pytest.mark.parametrize(
"options",
[
"",
# "--sparse",
"--branch v3",
"--repo https://github.com/explosion/projects --branch v3",
],
)
def test_project_clone(options):
with make_tempdir() as workspace:
out = workspace / "project"
target = "benchmarks/ner_conll03"
if not options:
options = []
else:
options = options.split()
result = CliRunner().invoke(
app, ["project", "clone", target, *options, str(out)]
)
assert result.exit_code == 0
assert (out / "README.md").is_file()
def test_project_push_pull(project_dir):
proj = dict(SAMPLE_PROJECT)
remote = "xyz"
with make_tempdir() as remote_dir:
proj["remotes"] = {remote: str(remote_dir)}
proj_text = srsly.yaml_dumps(proj)
(project_dir / "project.yml").write_text(proj_text)
test_file = project_dir / "abc.txt"
result = CliRunner().invoke(app, ["project", "run", "create", str(project_dir)])
assert result.exit_code == 0
assert test_file.is_file()
result = CliRunner().invoke(app, ["project", "push", remote, str(project_dir)])
assert result.exit_code == 0
result = CliRunner().invoke(app, ["project", "run", "clean", str(project_dir)])
assert result.exit_code == 0
assert not test_file.exists()
result = CliRunner().invoke(app, ["project", "pull", remote, str(project_dir)])
assert result.exit_code == 0
assert test_file.is_file()

2
spacy/tests/test_language.py
View File

@ -98,7 +98,7 @@ def assert_sents_error(doc):
def warn_error(proc_name, proc, docs, e): def warn_error(proc_name, proc, docs, e):
logger = logging.getLogger("spacy") logger = logging.getLogger("spacy")
logger.warning(f"Trouble with component {proc_name}.") logger.warning("Trouble with component %s.", proc_name)
@pytest.fixture @pytest.fixture

4
spacy/training/callbacks.py
View File

@ -11,7 +11,7 @@ def create_copy_from_base_model(
) -> Callable[[Language], Language]: ) -> Callable[[Language], Language]:
def copy_from_base_model(nlp): def copy_from_base_model(nlp):
if tokenizer: if tokenizer:
logger.info(f"Copying tokenizer from: {tokenizer}") logger.info("Copying tokenizer from: %s", tokenizer)
base_nlp = load_model(tokenizer) base_nlp = load_model(tokenizer)
if nlp.config["nlp"]["tokenizer"] == base_nlp.config["nlp"]["tokenizer"]: if nlp.config["nlp"]["tokenizer"] == base_nlp.config["nlp"]["tokenizer"]:
nlp.tokenizer.from_bytes(base_nlp.tokenizer.to_bytes(exclude=["vocab"])) nlp.tokenizer.from_bytes(base_nlp.tokenizer.to_bytes(exclude=["vocab"]))
@ -23,7 +23,7 @@ def create_copy_from_base_model(
) )
) )
if vocab: if vocab:
logger.info(f"Copying vocab from: {vocab}") logger.info("Copying vocab from: %s", vocab)
# only reload if the vocab is from a different model # only reload if the vocab is from a different model
if tokenizer != vocab: if tokenizer != vocab:
base_nlp = load_model(vocab) base_nlp = load_model(vocab)

2
spacy/training/corpus.py
View File

@ -29,7 +29,7 @@ def create_docbin_reader(
) -> Callable[["Language"], Iterable[Example]]: ) -> Callable[["Language"], Iterable[Example]]:
if path is None: if path is None:
raise ValueError(Errors.E913) raise ValueError(Errors.E913)
util.logger.debug(f"Loading corpus from path: {path}") util.logger.debug("Loading corpus from path: %s", path)
return Corpus( return Corpus(
path, path,
gold_preproc=gold_preproc, gold_preproc=gold_preproc,

