FM / lxmert

/usr/local/lib/python3.6/site-packages/transformers/models/lxmert/

/usr/local/lib/python3.6/site-packages/transformers/models/lxmert

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_lxmert.py	9226	0644	edit dl rm
convert_lxmert_original_tf_checkpoint_to_pytorch.py	2120	0644	edit dl rm
modeling_lxmert.py	64969	0644	edit dl rm
modeling_tf_lxmert.py	62768	0644	edit dl rm
tokenization_lxmert.py	1675	0644	edit dl rm
tokenization_lxmert_fast.py	2037	0644	edit dl rm
__init__.py	2766	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/lxmert/tokenization_lxmert.py (1675B)

# coding=utf-8
# Copyright 2020 The Google AI Team, Stanford University 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
#
# 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.

from ..bert.tokenization_bert import BertTokenizer

VOCAB_FILES_NAMES = {"vocab_file": "vocab.txt"}

PRETRAINED_VOCAB_FILES_MAP = {
    "vocab_file": {
        "unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt",
    }
}

PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
    "unc-nlp/lxmert-base-uncased": 512,
}

PRETRAINED_INIT_CONFIGURATION = {
    "unc-nlp/lxmert-base-uncased": {"do_lower_case": True},
}

class LxmertTokenizer(BertTokenizer):
    r"""
    Construct an LXMERT tokenizer.

[`LxmertTokenizer`] is identical to [`BertTokenizer`] and runs end-to-end tokenization: punctuation splitting and
    wordpiece.

Refer to superclass [`BertTokenizer`] 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

cmd: