50 lines
2.1 KiB
Python
50 lines
2.1 KiB
Python
# Copyright (c) 2023 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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""" Tokenization classes for LayoutLMv2 model."""
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from ..bert.tokenizer import BertTokenizer
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__all__ = ["LayoutLMv2Tokenizer"]
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PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
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"layoutlmv2-base-uncased": 512,
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"layoutlmv2-large-uncased": 512,
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"layoutlmv2-wo-backbone-base-uncased": 512,
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}
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class LayoutLMv2Tokenizer(BertTokenizer):
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"""
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The usage of LayoutLMv2Tokenizer 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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"layoutlmv2-base-uncased": "https://bj.bcebos.com/paddlenlp/models/transformers/layoutlmv2/layoutlmv2-base-uncased/vocab.txt",
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"layoutlmv2-large-uncased": "https://bj.bcebos.com/paddlenlp/models/transformers/layoutlmv2/layoutlmv2-large-uncased/vocab.txt",
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"layoutlmv2-wo-backbone-base-uncased": "https://bj.bcebos.com/paddlenlp/models/transformers/layoutlmv2/layoutlmv2-base-uncased/vocab.txt",
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}
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}
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pretrained_init_configuration = {
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"layoutlmv2-base-uncased": {"do_lower_case": True},
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"layoutlmv2-large-uncased": {"do_lower_case": True},
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"layoutlmv2-wo-backbone-base-uncased": {"do_lower_case": True},
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}
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max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
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