25
spacy/training/initialize.py
View File

@ -62,10 +62,10 @@ def init_nlp(config: Config, *, use_gpu: int = -1) -> "Language":
frozen_components = T["frozen_components"] frozen_components = T["frozen_components"]
# Sourced components that require resume_training # Sourced components that require resume_training
resume_components = [p for p in sourced if p not in frozen_components] resume_components = [p for p in sourced if p not in frozen_components]
logger.info(f"Pipeline: {nlp.pipe_names}") logger.info("Pipeline: %s", nlp.pipe_names)
if resume_components: if resume_components:
with nlp.select_pipes(enable=resume_components): with nlp.select_pipes(enable=resume_components):
logger.info(f"Resuming training for: {resume_components}") logger.info("Resuming training for: %s", resume_components)
nlp.resume_training(sgd=optimizer) nlp.resume_training(sgd=optimizer)
# Make sure that listeners are defined before initializing further # Make sure that listeners are defined before initializing further
nlp._link_components() nlp._link_components()
@ -73,16 +73,17 @@ def init_nlp(config: Config, *, use_gpu: int = -1) -> "Language":
if T["max_epochs"] == -1: if T["max_epochs"] == -1:
sample_size = 100 sample_size = 100
logger.debug( logger.debug(
f"Due to streamed train corpus, using only first {sample_size} " "Due to streamed train corpus, using only first %s examples for initialization. "
f"examples for initialization. If necessary, provide all labels " "If necessary, provide all labels in [initialize]. "
f"in [initialize]. More info: https://spacy.io/api/cli#init_labels" "More info: https://spacy.io/api/cli#init_labels",
sample_size,
) )
nlp.initialize( nlp.initialize(
lambda: islice(train_corpus(nlp), sample_size), sgd=optimizer lambda: islice(train_corpus(nlp), sample_size), sgd=optimizer
) )
else: else:
nlp.initialize(lambda: train_corpus(nlp), sgd=optimizer) nlp.initialize(lambda: train_corpus(nlp), sgd=optimizer)
logger.info(f"Initialized pipeline components: {nlp.pipe_names}") logger.info("Initialized pipeline components: %s", nlp.pipe_names)
# Detect components with listeners that are not frozen consistently # Detect components with listeners that are not frozen consistently
for name, proc in nlp.pipeline: for name, proc in nlp.pipeline:
for listener in getattr( for listener in getattr(
@ -109,7 +110,7 @@ def init_vocab(
) -> None: ) -> None:
if lookups: if lookups:
nlp.vocab.lookups = lookups nlp.vocab.lookups = lookups
logger.info(f"Added vocab lookups: {', '.join(lookups.tables)}") logger.info("Added vocab lookups: %s", ", ".join(lookups.tables))
data_path = ensure_path(data) data_path = ensure_path(data)
if data_path is not None: if data_path is not None:
lex_attrs = srsly.read_jsonl(data_path) lex_attrs = srsly.read_jsonl(data_path)
@ -125,11 +126,11 @@ def init_vocab(
else: else:
oov_prob = DEFAULT_OOV_PROB oov_prob = DEFAULT_OOV_PROB
nlp.vocab.cfg.update({"oov_prob": oov_prob}) nlp.vocab.cfg.update({"oov_prob": oov_prob})
logger.info(f"Added {len(nlp.vocab)} lexical entries to the vocab") logger.info("Added %d lexical entries to the vocab", len(nlp.vocab))
logger.info("Created vocabulary") logger.info("Created vocabulary")
if vectors is not None: if vectors is not None:
load_vectors_into_model(nlp, vectors) load_vectors_into_model(nlp, vectors)
logger.info(f"Added vectors: {vectors}") logger.info("Added vectors: %s", vectors)
# warn if source model vectors are not identical # warn if source model vectors are not identical
sourced_vectors_hashes = nlp.meta.pop("_sourced_vectors_hashes", {}) sourced_vectors_hashes = nlp.meta.pop("_sourced_vectors_hashes", {})
vectors_hash = hash(nlp.vocab.vectors.to_bytes(exclude=["strings"])) vectors_hash = hash(nlp.vocab.vectors.to_bytes(exclude=["strings"]))
@ -191,7 +192,7 @@ def init_tok2vec(
if weights_data is not None: if weights_data is not None:
layer = get_tok2vec_ref(nlp, P) layer = get_tok2vec_ref(nlp, P)
layer.from_bytes(weights_data) layer.from_bytes(weights_data)
logger.info(f"Loaded pretrained weights from {init_tok2vec}") logger.info("Loaded pretrained weights from %s", init_tok2vec)
return True return True
return False return False
@ -215,13 +216,13 @@ def convert_vectors(
nlp.vocab.deduplicate_vectors() nlp.vocab.deduplicate_vectors()
else: else:
if vectors_loc: if vectors_loc:
logger.info(f"Reading vectors from {vectors_loc}") logger.info("Reading vectors from %s", vectors_loc)
vectors_data, vector_keys, floret_settings = read_vectors( vectors_data, vector_keys, floret_settings = read_vectors(
vectors_loc, vectors_loc,
truncate, truncate,
mode=mode, mode=mode,
) )
logger.info(f"Loaded vectors from {vectors_loc}") logger.info("Loaded vectors from %s", vectors_loc)
else: else:
vectors_data, vector_keys = (None, None) vectors_data, vector_keys = (None, None)
if vector_keys is not None and mode != VectorsMode.floret: if vector_keys is not None and mode != VectorsMode.floret:

