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Merge branch 'master' of https://github.com/explosion/spaCy into predict-cli

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This commit is contained in:
kadarakos 2022-08-31 13:00:59 +00:00
commit 4c028b338e
21 changed files with 486 additions and 152 deletions
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1
pyproject.toml
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@ -6,7 +6,6 @@ requires = [
"preshed>=3.0.2,<3.1.0",
"murmurhash>=0.28.0,<1.1.0",
"thinc>=8.1.0,<8.2.0",
"pathy",
"numpy>=1.15.0",
]
build-backend = "setuptools.build_meta"

2
requirements.txt
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@ -1,5 +1,5 @@
# Our libraries
spacy-legacy>=3.0.9,<3.1.0
spacy-legacy>=3.0.10,<3.1.0
spacy-loggers>=1.0.0,<2.0.0
cymem>=2.0.2,<2.1.0
preshed>=3.0.2,<3.1.0

4
setup.cfg
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@ -41,7 +41,7 @@ setup_requires =
thinc>=8.1.0,<8.2.0
install_requires =
# Our libraries
spacy-legacy>=3.0.9,<3.1.0
spacy-legacy>=3.0.10,<3.1.0
spacy-loggers>=1.0.0,<2.0.0
murmurhash>=0.28.0,<1.1.0
cymem>=2.0.2,<2.1.0
@ -50,9 +50,9 @@ install_requires =
wasabi>=0.9.1,<1.1.0
srsly>=2.4.3,<3.0.0
catalogue>=2.0.6,<2.1.0
# Third-party dependencies
typer>=0.3.0,<0.5.0
pathy>=0.3.5
# Third-party dependencies
tqdm>=4.38.0,<5.0.0
numpy>=1.15.0
requests>=2.13.0,<3.0.0

12
spacy/__init__.py
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@ -31,21 +31,21 @@ def load(
name: Union[str, Path],
*,
vocab: Union[Vocab, bool] = True,
disable: Iterable[str] = util.SimpleFrozenList(),
enable: Iterable[str] = util.SimpleFrozenList(),
exclude: Iterable[str] = util.SimpleFrozenList(),
disable: Union[str, Iterable[str]] = util.SimpleFrozenList(),
enable: Union[str, Iterable[str]] = util.SimpleFrozenList(),
exclude: Union[str, Iterable[str]] = util.SimpleFrozenList(),
config: Union[Dict[str, Any], Config] = util.SimpleFrozenDict(),
) -> Language:
"""Load a spaCy model from an installed package or a local path.
name (str): Package name or model path.
vocab (Vocab): A Vocab object. If True, a vocab is created.
disable (Iterable[str]): Names of pipeline components to disable. Disabled
disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
pipes will be loaded but they won't be run unless you explicitly
enable them by calling nlp.enable_pipe.
enable (Iterable[str]): Names of pipeline components to enable. All other
enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
pipes will be disabled (but can be enabled later using nlp.enable_pipe).
exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
components won't be loaded.
config (Dict[str, Any] / Config): Config overrides as nested dict or dict
keyed by section values in dot notation.

18
spacy/lang/la/__init__.py Normal file
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@ -0,0 +1,18 @@
from ...language import Language, BaseDefaults
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
from .stop_words import STOP_WORDS
from .lex_attrs import LEX_ATTRS
class LatinDefaults(BaseDefaults):
tokenizer_exceptions = TOKENIZER_EXCEPTIONS
stop_words = STOP_WORDS
lex_attr_getters = LEX_ATTRS
class Latin(Language):
lang = "la"
Defaults = LatinDefaults
__all__ = ["Latin"]

32
spacy/lang/la/lex_attrs.py Normal file
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@ -0,0 +1,32 @@
from ...attrs import LIKE_NUM
import re
# cf. Goyvaerts/Levithan 2009; case-insensitive, allow 4
roman_numerals_compile = re.compile(r'(?i)^(?=[MDCLXVI])M*(C[MD]|D?C{0,4})(X[CL]|L?X{0,4})(I[XV]|V?I{0,4})$')
_num_words = set(
"""
unus una unum duo duae tres tria quattuor quinque sex septem octo novem decem
""".split()
)
_ordinal_words = set(
"""
primus prima primum secundus secunda secundum tertius tertia tertium
""".split()
)
def like_num(text):
if text.isdigit():
return True
if roman_numerals_compile.match(text):
return True
if text.lower() in _num_words:
return True
if text.lower() in _ordinal_words:
return True
return False
LEX_ATTRS = {LIKE_NUM: like_num}

37
spacy/lang/la/stop_words.py Normal file
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@ -0,0 +1,37 @@
# Corrected Perseus list, cf. https://wiki.digitalclassicist.org/Stopwords_for_Greek_and_Latin
STOP_WORDS = set(
"""
ab ac ad adhuc aliqui aliquis an ante apud at atque aut autem
cum cur
de deinde dum
ego enim ergo es est et etiam etsi ex
fio
haud hic
iam idem igitur ille in infra inter interim ipse is ita
magis modo mox
nam ne nec necque neque nisi non nos
o ob
per possum post pro
quae quam quare qui quia quicumque quidem quilibet quis quisnam quisquam quisque quisquis quo quoniam
sed si sic sive sub sui sum super suus
tam tamen trans tu tum
ubi uel uero
vel vero
""".split()
)

