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