2
spacy/training/loop.py
View File

@ -371,6 +371,6 @@ def clean_output_dir(path: Optional[Path]) -> None:
if subdir.exists(): if subdir.exists():
try: try:
shutil.rmtree(str(subdir)) shutil.rmtree(str(subdir))
logger.debug(f"Removed existing output directory: {subdir}") logger.debug("Removed existing output directory: %s", subdir)
except Exception as e: except Exception as e:
raise IOError(Errors.E901.format(path=path)) from e raise IOError(Errors.E901.format(path=path)) from e

30
spacy/util.py
View File

@ -33,6 +33,7 @@ import inspect
import pkgutil import pkgutil
import logging import logging
import socket import socket
import stat
try: try:
import cupy.random import cupy.random
@ -55,7 +56,7 @@ if TYPE_CHECKING:
# fmt: off # fmt: off
OOV_RANK = numpy.iinfo(numpy.uint64).max OOV_RANK = numpy.iinfo(numpy.uint64).max
DEFAULT_OOV_PROB = -20 DEFAULT_OOV_PROB = -20
LEXEME_NORM_LANGS = ["cs", "da", "de", "el", "en", "id", "lb", "mk", "pt", "ru", "sr", "ta", "th"] LEXEME_NORM_LANGS = ["cs", "da", "de", "el", "en", "grc", "id", "lb", "mk", "pt", "ru", "sr", "ta", "th"]
# Default order of sections in the config file. Not all sections needs to exist, # Default order of sections in the config file. Not all sections needs to exist,
# and additional sections are added at the end, in alphabetical order. # and additional sections are added at the end, in alphabetical order.
@ -139,8 +140,17 @@ class registry(thinc.registry):
return func return func
@classmethod @classmethod
def find(cls, registry_name: str, func_name: str) -> Callable: def find(
"""Get info about a registered function from the registry.""" cls, registry_name: str, func_name: str
) -> Dict[str, Optional[Union[str, int]]]:
"""Find information about a registered function, including the
module and path to the file it's defined in, the line number and the
docstring, if available.
registry_name (str): Name of the catalogue registry.
func_name (str): Name of the registered function.
RETURNS (Dict[str, Optional[Union[str, int]]]): The function info.
"""
# We're overwriting this classmethod so we're able to provide more # We're overwriting this classmethod so we're able to provide more
# specific error messages and implement a fallback to spacy-legacy. # specific error messages and implement a fallback to spacy-legacy.
if not hasattr(cls, registry_name): if not hasattr(cls, registry_name):
@ -1028,11 +1038,19 @@ def make_tempdir() -> Generator[Path, None, None]:
YIELDS (Path): The path of the temp directory. YIELDS (Path): The path of the temp directory.
""" """
d = Path(tempfile.mkdtemp())
yield d
# On Windows, git clones use read-only files, which cause permission errors
# when being deleted. This forcibly fixes permissions.
def force_remove(rmfunc, path, ex):
os.chmod(path, stat.S_IWRITE)
rmfunc(path)
try: try:
with tempfile.TemporaryDirectory() as td: shutil.rmtree(str(d), onerror=force_remove)
yield Path(td)
except PermissionError as e: except PermissionError as e:
warnings.warn(Warnings.W091.format(dir=td, msg=e)) warnings.warn(Warnings.W091.format(dir=d, msg=e))
def is_cwd(path: Union[Path, str]) -> bool: def is_cwd(path: Union[Path, str]) -> bool:

19
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@ -897,15 +897,21 @@ The `EntityLinker` model architecture is a Thinc `Model` with a
| `nO` | Output dimension, determined by the length of the vectors encoding each entity in the KB. If the `nO` dimension is not set, the entity linking component will set it when `initialize` is called. ~~Optional[int]~~ | | `nO` | Output dimension, determined by the length of the vectors encoding each entity in the KB. If the `nO` dimension is not set, the entity linking component will set it when `initialize` is called. ~~Optional[int]~~ |
| **CREATES** | The model using the architecture. ~~Model[List[Doc], Floats2d]~~ | | **CREATES** | The model using the architecture. ~~Model[List[Doc], Floats2d]~~ |
### spacy.EmptyKB.v1 {id="EmptyKB"} ### spacy.EmptyKB.v1 {id="EmptyKB.v1"}
A function that creates an empty `KnowledgeBase` from a [`Vocab`](/api/vocab) A function that creates an empty `KnowledgeBase` from a [`Vocab`](/api/vocab)
instance. This is the default when a new entity linker component is created. instance.
| Name | Description | | Name | Description |
| ---------------------- | ----------------------------------------------------------------------------------- | | ---------------------- | ----------------------------------------------------------------------------------- |
| `entity_vector_length` | The length of the vectors encoding each entity in the KB. Defaults to `64`. ~~int~~ | | `entity_vector_length` | The length of the vectors encoding each entity in the KB. Defaults to `64`. ~~int~~ |
### spacy.EmptyKB.v2 {id="EmptyKB"}
A function that creates an empty `KnowledgeBase` from a [`Vocab`](/api/vocab)
instance. This is the default when a new entity linker component is created. It
returns a `Callable[[Vocab, int], InMemoryLookupKB]`.
### spacy.KBFromFile.v1 {id="KBFromFile"} ### spacy.KBFromFile.v1 {id="KBFromFile"}
A function that reads an existing `KnowledgeBase` from file. A function that reads an existing `KnowledgeBase` from file.
@ -922,6 +928,15 @@ plausible [`Candidate`](/api/kb/#candidate) objects. The default
`CandidateGenerator` uses the text of a mention to find its potential aliases in `CandidateGenerator` uses the text of a mention to find its potential aliases in
the `KnowledgeBase`. Note that this function is case-dependent. the `KnowledgeBase`. Note that this function is case-dependent.
### spacy.CandidateBatchGenerator.v1 {id="CandidateBatchGenerator"}
A function that takes as input a [`KnowledgeBase`](/api/kb) and an `Iterable` of
[`Span`](/api/span) objects denoting named entities, and returns a list of
plausible [`Candidate`](/api/kb/#candidate) objects per specified
[`Span`](/api/span). The default `CandidateBatchGenerator` uses the text of a
mention to find its potential aliases in the `KnowledgeBase`. Note that this
function is case-dependent.
## Coreference {id="coref-architectures",tag="experimental"} ## Coreference {id="coref-architectures",tag="experimental"}
A [`CoreferenceResolver`](/api/coref) component identifies tokens that refer to A [`CoreferenceResolver`](/api/coref) component identifies tokens that refer to

2
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@ -1491,7 +1491,7 @@ $ python -m spacy project push [remote] [project_dir]
### project pull {id="project-pull",tag="command"} ### project pull {id="project-pull",tag="command"}
Download all files or directories listed as `outputs` for commands, unless they Download all files or directories listed as `outputs` for commands, unless they
are not already present locally. When searching for files in the remote, `pull` are already present locally. When searching for files in the remote, `pull`
won't just look at the output path, but will also consider the **command won't just look at the output path, but will also consider the **command
string** and the **hashes of the dependencies**. For instance, let's say you've string** and the **hashes of the dependencies**. For instance, let's say you've
previously pushed a checkpoint to the remote, but now you've changed some previously pushed a checkpoint to the remote, but now you've changed some

40
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@ -68,24 +68,28 @@ The following operators are supported by the `DependencyMatcher`, most of which
come directly from come directly from
[Semgrex](https://nlp.stanford.edu/nlp/javadoc/javanlp/edu/stanford/nlp/semgraph/semgrex/SemgrexPattern.html): [Semgrex](https://nlp.stanford.edu/nlp/javadoc/javanlp/edu/stanford/nlp/semgraph/semgrex/SemgrexPattern.html):
| Symbol | Description | | Symbol | Description |
| --------- | -------------------------------------------------------------------------------------------------------------------- | | --------------------------------------- | -------------------------------------------------------------------------------------------------------------------- |
| `A < B` | `A` is the immediate dependent of `B`. | | `A < B` | `A` is the immediate dependent of `B`. |
| `A > B` | `A` is the immediate head of `B`. | | `A > B` | `A` is the immediate head of `B`. |
| `A << B` | `A` is the dependent in a chain to `B` following dep &rarr; head paths. | | `A << B` | `A` is the dependent in a chain to `B` following dep &rarr; head paths. |
| `A >> B` | `A` is the head in a chain to `B` following head &rarr; dep paths. | | `A >> B` | `A` is the head in a chain to `B` following head &rarr; dep paths. |
| `A . B` | `A` immediately precedes `B`, i.e. `A.i == B.i - 1`, and both are within the same dependency tree. | | `A . B` | `A` immediately precedes `B`, i.e. `A.i == B.i - 1`, and both are within the same dependency tree. |
| `A .* B` | `A` precedes `B`, i.e. `A.i < B.i`, and both are within the same dependency tree _(not in Semgrex)_. | | `A .* B` | `A` precedes `B`, i.e. `A.i < B.i`, and both are within the same dependency tree _(not in Semgrex)_. |
| `A ; B` | `A` immediately follows `B`, i.e. `A.i == B.i + 1`, and both are within the same dependency tree _(not in Semgrex)_. | | `A ; B` | `A` immediately follows `B`, i.e. `A.i == B.i + 1`, and both are within the same dependency tree _(not in Semgrex)_. |
| `A ;* B` | `A` follows `B`, i.e. `A.i > B.i`, and both are within the same dependency tree _(not in Semgrex)_. | | `A ;* B` | `A` follows `B`, i.e. `A.i > B.i`, and both are within the same dependency tree _(not in Semgrex)_. |
| `A $+ B` | `B` is a right immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i - 1`. | | `A $+ B` | `B` is a right immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i - 1`. |
| `A $- B` | `B` is a left immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i + 1`. | | `A $- B` | `B` is a left immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i + 1`. |
| `A $++ B` | `B` is a right sibling of `A`, i.e. `A` and `B` have the same parent and `A.i < B.i`. | | `A $++ B` | `B` is a right sibling of `A`, i.e. `A` and `B` have the same parent and `A.i < B.i`. |
| `A $-- B` | `B` is a left sibling of `A`, i.e. `A` and `B` have the same parent and `A.i > B.i`. | | `A $-- B` | `B` is a left sibling of `A`, i.e. `A` and `B` have the same parent and `A.i > B.i`. |
| `A >++ B` | `B` is a right child of `A`, i.e. `A` is a parent of `B` and `A.i < B.i` _(not in Semgrex)_. | | `A >+ B` <Tag variant="new">3.5.1</Tag> | `B` is a right immediate child of `A`, i.e. `A` is a parent of `B` and `A.i == B.i - 1` _(not in Semgrex)_. |
| `A >-- B` | `B` is a left child of `A`, i.e. `A` is a parent of `B` and `A.i > B.i` _(not in Semgrex)_. | | `A >- B` <Tag variant="new">3.5.1</Tag> | `B` is a left immediate child of `A`, i.e. `A` is a parent of `B` and `A.i == B.i + 1` _(not in Semgrex)_. |
| `A <++ B` | `B` is a right parent of `A`, i.e. `A` is a child of `B` and `A.i < B.i` _(not in Semgrex)_. | | `A >++ B` | `B` is a right child of `A`, i.e. `A` is a parent of `B` and `A.i < B.i` _(not in Semgrex)_. |
| `A <-- B` | `B` is a left parent of `A`, i.e. `A` is a child of `B` and `A.i > B.i` _(not in Semgrex)_. | | `A >-- B` | `B` is a left child of `A`, i.e. `A` is a parent of `B` and `A.i > B.i` _(not in Semgrex)_. |
| `A <+ B` <Tag variant="new">3.5.1</Tag> | `B` is a right immediate parent of `A`, i.e. `A` is a child of `B` and `A.i == B.i - 1` _(not in Semgrex)_. |
| `A <- B` <Tag variant="new">3.5.1</Tag> | `B` is a left immediate parent of `A`, i.e. `A` is a child of `B` and `A.i == B.i + 1` _(not in Semgrex)_. |
| `A <++ B` | `B` is a right parent of `A`, i.e. `A` is a child of `B` and `A.i < B.i` _(not in Semgrex)_. |
| `A <-- B` | `B` is a left parent of `A`, i.e. `A` is a child of `B` and `A.i > B.i` _(not in Semgrex)_. |
## DependencyMatcher.\_\_init\_\_ {id="init",tag="method"} ## DependencyMatcher.\_\_init\_\_ {id="init",tag="method"}