30
spacy/lang/la/tokenizer_exceptions.py Normal file
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@ -0,0 +1,30 @@
from ..tokenizer_exceptions import BASE_EXCEPTIONS
from ...symbols import ORTH
from ...util import update_exc
## TODO: Look into systematically handling u/v
_exc = {
"mecum": [{ORTH: "me"}, {ORTH: "cum"}],
"tecum": [{ORTH: "te"}, {ORTH: "cum"}],
"nobiscum": [{ORTH: "nobis"}, {ORTH: "cum"}],
"vobiscum": [{ORTH: "vobis"}, {ORTH: "cum"}],
"uobiscum": [{ORTH: "uobis"}, {ORTH: "cum"}],
}
for orth in [
'A.', 'Agr.', 'Ap.', 'C.', 'Cn.', 'D.', 'F.', 'K.', 'L.', "M'.", 'M.', 'Mam.', 'N.', 'Oct.',
'Opet.', 'P.', 'Paul.', 'Post.', 'Pro.', 'Q.', 'S.', 'Ser.', 'Sert.', 'Sex.', 'St.', 'Sta.',
'T.', 'Ti.', 'V.', 'Vol.', 'Vop.', 'U.', 'Uol.', 'Uop.',
'Ian.', 'Febr.', 'Mart.', 'Apr.', 'Mai.', 'Iun.', 'Iul.', 'Aug.', 'Sept.', 'Oct.', 'Nov.', 'Nou.',
'Dec.',
'Non.', 'Id.', 'A.D.',
'Coll.', 'Cos.', 'Ord.', 'Pl.', 'S.C.', 'Suff.', 'Trib.',
]:
_exc[orth] = [{ORTH: orth}]
TOKENIZER_EXCEPTIONS = update_exc(BASE_EXCEPTIONS, _exc)

32
spacy/language.py
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@ -1063,7 +1063,7 @@ class Language:
"""
if enable is None and disable is None:
raise ValueError(Errors.E991)
if disable is not None and isinstance(disable, str):
if isinstance(disable, str):
disable = [disable]
if enable is not None:
if isinstance(enable, str):
@ -1698,9 +1698,9 @@ class Language:
config: Union[Dict[str, Any], Config] = {},
*,
vocab: Union[Vocab, bool] = True,
disable: Iterable[str] = SimpleFrozenList(),
enable: Iterable[str] = SimpleFrozenList(),
exclude: Iterable[str] = SimpleFrozenList(),
disable: Union[str, Iterable[str]] = SimpleFrozenList(),
enable: Union[str, Iterable[str]] = SimpleFrozenList(),
exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
meta: Dict[str, Any] = SimpleFrozenDict(),
auto_fill: bool = True,
validate: bool = True,
@ -1711,12 +1711,12 @@ class Language:
config (Dict[str, Any] / Config): The loaded config.
vocab (Vocab): A Vocab object. If True, a vocab is created.
disable (Iterable[str]): Names of pipeline components to disable.
disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable.
Disabled pipes will be loaded but they won't be run unless you
explicitly enable them by calling nlp.enable_pipe.
enable (Iterable[str]): Names of pipeline components to enable. All other
enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
exclude (Iterable[str]): Names of pipeline components to exclude.
exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude.
Excluded components won't be loaded.
meta (Dict[str, Any]): Meta overrides for nlp.meta.
auto_fill (bool): Automatically fill in missing values in config based
@ -1727,6 +1727,12 @@ class Language:
DOCS: https://spacy.io/api/language#from_config
"""
if isinstance(disable, str):
disable = [disable]
if isinstance(enable, str):
enable = [enable]
if isinstance(exclude, str):
exclude = [exclude]
if auto_fill:
config = Config(
cls.default_config, section_order=CONFIG_SECTION_ORDER
@ -2031,25 +2037,29 @@ class Language:
@staticmethod
def _resolve_component_status(
disable: Iterable[str], enable: Iterable[str], pipe_names: Collection[str]
disable: Union[str, Iterable[str]],
enable: Union[str, Iterable[str]],
pipe_names: Iterable[str],
) -> Tuple[str, ...]:
"""Derives whether (1) `disable` and `enable` values are consistent and (2)
resolves those to a single set of disabled components. Raises an error in
case of inconsistency.
disable (Iterable[str]): Names of components or serialization fields to disable.
enable (Iterable[str]): Names of pipeline components to enable.
disable (Union[str, Iterable[str]]): Name(s) of component(s) or serialization fields to disable.
enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable.
pipe_names (Iterable[str]): Names of all pipeline components.
RETURNS (Tuple[str, ...]): Names of components to exclude from pipeline w.r.t.
specified includes and excludes.
"""
if disable is not None and isinstance(disable, str):
if isinstance(disable, str):
disable = [disable]
to_disable = disable
if enable:
if isinstance(enable, str):
enable = [enable]
to_disable = [
pipe_name for pipe_name in pipe_names if pipe_name not in enable
]

