# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..bert.tokenizer import BertTokenizer
__all__ = ["DistilBertTokenizer"]
PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {"distilbert-base-uncased": 512, "distilbert-base-cased": 512}
[文档]class DistilBertTokenizer(BertTokenizer):
"""
Constructs a DistilBert tokenizer. The usage of DistilBertTokenizer is the same as
`BertTokenizer <https://paddlenlp.readthedocs.io/zh/latest/source/paddlenlp.transformers.bert.tokenizer.html>`__.
For more information regarding those methods, please refer to this superclass.
"""
resource_files_names = {"vocab_file": "vocab.txt"} # for save_pretrained
pretrained_resource_files_map = {
"vocab_file": {
"distilbert-base-uncased": "https://bj.bcebos.com/paddlenlp/models/transformers/distilbert/distilbert-base-uncased-vocab.txt",
"distilbert-base-cased": "https://bj.bcebos.com/paddlenlp/models/transformers/distilbert/distilbert-base-cased-vocab.txt",
}
}
pretrained_init_configuration = {
"distilbert-base-uncased": {"do_lower_case": True},
"distilbert-base-cased": {"do_lower_case": False},
}
max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
def __call__(
self,
text,
text_pair=None,
max_seq_len=None,
stride=0,
is_split_into_words=False,
pad_to_max_seq_len=False,
truncation_strategy="longest_first",
return_position_ids=False,
return_token_type_ids=False,
return_attention_mask=False,
return_length=False,
return_overflowing_tokens=False,
return_special_tokens_mask=False,
):
return super(DistilBertTokenizer, self).__call__(
text,
text_pair,
max_seq_len,
stride,
is_split_into_words,
pad_to_max_seq_len,
truncation_strategy,
return_position_ids,
return_token_type_ids,
return_attention_mask,
return_length,
return_overflowing_tokens,
return_special_tokens_mask,
)