Source code for transformers.models.layoutlm.tokenization_layoutlm_fast

# coding=utf-8
# Copyright 2018 The Microsoft Research Asia LayoutLM Team Authors.
#
# 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.
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""" Tokenization class for model LayoutLM."""


from ...utils import logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_layoutlm import LayoutLMTokenizer


logger = logging.get_logger(__name__)

VOCAB_FILES_NAMES = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

PRETRAINED_VOCAB_FILES_MAP = {
    "vocab_file": {
        "microsoft/layoutlm-base-uncased": "https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/vocab.txt",
        "microsoft/layoutlm-large-uncased": "https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/vocab.txt",
    },
    "tokenizer_file": {
        "microsoft/layoutlm-base-uncased": "https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/tokenizer.json",
        "microsoft/layoutlm-large-uncased": "https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/tokenizer.json",
    },
}


PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
    "microsoft/layoutlm-base-uncased": 512,
    "microsoft/layoutlm-large-uncased": 512,
}


PRETRAINED_INIT_CONFIGURATION = {
    "microsoft/layoutlm-base-uncased": {"do_lower_case": True},
    "microsoft/layoutlm-large-uncased": {"do_lower_case": True},
}


[docs]class LayoutLMTokenizerFast(BertTokenizerFast): r""" Constructs a "Fast" LayoutLMTokenizer. :class:`~transformers.LayoutLMTokenizerFast` is identical to :class:`~transformers.BertTokenizerFast` and runs end-to-end tokenization: punctuation splitting + wordpiece. Refer to superclass :class:`~transformers.BertTokenizerFast` for usage examples and documentation concerning parameters. """ vocab_files_names = VOCAB_FILES_NAMES pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES pretrained_init_configuration = PRETRAINED_INIT_CONFIGURATION slow_tokenizer_class = LayoutLMTokenizer