spaCy/spacy/tests/pipeline/test_pipe_factories.py

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Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
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import pytest
from spacy.language import Language
from spacy.lang.en import English
from spacy.lang.de import German
from spacy.tokens import Doc
from spacy.util import registry, SimpleFrozenDict, combine_score_weights
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
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from thinc.api import Model, Linear
from thinc.config import ConfigValidationError
from pydantic import StrictInt, StrictStr
from ..util import make_tempdir
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
def test_pipe_function_component():
name = "test_component"
@Language.component(name)
def component(doc: Doc) -> Doc:
return doc
assert name in registry.factories
nlp = Language()
with pytest.raises(ValueError):
nlp.add_pipe(component)
nlp.add_pipe(name)
assert name in nlp.pipe_names
assert nlp.pipe_factories[name] == name
assert Language.get_factory_meta(name)
assert nlp.get_pipe_meta(name)
pipe = nlp.get_pipe(name)
assert pipe == component
pipe = nlp.create_pipe(name)
assert pipe == component
def test_pipe_class_component_init():
name1 = "test_class_component1"
name2 = "test_class_component2"
@Language.factory(name1)
class Component1:
def __init__(self, nlp: Language, name: str):
self.nlp = nlp
def __call__(self, doc: Doc) -> Doc:
return doc
class Component2:
def __init__(self, nlp: Language, name: str):
self.nlp = nlp
def __call__(self, doc: Doc) -> Doc:
return doc
@Language.factory(name2)
def factory(nlp: Language, name=name2):
return Component2(nlp, name)
nlp = Language()
for name, Component in [(name1, Component1), (name2, Component2)]:
assert name in registry.factories
with pytest.raises(ValueError):
nlp.add_pipe(Component(nlp, name))
nlp.add_pipe(name)
assert name in nlp.pipe_names
assert nlp.pipe_factories[name] == name
assert Language.get_factory_meta(name)
assert nlp.get_pipe_meta(name)
pipe = nlp.get_pipe(name)
assert isinstance(pipe, Component)
assert isinstance(pipe.nlp, Language)
pipe = nlp.create_pipe(name)
assert isinstance(pipe, Component)
assert isinstance(pipe.nlp, Language)
def test_pipe_class_component_config():
name = "test_class_component_config"
@Language.factory(name)
class Component:
def __init__(
self, nlp: Language, name: str, value1: StrictInt, value2: StrictStr
):
self.nlp = nlp
self.value1 = value1
self.value2 = value2
self.is_base = True
def __call__(self, doc: Doc) -> Doc:
return doc
@English.factory(name)
class ComponentEN:
def __init__(
self, nlp: Language, name: str, value1: StrictInt, value2: StrictStr
):
self.nlp = nlp
self.value1 = value1
self.value2 = value2
self.is_base = False
def __call__(self, doc: Doc) -> Doc:
return doc
nlp = Language()
with pytest.raises(ConfigValidationError): # no config provided
nlp.add_pipe(name)
with pytest.raises(ConfigValidationError): # invalid config
nlp.add_pipe(name, config={"value1": "10", "value2": "hello"})
nlp.add_pipe(name, config={"value1": 10, "value2": "hello"})
pipe = nlp.get_pipe(name)
assert isinstance(pipe.nlp, Language)
assert pipe.value1 == 10
assert pipe.value2 == "hello"
assert pipe.is_base is True
nlp_en = English()
with pytest.raises(ConfigValidationError): # invalid config
nlp_en.add_pipe(name, config={"value1": "10", "value2": "hello"})
nlp_en.add_pipe(name, config={"value1": 10, "value2": "hello"})
pipe = nlp_en.get_pipe(name)
assert isinstance(pipe.nlp, English)
assert pipe.value1 == 10
assert pipe.value2 == "hello"
assert pipe.is_base is False
def test_pipe_class_component_defaults():
name = "test_class_component_defaults"
@Language.factory(name)
class Component:
def __init__(
self,
nlp: Language,
name: str,
value1: StrictInt = 10,
value2: StrictStr = "hello",
):
self.nlp = nlp
self.value1 = value1
self.value2 = value2
def __call__(self, doc: Doc) -> Doc:
return doc
nlp = Language()
nlp.add_pipe(name)
pipe = nlp.get_pipe(name)
assert isinstance(pipe.nlp, Language)
assert pipe.value1 == 10
assert pipe.value2 == "hello"
def test_pipe_class_component_model():
name = "test_class_component_model"
default_config = {
"model": {
"@architectures": "spacy.TextCatEnsemble.v1",
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
"exclusive_classes": False,
"pretrained_vectors": None,
"width": 64,
"embed_size": 2000,
"window_size": 1,
"conv_depth": 2,
"ngram_size": 1,
"dropout": None,
},
"value1": 10,
}
@Language.factory(name, default_config=default_config)
class Component:
def __init__(self, nlp: Language, model: Model, name: str, value1: StrictInt):
self.nlp = nlp
self.model = model
self.value1 = value1
self.name = name
def __call__(self, doc: Doc) -> Doc:
return doc
nlp = Language()
nlp.add_pipe(name)
pipe = nlp.get_pipe(name)
assert isinstance(pipe.nlp, Language)
assert pipe.value1 == 10
assert isinstance(pipe.model, Model)
def test_pipe_class_component_model_custom():
name = "test_class_component_model_custom"
arch = f"{name}.arch"
default_config = {"value1": 1, "model": {"@architectures": arch, "nO": 0, "nI": 0}}
@Language.factory(name, default_config=default_config)
class Component:
def __init__(
self, nlp: Language, model: Model, name: str, value1: StrictInt = 10
):
self.nlp = nlp
self.model = model
self.value1 = value1
self.name = name
def __call__(self, doc: Doc) -> Doc:
return doc
@registry.architectures(arch)
def make_custom_arch(nO: StrictInt, nI: StrictInt):
return Linear(nO, nI)
nlp = Language()
config = {"value1": 20, "model": {"@architectures": arch, "nO": 1, "nI": 2}}
nlp.add_pipe(name, config=config)
pipe = nlp.get_pipe(name)
assert isinstance(pipe.nlp, Language)
assert pipe.value1 == 20
assert isinstance(pipe.model, Model)
assert pipe.model.name == "linear"
nlp = Language()
with pytest.raises(ConfigValidationError):
config = {"value1": "20", "model": {"@architectures": arch, "nO": 1, "nI": 2}}
nlp.add_pipe(name, config=config)
with pytest.raises(ConfigValidationError):
config = {"value1": 20, "model": {"@architectures": arch, "nO": 1.0, "nI": 2.0}}
nlp.add_pipe(name, config=config)
def test_pipe_factories_wrong_formats():
with pytest.raises(ValueError):
# Decorator is not called
@Language.component
def component(foo: int, bar: str):
...
with pytest.raises(ValueError):
# Decorator is not called
@Language.factory
def factory1(foo: int, bar: str):
...
with pytest.raises(ValueError):
# Factory function is missing "nlp" and "name" arguments
@Language.factory("test_pipe_factories_missing_args")
def factory2(foo: int, bar: str):
...
def test_pipe_factory_meta_config_cleanup():
"""Test that component-specific meta and config entries are represented
correctly and cleaned up when pipes are removed, replaced or renamed."""
nlp = Language()
nlp.add_pipe("ner", name="ner_component")
nlp.add_pipe("textcat")
assert nlp.get_factory_meta("ner")
assert nlp.get_pipe_meta("ner_component")
assert nlp.get_pipe_config("ner_component")
assert nlp.get_factory_meta("textcat")
assert nlp.get_pipe_meta("textcat")
assert nlp.get_pipe_config("textcat")
nlp.rename_pipe("textcat", "tc")
assert nlp.get_pipe_meta("tc")
assert nlp.get_pipe_config("tc")
with pytest.raises(ValueError):
nlp.remove_pipe("ner")
nlp.remove_pipe("ner_component")
assert "ner_component" not in nlp._pipe_meta
assert "ner_component" not in nlp._pipe_configs
with pytest.raises(ValueError):
nlp.replace_pipe("textcat", "parser")
nlp.replace_pipe("tc", "parser")
assert nlp.get_factory_meta("parser")
assert nlp.get_pipe_meta("tc").factory == "parser"
def test_pipe_factories_empty_dict_default():
"""Test that default config values can be empty dicts and that no config
validation error is raised."""
