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	* Integrate models into pipeline * Add basic serialization (maybe incorrect) * Fix pickle on vocab
		
			
				
	
	
		
			36 lines
		
	
	
		
			1.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			36 lines
		
	
	
		
			1.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| # coding: utf-8
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| from __future__ import unicode_literals
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| 
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| import pytest
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| import dill as pickle
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| 
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| from ..vocab import Vocab
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| from ..attrs import NORM
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| 
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| 
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| @pytest.mark.parametrize('text1,text2', [('hello', 'bye')])
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| def test_pickle_string_store(stringstore, text1, text2):
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|     store1 = stringstore[text1]
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|     store2 = stringstore[text2]
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|     data = pickle.dumps(stringstore, protocol=-1)
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|     unpickled = pickle.loads(data)
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|     assert unpickled[text1] == store1
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|     assert unpickled[text2] == store2
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|     assert len(stringstore) == len(unpickled)
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| 
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| 
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| @pytest.mark.parametrize('text1,text2', [('dog', 'cat')])
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| def test_pickle_vocab(text1, text2):
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|     vocab = Vocab(lex_attr_getters={int(NORM): lambda string: string[:-1]})
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|     lex1 = vocab[text1]
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|     lex2 = vocab[text2]
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|     assert lex1.norm_ == text1[:-1]
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|     assert lex2.norm_ == text2[:-1]
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|     data = pickle.dumps(vocab)
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|     unpickled = pickle.loads(data)
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|     assert unpickled[text1].orth == lex1.orth
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|     assert unpickled[text2].orth == lex2.orth
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|     assert unpickled[text1].norm == lex1.norm
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|     assert unpickled[text2].norm == lex2.norm
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|     assert unpickled[text1].norm != unpickled[text2].norm
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