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Source code for transformers.models.bart.tokenization_bart
# coding=utf-8
# Copyright 2020 The Facebook AI Research 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
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# 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.
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from ...utils import logging
from ..roberta.tokenization_roberta import RobertaTokenizer
logger = logging.get_logger(__name__)
# vocab and merges same as roberta
vocab_url = "https://huggingface.co/roberta-large/resolve/main/vocab.json"
merges_url = "https://huggingface.co/roberta-large/resolve/main/merges.txt"
_all_bart_models = [
"facebook/bart-base",
"facebook/bart-large",
"facebook/bart-large-mnli",
"facebook/bart-large-cnn",
"facebook/bart-large-xsum",
"yjernite/bart_eli5",
# This is not exhaustive: see https://huggingface.co/models?filter=bart
]
[docs]class BartTokenizer(RobertaTokenizer):
r"""
Construct a BART tokenizer.
:class:`~transformers.BartTokenizer` is identical to :class:`~transformers.RobertaTokenizer`. Refer to superclass
:class:`~transformers.RobertaTokenizer` for usage examples and documentation concerning the initialization
parameters and other methods.
"""
# merges and vocab same as Roberta
max_model_input_sizes = {m: 1024 for m in _all_bart_models}
pretrained_vocab_files_map = {
"vocab_file": {m: vocab_url for m in _all_bart_models},
"merges_file": {m: merges_url for m in _all_bart_models},
}