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@ -53,20 +53,22 @@ architectures and their arguments and hyperparameters.
> nlp.add_pipe("entity_linker", config=config) > nlp.add_pipe("entity_linker", config=config)
> ``` > ```
| Setting | Description | | Setting | Description |
| ----------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | --------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `labels_discard` | NER labels that will automatically get a "NIL" prediction. Defaults to `[]`. ~~Iterable[str]~~ | | `labels_discard` | NER labels that will automatically get a "NIL" prediction. Defaults to `[]`. ~~Iterable[str]~~ |
| `n_sents` | The number of neighbouring sentences to take into account. Defaults to 0. ~~int~~ | | `n_sents` | The number of neighbouring sentences to take into account. Defaults to 0. ~~int~~ |
| `incl_prior` | Whether or not to include prior probabilities from the KB in the model. Defaults to `True`. ~~bool~~ | | `incl_prior` | Whether or not to include prior probabilities from the KB in the model. Defaults to `True`. ~~bool~~ |
| `incl_context` | Whether or not to include the local context in the model. Defaults to `True`. ~~bool~~ | | `incl_context` | Whether or not to include the local context in the model. Defaults to `True`. ~~bool~~ |
| `model` | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. Defaults to [EntityLinker](/api/architectures#EntityLinker). ~~Model~~ | | `model` | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. Defaults to [EntityLinker](/api/architectures#EntityLinker). ~~Model~~ |
| `entity_vector_length` | Size of encoding vectors in the KB. Defaults to `64`. ~~int~~ | | `entity_vector_length` | Size of encoding vectors in the KB. Defaults to `64`. ~~int~~ |
| `use_gold_ents` | Whether to copy entities from the gold docs or not. Defaults to `True`. If `False`, entities must be set in the training data or by an annotating component in the pipeline. ~~int~~ | | `use_gold_ents` | Whether to copy entities from the gold docs or not. Defaults to `True`. If `False`, entities must be set in the training data or by an annotating component in the pipeline. ~~int~~ |
| `get_candidates` | Function that generates plausible candidates for a given `Span` object. Defaults to [CandidateGenerator](/api/architectures#CandidateGenerator), a function looking up exact, case-dependent aliases in the KB. ~~Callable[[KnowledgeBase, Span], Iterable[Candidate]]~~ | | `get_candidates` | Function that generates plausible candidates for a given `Span` object. Defaults to [CandidateGenerator](/api/architectures#CandidateGenerator), a function looking up exact, case-dependent aliases in the KB. ~~Callable[[KnowledgeBase, Span], Iterable[Candidate]]~~ |
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `False`. ~~bool~~ | | `get_candidates_batch` <Tag variant="new">3.5</Tag> | Function that generates plausible candidates for a given batch of `Span` objects. Defaults to [CandidateBatchGenerator](/api/architectures#CandidateBatchGenerator), a function looking up exact, case-dependent aliases in the KB. ~~Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]]~~ |
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~ | | `generate_empty_kb` <Tag variant="new">3.6</Tag> | Function that generates an empty `KnowledgeBase` object. Defaults to [`spacy.EmptyKB.v2`](/api/architectures#EmptyKB), which generates an empty [`InMemoryLookupKB`](/api/inmemorylookupkb). ~~Callable[[Vocab, int], KnowledgeBase]~~ |
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~ |
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~ |
| `save_activations` <Tag variant="new">4.0</Tag> | Save activations in `Doc` when annotating. Saved activations are `"ents"` and `"scores"`. ~~Union[bool, list[str]]~~ | | `save_activations` <Tag variant="new">4.0</Tag> | Save activations in `Doc` when annotating. Saved activations are `"ents"` and `"scores"`. ~~Union[bool, list[str]]~~ |
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the treshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ | | `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the treshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
```python ```python
%%GITHUB_SPACY/spacy/pipeline/entity_linker.py %%GITHUB_SPACY/spacy/pipeline/entity_linker.py

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@ -354,22 +354,22 @@ If a setting is not present in the options, the default value will be used.
> displacy.serve(doc, style="dep", options=options) > displacy.serve(doc, style="dep", options=options)
> ``` > ```
| Name | Description | | Name | Description |
| ------------------ | -------------------------------------------------------------------------------------------------------------------------------------------- | | ------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `fine_grained` | Use fine-grained part-of-speech tags (`Token.tag_`) instead of coarse-grained tags (`Token.pos_`). Defaults to `False`. ~~bool~~ | | `fine_grained` | Use fine-grained part-of-speech tags (`Token.tag_`) instead of coarse-grained tags (`Token.pos_`). Defaults to `False`. ~~bool~~ |