5
spacy/tests/conftest.py
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@ -256,6 +256,11 @@ def ko_tokenizer_tokenizer():
return nlp.tokenizer
@pytest.fixture(scope="module")
def la_tokenizer():
return get_lang_class("la")().tokenizer
@pytest.fixture(scope="session")
def lb_tokenizer():
return get_lang_class("lb")().tokenizer

0
spacy/tests/lang/la/__init__.py Normal file
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7
spacy/tests/lang/la/test_exception.py Normal file
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@ -0,0 +1,7 @@
import pytest
def test_la_tokenizer_handles_exc_in_text(la_tokenizer):
text = "scio te omnia facturum, ut nobiscum quam primum sis"
tokens = la_tokenizer(text)
assert len(tokens) == 11
assert tokens[6].text == "nobis"

33
spacy/tests/lang/la/test_text.py Normal file
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@ -0,0 +1,33 @@
import pytest
from spacy.lang.la.lex_attrs import like_num
@pytest.mark.parametrize(
"text,match",
[
("IIII", True),
("VI", True),
("vi", True),
("IV", True),
("iv", True),
("IX", True),
("ix", True),
("MMXXII", True),
("0", True),
("1", True),
("quattuor", True),
("decem", True),
("tertius", True),
("canis", False),
("MMXX11", False),
(",", False),
],
)
def test_lex_attrs_like_number(la_tokenizer, text, match):
tokens = la_tokenizer(text)
assert len(tokens) == 1
assert tokens[0].like_num == match
@pytest.mark.parametrize("word", ["quinque"])
def test_la_lex_attrs_capitals(word):
assert like_num(word)
assert like_num(word.upper())

11
spacy/tests/pipeline/test_pipe_methods.py
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@ -618,6 +618,7 @@ def test_load_disable_enable() -> None:
base_nlp.to_disk(tmp_dir)
to_disable = ["parser", "tagger"]
to_enable = ["tagger", "parser"]
single_str = "tagger"
# Setting only `disable`.
nlp = spacy.load(tmp_dir, disable=to_disable)
@ -632,6 +633,16 @@ def test_load_disable_enable() -> None:
]
)
# Loading with a string representing one component
nlp = spacy.load(tmp_dir, exclude=single_str)
assert single_str not in nlp.component_names
nlp = spacy.load(tmp_dir, disable=single_str)
assert single_str in nlp.component_names
assert single_str not in nlp.pipe_names
assert nlp._disabled == {single_str}
assert nlp.disabled == [single_str]
# Testing consistent enable/disable combination.
nlp = spacy.load(
tmp_dir,

25
spacy/tests/test_misc.py
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@ -10,7 +10,8 @@ from spacy.ml._precomputable_affine import _backprop_precomputable_affine_paddin
from spacy.util import dot_to_object, SimpleFrozenList, import_file
from spacy.util import to_ternary_int
from thinc.api import Config, Optimizer, ConfigValidationError
from thinc.api import set_current_ops
from thinc.api import get_current_ops, set_current_ops, NumpyOps, CupyOps, MPSOps
from thinc.compat import has_cupy_gpu, has_torch_mps_gpu
from spacy.training.batchers import minibatch_by_words
from spacy.lang.en import English
from spacy.lang.nl import Dutch
@ -18,7 +19,6 @@ from spacy.language import DEFAULT_CONFIG_PATH
from spacy.schemas import ConfigSchemaTraining, TokenPattern, TokenPatternSchema
from pydantic import ValidationError
from thinc.api import get_current_ops, NumpyOps, CupyOps
from .util import get_random_doc, make_tempdir
@ -111,26 +111,25 @@ def test_PrecomputableAffine(nO=4, nI=5, nF=3, nP=2):
def test_prefer_gpu():
current_ops = get_current_ops()
try:
import cupy # noqa: F401
prefer_gpu()
if has_cupy_gpu:
assert prefer_gpu()
assert isinstance(get_current_ops(), CupyOps)
except ImportError:
elif has_torch_mps_gpu:
assert prefer_gpu()
assert isinstance(get_current_ops(), MPSOps)
else:
assert not prefer_gpu()
set_current_ops(current_ops)
def test_require_gpu():
current_ops = get_current_ops()
try:
import cupy # noqa: F401
if has_cupy_gpu:
require_gpu()
assert isinstance(get_current_ops(), CupyOps)
except ImportError:
with pytest.raises(ValueError):
require_gpu()
elif has_torch_mps_gpu:
require_gpu()
assert isinstance(get_current_ops(), MPSOps)
set_current_ops(current_ops)

30
spacy/tests/training/test_logger.py Normal file
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@ -0,0 +1,30 @@
import pytest
import spacy
from spacy.training import loggers
@pytest.fixture()
def nlp():
nlp = spacy.blank("en")
nlp.add_pipe("ner")
return nlp
@pytest.fixture()
def info():
return {
"losses": {"ner": 100},
"other_scores": {"ENTS_F": 0.85, "ENTS_P": 0.90, "ENTS_R": 0.80},
"epoch": 100,
"step": 125,
"score": 85,
}
def test_console_logger(nlp, info):
console_logger = loggers.console_logger(
progress_bar=True, console_output=True, output_file=None
)
log_step, finalize = console_logger(nlp)
log_step(info)

