



"""simple docstring"""




from string import ascii_uppercase

_lowercase		:				int      		={str(ord(c) - 55): c for c in ascii_uppercase}

def      lowerCAmelCase_					(  _lowercase    :       int						,       _lowercase    :       int)							->	str:







			"""simple docstring"""
			if isinstance(_A						,       _A):
						raise TypeError("""int() can't convert non-string with explicit base""")
			if num < 0:
						raise ValueError("""parameter must be positive int""")
			if isinstance(_A						,       _A):
						raise TypeError("""'str' object cannot be interpreted as an integer""")
			if isinstance(_A						,       _A):
						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""")
			a__       :						Union[str, Any]							=  """"""
			a__       :						Tuple							=  0
			a__       :						List[str]							=  0
			while div != 1:
						a__	,						a__       :						str							=  divmod(_A						,       _A)
						if base >= 11 and 9 < mod < 36:
									a__       :						Optional[int]							=  ALPHABET_VALUES[str(_A)]
						else:
									a__       :						Tuple							=  str(_A)
						new_value += actual_value
						a__       :						Optional[int]							=  num // base
						a__       :						str							=  div
						if div == 0:
									return str(new_value[::-1])
						elif div == 1:
									new_value += str(_A)
									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_flax_available, is_torch_available


_lowercase		:				int      		={
    "configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:				Optional[Any]      		=[
		    "LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "LongT5EncoderModel",
		    "LongT5ForConditionalGeneration",
		    "LongT5Model",
		    "LongT5PreTrainedModel",
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:				List[Any]      		=[
		    "FlaxLongT5ForConditionalGeneration",
		    "FlaxLongT5Model",
		    "FlaxLongT5PreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_longta import LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP, LongTaConfig, LongTaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_longta import (
				    LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST,
				    LongTaEncoderModel,
				    LongTaForConditionalGeneration,
				    LongTaModel,
				    LongTaPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_longta import (
				    FlaxLongTaForConditionalGeneration,
				    FlaxLongTaModel,
				    FlaxLongTaPreTrainedModel,
				)


else:
		import sys

		_lowercase		:				Any      		=_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