| `add_lemma` | Print the lemmas in a separate row below the token texts. Defaults to `False`. ~~bool~~ | | `add_lemma` | Print the lemmas in a separate row below the token texts. Defaults to `False`. ~~bool~~ |
| `collapse_punct` | Attach punctuation to tokens. Can make the parse more readable, as it prevents long arcs to attach punctuation. Defaults to `True`. ~~bool~~ | | `collapse_punct` | Attach punctuation to tokens. Can make the parse more readable, as it prevents long arcs to attach punctuation. Defaults to `True`. ~~bool~~ |
| `collapse_phrases` | Merge noun phrases into one token. Defaults to `False`. ~~bool~~ | | `collapse_phrases` | Merge noun phrases into one token. Defaults to `False`. ~~bool~~ |
| `compact` | "Compact mode" with square arrows that takes up less space. Defaults to `False`. ~~bool~~ | | `compact` | "Compact mode" with square arrows that takes up less space. Defaults to `False`. ~~bool~~ |
| `color` | Text color (HEX, RGB or color names). Defaults to `"#000000"`. ~~str~~ | | `color` | Text color. Can be provided in any CSS legal format as a string e.g.: `"#00ff00"`, `"rgb(0, 255, 0)"`, `"hsl(120, 100%, 50%)"` and `"green"` all correspond to the color green (without transparency). Defaults to `"#000000"`. ~~str~~ |
| `bg` | Background color (HEX, RGB or color names). Defaults to `"#ffffff"`. ~~str~~ | | `bg` | Background color. Can be provided in any CSS legal format as a string e.g.: `"#00ff00"`, `"rgb(0, 255, 0)"`, `"hsl(120, 100%, 50%)"` and `"green"` all correspond to the color green (without transparency). Defaults to `"#ffffff"`. ~~str~~ |
| `font` | Font name or font family for all text. Defaults to `"Arial"`. ~~str~~ | | `font` | Font name or font family for all text. Defaults to `"Arial"`. ~~str~~ |
| `offset_x` | Spacing on left side of the SVG in px. Defaults to `50`. ~~int~~ | | `offset_x` | Spacing on left side of the SVG in px. Defaults to `50`. ~~int~~ |
| `arrow_stroke` | Width of arrow path in px. Defaults to `2`. ~~int~~ | | `arrow_stroke` | Width of arrow path in px. Defaults to `2`. ~~int~~ |
| `arrow_width` | Width of arrow head in px. Defaults to `10` in regular mode and `8` in compact mode. ~~int~~ | | `arrow_width` | Width of arrow head in px. Defaults to `10` in regular mode and `8` in compact mode. ~~int~~ |
| `arrow_spacing` | Spacing between arrows in px to avoid overlaps. Defaults to `20` in regular mode and `12` in compact mode. ~~int~~ | | `arrow_spacing` | Spacing between arrows in px to avoid overlaps. Defaults to `20` in regular mode and `12` in compact mode. ~~int~~ |
| `word_spacing` | Vertical spacing between words and arcs in px. Defaults to `45`. ~~int~~ | | `word_spacing` | Vertical spacing between words and arcs in px. Defaults to `45`. ~~int~~ |
| `distance` | Distance between words in px. Defaults to `175` in regular mode and `150` in compact mode. ~~int~~ | | `distance` | Distance between words in px. Defaults to `175` in regular mode and `150` in compact mode. ~~int~~ |
#### Named Entity Visualizer options {id="displacy_options-ent"} #### Named Entity Visualizer options {id="displacy_options-ent"}

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@ -1100,20 +1100,28 @@ The following operators are supported by the `DependencyMatcher`, most of which
come directly from come directly from
[Semgrex](https://nlp.stanford.edu/nlp/javadoc/javanlp/edu/stanford/nlp/semgraph/semgrex/SemgrexPattern.html): [Semgrex](https://nlp.stanford.edu/nlp/javadoc/javanlp/edu/stanford/nlp/semgraph/semgrex/SemgrexPattern.html):
| Symbol | Description | | Symbol | Description |
| --------- | -------------------------------------------------------------------------------------------------------------------- | | --------------------------------------- | -------------------------------------------------------------------------------------------------------------------- |
| `A < B` | `A` is the immediate dependent of `B`. | | `A < B` | `A` is the immediate dependent of `B`. |
| `A > B` | `A` is the immediate head of `B`. | | `A > B` | `A` is the immediate head of `B`. |
| `A << B` | `A` is the dependent in a chain to `B` following dep &rarr; head paths. | | `A << B` | `A` is the dependent in a chain to `B` following dep &rarr; head paths. |
| `A >> B` | `A` is the head in a chain to `B` following head &rarr; dep paths. | | `A >> B` | `A` is the head in a chain to `B` following head &rarr; dep paths. |
| `A . B` | `A` immediately precedes `B`, i.e. `A.i == B.i - 1`, and both are within the same dependency tree. | | `A . B` | `A` immediately precedes `B`, i.e. `A.i == B.i - 1`, and both are within the same dependency tree. |
| `A .* B` | `A` precedes `B`, i.e. `A.i < B.i`, and both are within the same dependency tree _(not in Semgrex)_. | | `A .* B` | `A` precedes `B`, i.e. `A.i < B.i`, and both are within the same dependency tree _(not in Semgrex)_. |
