PreFLMR_ViT-G / tokenization_flmr_fast.py
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# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team, The Hugging Face 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
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"""Tokenization classes for FLMR."""
from transformers.utils import logging
from transformers.models.bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_flmr import FLMRContextEncoderTokenizer, FLMRQueryEncoderTokenizer
logger = logging.get_logger(__name__)
VOCAB_FILES_NAMES = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer_config.json"}
CONTEXT_ENCODER_PRETRAINED_VOCAB_FILES_MAP = {
"vocab_file": {
"LinWeizheDragon/PreFLMR_ViT-L": (
"https://huggingface.co/LinWeizheDragon/PreFLMR_ViT-L/resolve/main/context_tokenizer/vocab.txt"
),
"LinWeizheDragon/FLMR": (
"https://huggingface.co/LinWeizheDragon/FLMR/resolve/main/context_tokenizer/vocab.txt"
),
},
"tokenizer_file": {
"LinWeizheDragon/PreFLMR_ViT-L": (
"https://huggingface.co/LinWeizheDragon/PreFLMR_ViT-L/resolve/main/context_tokenizer/tokenizer_config.json"
),
"LinWeizheDragon/FLMR": (
"https://huggingface.co/LinWeizheDragon/FLMR/resolve/main/context_tokenizer/tokenizer_config.json"
),
},
}
QUESTION_ENCODER_PRETRAINED_VOCAB_FILES_MAP = {
"vocab_file": {
"LinWeizheDragon/PreFLMR_ViT-L": (
"https://huggingface.co/LinWeizheDragon/PreFLMR_ViT-L/resolve/main/query_tokenizer/vocab.txt"
),
"LinWeizheDragon/FLMR": ("https://huggingface.co/LinWeizheDragon/FLMR/resolve/main/query_tokenizer/vocab.txt"),
},
"tokenizer_file": {
"LinWeizheDragon/PreFLMR_ViT-L": (
"https://huggingface.co/LinWeizheDragon/PreFLMR_ViT-L/resolve/main/query_tokenizer/tokenizer_config.json"
),
"LinWeizheDragon/FLMR": (
"https://huggingface.co/LinWeizheDragon/FLMR/resolve/main/query_tokenizer/tokenizer_config.json"
),
},
}
CONTEXT_ENCODER_PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
"LinWeizheDragon/PreFLMR_ViT-L": 512,
"LinWeizheDragon/FLMR": 512,
}
QUESTION_ENCODER_PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
"LinWeizheDragon/PreFLMR_ViT-L": 512,
"LinWeizheDragon/FLMR": 512,
}
CONTEXT_ENCODER_PRETRAINED_INIT_CONFIGURATION = {
"LinWeizheDragon/PreFLMR_ViT-L": {"do_lower_case": True},
"LinWeizheDragon/FLMR": {"do_lower_case": True},
}
QUESTION_ENCODER_PRETRAINED_INIT_CONFIGURATION = {
"LinWeizheDragon/PreFLMR_ViT-L": {"do_lower_case": True},
"LinWeizheDragon/FLMR": {"do_lower_case": True},
}
class FLMRContextEncoderTokenizerFast(BertTokenizerFast):
r"""
Construct a "fast" FLMRContextEncoder tokenizer (backed by HuggingFace's *tokenizers* library).
[`FLMRContextEncoderTokenizerFast`] is identical to [`BertTokenizerFast`] and runs end-to-end tokenization:
punctuation splitting and wordpiece.
Refer to superclass [`BertTokenizerFast`] for usage examples and documentation concerning parameters.
"""
vocab_files_names = VOCAB_FILES_NAMES
pretrained_vocab_files_map = CONTEXT_ENCODER_PRETRAINED_VOCAB_FILES_MAP
max_model_input_sizes = CONTEXT_ENCODER_PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
pretrained_init_configuration = CONTEXT_ENCODER_PRETRAINED_INIT_CONFIGURATION
slow_tokenizer_class = FLMRContextEncoderTokenizer
class FLMRQueryEncoderTokenizerFast(BertTokenizerFast):
r"""
Constructs a "fast" FLMRQueryEncoderTokenizer tokenizer (backed by HuggingFace's *tokenizers* library).
[`FLMRQueryEncoderTokenizerFast`] is identical to [`BertTokenizerFast`] and runs end-to-end tokenization:
punctuation splitting and wordpiece.
Refer to superclass [`BertTokenizerFast`] for usage examples and documentation concerning parameters.
"""
vocab_files_names = VOCAB_FILES_NAMES
pretrained_vocab_files_map = QUESTION_ENCODER_PRETRAINED_VOCAB_FILES_MAP
max_model_input_sizes = QUESTION_ENCODER_PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
pretrained_init_configuration = QUESTION_ENCODER_PRETRAINED_INIT_CONFIGURATION
slow_tokenizer_class = FLMRQueryEncoderTokenizer