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tokenization_layoutlm_fast.py
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tokenization_layoutlm_fast.py
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# 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.
# See the License for the specific language governing permissions and
# limitations under the License.
""" 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
},
}
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
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