102
spacy/training/loggers.py
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@ -1,10 +1,13 @@
from typing import TYPE_CHECKING, Dict, Any, Tuple, Callable, List, Optional, IO
from typing import TYPE_CHECKING, Dict, Any, Tuple, Callable, List, Optional, IO, Union
from wasabi import Printer
from pathlib import Path
import tqdm
import sys
import srsly
from ..util import registry
from ..errors import Errors
from .. import util
if TYPE_CHECKING:
from ..language import Language # noqa: F401
@ -23,13 +26,44 @@ def setup_table(
return final_cols, final_widths, ["r" for _ in final_widths]
@registry.loggers("spacy.ConsoleLogger.v1")
def console_logger(progress_bar: bool = False):
@registry.loggers("spacy.ConsoleLogger.v2")
def console_logger(
progress_bar: bool = False,
console_output: bool = True,
output_file: Optional[Union[str, Path]] = None,
):
"""The ConsoleLogger.v2 prints out training logs in the console and/or saves them to a jsonl file.
progress_bar (bool): Whether the logger should print the progress bar.
console_output (bool): Whether the logger should print the logs on the console.
output_file (Optional[Union[str, Path]]): The file to save the training logs to.
"""
_log_exist = False
if output_file:
output_file = util.ensure_path(output_file) # type: ignore
if output_file.exists(): # type: ignore
_log_exist = True
if not output_file.parents[0].exists(): # type: ignore
output_file.parents[0].mkdir(parents=True) # type: ignore
def setup_printer(
nlp: "Language", stdout: IO = sys.stdout, stderr: IO = sys.stderr
) -> Tuple[Callable[[Optional[Dict[str, Any]]], None], Callable[[], None]]:
write = lambda text: print(text, file=stdout, flush=True)
msg = Printer(no_print=True)
nonlocal output_file
output_stream = None
if _log_exist:
write(
msg.warn(
f"Saving logs is disabled because {output_file} already exists."
)
)
output_file = None
elif output_file:
write(msg.info(f"Saving results to {output_file}"))
output_stream = open(output_file, "w", encoding="utf-8")
# ensure that only trainable components are logged
logged_pipes = [
name
@ -40,13 +74,15 @@ def console_logger(progress_bar: bool = False):
score_weights = nlp.config["training"]["score_weights"]
score_cols = [col for col, value in score_weights.items() if value is not None]
loss_cols = [f"Loss {pipe}" for pipe in logged_pipes]
spacing = 2
table_header, table_widths, table_aligns = setup_table(
cols=["E", "#"] + loss_cols + score_cols + ["Score"],
widths=[3, 6] + [8 for _ in loss_cols] + [6 for _ in score_cols] + [6],
)
write(msg.row(table_header, widths=table_widths, spacing=spacing))
write(msg.row(["-" * width for width in table_widths], spacing=spacing))
if console_output:
spacing = 2
table_header, table_widths, table_aligns = setup_table(
cols=["E", "#"] + loss_cols + score_cols + ["Score"],
widths=[3, 6] + [8 for _ in loss_cols] + [6 for _ in score_cols] + [6],
)
write(msg.row(table_header, widths=table_widths, spacing=spacing))
write(msg.row(["-" * width for width in table_widths], spacing=spacing))
progress = None
def log_step(info: Optional[Dict[str, Any]]) -> None:
@ -57,12 +93,15 @@ def console_logger(progress_bar: bool = False):
if progress is not None:
progress.update(1)
return
losses = [
"{0:.2f}".format(float(info["losses"][pipe_name]))
for pipe_name in logged_pipes
]
losses = []
log_losses = {}
for pipe_name in logged_pipes:
losses.append("{0:.2f}".format(float(info["losses"][pipe_name])))
log_losses[pipe_name] = float(info["losses"][pipe_name])
scores = []
log_scores = {}
for col in score_cols:
score = info["other_scores"].get(col, 0.0)
try:
@ -73,6 +112,7 @@ def console_logger(progress_bar: bool = False):
if col != "speed":
score *= 100
scores.append("{0:.2f}".format(score))
log_scores[str(col)] = score
data = (
[info["epoch"], info["step"]]
@ -80,20 +120,36 @@ def console_logger(progress_bar: bool = False):
+ scores
+ ["{0:.2f}".format(float(info["score"]))]
)
if output_stream:
# Write to log file per log_step
log_data = {
"epoch": info["epoch"],
"step": info["step"],
"losses": log_losses,
"scores": log_scores,
"score": float(info["score"]),
}
output_stream.write(srsly.json_dumps(log_data) + "\n")
if progress is not None:
progress.close()
write(
msg.row(data, widths=table_widths, aligns=table_aligns, spacing=spacing)
)
if progress_bar:
# Set disable=None, so that it disables on non-TTY
progress = tqdm.tqdm(
total=eval_frequency, disable=None, leave=False, file=stderr
if console_output:
write(
msg.row(
data, widths=table_widths, aligns=table_aligns, spacing=spacing
)
)
progress.set_description(f"Epoch {info['epoch']+1}")
if progress_bar:
# Set disable=None, so that it disables on non-TTY
progress = tqdm.tqdm(
total=eval_frequency, disable=None, leave=False, file=stderr
)
progress.set_description(f"Epoch {info['epoch']+1}")
def finalize() -> None:
pass
if output_stream:
output_stream.close()
return log_step, finalize

