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* Add split one token into several (resolves #2838) * Improve error message for token splitting * Make retokenizer.split() tests use a Token object Change retokenizer.split() to use a Token object, instead of an index. * Pass Token into retokenize.split() Tweak retokenize.split() API so that we pass the `Token` object, not the index. * Fix token.idx in retokenize.split() * Test that token.idx is correct after split * Fix token.idx for split tokens * Fix retokenize.split() * Fix retokenize.split * Fix retokenize.split() test
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@ -253,6 +253,9 @@ class Errors(object):
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E098 = ("Trying to set conflicting doc.ents: '{span1}' and '{span2}'. A token"
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" can only be part of one entity, so make sure the entities you're "
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"setting don't overlap.")
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E099 = ("The newly split token can only have one root (head = 0).")
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E100 = ("The newly split token needs to have a root (head = 0)")
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E101 = ("All subtokens must have associated heads")
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@add_codes
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class TempErrors(object):
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114
spacy/tests/doc/test_doc_spilt.py
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114
spacy/tests/doc/test_doc_spilt.py
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@ -0,0 +1,114 @@
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# coding: utf-8
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from __future__ import unicode_literals
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from ..util import get_doc
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from ...vocab import Vocab
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from ...tokens import Doc
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from ...tokens import Span
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import pytest
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def test_doc_split(en_tokenizer):
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text = "LosAngeles start."
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heads = [1, 1, 0]
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads)
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assert len(doc) == 3
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assert len(str(doc)) == 19
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assert doc[0].head.text == 'start'
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assert doc[1].head.text == '.'
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [1, 0], attrs={'tag':'NNP', 'lemma':'Los Angeles', 'ent_type':'GPE'})
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assert len(doc) == 4
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assert doc[0].text == 'Los'
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assert doc[0].head.text == 'Angeles'
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assert doc[0].idx == 0
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assert doc[1].idx == 3
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assert doc[1].text == 'Angeles'
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assert doc[1].head.text == 'start'
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assert doc[2].text == 'start'
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assert doc[2].head.text == '.'
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assert doc[3].text == '.'
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assert doc[3].head.text == '.'
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assert len(str(doc)) == 19
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def test_split_dependencies(en_tokenizer):
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text = "LosAngeles start."
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, [t.text for t in tokens])
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dep1 = doc.vocab.strings.add('amod')
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dep2 = doc.vocab.strings.add('subject')
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [1, 0], [dep1, dep2])
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assert doc[0].dep == dep1
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assert doc[1].dep == dep2
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def test_split_heads_error(en_tokenizer):
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text = "LosAngeles start."
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, [t.text for t in tokens])
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#Not enough heads
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with pytest.raises(ValueError):
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [0])
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#Too many heads
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with pytest.raises(ValueError):
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [1, 1, 0])
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#No token head
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with pytest.raises(ValueError):
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [1, 1])
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#Several token heads
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with pytest.raises(ValueError):
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [0, 0])
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def test_spans_entity_merge_iob():
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# Test entity IOB stays consistent after merging
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words = ["abc", "d", "e"]
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doc = Doc(Vocab(), words=words)
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doc.ents = [(doc.vocab.strings.add('ent-abcd'), 0, 2)]
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assert doc[0].ent_iob_ == "B"
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assert doc[1].ent_iob_ == "I"
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["a", "b", "c"], [1, 1, 0])
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assert doc[0].ent_iob_ == "B"
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assert doc[1].ent_iob_ == "I"
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assert doc[2].ent_iob_ == "I"
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assert doc[3].ent_iob_ == "I"
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def test_spans_sentence_update_after_merge(en_tokenizer):
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text = "StewartLee is a stand up comedian. He lives in England and loves JoePasquale."
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heads = [1, 0, 1, 2, -1, -4, -5, 1, 0, -1, -1, -3, -4, 1, -2]
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deps = ['nsubj', 'ROOT', 'det', 'amod', 'prt', 'attr',
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'punct', 'nsubj', 'ROOT', 'prep', 'pobj', 'cc', 'conj',
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'compound', 'punct']
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, deps=deps)
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sent1, sent2 = list(doc.sents)
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init_len = len(sent1)
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init_len2 = len(sent2)
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Stewart", "Lee"], [1, 0])
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retokenizer.split(doc[14], ["Joe", "Pasquale"], [1, 0])
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sent1, sent2 = list(doc.sents)
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assert len(sent1) == init_len + 1
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assert len(sent2) == init_len2 + 1
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@ -43,12 +43,12 @@ cdef class Retokenizer:
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attrs = intify_attrs(attrs, strings_map=self.doc.vocab.strings)
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self.merges.append((span, attrs))
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def split(self, Token token, orths, attrs=SimpleFrozenDict()):
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def split(self, Token token, orths, heads, deps=[], attrs=SimpleFrozenDict()):
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"""Mark a Token for splitting, into the specified orths. The attrs
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will be applied to each subtoken.
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"""
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attrs = intify_attrs(attrs, strings_map=self.doc.vocab.strings)
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self.splits.append((token.start_char, orths, attrs))
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self.splits.append((token.i, orths, heads, deps, attrs))
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def __enter__(self):
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self.merges = []
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@ -65,8 +65,12 @@ cdef class Retokenizer:
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end = span.end
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_merge(self.doc, start, end, attrs)
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for start_char, orths, attrs in self.splits:
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raise NotImplementedError
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offset = 0
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# Iterate in order, to keep the offset simple.
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for token_index, orths, heads, deps, attrs in sorted(self.splits):
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_split(self.doc, token_index + offset, orths, heads, deps, attrs)
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# Adjust for the previous tokens
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offset += len(orths)-1
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def _merge(Doc doc, int start, int end, attributes):
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"""Retokenize the document, such that the span at
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@ -279,3 +283,111 @@ def _bulk_merge(Doc doc, merges):
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# Return the merged Python object
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return doc[spans[0].start]
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def _split(Doc doc, int token_index, orths, heads, deps, attrs):
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"""Retokenize the document, such that the token at
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`doc[token_index]` is split into tokens with the orth 'orths'
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token_index(int): token index of the token to split.
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orths: IDs of the verbatim text content of the tokens to create
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**attributes: Attributes to assign to each of the newly created tokens. By default,
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attributes are inherited from the original token.
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RETURNS (Token): The first newly created token.
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"""
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cdef int nb_subtokens = len(orths)
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cdef const LexemeC* lex
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cdef TokenC* token
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cdef TokenC orig_token = doc.c[token_index]
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if(len(heads) != nb_subtokens):
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raise ValueError(Errors.E101)
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token_head_index = -1
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for index, head in enumerate(heads):
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if head == 0:
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if token_head_index != -1:
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raise ValueError(Errors.E098)
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token_head_index = index
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if token_head_index == -1:
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raise ValueError(Errors.E099)
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# First, make the dependencies absolutes, and adjust all possible dependencies before
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# creating the tokens
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for i in range(doc.length):
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doc.c[i].head += i
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# Adjust dependencies
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offset = nb_subtokens - 1
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for i in range(doc.length):
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head_idx = doc.c[i].head
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if head_idx == token_index:
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doc.c[i].head = token_head_index
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elif head_idx > token_index:
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doc.c[i].head += offset
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new_token_head = doc.c[token_index].head
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# Double doc.c max_length if necessary (until big enough for all new tokens)
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while doc.length + nb_subtokens - 1 >= doc.max_length:
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doc._realloc(doc.length * 2)
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# Move tokens after the split to create space for the new tokens
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doc.length = len(doc) + nb_subtokens -1
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for token_to_move in range(doc.length - 1, token_index, -1):
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doc.c[token_to_move + nb_subtokens - 1] = doc.c[token_to_move]
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# Host the tokens in the newly created space
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cdef int idx_offset = 0
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for i, orth in enumerate(orths):
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token = &doc.c[token_index + i]
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lex = doc.vocab.get(doc.mem, orth)
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token.lex = lex
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# Update the character offset of the subtokens
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if i != 0:
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token.idx = orig_token.idx + idx_offset
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idx_offset += len(orth)
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# Set token.spacy to False for all non-last split tokens, and
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# to origToken.spacy for the last token
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if (i < nb_subtokens - 1):
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token.spacy = False
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else:
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token.spacy = orig_token.spacy
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# Apply attrs to each subtoken
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for attr_name, attr_value in attrs.items():
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if attr_name == TAG:
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doc.vocab.morphology.assign_tag(token, attr_value)
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else:
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Token.set_struct_attr(token, attr_name, attr_value)
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# Make IOB consistent
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if (orig_token.ent_iob == 3):
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if i == 0:
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token.ent_iob = 3
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else:
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token.ent_iob = 1
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else:
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# In all other cases subtokens inherit iob from origToken
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token.ent_iob = orig_token.ent_iob
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# Use the head of the new token everywhere. This will be partially overwritten later on.
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token.head = new_token_head
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# Transform the dependencies into relative ones again
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for i in range(doc.length):
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doc.c[i].head -= i
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# Assign correct dependencies to the inner token
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for i, head in enumerate(heads):
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if head != 0:
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# the token's head's head is already correct
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doc.c[token_index + i].head = head
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for i, dep in enumerate(deps):
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doc[token_index + i].dep = dep
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# set children from head
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set_children_from_heads(doc.c, doc.length)
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