# TODO: fix this
name = "test_pipe_factories_empty_dict_default"
@Language.factory(name, default_config={"foo": {}})
def factory(nlp: Language, name: str, foo: dict):
...
nlp = Language()
nlp.create_pipe(name)
def test_pipe_factories_language_specific():
"""Test that language sub-classes can have their own factories, with
fallbacks to the base factories."""
name1 = "specific_component1"
name2 = "specific_component2"
Language.component(name1, func=lambda: "base")
English.component(name1, func=lambda: "en")
German.component(name2, func=lambda: "de")
assert Language.has_factory(name1)
assert not Language.has_factory(name2)
assert English.has_factory(name1)
assert not English.has_factory(name2)
assert German.has_factory(name1)
assert German.has_factory(name2)
nlp = Language()
assert nlp.create_pipe(name1)() == "base"
with pytest.raises(ValueError):
nlp.create_pipe(name2)
nlp_en = English()
assert nlp_en.create_pipe(name1)() == "en"
with pytest.raises(ValueError):
nlp_en.create_pipe(name2)
nlp_de = German()
assert nlp_de.create_pipe(name1)() == "base"
assert nlp_de.create_pipe(name2)() == "de"
def test_language_factories_invalid():
"""Test that assigning directly to Language.factories is now invalid and
raises a custom error."""
assert isinstance(Language.factories, SimpleFrozenDict)
with pytest.raises(NotImplementedError):
Language.factories["foo"] = "bar"
nlp = Language()
assert isinstance(nlp.factories, SimpleFrozenDict)
assert len(nlp.factories)
with pytest.raises(NotImplementedError):
nlp.factories["foo"] = "bar"
@pytest.mark.parametrize(
"weights,expected",
[
([{"a": 1.0}, {"b": 1.0}, {"c": 1.0}], {"a": 0.33, "b": 0.33, "c": 0.33}),
([{"a": 1.0}, {"b": 50}, {"c": 123}], {"a": 0.33, "b": 0.33, "c": 0.33}),
(
[{"a": 0.7, "b": 0.3}, {"c": 1.0}, {"d": 0.5, "e": 0.5}],
{"a": 0.23, "b": 0.1, "c": 0.33, "d": 0.17, "e": 0.17},
),
(
[{"a": 100, "b": 400}, {"c": 0.5, "d": 0.5}],
{"a": 0.1, "b": 0.4, "c": 0.25, "d": 0.25},
),
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(
[{"a": 0.5, "b": 0.5}, {"b": 1.0}],
{"a": 0.25, "b": 0.75},
),
],
)
def test_language_factories_combine_score_weights(weights, expected):
result = combine_score_weights(weights)
assert sum(result.values()) in (0.99, 1.0)
assert result == expected
def test_language_factories_scores():
name = "test_language_factories_scores"
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func = lambda nlp, name: lambda doc: doc
weights1 = {"a1": 0.5, "a2": 0.5}
weights2 = {"b1": 0.2, "b2": 0.7, "b3": 0.1}
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Language.factory(
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f"{name}1",
scores=list(weights1),
default_score_weights=weights1,
func=func,
)
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Language.factory(
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f"{name}2",
scores=list(weights2),
default_score_weights=weights2,
func=func,
)
meta1 = Language.get_factory_meta(f"{name}1")
assert meta1.default_score_weights == weights1
meta2 = Language.get_factory_meta(f"{name}2")
assert meta2.default_score_weights == weights2
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nlp = Language()
nlp._config["training"]["score_weights"] = {}
nlp.add_pipe(f"{name}1")
nlp.add_pipe(f"{name}2")
cfg = nlp.config["training"]
expected_weights = {"a1": 0.25, "a2": 0.25, "b1": 0.1, "b2": 0.35, "b3": 0.05}
assert cfg["score_weights"] == expected_weights
def test_pipe_factories_from_source():
"""Test adding components from a source model."""