60
spacy/util.py
View File

@ -398,9 +398,9 @@ def load_model(
name: Union[str, Path],
*,
vocab: Union["Vocab", bool] = True,
disable: Iterable[str] = SimpleFrozenList(),
enable: Iterable[str] = SimpleFrozenList(),
exclude: Iterable[str] = SimpleFrozenList(),
disable: Union[str, Iterable[str]] = SimpleFrozenList(),
enable: Union[str, Iterable[str]] = SimpleFrozenList(),
exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
) -> "Language":
"""Load a model from a package or data path.
@ -408,9 +408,9 @@ def load_model(
name (str): Package name or model path.
vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
a new Vocab object will be created.
disable (Iterable[str]): Names of pipeline components to disable.
enable (Iterable[str]): Names of pipeline components to enable. All others will be disabled.
exclude (Iterable[str]): Names of pipeline components to exclude.
disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable.
enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All others will be disabled.
exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude.
config (Dict[str, Any] / Config): Config overrides as nested dict or dict
keyed by section values in dot notation.
RETURNS (Language): The loaded nlp object.
@ -440,9 +440,9 @@ def load_model_from_package(
name: str,
*,
vocab: Union["Vocab", bool] = True,
disable: Iterable[str] = SimpleFrozenList(),
enable: Iterable[str] = SimpleFrozenList(),
exclude: Iterable[str] = SimpleFrozenList(),
disable: Union[str, Iterable[str]] = SimpleFrozenList(),
enable: Union[str, Iterable[str]] = SimpleFrozenList(),
exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
) -> "Language":
"""Load a model from an installed package.
@ -450,12 +450,12 @@ def load_model_from_package(
name (str): The package name.
vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
a new Vocab object will be created.
disable (Iterable[str]): Names of pipeline components to disable. Disabled
disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
pipes will be loaded but they won't be run unless you explicitly
enable them by calling nlp.enable_pipe.
enable (Iterable[str]): Names of pipeline components to enable. All other
enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
components won't be loaded.
config (Dict[str, Any] / Config): Config overrides as nested dict or dict
keyed by section values in dot notation.
@ -470,9 +470,9 @@ def load_model_from_path(
*,
meta: Optional[Dict[str, Any]] = None,
vocab: Union["Vocab", bool] = True,
disable: Iterable[str] = SimpleFrozenList(),
enable: Iterable[str] = SimpleFrozenList(),
exclude: Iterable[str] = SimpleFrozenList(),
disable: Union[str, Iterable[str]] = SimpleFrozenList(),
enable: Union[str, Iterable[str]] = SimpleFrozenList(),
exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
) -> "Language":
"""Load a model from a data directory path. Creates Language class with
@ -482,12 +482,12 @@ def load_model_from_path(
meta (Dict[str, Any]): Optional model meta.
vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
a new Vocab object will be created.
disable (Iterable[str]): Names of pipeline components to disable. Disabled
disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
pipes will be loaded but they won't be run unless you explicitly
enable them by calling nlp.enable_pipe.
enable (Iterable[str]): Names of pipeline components to enable. All other
enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
components won't be loaded.
config (Dict[str, Any] / Config): Config overrides as nested dict or dict
keyed by section values in dot notation.
@ -516,9 +516,9 @@ def load_model_from_config(
*,
meta: Dict[str, Any] = SimpleFrozenDict(),
vocab: Union["Vocab", bool] = True,
disable: Iterable[str] = SimpleFrozenList(),
enable: Iterable[str] = SimpleFrozenList(),
exclude: Iterable[str] = SimpleFrozenList(),
disable: Union[str, Iterable[str]] = SimpleFrozenList(),
enable: Union[str, Iterable[str]] = SimpleFrozenList(),
exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
auto_fill: bool = False,
validate: bool = True,
) -> "Language":
@ -529,12 +529,12 @@ def load_model_from_config(
meta (Dict[str, Any]): Optional model meta.
vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
a new Vocab object will be created.
disable (Iterable[str]): Names of pipeline components to disable. Disabled
disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
pipes will be loaded but they won't be run unless you explicitly
enable them by calling nlp.enable_pipe.
enable (Iterable[str]): Names of pipeline components to enable. All other
enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
components won't be loaded.
auto_fill (bool): Whether to auto-fill config with missing defaults.
validate (bool): Whether to show config validation errors.
@ -616,9 +616,9 @@ def load_model_from_init_py(
init_file: Union[Path, str],
*,
vocab: Union["Vocab", bool] = True,
disable: Iterable[str] = SimpleFrozenList(),
enable: Iterable[str] = SimpleFrozenList(),
exclude: Iterable[str] = SimpleFrozenList(),
disable: Union[str, Iterable[str]] = SimpleFrozenList(),
enable: Union[str, Iterable[str]] = SimpleFrozenList(),
exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
) -> "Language":
"""Helper function to use in the `load()` method of a model package's
@ -626,12 +626,12 @@ def load_model_from_init_py(
vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
a new Vocab object will be created.
disable (Iterable[str]): Names of pipeline components to disable. Disabled
disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
pipes will be loaded but they won't be run unless you explicitly
enable them by calling nlp.enable_pipe.
enable (Iterable[str]): Names of pipeline components to enable. All other
enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
components won't be loaded.
config (Dict[str, Any] / Config): Config overrides as nested dict or dict
keyed by section values in dot notation.