| `A ; B` | `A` immediately follows `B`, i.e. `A.i == B.i + 1`, and both are within the same dependency tree _(not in Semgrex)_. | | `A ; B` | `A` immediately follows `B`, i.e. `A.i == B.i + 1`, and both are within the same dependency tree _(not in Semgrex)_. |
| `A ;* B` | `A` follows `B`, i.e. `A.i > B.i`, and both are within the same dependency tree _(not in Semgrex)_. | | `A ;* B` | `A` follows `B`, i.e. `A.i > B.i`, and both are within the same dependency tree _(not in Semgrex)_. |
| `A $+ B` | `B` is a right immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i - 1`. | | `A $+ B` | `B` is a right immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i - 1`. |
| `A $- B` | `B` is a left immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i + 1`. | | `A $- B` | `B` is a left immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i + 1`. |
| `A $++ B` | `B` is a right sibling of `A`, i.e. `A` and `B` have the same parent and `A.i < B.i`. | | `A $++ B` | `B` is a right sibling of `A`, i.e. `A` and `B` have the same parent and `A.i < B.i`. |
| `A $-- B` | `B` is a left sibling of `A`, i.e. `A` and `B` have the same parent and `A.i > B.i`. | | `A $-- B` | `B` is a left sibling of `A`, i.e. `A` and `B` have the same parent and `A.i > B.i`. |
| `A >+ B` <Tag variant="new">3.5.1</Tag> | `B` is a right immediate child of `A`, i.e. `A` is a parent of `B` and `A.i == B.i - 1` _(not in Semgrex)_. |
| `A >- B` <Tag variant="new">3.5.1</Tag> | `B` is a left immediate child of `A`, i.e. `A` is a parent of `B` and `A.i == B.i + 1` _(not in Semgrex)_. |
| `A >++ B` | `B` is a right child of `A`, i.e. `A` is a parent of `B` and `A.i < B.i` _(not in Semgrex)_. |
| `A >-- B` | `B` is a left child of `A`, i.e. `A` is a parent of `B` and `A.i > B.i` _(not in Semgrex)_. |
| `A <+ B` <Tag variant="new">3.5.1</Tag> | `B` is a right immediate parent of `A`, i.e. `A` is a child of `B` and `A.i == B.i - 1` _(not in Semgrex)_. |
| `A <- B` <Tag variant="new">3.5.1</Tag> | `B` is a left immediate parent of `A`, i.e. `A` is a child of `B` and `A.i == B.i + 1` _(not in Semgrex)_. |
| `A <++ B` | `B` is a right parent of `A`, i.e. `A` is a child of `B` and `A.i < B.i` _(not in Semgrex)_. |
| `A <-- B` | `B` is a left parent of `A`, i.e. `A` is a child of `B` and `A.i > B.i` _(not in Semgrex)_. |
### Designing dependency matcher patterns {id="dependencymatcher-patterns"} ### Designing dependency matcher patterns {id="dependencymatcher-patterns"}
@ -1445,8 +1453,8 @@ nlp.to_disk("/path/to/pipeline")
The saved pipeline now includes the `"entity_ruler"` in its The saved pipeline now includes the `"entity_ruler"` in its
[`config.cfg`](/api/data-formats#config) and the pipeline directory contains a [`config.cfg`](/api/data-formats#config) and the pipeline directory contains a
file `entityruler.jsonl` with the patterns. When you load the pipeline back in, file `patterns.jsonl` with the patterns. When you load the pipeline back in, all
all pipeline components will be restored and deserialized – including the entity pipeline components will be restored and deserialized – including the entity
ruler. This lets you ship powerful pipeline packages with binary weights _and_ ruler. This lets you ship powerful pipeline packages with binary weights _and_
rules included! rules included!

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</Infobox> </Infobox>
| Argument | Description | | Argument | Description |
| --------- | ----------------------------------------------------------------------------------------- | | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `compact` | "Compact mode" with square arrows that takes up less space. Defaults to `False`. ~~bool~~ | | `compact` | "Compact mode" with square arrows that takes up less space. Defaults to `False`. ~~bool~~ |
| `color` | Text color (HEX, RGB or color names). Defaults to `"#000000"`. ~~str~~ | | `color` | Text color. Can be provided in any CSS legal format as a string e.g.: `"#00ff00"`, `"rgb(0, 255, 0)"`, `"hsl(120, 100%, 50%)"` and `"green"` all correspond to the color green (without transparency). Defaults to `"#000000"`. ~~str~~ |
| `bg` | Background color (HEX, RGB or color names). Defaults to `"#ffffff"`. ~~str~~ | | `bg` | Background color. Can be provided in any CSS legal format as a string e.g.: `"#00ff00"`, `"rgb(0, 255, 0)"`, `"hsl(120, 100%, 50%)"` and `"green"` all correspond to the color green (without transparency). Defaults to `"#ffffff"`. ~~str~~ |
| `font` | Font name or font family for all text. Defaults to `"Arial"`. ~~str~~ | | `font` | Font name or font family for all text. Defaults to `"Arial"`. ~~str~~ |
For a list of all available options, see the For a list of all available options, see the
[`displacy` API documentation](/api/top-level#displacy_options). [`displacy` API documentation](/api/top-level#displacy_options).