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update tokenizer - update squad example for xlnet

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thomwolf
2019-07-15 17:30:42 +02:00
parent 3b469cb422
commit 15d8b1266c
20 changed files with 191 additions and 131 deletions
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72
pytorch_transformers/tokenization_utils.py
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@@ -361,52 +361,26 @@ class PreTrainedTokenizer(object):
(resp.) a sequence of ids, using the vocabulary.
"""
if isinstance(tokens, str) or (six.PY2 and isinstance(tokens, unicode)):
return self.convert_token_to_id_with_added_voc(tokens)
return self._convert_token_to_id_with_added_voc(tokens)
ids = []
for token in tokens:
ids.append(self.convert_token_to_id_with_added_voc(token))
ids.append(self._convert_token_to_id_with_added_voc(token))
if len(ids) > self.max_len:
logger.warning("Token indices sequence length is longer than the specified maximum sequence length "
"for this model ({} > {}). Running this sequence through the model will result in "
"indexing errors".format(len(ids), self.max_len))
return ids
def convert_token_to_id_with_added_voc(self, token):
def _convert_token_to_id_with_added_voc(self, token):
if token in self.added_tokens_encoder:
return self.added_tokens_encoder[token]
return self._convert_token_to_id(token)
def _convert_token_to_id(self, token):
raise NotImplementedError
def convert_ids_to_tokens(self, ids, skip_special_tokens=False):
""" Converts a single index or a sequence of indices (integers) in a token "
(resp.) a sequence of tokens (str/unicode), using the vocabulary and added tokens.
Args:
skip_special_tokens: Don't decode special tokens (self.all_special_tokens). Default: False
"""
if isinstance(ids, int):
return self.convert_id_to_token(ids)
tokens = []
for index in ids:
if index in self.all_special_ids and skip_special_tokens:
continue
if index in self.added_tokens_decoder:
tokens.append(self.added_tokens_decoder[index])
else:
tokens.append(self._convert_id_to_token(index))
return tokens
def _convert_id_to_token(self, index):
raise NotImplementedError
def encode(self, text):
""" Converts a string in a sequence of ids (integer), using the tokenizer and vocabulary.
same as self.convert_tokens_to_ids(self.tokenize(text)).
@@ -414,22 +388,48 @@ class PreTrainedTokenizer(object):
return self.convert_tokens_to_ids(self.tokenize(text))
def convert_ids_to_tokens(self, ids, skip_special_tokens=False):
""" Converts a single index or a sequence of indices (integers) in a token "
(resp.) a sequence of tokens (str/unicode), using the vocabulary and added tokens.
Args:
skip_special_tokens: Don't decode special tokens (self.all_special_tokens). Default: False
"""
if isinstance(ids, int):
if ids in self.added_tokens_decoder:
return self.added_tokens_decoder[ids]
else:
return self._convert_id_to_token(ids)
tokens = []
for index in ids:
if index in self.all_special_ids and skip_special_tokens:
continue
if index in self.added_tokens_decoder:
tokens.append(self.added_tokens_decoder[index])
else:
tokens.append(self._convert_id_to_token(index))
return tokens
def _convert_id_to_token(self, index):
raise NotImplementedError
def convert_tokens_to_string(self, tokens):
""" Converts a sequence of tokens (string) in a single string.
The most simple way to do it is ' '.join(self.convert_ids_to_tokens(token_ids))
but we often want to remove sub-word tokenization artifacts at the same time.
"""
return ' '.join(self.convert_ids_to_tokens(tokens))
def decode(self, token_ids, skip_special_tokens=False, clean_up_tokenization_spaces=True):
""" Converts a sequence of ids (integer) in a string, using the tokenizer and vocabulary
with options to remove special tokens and clean up tokenization spaces.
"""
filtered_tokens = self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens)
text = self._convert_ids_to_string(filtered_tokens)
text = self.convert_tokens_to_string(filtered_tokens)
if clean_up_tokenization_spaces:
text = clean_up_tokenization(text)
return text
def _convert_ids_to_string(self, tokens_ids):
""" Converts a sequence of ids (integer) in a string, using the tokenizer and vocabulary.
roughtly same as ' '.join(self.convert_ids_to_tokens(token_ids)).
"""
return ' '.join(self.convert_ids_to_tokens(tokens_ids))
@property
def special_tokens_map(self):
""" A dictionary mapping special token class attribute (cls_token, unk_token...) to their