






from __future__ import annotations

from collections.abc import Generator







def 		_UpperCamelCase      (			UpperCamelCase_				:    int						)     ->      Generator[int, None, None]:

						"""simple docstring"""



						if not isinstance(UpperCamelCase_			,				UpperCamelCase_						) or n < 1:
												raise Exception('Sequence only defined for positive integers'						)

						yield n
						while n != 1:
												if n % 2 == 0:
																		n //= 2
												else:
																		lowerCAmelCase__			  =  3 * n + 1
												yield n







def 		_UpperCamelCase      (			)     ->      List[Any]:

						"""simple docstring"""



						lowerCAmelCase__			  =  43
						lowerCAmelCase__			  =  tuple(collatz_sequence(UpperCamelCase_						)						)
						print(UpperCamelCase_						)
						print(F"Collatz sequence from {n} took {len(UpperCamelCase_						)} steps."						)


if __name__ == "__main__":
					main()













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case			:			Optional[int]			   =   {"""configuration_sew_d""": ["""SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWDConfig"""]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case			:			List[Any]			   =   [
					    """SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """SEWDForCTC""",
					    """SEWDForSequenceClassification""",
					    """SEWDModel""",
					    """SEWDPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_sew_d import (
										    SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SEWDForCTC,
										    SEWDForSequenceClassification,
										    SEWDModel,
										    SEWDPreTrainedModel,
										)


else:
					import sys

					__snake_case			:			Dict			   =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





