



"""simple docstring"""


from string import ascii_uppercase

__A   :							Dict										=   {str(ord(c) - 55): c for c in ascii_uppercase}







def  lowercase	(      _SCREAMING_SNAKE_CASE   :						int					,     _SCREAMING_SNAKE_CASE   :						int				):






				'''simple docstring'''



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








"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


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

__A   :							Optional[Any]										=   {
    "google/bit-50": "https://huggingface.co/google/bit-50/resolve/main/config.json",
}
class 			_a (					lowerCAmelCase			,							lowerCAmelCase):
			"""simple docstring"""
			UpperCamelCase__			      =	"""bit"""
			UpperCamelCase__			      =	["""preactivation""", """bottleneck"""]
			UpperCamelCase__			      =	["""SAME""", """VALID"""]



			def __init__(		self     :    List[Any]				,   __UpperCamelCase     :    Optional[int]=3				,   __UpperCamelCase     :    Optional[int]=6_4				,   __UpperCamelCase     :    List[Any]=[2_5_6, 5_1_2, 1_0_2_4, 2_0_4_8]				,   __UpperCamelCase     :    Any=[3, 4, 6, 3]				,   __UpperCamelCase     :    str="preactivation"				,   __UpperCamelCase     :    Union[str, Any]="relu"				,   __UpperCamelCase     :    str=None				,   __UpperCamelCase     :    Dict=3_2				,   __UpperCamelCase     :    List[str]=0.0				,   __UpperCamelCase     :    Any=False				,   __UpperCamelCase     :    Union[str, Any]=3_2				,   __UpperCamelCase     :    List[str]=1				,   __UpperCamelCase     :    List[str]=None				,   __UpperCamelCase     :    Optional[Any]=None				,   **__UpperCamelCase     :    List[str]				,   )->List[Any]:
							super().__init__(**__UpperCamelCase   )
							if layer_type not in self.layer_types:
											raise ValueError(F'layer_type={layer_type} is not one of {",".join(self.layer_types   )}'   )
							if global_padding is not None:
											if global_padding.upper() in self.supported_padding:
															_UpperCAmelCase					=    global_padding.upper()
											else:
															raise ValueError(F'Padding strategy {global_padding} not supported'   )
							_UpperCAmelCase					=    num_channels
							_UpperCAmelCase					=    embedding_size
							_UpperCAmelCase					=    hidden_sizes
							_UpperCAmelCase					=    depths
							_UpperCAmelCase					=    layer_type
							_UpperCAmelCase					=    hidden_act
							_UpperCAmelCase					=    global_padding
							_UpperCAmelCase					=    num_groups
							_UpperCAmelCase					=    drop_path_rate
							_UpperCAmelCase					=    embedding_dynamic_padding
							_UpperCAmelCase					=    output_stride
							_UpperCAmelCase					=    width_factor

							_UpperCAmelCase					=    ['''stem'''] + [F'stage{idx}' for idx in range(1				,   len(__UpperCamelCase   ) + 1   )]
							_UpperCAmelCase		,						_UpperCAmelCase					=    get_aligned_output_features_output_indices(
							    out_features=__UpperCamelCase				,   out_indices=__UpperCamelCase				,   stage_names=self.stage_names   )



