mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-25 17:36:30 +03:00
Format
This commit is contained in:
parent
4332d12ce2
commit
b9730a64cb
|
@ -801,8 +801,11 @@ class Language:
|
|||
self._components.insert(pipe_index, (name, pipe_component))
|
||||
return pipe_component
|
||||
|
||||
def add_pipe_instance(self, component: PipeCallable,
|
||||
/, name: Optional[str] = None,
|
||||
def add_pipe_instance(
|
||||
self,
|
||||
component: PipeCallable,
|
||||
/,
|
||||
name: Optional[str] = None,
|
||||
*,
|
||||
before: Optional[Union[str, int]] = None,
|
||||
after: Optional[Union[str, int]] = None,
|
||||
|
@ -1743,7 +1746,7 @@ class Language:
|
|||
meta: Dict[str, Any] = SimpleFrozenDict(),
|
||||
auto_fill: bool = True,
|
||||
validate: bool = True,
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict()
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict(),
|
||||
) -> "Language":
|
||||
"""Create the nlp object from a loaded config. Will set up the tokenizer
|
||||
and language data, add pipeline components etc. If no config is provided,
|
||||
|
@ -1844,7 +1847,7 @@ class Language:
|
|||
# and aren't built by factory.
|
||||
missing_components = _find_missing_components(pipeline, pipe_instances, exclude)
|
||||
if missing_components:
|
||||
raise ValueError(Errors.E1052.format(", ",join(missing_components)))
|
||||
raise ValueError(Errors.E1052.format(", ", join(missing_components)))
|
||||
# If components are loaded from a source (existing models), we cache
|
||||
# them here so they're only loaded once
|
||||
source_nlps = {}
|
||||
|
@ -1858,9 +1861,7 @@ class Language:
|
|||
if pipe_name in exclude:
|
||||
continue
|
||||
else:
|
||||
nlp.add_pipe_instance(
|
||||
pipe_instances[pipe_name]
|
||||
)
|
||||
nlp.add_pipe_instance(pipe_instances[pipe_name])
|
||||
# Is it important that we instantiate pipes that
|
||||
# aren't excluded? It seems like we would want
|
||||
# the exclude check above. I've left it how it
|
||||
|
@ -2384,7 +2385,9 @@ class _Sender:
|
|||
self.send()
|
||||
|
||||
|
||||
def _get_instantiated_vocab(vocab: Union[bool, Vocab], pipe_instances: Dict[str, Any]) -> Union[bool, Vocab]:
|
||||
def _get_instantiated_vocab(
|
||||
vocab: Union[bool, Vocab], pipe_instances: Dict[str, Any]
|
||||
) -> Union[bool, Vocab]:
|
||||
vocab_instances = {}
|
||||
for name, instance in pipe_instances.items():
|
||||
if hasattr(instance, "vocab") and isinstance(instance.vocab, Vocab):
|
||||
|
@ -2410,8 +2413,8 @@ def _get_instantiated_vocab(vocab: Union[bool, Vocab], pipe_instances: Dict[str,
|
|||
|
||||
|
||||
def _find_missing_components(
|
||||
pipeline: List[str],
|
||||
pipe_instances: Dict[str, Any],
|
||||
exclude: List[str]
|
||||
pipeline: List[str], pipe_instances: Dict[str, Any], exclude: List[str]
|
||||
) -> List[str]:
|
||||
return [name for name in pipeline if name not in pipe_instances and name not in exclude]
|
||||
return [
|
||||
name for name in pipeline if name not in pipe_instances and name not in exclude
|
||||
]
|
||||
|
|
|
@ -801,15 +801,18 @@ def test_component_return():
|
|||
nlp("text")
|
||||
|
||||
|
||||
@pytest.mark.parametrize("components,kwargs,position", [
|
||||
(["t1", "t2"], {"before": "t1"}, 0),
|
||||
(["t1", "t2"], {"after": "t1"}, 1),
|
||||
(["t1", "t2"], {"after": "t1"}, 1),
|
||||
(["t1", "t2"], {"first": True}, 0),
|
||||
(["t1", "t2"], {"last": True}, 2),
|
||||
(["t1", "t2"], {"last": False}, 2),
|
||||
(["t1", "t2"], {"first": False}, ValueError),
|
||||
])
|
||||
@pytest.mark.parametrize(
|
||||
"components,kwargs,position",
|
||||
[
|
||||
(["t1", "t2"], {"before": "t1"}, 0),
|
||||
(["t1", "t2"], {"after": "t1"}, 1),
|
||||
(["t1", "t2"], {"after": "t1"}, 1),
|
||||
(["t1", "t2"], {"first": True}, 0),
|
||||
(["t1", "t2"], {"last": True}, 2),
|
||||
(["t1", "t2"], {"last": False}, 2),
|
||||
(["t1", "t2"], {"first": False}, ValueError),
|
||||
],
|
||||
)
|
||||
def test_add_pipe_instance(components, kwargs, position):
|
||||
nlp = Language()
|
||||
for name in components:
|
||||
|
@ -822,7 +825,9 @@ def test_add_pipe_instance(components, kwargs, position):
