
import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig






class 							SCREAMING_SNAKE_CASE__     (				SCREAMING_SNAKE_CASE_     ):

							"""simple docstring"""






							_snake_case  		=	CustomConfig



							def __init__(	self  ,						SCREAMING_SNAKE_CASE_      )-> Dict:





													'''simple docstring'''






													super().__init__(SCREAMING_SNAKE_CASE_      )
													__UpperCamelCase  	=      torch.nn.Linear(config.hidden_size  ,						config.hidden_size      )



							def      A__		(	self  ,						SCREAMING_SNAKE_CASE_      )-> Tuple:





													'''simple docstring'''






													return self.linear(SCREAMING_SNAKE_CASE_      )



							def      A__		(	self  ,						SCREAMING_SNAKE_CASE_      )-> Any:





													'''simple docstring'''






													pass






class 							SCREAMING_SNAKE_CASE__     (				SCREAMING_SNAKE_CASE_     ):

							"""simple docstring"""






							_snake_case  		=	NoSuperInitConfig



							def __init__(	self  ,						SCREAMING_SNAKE_CASE_      )-> Optional[Any]:





													'''simple docstring'''






													super().__init__(SCREAMING_SNAKE_CASE_      )
													__UpperCamelCase  	=      torch.nn.Linear(config.attribute  ,						config.attribute      )



							def      A__		(	self  ,						SCREAMING_SNAKE_CASE_      )-> Optional[Any]:





													'''simple docstring'''






													return self.linear(SCREAMING_SNAKE_CASE_      )



							def      A__		(	self  ,						SCREAMING_SNAKE_CASE_      )-> Optional[int]:





													'''simple docstring'''






													pass







'''simple docstring'''







from __future__ import annotations

from collections.abc import Generator






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):
	if not isinstance(snake_case_							,       snake_case_	) or n < 1:
		raise Exception("""Sequence only defined for positive integers"""	)

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






def 					_SCREAMING_SNAKE_CASE		(						):
	_lowercase							=     43
	_lowercase							=     tuple(collatz_sequence(snake_case_	)	)
	print(snake_case_	)
	print(F"""Collatz sequence from {n} took {len(snake_case_	)} steps."""	)


if __name__ == "__main__":
							main()




