mirror of
https://github.com/explosion/spaCy.git
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76 lines
2.4 KiB
Python
76 lines
2.4 KiB
Python
import pytest
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try:
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from pydantic.v1 import StrictBool
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except ImportError:
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from pydantic import StrictBool # type: ignore
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from thinc.api import ConfigValidationError
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from spacy.lang.en import English
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from spacy.language import Language
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from spacy.training import Example
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def test_initialize_arguments():
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name = "test_initialize_arguments"
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class CustomTokenizer:
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def __init__(self, tokenizer):
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self.tokenizer = tokenizer
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self.from_initialize = None
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def __call__(self, text):
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return self.tokenizer(text)
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def initialize(self, get_examples, nlp, custom: int):
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self.from_initialize = custom
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class Component:
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def __init__(self):
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self.from_initialize = None
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def initialize(
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self, get_examples, nlp, custom1: str, custom2: StrictBool = False
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):
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self.from_initialize = (custom1, custom2)
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Language.factory(name, func=lambda nlp, name: Component())
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nlp = English()
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nlp.tokenizer = CustomTokenizer(nlp.tokenizer)
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example = Example.from_dict(nlp("x"), {})
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get_examples = lambda: [example]
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nlp.add_pipe(name)
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# The settings here will typically come from the [initialize] block
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init_cfg = {"tokenizer": {"custom": 1}, "components": {name: {}}}
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nlp.config["initialize"].update(init_cfg)
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with pytest.raises(ConfigValidationError) as e:
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# Empty config for component, no required custom1 argument
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nlp.initialize(get_examples)
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errors = e.value.errors
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assert len(errors) == 1
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assert errors[0]["loc"] == ("custom1",)
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assert errors[0]["type"] == "value_error.missing"
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init_cfg = {
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"tokenizer": {"custom": 1},
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"components": {name: {"custom1": "x", "custom2": 1}},
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}
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nlp.config["initialize"].update(init_cfg)
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with pytest.raises(ConfigValidationError) as e:
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# Wrong type of custom 2
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nlp.initialize(get_examples)
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errors = e.value.errors
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assert len(errors) == 1
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assert errors[0]["loc"] == ("custom2",)
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assert errors[0]["type"] == "value_error.strictbool"
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init_cfg = {
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"tokenizer": {"custom": 1},
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"components": {name: {"custom1": "x"}},
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}
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nlp.config["initialize"].update(init_cfg)
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nlp.initialize(get_examples)
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assert nlp.tokenizer.from_initialize == 1
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pipe = nlp.get_pipe(name)
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assert pipe.from_initialize == ("x", False)
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