





import random
import sys

UpperCAmelCase__    :      Any       					="ABCDEFGHIJKLMNOPQRSTUVWXYZ"





def   _lowercase       (    )    ->	str:
				lowerCamelCase									=input("""Enter message: """					)
				lowerCamelCase									="""LFWOAYUISVKMNXPBDCRJTQEGHZ"""
				lowerCamelCase									=input("""Encrypt/Decrypt [e/d]: """					)

				check_valid_key(lowerCAmelCase__					)

				if resp.lower().startswith("""e"""					):
								lowerCamelCase									="""encrypt"""
								lowerCamelCase									=encrypt_message(lowerCAmelCase__      ,   lowerCAmelCase__					)
				elif resp.lower().startswith("""d"""					):
								lowerCamelCase									="""decrypt"""
								lowerCamelCase									=decrypt_message(lowerCAmelCase__      ,   lowerCAmelCase__					)

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





def   _lowercase       (    _UpperCAmelCase					)    ->	int:
				lowerCamelCase									=list(lowerCAmelCase__					)
				lowerCamelCase									=list(lowerCAmelCase__					)
				key_list.sort()
				letters_list.sort()

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





def   _lowercase       (    _UpperCAmelCase      ,   _UpperCAmelCase					)    ->	Optional[int]:
				return translate_message(lowerCAmelCase__      ,   lowerCAmelCase__      ,   """encrypt"""					)





def   _lowercase       (    _UpperCAmelCase      ,   _UpperCAmelCase					)    ->	List[Any]:
				return translate_message(lowerCAmelCase__      ,   lowerCAmelCase__      ,   """decrypt"""					)





def   _lowercase       (    _UpperCAmelCase      ,   _UpperCAmelCase      ,   _UpperCAmelCase					)    ->	List[str]:
				lowerCamelCase									=""""""
				lowerCamelCase									=LETTERS
				lowerCamelCase									=key

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

				for symbol in message:
								if symbol.upper() in chars_a:
												lowerCamelCase									=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   _lowercase       (    )    ->	Any:
				lowerCamelCase									=list(lowerCAmelCase__					)
				random.shuffle(lowerCAmelCase__					)
				return "".join(lowerCAmelCase__					)


if __name__ == "__main__":
							main()







import torch

from accelerate import Accelerator, DistributedType







class 							lowercase						:




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

												return self




							def __exit__(							self  ,A__  ,A__  ,A__):
												if self.enabled:
																	# Average all models on exit
																	self._sync_and_avg_model_params()
																	self.model_sync_obj.__exit__(A__  ,A__  ,A__)




							def __init__(							self  ,A__  ,A__  ,A__  ,A__ = True):
												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)''')
												lowercase		      =		enabled and accelerator.distributed_type != DistributedType.NO
												lowercase		      =		0
												if self.enabled:
																	lowercase		      =		accelerator
																	lowercase		      =		model
																	lowercase		      =		local_sgd_steps




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




