from string import ascii_uppercase

__lowerCamelCase      :			Optional[Any]							       =		{str(ord(c) - 55): c for c in ascii_uppercase}



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int			,					__UpperCamelCase   :	int     )							-> str:







  """simple docstring"""





  if isinstance(__UpperCamelCase			,					__UpperCamelCase     ):
    raise TypeError("""int() can't convert non-string with explicit base"""     )
  if num < 0:
    raise ValueError("""parameter must be positive int"""     )
  if isinstance(__UpperCamelCase			,					__UpperCamelCase     ):
    raise TypeError("""'str' object cannot be interpreted as an integer"""     )
  if isinstance(__UpperCamelCase			,					__UpperCamelCase     ):
    raise TypeError("""'float' object cannot be interpreted as an integer"""     )
  if base in (0, 1):
    raise ValueError("""base must be >= 2"""     )
  if base > 36:
    raise ValueError("""base must be <= 36"""     )
  SCREAMING_SNAKE_CASE__      							=				""""""
  SCREAMING_SNAKE_CASE__      							=				0
  SCREAMING_SNAKE_CASE__      							=				0
  while div != 1:
    SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__      							=				divmod(__UpperCamelCase			,					__UpperCamelCase     )
    if base >= 11 and 9 < mod < 36:
      SCREAMING_SNAKE_CASE__      							=				ALPHABET_VALUES[str(__UpperCamelCase     )]
    else:
      SCREAMING_SNAKE_CASE__      							=				str(__UpperCamelCase     )
    new_value += actual_value
    SCREAMING_SNAKE_CASE__      							=				num // base
    SCREAMING_SNAKE_CASE__      							=				div
    if div == 0:
      return str(new_value[::-1]     )
    elif div == 1:
      new_value += str(__UpperCamelCase     )
      return str(new_value[::-1]     )

  return new_value[::-1]


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   for base in range(2, 37):
      for num in range(1000):
         assert int(decimal_to_any(num, base), base) == num, (
             num,
             base,
             decimal_to_any(num, base),
             int(decimal_to_any(num, base), base),
         )

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


__lowerCamelCase      :			Optional[Any]							       =		{
    '''configuration_efficientformer''': [
        '''EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''EfficientFormerConfig''',
    ]
}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase      :			Dict							       =		['''EfficientFormerImageProcessor''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase      :			Optional[int]							       =		[
       '''EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''EfficientFormerForImageClassification''',
       '''EfficientFormerForImageClassificationWithTeacher''',
       '''EfficientFormerModel''',
       '''EfficientFormerPreTrainedModel''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase      :			Any							       =		[
       '''TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFEfficientFormerForImageClassification''',
       '''TFEfficientFormerForImageClassificationWithTeacher''',
       '''TFEfficientFormerModel''',
       '''TFEfficientFormerPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .image_processing_efficientformer import EfficientFormerImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_efficientformer import (
          EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          EfficientFormerForImageClassification,
          EfficientFormerForImageClassificationWithTeacher,
          EfficientFormerModel,
          EfficientFormerPreTrainedModel,
      )
   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_efficientformer import (
          TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFEfficientFormerForImageClassification,
          TFEfficientFormerForImageClassificationWithTeacher,
          TFEfficientFormerModel,
          TFEfficientFormerPreTrainedModel,
      )

else:
   import sys

   __lowerCamelCase      :			List[Any]							       =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