|
|||
assert nlp.pipe_names == pipe_names
|
||||
else:
|
||||
with pytest.raises(ValueError):
|
||||
result = nlp.add_pipe_instance(evil_component, name="new_component", **kwargs)
|
||||
result = nlp.add_pipe_instance(
|
||||
evil_component, name="new_component", **kwargs
|
||||
)
|
||||
|
||||
|
||||
def test_add_pipe_instance_to_bytes():
|
||||
|
@ -831,4 +836,3 @@ def test_add_pipe_instance_to_bytes():
|
|||
nlp.add_pipe("textcat", name="t2")
|
||||
nlp.add_pipe_instance(evil_component, name="new_component")
|
||||
b = nlp.to_bytes()
|
||||
|
||||
|
|
|
@ -415,7 +415,7 @@ def load_model(
|
|||
enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
|
||||
exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
|
||||
config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict()
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict(),
|
||||
) -> "Language":
|
||||
"""Load a model from a package or data path.
|
||||
|
||||
|
@ -427,7 +427,7 @@ def load_model(
|
|||
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.
|
||||
pipe_instances (Dict[str, Any]): Dictionary of components
|
||||
pipe_instances (Dict[str, Any]): Dictionary of components
|
||||
to be added to the pipeline directly (not created from
|
||||
config)
|
||||
RETURNS (Language): The loaded nlp object.
|
||||
|
@ -438,7 +438,7 @@ def load_model(
|
|||
"enable": enable,
|
||||
"exclude": exclude,
|
||||
"config": config,
|
||||
"pipe_instances": pipe_instances
|
||||
"pipe_instances": pipe_instances,
|
||||
}
|
||||
if isinstance(name, str): # name or string path
|
||||
if name.startswith("blank:"): # shortcut for blank model
|
||||
|
@ -462,7 +462,7 @@ def load_model_from_package(
|
|||
enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
|
||||
exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
|
||||
config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict()
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict(),
|
||||
) -> "Language":
|
||||
"""Load a model from an installed package.
|
||||
|
||||
|
@ -478,7 +478,7 @@ def load_model_from_package(
|
|||
components won't be loaded.
|
||||
config (Dict[str, Any] / Config): Config overrides as nested dict or dict
|
||||
keyed by section values in dot notation.
|
||||
pipe_instances (Dict[str, Any]): Dictionary of components
|
||||
pipe_instances (Dict[str, Any]): Dictionary of components
|
||||
to be added to the pipeline directly (not created from
|
||||
config)
|
||||
RETURNS (Language): The loaded nlp object.
|
||||
|
@ -496,7 +496,7 @@ def load_model_from_path(
|
|||
enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
|
||||
exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
|
||||
config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict()
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict(),
|
||||
) -> "Language":
|
||||
"""Load a model from a data directory path. Creates Language class with
|
||||
pipeline from config.cfg and then calls from_disk() with path.
|
||||
|
@ -533,7 +533,7 @@ def load_model_from_path(
|
|||
enable=enable,
|
||||
exclude=exclude,
|
||||
meta=meta,
|
||||
pipe_instances=pipe_instances
|
||||
pipe_instances=pipe_instances,
|
||||
)
|
||||
return nlp.from_disk(model_path, exclude=exclude, overrides=overrides)
|
||||
|
||||
|
@ -548,7 +548,7 @@ def load_model_from_config(
|
|||
exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
|
||||
auto_fill: bool = False,
|
||||
validate: bool = True,
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict()
|
||||
pipe_instances: Dict[str, Any] = SimpleFrozenDict(),
|
||||
) -> "Language":
|
||||
"""Create an nlp object from a config. Expects the full config file including
|
||||
a section "nlp" containing the settings for the nlp object.
|
||||
|
@ -588,7 +588,7 @@ def load_model_from_config(
|
|||
auto_fill=auto_fill,
|
||||
validate=validate,
|
||||
meta=meta,
|
||||
pipe_instances=pipe_instances
|
||||
pipe_instances=pipe_instances,
|
||||
)
|
||||
return nlp
|
||||
|
||||
|
|
Loading…
Reference in New Issue
Block a user