PreFLMR_ViT-L / 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
	# limitations under the License.
	"""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