





from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer


_A					:				Optional[int]				=			logging.get_logger(__name__)

_A					:				Any				=			{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

_A					:				Any				=			{
    """vocab_file""": {
        """allegro/herbert-base-cased""": """https://huggingface.co/allegro/herbert-base-cased/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """allegro/herbert-base-cased""": """https://huggingface.co/allegro/herbert-base-cased/resolve/main/merges.txt"""
    },
}

_A					:				List[str]				=			{"""allegro/herbert-base-cased""": 5_14}
_A					:				Optional[Any]				=			{}



class 					__snake_case	(  __SCREAMING_SNAKE_CASE    ):


    '''simple docstring'''







    lowerCamelCase__    :		Optional[Any]				=	VOCAB_FILES_NAMES
    lowerCamelCase__    :		List[str]				=	PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase__    :		Optional[Any]				=	PRETRAINED_INIT_CONFIGURATION
    lowerCamelCase__    :		Optional[Any]				=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase__    :		Optional[int]				=	HerbertTokenizer



    def __init__(       self   ,				A_=None   ,				A_=None   ,				A_=None   ,				A_="<s>"   ,				A_="<unk>"   ,				A_="<pad>"   ,				A_="<mask>"   ,				A_="</s>"   ,				**A_   ,				):





        '''simple docstring'''

        super().__init__(
            A_   ,				A_   ,				tokenizer_file=A_   ,				cls_token=A_   ,				unk_token=A_   ,				pad_token=A_   ,				mask_token=A_   ,				sep_token=A_   ,				**A_   ,				)



    def  lowercase_					(       self   ,				A_   ,				A_ = None     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			[self.cls_token_id]
        SCREAMING_SNAKE_CASE__											=			[self.sep_token_id]
        if token_ids_a is None:
            return cls + token_ids_a + sep

        return cls + token_ids_a + sep + token_ids_a + sep



    def  lowercase_					(       self   ,				A_   ,				A_ = None   ,				A_ = False     ):





        '''simple docstring'''

        if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=A_   ,				token_ids_a=A_   ,				already_has_special_tokens=A_     )

        if token_ids_a is None:
            return [1] + ([0] * len(A_     )) + [1]
        return [1] + ([0] * len(A_     )) + [1] + ([0] * len(A_     )) + [1]



    def  lowercase_					(       self   ,				A_   ,				A_ = None     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			[self.sep_token_id]
        SCREAMING_SNAKE_CASE__											=			[self.cls_token_id]

        if token_ids_a is None:
            return len(cls + token_ids_a + sep     ) * [0]
        return len(cls + token_ids_a + sep     ) * [0] + len(token_ids_a + sep     ) * [1]




    def  lowercase_					(       self   ,				A_   ,				A_ = None     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			self._tokenizer.model.save(A_   ,				name=A_     )
        return tuple(A_     )







from torch import nn


def 							__snake_case							(    lowerCAmelCase_	)				->						Tuple:
    if act_fn in ["swish", "silu"]:
        return nn.SiLU()
    elif act_fn == "mish":
        return nn.Mish()
    elif act_fn == "gelu":
        return nn.GELU()
    else:
        raise ValueError(f'''Unsupported activation function: {act_fn}'''	)
