
from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
      from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore






class     a_       (			snake_case__							):



       """simple docstring"""
       __SCREAMING_SNAKE_CASE       :					str						=  c_float






       @property
       def 	__lowerCAmelCase     (		self   )					->str:
           return sizeof(self.value   )







def 				UpperCAmelCase_(    a__ ,						a__ ,						a__ = 0   ):



    """simple docstring"""



    if dimension <= 0:
        SCREAMING_SNAKE_CASE				:				str				      = fixed_dimension

    dimension -= num_token_to_add
    return dimension







def 				UpperCAmelCase_(    a__ ,						a__   ):



    """simple docstring"""



    return num_parameters * dtype.size







def 				UpperCAmelCase_(    a__   ):



    """simple docstring"""



    from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

    try:
        return AutoProcessor.from_pretrained(a__   )
    except (ValueError, OSError, KeyError):
        SCREAMING_SNAKE_CASE				:				Dict				      = None, None
        try:
            SCREAMING_SNAKE_CASE				:				Tuple				      = AutoTokenizer.from_pretrained(a__   )
        except (OSError, KeyError):
            pass
        try:
            SCREAMING_SNAKE_CASE				:				int				      = AutoFeatureExtractor.from_pretrained(a__   )
        except (OSError, KeyError):
            pass

        if tokenizer is not None and feature_extractor is not None:
            raise ValueError(
                F"""Couldn\'t auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor."""   )
        elif tokenizer is None and feature_extractor is None:
            return None
        elif tokenizer is not None:
            return tokenizer
        else:
            return feature_extractor



"""simple docstring"""





from __future__ import annotations



def 							_lowerCAmelCase   (    UpperCAmelCase  :				list[int]   ,				UpperCAmelCase  :				int					):


					'''simple docstring'''






					UpperCamelCase__		:     dict[int, int]								={}
					for index, val in enumerate(UpperCAmelCase					):
										UpperCamelCase__		:     List[Any]								=target - val
										if compl in chk_map:
															return [chk_map[compl], index]
										UpperCamelCase__		:     Any								=index
					return []


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				print(F'''{two_sum([2, 7, 1_1, 1_5], 9) = }''')


