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R# )z$Tokenization classes for FNet model.)Úlogging)ÚAlbertTokenizerc                   ó"   € ] tR t^tRtRR.tRtR# )ÚFNetTokenizera
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Construct an FNet tokenizer. Based on [Unigram](https://huggingface.co/docs/tokenizers/python/latest/components.html?highlight=unigram#models).

This tokenizer inherits from [`AlbertTokenizer`] which contains most of the main methods. Users should refer to
this superclass for more information regarding those methods.

Args:
    do_lower_case (`bool`, *optional*, defaults to `True`):
        Whether or not to lowercase the input when tokenizing.
    keep_accents (`bool`, *optional*, defaults to `False`):
        Whether or not to keep accents when tokenizing.
    bos_token (`str`, *optional*, defaults to `"[CLS]"`):
        The beginning of sequence token that was used during pretraining. Can be used a sequence classifier token.
    eos_token (`str`, *optional*, defaults to `"[SEP]"`):
        The end of sequence token.
    unk_token (`str`, *optional*, defaults to `"<unk>"`):
        The unknown token. A token that is not in the vocabulary cannot be converted to an ID and is set to be this
        token instead.
    sep_token (`str`, *optional*, defaults to `"[SEP]"`):
        The separator token, which is used when building a sequence from multiple sequences, e.g. two sequences for
        sequence classification or for a text and a question for question answering. It is also used as the last
        token of a sequence built with special tokens.
    pad_token (`str`, *optional*, defaults to `"<pad>"`):
        The token used for padding, for example when batching sequences of different lengths.
    cls_token (`str`, *optional*, defaults to `"[CLS]"`):
        The classifier token which is used when doing sequence classification (classification of the whole sequence
        instead of per-token classification). It is the first token of the sequence when built with special tokens.
    mask_token (`str`, *optional*, defaults to `"[MASK]"`):
        The token used for masking values. This is the token used when training this model with masked language
        modeling. This is the token which the model will try to predict.
Ú	input_idsÚtoken_type_ids© N)Ú__name__Ú
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