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