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	* Get basic beam tests working * Get basic beam tests working * Compile _beam_utils * Remove prints * Test beam density * Beam parser seems to train * Draft beam NER * Upd beam * Add hypothesis as dev dependency * Implement missing is-gold-parse method * Implement early update * Fix state hashing * Fix test * Fix test * Default to non-beam in parser constructor * Improve oracle for beam * Start refactoring beam * Update test * Refactor beam * Update nn * Refactor beam and weight by cost * Update ner beam settings * Update test * Add __init__.pxd * Upd test * Fix test * Upd test * Fix test * Remove ring buffer history from StateC * WIP change arc-eager transitions * Add state tests * Support ternary sent start values * Fix arc eager * Fix NER * Pass oracle cut size for beam * Fix ner test * Fix beam * Improve StateC.clone * Improve StateClass.borrow * Work directly with StateC, not StateClass * Remove print statements * Fix state copy * Improve state class * Refactor parser oracles * Fix arc eager oracle * Fix arc eager oracle * Use a vector to implement the stack * Refactor state data structure * Fix alignment of sent start * Add get_aligned_sent_starts method * Add test for ae oracle when bad sentence starts * Fix sentence segment handling * Avoid Reduce that inserts illegal sentence * Update preset SBD test * Fix test * Remove prints * Fix sent starts in Example * Improve python API of StateClass * Tweak comments and debug output of arc eager * Upd test * Fix state test * Fix state test
		
			
				
	
	
		
			93 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			93 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import pytest
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| from thinc.api import Adam
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| from spacy.attrs import NORM
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| from spacy.vocab import Vocab
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| from spacy import registry
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| from spacy.training import Example
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| from spacy.pipeline.dep_parser import DEFAULT_PARSER_MODEL
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| from spacy.tokens import Doc
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| from spacy.pipeline import DependencyParser
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| 
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| 
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| @pytest.fixture
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| def vocab():
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|     return Vocab(lex_attr_getters={NORM: lambda s: s})
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| 
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| 
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| def _parser_example(parser):
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|     doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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|     gold = {"heads": [1, 1, 3, 3], "deps": ["right", "ROOT", "left", "ROOT"]}
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|     return Example.from_dict(doc, gold)
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| 
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| 
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| @pytest.fixture
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| def parser(vocab):
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|     vocab.strings.add("ROOT")
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|     config = {
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|         "learn_tokens": False,
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|         "min_action_freq": 30,
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|         "update_with_oracle_cut_size": 100,
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|     }
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|     cfg = {"model": DEFAULT_PARSER_MODEL}
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|     model = registry.resolve(cfg, validate=True)["model"]
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|     parser = DependencyParser(vocab, model, **config)
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|     parser.cfg["token_vector_width"] = 4
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|     parser.cfg["hidden_width"] = 32
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|     # parser.add_label('right')
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|     parser.add_label("left")
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|     parser.initialize(lambda: [_parser_example(parser)])
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|     sgd = Adam(0.001)
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| 
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|     for i in range(10):
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|         losses = {}
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|         doc = Doc(vocab, words=["a", "b", "c", "d"])
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|         example = Example.from_dict(
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|             doc, {"heads": [1, 1, 3, 3], "deps": ["left", "ROOT", "left", "ROOT"]}
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|         )
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|         parser.update([example], sgd=sgd, losses=losses)
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|     return parser
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| 
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| 
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| def test_no_sentences(parser):
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|     doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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|     doc = parser(doc)
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|     assert len(list(doc.sents)) >= 1
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| 
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| 
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| def test_sents_1(parser):
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|     doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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|     doc[2].sent_start = True
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|     doc = parser(doc)
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|     assert len(list(doc.sents)) >= 2
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|     doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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|     doc[1].sent_start = False
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|     doc[2].sent_start = True
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|     doc[3].sent_start = False
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|     doc = parser(doc)
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|     assert len(list(doc.sents)) == 2
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| 
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| 
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| def test_sents_1_2(parser):
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|     doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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|     doc[1].sent_start = True
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|     doc[2].sent_start = True
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|     doc = parser(doc)
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|     assert len(list(doc.sents)) >= 3
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| 
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| 
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| def test_sents_1_3(parser):
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|     doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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|     doc[0].is_sent_start = True
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|     doc[1].is_sent_start = True
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|     doc[2].is_sent_start = None
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|     doc[3].is_sent_start = True
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|     doc = parser(doc)
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|     assert len(list(doc.sents)) >= 3
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|     doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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|     doc[0].is_sent_start = True
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|     doc[1].is_sent_start = True
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|     doc[2].is_sent_start = False
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|     doc[3].is_sent_start = True
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|     doc = parser(doc)
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|     assert len(list(doc.sents)) == 3
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