

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  __snake_case					(      A__    ):
  __lowerCAmelCase       :		int  	=					c_float

  @property
  def   lowerCAmelCase__       (   self):
      return sizeof(self.value)






def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						int	,				_SCREAMING_SNAKE_CASE   :						int	,				_SCREAMING_SNAKE_CASE   :						int = 0    ):





    """simple docstring"""


    if dimension <= 0:
        SCREAMING_SNAKE_CASE_													=  fixed_dimension

    dimension -= num_token_to_add
    return dimension


def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						int	,				_SCREAMING_SNAKE_CASE   :						ParameterFormat    ):





    """simple docstring"""


    return num_parameters * dtype.size





def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						str    ):





    """simple docstring"""


    from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

    try:
        return AutoProcessor.from_pretrained(_SCREAMING_SNAKE_CASE    )
    except (ValueError, OSError, KeyError):
        SCREAMING_SNAKE_CASE_													=  None, None
        try:
            SCREAMING_SNAKE_CASE_													=  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE    )
        except (OSError, KeyError):
            pass
        try:
            SCREAMING_SNAKE_CASE_													=  AutoFeatureExtractor.from_pretrained(_SCREAMING_SNAKE_CASE    )
        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





def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						float	,				_SCREAMING_SNAKE_CASE   :						float    ):





    """simple docstring"""


    return a + b


if __name__ == "__main__":
       UpperCamelCase__					: Union[str, Any]								=      5
       UpperCamelCase__					: List[Any]								=      6
       print(F'The sum of {a} + {b} is {add(a, b)}')


