tokenization_distilbert.py

# 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.
# 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,
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"""Tokenization classes for DistilBERT."""


import logging

from .tokenization_bert import BertTokenizer


logger = logging.getLogger(__name__)

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

PRETRAINED_VOCAB_FILES_MAP = {
    "vocab_file": {
        "distilbert-base-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt",
        "distilbert-base-uncased-distilled-squad": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-vocab.txt",
        "distilbert-base-german-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/distilbert-base-german-cased-vocab.txt",
        "distilbert-base-multilingual-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-multilingual-cased-vocab.txt",
    }
}

PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
    "distilbert-base-uncased": 512,
    "distilbert-base-uncased-distilled-squad": 512,
    "distilbert-base-german-cased": 512,
    "distilbert-base-multilingual-cased": 512,
}


class DistilBertTokenizer(BertTokenizer):
    r"""
    Constructs a DistilBertTokenizer.
    :class:`~transformers.DistilBertTokenizer` is identical to BertTokenizer and runs end-to-end tokenization: punctuation splitting + wordpiece

    Args:
        vocab_file: Path to a one-wordpiece-per-line vocabulary file
        do_lower_case: Whether to lower case the input. Only has an effect when do_basic_tokenize=True
        do_basic_tokenize: Whether to do basic tokenization before wordpiece.
        max_len: An artificial maximum length to truncate tokenized sequences to; Effective maximum length is always the
            minimum of this value (if specified) and the underlying BERT model's sequence length.
        never_split: List of tokens which will never be split during tokenization. Only has an effect when
            do_basic_tokenize=True
    """

    vocab_files_names = VOCAB_FILES_NAMES
    pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
    max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES