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* 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>
79 lines
2.8 KiB
Python
79 lines
2.8 KiB
Python
import pytest
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from spacy.lang.zh import Chinese, _get_pkuseg_trie_data
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from thinc.config import ConfigValidationError
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# fmt: off
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TEXTS = ("作为语言而言,为世界使用人数最多的语言,目前世界有五分之一人口做为母语。",)
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JIEBA_TOKENIZER_TESTS = [
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(TEXTS[0],
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['作为', '语言', '而言', ',', '为', '世界', '使用', '人', '数最多',
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'的', '语言', ',', '目前', '世界', '有', '五分之一', '人口', '做',
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'为', '母语', '。']),
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]
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PKUSEG_TOKENIZER_TESTS = [
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(TEXTS[0],
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['作为', '语言', '而言', ',', '为', '世界', '使用', '人数', '最多',
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'的', '语言', ',', '目前', '世界', '有', '五分之一', '人口', '做为',
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'母语', '。']),
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]
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# fmt: on
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@pytest.mark.parametrize("text", TEXTS)
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def test_zh_tokenizer_char(zh_tokenizer_char, text):
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tokens = [token.text for token in zh_tokenizer_char(text)]
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assert tokens == list(text)
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@pytest.mark.parametrize("text,expected_tokens", JIEBA_TOKENIZER_TESTS)
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def test_zh_tokenizer_jieba(zh_tokenizer_jieba, text, expected_tokens):
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tokens = [token.text for token in zh_tokenizer_jieba(text)]
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assert tokens == expected_tokens
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@pytest.mark.parametrize("text,expected_tokens", PKUSEG_TOKENIZER_TESTS)
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def test_zh_tokenizer_pkuseg(zh_tokenizer_pkuseg, text, expected_tokens):
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tokens = [token.text for token in zh_tokenizer_pkuseg(text)]
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assert tokens == expected_tokens
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def test_zh_tokenizer_pkuseg_user_dict(zh_tokenizer_pkuseg, zh_tokenizer_char):
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user_dict = _get_pkuseg_trie_data(zh_tokenizer_pkuseg.pkuseg_seg.preprocesser.trie)
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zh_tokenizer_pkuseg.pkuseg_update_user_dict(["nonsense_asdf"])
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updated_user_dict = _get_pkuseg_trie_data(
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zh_tokenizer_pkuseg.pkuseg_seg.preprocesser.trie
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)
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assert len(user_dict) == len(updated_user_dict) - 1
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# reset user dict
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zh_tokenizer_pkuseg.pkuseg_update_user_dict([], reset=True)
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reset_user_dict = _get_pkuseg_trie_data(
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zh_tokenizer_pkuseg.pkuseg_seg.preprocesser.trie
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)
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assert len(reset_user_dict) == 0
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# warn if not relevant
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with pytest.warns(UserWarning):
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zh_tokenizer_char.pkuseg_update_user_dict(["nonsense_asdf"])
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def test_zh_extra_spaces(zh_tokenizer_char):
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# note: three spaces after "I"
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tokens = zh_tokenizer_char("I like cheese.")
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assert tokens[1].orth_ == " "
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def test_zh_unsupported_segmenter():
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config = {"nlp": {"tokenizer": {"segmenter": "unk"}}}
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with pytest.raises(ConfigValidationError):
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Chinese.from_config(config)
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def test_zh_uninitialized_pkuseg():
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config = {"nlp": {"tokenizer": {"segmenter": "char"}}}
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nlp = Chinese.from_config(config)
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nlp.tokenizer.segmenter = "pkuseg"
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with pytest.raises(ValueError):
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nlp("test")
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