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Fixed error with encoding

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LysandreJik
2019-08-13 12:00:24 -04:00
parent 634a3172d8
commit 3d87991f60
2 changed files with 8 additions and 10 deletions
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11
pytorch_transformers/tokenization_utils.py
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@@ -519,24 +519,19 @@ class PreTrainedTokenizer(object):
def _convert_token_to_id(self, token):
raise NotImplementedError
def encode(self, text, add_special_tokens=False, *sequences):
def encode(self, text, text_pair=None, add_special_tokens=False):
""" Converts a string in a sequence of ids (integer), using the tokenizer and vocabulary.
Same doing ``self.convert_tokens_to_ids(self.tokenize(text))``.
"""
if len(sequences) == 0:
if text_pair is None:
if add_special_tokens:
return self.add_special_tokens_single_sentence(self.convert_tokens_to_ids(self.tokenize(text)))
else:
return self.convert_tokens_to_ids(self.tokenize(text))
if len(sequences) > 1:
logger.warning("Tokenization currently only supports sentence pairs. Ignoring every string following the "
"initial two.")
first_sentence_tokens = [self._convert_token_to_id(token) for token in self.tokenize(text)]
second_sentence_tokens = [self._convert_token_to_id(token) for token in self.tokenize(sequences[0])]
second_sentence_tokens = [self._convert_token_to_id(token) for token in self.tokenize(text_pair)]
if add_special_tokens:
return self.add_special_tokens_sentences_pair(first_sentence_tokens, second_sentence_tokens)