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Tidy up __init__.py
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@ -104,7 +104,6 @@ exclude =
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.git,
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__pycache__,
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_tokenizer_exceptions_list.py,
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spacy/__init__.py
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[tool:pytest]
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markers =
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@ -1,32 +1,50 @@
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from typing import Union, Iterable, Dict, Any
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from pathlib import Path
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import warnings
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import sys
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warnings.filterwarnings("ignore", message="numpy.dtype size changed")
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warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
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warnings.filterwarnings("ignore", message="numpy.dtype size changed") # noqa
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warnings.filterwarnings("ignore", message="numpy.ufunc size changed") # noqa
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# These are imported as part of the API
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from thinc.api import prefer_gpu, require_gpu
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from thinc.api import prefer_gpu, require_gpu # noqa: F401
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from . import pipeline
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from .cli.info import info
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from .glossary import explain
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from .about import __version__
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from .errors import Errors, Warnings
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from . import pipeline # noqa: F401
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from .cli.info import info # noqa: F401
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from .glossary import explain # noqa: F401
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from .about import __version__ # noqa: F401
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from .util import registry # noqa: F401
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from .errors import Errors
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from .language import Language
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from . import util
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from .util import registry
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if sys.maxunicode == 65535:
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raise SystemError(Errors.E130)
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config = registry
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def load(
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name: Union[str, Path],
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disable: Iterable[str] = tuple(),
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component_cfg: Dict[str, Dict[str, Any]] = util.SimpleFrozenDict(),
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) -> Language:
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"""Load a spaCy model from an installed package or a local path.
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name (str): Package name or model path.
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disable (Iterable[str]): Names of pipeline components to disable.
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component_cfg (Dict[str, dict]): Config overrides for pipeline components,
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keyed by component names.
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RETURNS (Language): The loaded nlp object.
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"""
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return util.load_model(name, disable=disable, component_cfg=component_cfg)
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def load(name, **overrides):
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return util.load_model(name, **overrides)
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def blank(name: str, **overrides) -> Language:
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"""Create a blank nlp object for a given language code.
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def blank(name, **kwargs):
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name (str): The language code, e.g. "en".
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**overrides: Keyword arguments passed to language subclass on init.
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RETURNS (Language): The nlp object.
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"""
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LangClass = util.get_lang_class(name)
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return LangClass(**kwargs)
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return LangClass(**overrides)
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