Source code for transformers.models.retribert.tokenization_retribert

# coding=utf-8
# Copyright 2018 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.
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#     http://www.apache.org/licenses/LICENSE-2.0
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"""Tokenization classes for RetriBERT."""

from ...utils import logging
from ..bert.tokenization_bert import BertTokenizer


logger = logging.get_logger(__name__)

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

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

PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
    "yjernite/retribert-base-uncased": 512,
}


PRETRAINED_INIT_CONFIGURATION = {
    "yjernite/retribert-base-uncased": {"do_lower_case": True},
}


[docs]class RetriBertTokenizer(BertTokenizer): r""" Constructs a RetriBERT tokenizer. :class:`~transformers.RetroBertTokenizer` is identical to :class:`~transformers.BertTokenizer` and runs end-to-end tokenization: punctuation splitting and wordpiece. Refer to superclass :class:`~transformers.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 model_input_names = ["input_ids", "attention_mask"]