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			74 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			74 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| # coding: utf-8
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| from __future__ import unicode_literals
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| 
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| from ..tokens import Doc
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| from ..attrs import ORTH, POS, HEAD, DEP
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| 
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| import numpy
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| 
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| 
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| def get_doc(vocab, words=[], pos=None, heads=None, deps=None, tags=None, ents=None):
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|     """Create Doc object from given vocab, words and annotations."""
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|     pos = pos or [''] * len(words)
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|     heads = heads or [0] * len(words)
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|     deps = deps or [''] * len(words)
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| 
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|     doc = Doc(vocab, words=words)
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|     attrs = doc.to_array([POS, HEAD, DEP])
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|     for i, (p, head, dep) in enumerate(zip(pos, heads, deps)):
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|         attrs[i, 0] = doc.vocab.strings[p]
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|         attrs[i, 1] = head
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|         attrs[i, 2] = doc.vocab.strings[dep]
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|     doc.from_array([POS, HEAD, DEP], attrs)
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|     if ents:
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|         doc.ents = [(ent_id, doc.vocab.strings[label], start, end) for ent_id, label, start, end in ents]
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|     if tags:
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|         for token in doc:
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|             token.tag_ = tags[token.i]
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|     return doc
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| 
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| 
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| def apply_transition_sequence(parser, doc, sequence):
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|     """Perform a series of pre-specified transitions, to put the parser in a
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|     desired state."""
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|     for action_name in sequence:
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|         if '-' in action_name:
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|             move, label = action_name.split('-')
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|             parser.add_label(label)
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|     with parser.step_through(doc) as stepwise:
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|         for transition in sequence:
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|             stepwise.transition(transition)
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| 
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| 
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| def add_vecs_to_vocab(vocab, vectors):
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|     """Add list of vector tuples to given vocab. All vectors need to have the
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|     same length. Format: [("text", [1, 2, 3])]"""
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|     length = len(vectors[0][1])
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|     vocab.resize_vectors(length)
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|     for word, vec in vectors:
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|         vocab[word].vector = vec
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|     return vocab
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| 
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| 
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| def get_cosine(vec1, vec2):
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|     """Get cosine for two given vectors"""
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|     return numpy.dot(vec1, vec2) / (numpy.linalg.norm(vec1) * numpy.linalg.norm(vec2))
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| 
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| 
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| def assert_docs_equal(doc1, doc2):
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|     """Compare two Doc objects and assert that they're equal. Tests for tokens,
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|     tags, dependencies and entities."""
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|     assert [ t.orth for t in doc1 ] == [ t.orth for t in doc2 ]
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| 
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|     assert [ t.pos for t in doc1 ] == [ t.pos for t in doc2 ]
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|     assert [ t.tag for t in doc1 ] == [ t.tag for t in doc2 ]
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| 
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|     assert [ t.head.i for t in doc1 ] == [ t.head.i for t in doc2 ]
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|     assert [ t.dep for t in doc1 ] == [ t.dep for t in doc2 ]
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|     if doc1.is_parsed and doc2.is_parsed:
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|         assert [ s for s in doc1.sents ] == [ s for s in doc2.sents ]
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| 
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|     assert [ t.ent_type for t in doc1 ] == [ t.ent_type for t in doc2 ]
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|     assert [ t.ent_iob for t in doc1 ] == [ t.ent_iob for t in doc2 ]
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|     assert [ ent for ent in doc1.ents ] == [ ent for ent in doc2.ents ]
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