






import torch

from accelerate import Accelerator, DistributedType







class 				lowerCamelCase_     :
							def __enter__(						self		:					Any					):





								'''simple docstring'''



								if self.enabled:
									a		=			self.model.no_sync()
									self.model_sync_obj.__enter__()

								return self
							def __exit__(						self		:					str							,__lowerCamelCase		:					List[str]							,__lowerCamelCase		:					List[Any]							,__lowerCamelCase		:					Optional[Any]					):





								'''simple docstring'''



								if self.enabled:
									# Average all models on exit
									self._sync_and_avg_model_params()
									self.model_sync_obj.__exit__(__lowerCamelCase							,__lowerCamelCase							,__lowerCamelCase					)
							def __init__(						self		:					Tuple							,__lowerCamelCase		:					Accelerator							,__lowerCamelCase		:					torch.nn.Module							,__lowerCamelCase		:					int							,__lowerCamelCase		:					bool = True					):





								'''simple docstring'''



								if accelerator.distributed_type not in [
								    DistributedType.NO,
								    DistributedType.MULTI_CPU,
								    DistributedType.MULTI_GPU,
								]:
									raise NotImplementedError('''LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)'''					)
								a		=			enabled and accelerator.distributed_type != DistributedType.NO
								a		=			0
								if self.enabled:
									a		=			accelerator
									a		=			model
									a		=			local_sgd_steps
							def  SCREAMING_SNAKE_CASE_ (						self		:					int					):





								'''simple docstring'''



								self.num_steps += 1
								if not self.enabled:
									return

								if self.num_steps % self.local_sgd_steps == 0:
									self._sync_and_avg_model_params()




							def  SCREAMING_SNAKE_CASE_ (						self		:					int					):





								'''simple docstring'''



								self.accelerator.wait_for_everyone()
								with self.accelerator.autocast():
									for param in self.model.parameters():
										a		=			self.accelerator.reduce(param.data							,reduction='''mean'''					)













import random
import sys

UpperCamelCase__						:      List[str]								=					"""ABCDEFGHIJKLMNOPQRSTUVWXYZ"""





def   SCREAMING_SNAKE_CASE__						(   )   ->  None:


	"""simple docstring"""



	a		=			input('''Enter message: '''  )
	a		=			'''LFWOAYUISVKMNXPBDCRJTQEGHZ'''
	a		=			input('''Encrypt/Decrypt [e/d]: '''  )

	check_valid_key(snake_case_  )

	if resp.lower().startswith('''e'''  ):
		a		=			'''encrypt'''
		a		=			encrypt_message(snake_case_,  snake_case_  )
	elif resp.lower().startswith('''d'''  ):
		a		=			'''decrypt'''
		a		=			decrypt_message(snake_case_,  snake_case_  )

	print(f"""\n{mode.title()}ion: \n{translated}"""  )





def   SCREAMING_SNAKE_CASE__						(   snake_case_  )   ->  None:


	"""simple docstring"""



	a		=			list(snake_case_  )
	a		=			list(snake_case_  )
	key_list.sort()
	letters_list.sort()

	if key_list != letters_list:
		sys.exit('''Error in the key or symbol set.'''  )





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_  )   ->  str:


	"""simple docstring"""



	return translate_message(snake_case_,  snake_case_,  '''encrypt'''  )





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_  )   ->  str:


	"""simple docstring"""



	return translate_message(snake_case_,  snake_case_,  '''decrypt'''  )





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_,  snake_case_  )   ->  str:


	"""simple docstring"""



	a		=			''''''
	a		=			LETTERS
	a		=			key

	if mode == "decrypt":
		a	, a		=			chars_b, chars_a

	for symbol in message:
		if symbol.upper() in chars_a:
			a		=			chars_a.find(symbol.upper()  )
			if symbol.isupper():
				translated += chars_b[sym_index].upper()
			else:
				translated += chars_b[sym_index].lower()
		else:
			translated += symbol

	return translated





def   SCREAMING_SNAKE_CASE__						(   )   ->  str:


	"""simple docstring"""



	a		=			list(snake_case_  )
	random.shuffle(snake_case_  )
	return "".join(snake_case_  )


if __name__ == "__main__":
				main()