source_nlp = English()
source_nlp.add_pipe("tagger", name="my_tagger")
nlp = English()
with pytest.raises(ValueError):
nlp.add_pipe("my_tagger", source="en_core_web_sm")
nlp.add_pipe("my_tagger", source=source_nlp)
assert "my_tagger" in nlp.pipe_names
with pytest.raises(KeyError):
nlp.add_pipe("custom", source=source_nlp)
def test_pipe_factories_from_source_custom():
"""Test adding components from a source model with custom components."""
name = "test_pipe_factories_from_source_custom"
@Language.factory(name, default_config={"arg": "hello"})
def test_factory(nlp, name, arg: str):
return lambda doc: doc
source_nlp = English()
source_nlp.add_pipe("tagger")
source_nlp.add_pipe(name, config={"arg": "world"})
nlp = English()
nlp.add_pipe(name, source=source_nlp)
assert name in nlp.pipe_names
assert nlp.get_pipe_meta(name).default_config["arg"] == "hello"
config = nlp.config["components"][name]
assert config["factory"] == name
assert config["arg"] == "world"
def test_pipe_factories_from_source_config():
name = "test_pipe_factories_from_source_config"
@Language.factory(name, default_config={"arg": "hello"})
def test_factory(nlp, name, arg: str):
return lambda doc: doc
source_nlp = English()
source_nlp.add_pipe("tagger")
source_nlp.add_pipe(name, name="yolo", config={"arg": "world"})
dest_nlp_cfg = {"lang": "en", "pipeline": ["parser", "custom"]}
with make_tempdir() as tempdir:
source_nlp.to_disk(tempdir)
dest_components_cfg = {
"parser": {"factory": "parser"},
"custom": {"source": str(tempdir), "component": "yolo"},
}
dest_config = {"nlp": dest_nlp_cfg, "components": dest_components_cfg}
nlp = English.from_config(dest_config)
assert nlp.pipe_names == ["parser", "custom"]
assert nlp.pipe_factories == {"parser": "parser", "custom": name}
meta = nlp.get_pipe_meta("custom")
assert meta.factory == name
assert meta.default_config["arg"] == "hello"
config = nlp.config["components"]["custom"]
assert config["factory"] == name
assert config["arg"] == "world"
def test_pipe_factories_decorator_idempotent():
"""Check that decorator can be run multiple times if the function is the
same. This is especially relevant for live reloading because we don't
want spaCy to raise an error if a module registering components is reloaded.
"""
name = "test_pipe_factories_decorator_idempotent"
func = lambda nlp, name: lambda doc: doc
for i in range(5):
Language.factory(name, func=func)
nlp = Language()
nlp.add_pipe(name)
Language.factory(name, func=func)
# Make sure it also works for component decorator, which creates the
# factory function
name2 = f"{name}2"
func2 = lambda doc: doc
for i in range(5):
Language.component(name2, func=func2)
nlp = Language()
nlp.add_pipe(name)
Language.component(name2, func=func2)
def test_pipe_factories_config_excludes_nlp():
"""Test that the extra values we temporarily add to component config
blocks/functions are removed and not copied around.
"""
name = "test_pipe_factories_config_excludes_nlp"
func = lambda nlp, name: lambda doc: doc
Language.factory(name, func=func)
config = {
"nlp": {"lang": "en", "pipeline": [name]},
"components": {name: {"factory": name}},
}
nlp = English.from_config(config)
assert nlp.pipe_names == [name]
pipe_cfg = nlp.get_pipe_config(name)
pipe_cfg == {"factory": name}
assert nlp._pipe_configs[name] == {"factory": name}