27
website/docs/api/language.md
View File

@ -63,17 +63,18 @@ spaCy loads a model under the hood based on its
> nlp = Language.from_config(config)
> ```
| Name | Description |
| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `config` | The loaded config. ~~Union[Dict[str, Any], Config]~~ |
| _keyword-only_ | |
| `vocab` | A `Vocab` object. If `True`, a vocab is created using the default language data settings. ~~Vocab~~ |
| `disable` | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~List[str]~~ |
| `exclude` | Names of pipeline components to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~List[str]~~ |
| `meta` | [Meta data](/api/data-formats#meta) overrides. ~~Dict[str, Any]~~ |
| `auto_fill` | Whether to automatically fill in missing values in the config, based on defaults and function argument annotations. Defaults to `True`. ~~bool~~ |
| `validate` | Whether to validate the component config and arguments against the types expected by the factory. Defaults to `True`. ~~bool~~ |
| **RETURNS** | The initialized object. ~~Language~~ |
| Name | Description |
| ------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `config` | The loaded config. ~~Union[Dict[str, Any], Config]~~ |
| _keyword-only_ | |
| `vocab` | A `Vocab` object. If `True`, a vocab is created using the default language data settings. ~~Vocab~~ |
| `disable` | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
| `exclude` | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~ |
| `meta` | [Meta data](/api/data-formats#meta) overrides. ~~Dict[str, Any]~~ |
| `auto_fill` | Whether to automatically fill in missing values in the config, based on defaults and function argument annotations. Defaults to `True`. ~~bool~~ |
| `validate` | Whether to validate the component config and arguments against the types expected by the factory. Defaults to `True`. ~~bool~~ |
| **RETURNS** | The initialized object. ~~Language~~ |
## Language.component {#component tag="classmethod" new="3"}
@ -695,8 +696,8 @@ As of spaCy v3.0, the `disable_pipes` method has been renamed to `select_pipes`:
| Name | Description |
| -------------- | ------------------------------------------------------------------------------------------------------ |
| _keyword-only_ | |
| `disable` | Name(s) of pipeline components to disable. ~~Optional[Union[str, Iterable[str]]]~~ |
| `enable` | Name(s) of pipeline components that will not be disabled. ~~Optional[Union[str, Iterable[str]]]~~ |
| `disable` | Name(s) of pipeline component(s) to disable. ~~Optional[Union[str, Iterable[str]]]~~ |
| `enable` | Name(s) of pipeline component(s) that will not be disabled. ~~Optional[Union[str, Iterable[str]]]~~ |
| **RETURNS** | The disabled pipes that can be restored by calling the object's `.restore()` method. ~~DisabledPipes~~ |
## Language.get_factory_meta {#get_factory_meta tag="classmethod" new="3"}

53
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View File

@ -248,6 +248,59 @@ added to an existing vectors table. See more details in
## Loggers {#loggers}
These functions are available from `@spacy.registry.loggers`.
### spacy.ConsoleLogger.v1 {#ConsoleLogger_v1}
> #### Example config
>
> ```ini
> [training.logger]
> @loggers = "spacy.ConsoleLogger.v1"
> progress_bar = true
> ```
Writes the results of a training step to the console in a tabular format.
<Accordion title="Example console output" spaced>
```cli
$ python -m spacy train config.cfg
```
```
ℹ Using CPU
ℹ Loading config and nlp from: config.cfg
ℹ Pipeline: ['tok2vec', 'tagger']
ℹ Start training
ℹ Training. Initial learn rate: 0.0
E # LOSS TOK2VEC LOSS TAGGER TAG_ACC SCORE
--- ------ ------------ ----------- ------- ------
0 0 0.00 86.20 0.22 0.00
0 200 3.08 18968.78 34.00 0.34
0 400 31.81 22539.06 33.64 0.34
0 600 92.13 22794.91 43.80 0.44
0 800 183.62 21541.39 56.05 0.56
0 1000 352.49 25461.82 65.15 0.65
0 1200 422.87 23708.82 71.84 0.72
0 1400 601.92 24994.79 76.57 0.77
0 1600 662.57 22268.02 80.20 0.80
0 1800 1101.50 28413.77 82.56 0.83
0 2000 1253.43 28736.36 85.00 0.85
0 2200 1411.02 28237.53 87.42 0.87
0 2400 1605.35 28439.95 88.70 0.89
```
Note that the cumulative loss keeps increasing within one epoch, but should
start decreasing across epochs.
</Accordion>
| Name | Description |
| -------------- | --------------------------------------------------------- |
| `progress_bar` | Whether the logger should print the progress bar ~~bool~~ |
Logging utilities for spaCy are implemented in the
[`spacy-loggers`](https://github.com/explosion/spacy-loggers) repo, and the
functions are typically available from `@spacy.registry.loggers`.

