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	* Add Lemmatizer and simplify related components * Add `Lemmatizer` pipe with `lookup` and `rule` modes using the `Lookups` tables. * Reduce `Tagger` to a simple tagger that sets `Token.tag` (no pos or lemma) * Reduce `Morphology` to only keep track of morph tags (no tag map, lemmatizer, or morph rules) * Remove lemmatizer from `Vocab` * Adjust many many tests Differences: * No default lookup lemmas * No special treatment of TAG in `from_array` and similar required * Easier to modify labels in a `Tagger` * No extra strings added from morphology / tag map * Fix test * Initial fix for Lemmatizer config/serialization * Adjust init test to be more generic * Adjust init test to force empty Lookups * Add simple cache to rule-based lemmatizer * Convert language-specific lemmatizers Convert language-specific lemmatizers to component lemmatizers. Remove previous lemmatizer class. * Fix French and Polish lemmatizers * Remove outdated UPOS conversions * Update Russian lemmatizer init in tests * Add minimal init/run tests for custom lemmatizers * Add option to overwrite existing lemmas * Update mode setting, lookup loading, and caching * Make `mode` an immutable property * Only enforce strict `load_lookups` for known supported modes * Move caching into individual `_lemmatize` methods * Implement strict when lang is not found in lookups * Fix tables/lookups in make_lemmatizer * Reallow provided lookups and allow for stricter checks * Add lookups asset to all Lemmatizer pipe tests * Rename lookups in lemmatizer init test * Clean up merge * Refactor lookup table loading * Add helper from `load_lemmatizer_lookups` that loads required and optional lookups tables based on settings provided by a config. Additional slight refactor of lookups: * Add `Lookups.set_table` to set a table from a provided `Table` * Reorder class definitions to be able to specify type as `Table` * Move registry assets into test methods * Refactor lookups tables config Use class methods within `Lemmatizer` to provide the config for particular modes and to load the lookups from a config. * Add pipe and score to lemmatizer * Simplify Tagger.score * Add missing import * Clean up imports and auto-format * Remove unused kwarg * Tidy up and auto-format * Update docstrings for Lemmatizer Update docstrings for Lemmatizer. Additionally modify `is_base_form` API to take `Token` instead of individual features. * Update docstrings * Remove tag map values from Tagger.add_label * Update API docs * Fix relative link in Lemmatizer API docs
		
			
				
	
	
		
			152 lines
		
	
	
		
			4.5 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			152 lines
		
	
	
		
			4.5 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import pytest
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| from spacy.vocab import Vocab
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| from spacy.tokenizer import Tokenizer
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| from spacy.util import ensure_path
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| 
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| 
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| def test_tokenizer_handles_no_word(tokenizer):
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|     tokens = tokenizer("")
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|     assert len(tokens) == 0
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| 
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| 
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| @pytest.mark.parametrize("text", ["lorem"])
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| def test_tokenizer_handles_single_word(tokenizer, text):
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|     tokens = tokenizer(text)
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|     assert tokens[0].text == text
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| 
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| 
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| def test_tokenizer_handles_punct(tokenizer):
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|     text = "Lorem, ipsum."
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|     tokens = tokenizer(text)
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|     assert len(tokens) == 4
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|     assert tokens[0].text == "Lorem"
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|     assert tokens[1].text == ","
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|     assert tokens[2].text == "ipsum"
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|     assert tokens[1].text != "Lorem"
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| 
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| 
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| def test_tokenizer_handles_punct_braces(tokenizer):
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|     text = "Lorem, (ipsum)."
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|     tokens = tokenizer(text)
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|     assert len(tokens) == 6
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| 
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| 
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| def test_tokenizer_handles_digits(tokenizer):
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|     exceptions = ["hu", "bn"]
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|     text = "Lorem ipsum: 1984."
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|     tokens = tokenizer(text)
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| 
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|     if tokens[0].lang_ not in exceptions:
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|         assert len(tokens) == 5
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|         assert tokens[0].text == "Lorem"
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|         assert tokens[3].text == "1984"
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| 
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| 
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| @pytest.mark.parametrize(
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|     "text",
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|     ["google.com", "python.org", "spacy.io", "explosion.ai", "http://www.google.com"],
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| )
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| def test_tokenizer_keep_urls(tokenizer, text):
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|     tokens = tokenizer(text)
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|     assert len(tokens) == 1
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| 
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| 
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| @pytest.mark.parametrize("text", ["NASDAQ:GOOG"])
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| def test_tokenizer_colons(tokenizer, text):
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|     tokens = tokenizer(text)
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|     assert len(tokens) == 3
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| 
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| 
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| @pytest.mark.parametrize(
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|     "text", ["hello123@example.com", "hi+there@gmail.it", "matt@explosion.ai"]
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| )
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| def test_tokenizer_keeps_email(tokenizer, text):
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|     tokens = tokenizer(text)
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|     assert len(tokens) == 1
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| 
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| 
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| def test_tokenizer_handles_long_text(tokenizer):
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|     text = """Lorem ipsum dolor sit amet, consectetur adipiscing elit
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| 
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| Cras egestas orci non porttitor maximus.
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| Maecenas quis odio id dolor rhoncus dignissim. Curabitur sed velit at orci ultrices sagittis. Nulla commodo euismod arcu eget vulputate.
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| 
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| Phasellus tincidunt, augue quis porta finibus, massa sapien consectetur augue, non lacinia enim nibh eget ipsum. Vestibulum in bibendum mauris.
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| 
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| "Nullam porta fringilla enim, a dictum orci consequat in." Mauris nec malesuada justo."""
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| 
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|     tokens = tokenizer(text)
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|     assert len(tokens) > 5
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| 
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| 
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| @pytest.mark.parametrize("file_name", ["sun.txt"])
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| def test_tokenizer_handle_text_from_file(tokenizer, file_name):
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|     loc = ensure_path(__file__).parent / file_name
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|     text = loc.open("r", encoding="utf8").read()
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|     assert len(text) != 0
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|     tokens = tokenizer(text)
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|     assert len(tokens) > 100
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| 
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| 
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| def test_tokenizer_suspected_freeing_strings(tokenizer):
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|     text1 = "Lorem dolor sit amet, consectetur adipiscing elit."
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|     text2 = "Lorem ipsum dolor sit amet, consectetur adipiscing elit."
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|     tokens1 = tokenizer(text1)
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|     tokens2 = tokenizer(text2)
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|     assert tokens1[0].text == "Lorem"
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|     assert tokens2[0].text == "Lorem"
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| 
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| 
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| @pytest.mark.parametrize("text,tokens", [("lorem", [{"orth": "lo"}, {"orth": "rem"}])])
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| def test_tokenizer_add_special_case(tokenizer, text, tokens):
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|     tokenizer.add_special_case(text, tokens)
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|     doc = tokenizer(text)
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|     assert doc[0].text == tokens[0]["orth"]
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|     assert doc[1].text == tokens[1]["orth"]
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| 
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| 
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| @pytest.mark.parametrize("text,tokens", [("lorem", [{"orth": "lo"}, {"orth": "re"}])])
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| def test_tokenizer_validate_special_case(tokenizer, text, tokens):
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|     with pytest.raises(ValueError):
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|         tokenizer.add_special_case(text, tokens)
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| 
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| 
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| @pytest.mark.parametrize(
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|     "text,tokens", [("lorem", [{"orth": "lo", "norm": "LO"}, {"orth": "rem"}])]
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| )
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| def test_tokenizer_add_special_case_tag(text, tokens):
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|     vocab = Vocab()
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|     tokenizer = Tokenizer(vocab, {}, None, None, None)
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|     tokenizer.add_special_case(text, tokens)
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|     doc = tokenizer(text)
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|     assert doc[0].text == tokens[0]["orth"]
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|     assert doc[0].norm_ == tokens[0]["norm"]
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|     assert doc[1].text == tokens[1]["orth"]
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| 
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| 
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| def test_tokenizer_special_cases_with_affixes(tokenizer):
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|     text = '(((_SPECIAL_ A/B, A/B-A/B")'
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|     tokenizer.add_special_case("_SPECIAL_", [{"orth": "_SPECIAL_"}])
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|     tokenizer.add_special_case("A/B", [{"orth": "A/B"}])
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|     doc = tokenizer(text)
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|     assert [token.text for token in doc] == [
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|         "(",
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|         "(",
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|         "(",
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|         "_SPECIAL_",
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|         "A/B",
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|         ",",
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|         "A/B",
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|         "-",
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|         "A/B",
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|         '"',
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|         ")",
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|     ]
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| 
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| 
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| def test_tokenizer_special_cases_with_period(tokenizer):
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|     text = "_SPECIAL_."
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|     tokenizer.add_special_case("_SPECIAL_", [{"orth": "_SPECIAL_"}])
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|     doc = tokenizer(text)
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|     assert [token.text for token in doc] == ["_SPECIAL_", "."]
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