Source code for transformers.tokenization_mobilebert

# coding=utf-8
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"""Tokenization classes for MobileBERT."""

from .tokenization_bert import BertTokenizer, BertTokenizerFast
from .utils import logging


logger = logging.get_logger(__name__)

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

PRETRAINED_VOCAB_FILES_MAP = {
    "vocab_file": {
        "mobilebert-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/google/mobilebert-uncased/vocab.txt"
    }
}

PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {}


PRETRAINED_INIT_CONFIGURATION = {}


class MobileBertTokenizer(BertTokenizer):
    r"""
    Construct a MobileBERT tokenizer.

    :class:`~transformers.MobileBertTokenizer 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


class MobileBertTokenizerFast(BertTokenizerFast):
    r"""
    Construct a "fast" MobileBERT tokenizer (backed by HuggingFace's `tokenizers` library).

    :class:`~transformers.MobileBertTokenizerFast` is identical to :class:`~transformers.BertTokenizerFast` and runs
    end-to-end tokenization: punctuation splitting and wordpiece.

    Refer to superclass :class:`~transformers.BertTokenizerFast` 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