117
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View File

@ -45,16 +45,16 @@ specified separately using the new `exclude` keyword argument.
> nlp = spacy.load("en_core_web_sm", exclude=["parser", "tagger"])
> ```
| Name | Description |
| ------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `name` | Pipeline to load, i.e. package name or path. ~~Union[str, Path]~~ |
| _keyword-only_ | |
| `vocab` | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~ |
| `disable` | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). ~~List[str]~~ |
| `enable` | Names of pipeline components to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled. ~~List[str]~~ |
| `exclude` <Tag variant="new">3</Tag> | Names of pipeline components to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~List[str]~~ |
| `config` <Tag variant="new">3</Tag> | Optional config overrides, either as nested dict or dict keyed by section value in dot notation, e.g. `"components.name.value"`. ~~Union[Dict[str, Any], Config]~~ |
| **RETURNS** | A `Language` object with the loaded pipeline. ~~Language~~ |
| Name | Description |
| ------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `name` | Pipeline to load, i.e. package name or path. ~~Union[str, Path]~~ |
| _keyword-only_ | |
| `vocab` | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~ |
| `disable` | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled. ~~Union[str, Iterable[str]]~~ |
| `exclude` <Tag variant="new">3</Tag> | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~ |
| `config` <Tag variant="new">3</Tag> | Optional config overrides, either as nested dict or dict keyed by section value in dot notation, e.g. `"components.name.value"`. ~~Union[Dict[str, Any], Config]~~ |
| **RETURNS** | A `Language` object with the loaded pipeline. ~~Language~~ |
Essentially, `spacy.load()` is a convenience wrapper that reads the pipeline's
[`config.cfg`](/api/data-formats#config), uses the language and pipeline
@ -275,8 +275,8 @@ Render a dependency parse tree or named entity visualization.
### displacy.parse_deps {#displacy.parse_deps tag="method" new="2"}
Generate dependency parse in `{'words': [], 'arcs': []}` format.
For use with the `manual=True` argument in `displacy.render`.
Generate dependency parse in `{'words': [], 'arcs': []}` format. For use with
the `manual=True` argument in `displacy.render`.
> #### Example
>
@ -297,8 +297,8 @@ For use with the `manual=True` argument in `displacy.render`.
### displacy.parse_ents {#displacy.parse_ents tag="method" new="2"}
Generate named entities in `[{start: i, end: i, label: 'label'}]` format.
For use with the `manual=True` argument in `displacy.render`.
Generate named entities in `[{start: i, end: i, label: 'label'}]` format. For
use with the `manual=True` argument in `displacy.render`.
> #### Example
>
@ -319,8 +319,8 @@ For use with the `manual=True` argument in `displacy.render`.
### displacy.parse_spans {#displacy.parse_spans tag="method" new="2"}
Generate spans in `[{start_token: i, end_token: i, label: 'label'}]` format.
For use with the `manual=True` argument in `displacy.render`.
Generate spans in `[{start_token: i, end_token: i, label: 'label'}]` format. For
use with the `manual=True` argument in `displacy.render`.
> #### Example
>
@ -451,7 +451,7 @@ factories.
| Registry name | Description |
| ----------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `architectures` | Registry for functions that create [model architectures](/api/architectures). Can be used to register custom model architectures and reference them in the `config.cfg`. |
| `augmenters` | Registry for functions that create [data augmentation](#augmenters) callbacks for corpora and other training data iterators. |
| `augmenters` | Registry for functions that create [data augmentation](#augmenters) callbacks for corpora and other training data iterators. |
| `batchers` | Registry for training and evaluation [data batchers](#batchers). |
| `callbacks` | Registry for custom callbacks to [modify the `nlp` object](/usage/training#custom-code-nlp-callbacks) before training. |
| `displacy_colors` | Registry for custom color scheme for the [`displacy` NER visualizer](/usage/visualizers). Automatically reads from [entry points](/usage/saving-loading#entry-points). |
@ -505,7 +505,7 @@ finished. To log each training step, a
and the accuracy scores on the development set.
The built-in, default logger is the ConsoleLogger, which prints results to the
console in tabular format. The
console in tabular format and saves them to a `jsonl` file. The
[spacy-loggers](https://github.com/explosion/spacy-loggers) package, included as
a dependency of spaCy, enables other loggers, such as one that sends results to
a [Weights & Biases](https://www.wandb.com/) dashboard.
@ -513,16 +513,20 @@ a [Weights & Biases](https://www.wandb.com/) dashboard.
Instead of using one of the built-in loggers, you can
[implement your own](/usage/training#custom-logging).
#### spacy.ConsoleLogger.v1 {#ConsoleLogger tag="registered function"}
#### spacy.ConsoleLogger.v2 {#ConsoleLogger tag="registered function"}
> #### Example config
>
> ```ini
> [training.logger]
> @loggers = "spacy.ConsoleLogger.v1"
> @loggers = "spacy.ConsoleLogger.v2"
> progress_bar = true
> console_output = true
> output_file = "training_log.jsonl"
> ```
Writes the results of a training step to the console in a tabular format.
Writes the results of a training step to the console in a tabular format and
saves them to a `jsonl` file.
<Accordion title="Example console output" spaced>
@ -536,22 +540,23 @@ $ python -m spacy train config.cfg
ℹ Pipeline: ['tok2vec', 'tagger']
ℹ Start training
ℹ Training. Initial learn rate: 0.0
ℹ Saving results to training_log.jsonl
E # LOSS TOK2VEC LOSS TAGGER TAG_ACC SCORE
--- ------ ------------ ----------- ------- ------
1 0 0.00 86.20 0.22 0.00
1 200 3.08 18968.78 34.00 0.34
1 400 31.81 22539.06 33.64 0.34
1 600 92.13 22794.91 43.80 0.44
1 800 183.62 21541.39 56.05 0.56
1 1000 352.49 25461.82 65.15 0.65
1 1200 422.87 23708.82 71.84 0.72
1 1400 601.92 24994.79 76.57 0.77
1 1600 662.57 22268.02 80.20 0.80
1 1800 1101.50 28413.77 82.56 0.83
1 2000 1253.43 28736.36 85.00 0.85
1 2200 1411.02 28237.53 87.42 0.87
1 2400 1605.35 28439.95 88.70 0.89
0 0 0.00 86.20 0.22 0.00
0 200 3.08 18968.78 34.00 0.34
0 400 31.81 22539.06 33.64 0.34
0 600 92.13 22794.91 43.80 0.44
0 800 183.62 21541.39 56.05 0.56
0 1000 352.49 25461.82 65.15 0.65
0 1200 422.87 23708.82 71.84 0.72
0 1400 601.92 24994.79 76.57 0.77
0 1600 662.57 22268.02 80.20 0.80
0 1800 1101.50 28413.77 82.56 0.83
0 2000 1253.43 28736.36 85.00 0.85
0 2200 1411.02 28237.53 87.42 0.87
0 2400 1605.35 28439.95 88.70 0.89
```
Note that the cumulative loss keeps increasing within one epoch, but should
@ -559,6 +564,12 @@ start decreasing across epochs.
</Accordion>
| Name | Description |
| ---------------- | --------------------------------------------------------------------- |
| `progress_bar` | Whether the logger should print the progress bar ~~bool~~ |
| `console_output` | Whether the logger should print the logs on the console. ~~bool~~ |
| `output_file` | The file to save the training logs to. ~~Optional[Union[str, Path]]~~ |
## Readers {#readers}
### File readers {#file-readers source="github.com/explosion/srsly" new="3"}
@ -1038,15 +1049,16 @@ and create a `Language` object. The model data will then be loaded in via
> nlp = util.load_model("/path/to/data")
> ```
| Name | Description |
| ------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `name` | Package name or path. ~~str~~ |
| _keyword-only_ | |
| `vocab` | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~ |
| `disable` | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~List[str]~~ |
| `exclude` <Tag variant="new">3</Tag> | Names of pipeline components to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~List[str]~~ |
| `config` <Tag variant="new">3</Tag> | Config overrides as nested dict or flat dict keyed by section values in dot notation, e.g. `"nlp.pipeline"`. ~~Union[Dict[str, Any], Config]~~ |
| **RETURNS** | `Language` class with the loaded pipeline. ~~Language~~ |
| Name | Description |
| ------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `name` | Package name or path. ~~str~~ |
| _keyword-only_ | |
| `vocab` | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~ |
| `disable` | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
| `exclude` | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~ |
| `config` <Tag variant="new">3</Tag> | Config overrides as nested dict or flat dict keyed by section values in dot notation, e.g. `"nlp.pipeline"`. ~~Union[Dict[str, Any], Config]~~ |
| **RETURNS** | `Language` class with the loaded pipeline. ~~Language~~ |
### util.load_model_from_init_py {#util.load_model_from_init_py tag="function" new="2"}
@ -1062,15 +1074,16 @@ A helper function to use in the `load()` method of a pipeline package's
> return load_model_from_init_py(__file__, **overrides)
> ```
| Name | Description |
| ------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `init_file` | Path to package's `__init__.py`, i.e. `__file__`. ~~Union[str, Path]~~ |
| _keyword-only_ | |
| `vocab` <Tag variant="new">3</Tag> | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~ |
| `disable` | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). ~~List[str]~~ |
| `exclude` <Tag variant="new">3</Tag> | Names of pipeline components to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~List[str]~~ |
| `config` <Tag variant="new">3</Tag> | Config overrides as nested dict or flat dict keyed by section values in dot notation, e.g. `"nlp.pipeline"`. ~~Union[Dict[str, Any], Config]~~ |
| **RETURNS** | `Language` class with the loaded pipeline. ~~Language~~ |
| Name | Description |
| ------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `init_file` | Path to package's `__init__.py`, i.e. `__file__`. ~~Union[str, Path]~~ |
| _keyword-only_ | |
| `vocab` <Tag variant="new">3</Tag> | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~ |
| `disable` | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
| `exclude` <Tag variant="new">3</Tag> | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~ |
| `config` <Tag variant="new">3</Tag> | Config overrides as nested dict or flat dict keyed by section values in dot notation, e.g. `"nlp.pipeline"`. ~~Union[Dict[str, Any], Config]~~ |
| **RETURNS** | `Language` class with the loaded pipeline. ~~Language~~ |
### util.load_config {#util.load_config tag="function" new="3"}