Source code for transformers.models.mobilebert.tokenization_mobilebert_fast

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#     http://www.apache.org/licenses/LICENSE-2.0
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"""Tokenization classes for MobileBERT."""

from ...utils import logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_mobilebert import MobileBertTokenizer


logger = logging.get_logger(__name__)

VOCAB_FILES_NAMES = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

PRETRAINED_VOCAB_FILES_MAP = {
    "vocab_file": {"mobilebert-uncased": "https://huggingface.co/google/mobilebert-uncased/resolve/main/vocab.txt"},
    "tokenizer_file": {
        "mobilebert-uncased": "https://huggingface.co/google/mobilebert-uncased/resolve/main/tokenizer.json"
    },
}

PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {"mobilebert-uncased": 512}


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
    slow_tokenizer_class = MobileBertTokenizer