61 lines
2.2 KiB
Python
61 lines
2.2 KiB
Python
# coding=utf-8
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# Copyright 2020 The Allen Institute for AI team 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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import logging
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from .tokenization_roberta import RobertaTokenizer, RobertaTokenizerFast
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logger = logging.getLogger(__name__)
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# vocab and merges same as roberta
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vocab_url = "https://s3.amazonaws.com/models.huggingface.co/bert/roberta-large-vocab.json"
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merges_url = "https://s3.amazonaws.com/models.huggingface.co/bert/roberta-large-merges.txt"
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_all_longformer_models = [
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"allenai/longformer-base-4096",
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"allenai/longformer-large-4096",
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"allenai/longformer-large-4096-finetuned-triviaqa",
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"allenai/longformer-base-4096-extra.pos.embd.only",
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"allenai/longformer-large-4096-extra.pos.embd.only",
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]
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PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
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"allenai/longformer-base-4096": 4096,
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"allenai/longformer-large-4096": 4096,
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"allenai/longformer-large-4096-finetuned-triviaqa": 4096,
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"allenai/longformer-base-4096-extra.pos.embd.only": 4096,
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"allenai/longformer-large-4096-extra.pos.embd.only": 4096,
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}
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class LongformerTokenizer(RobertaTokenizer):
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# merges and vocab same as Roberta
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max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
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pretrained_vocab_files_map = {
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"vocab_file": {m: vocab_url for m in _all_longformer_models},
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"merges_file": {m: merges_url for m in _all_longformer_models},
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}
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class LongformerTokenizerFast(RobertaTokenizerFast):
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# merges and vocab same as Roberta
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max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
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pretrained_vocab_files_map = {
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"vocab_file": {m: vocab_url for m in _all_longformer_models},
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"merges_file": {m: merges_url for m in _all_longformer_models},
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}
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