



'''simple docstring'''
from __future__ import annotations

from string import ascii_letters


def   lowercase_	(   lowerCAmelCase__	:  str			,							lowerCAmelCase__	:  int			,							lowerCAmelCase__	:  str | None = None ):

			"""simple docstring"""





			__UpperCAmelCase   :      List[Any]										=     alphabet or ascii_letters

			# The final result string
			__UpperCAmelCase   :      Optional[Any]										=     """"""

			for character in input_string:
						if character not in alpha:
									# Append without encryption if character is not in the alphabet
									result += character
						else:
									# Get the index of the new key and make sure it isn't too large
									__UpperCAmelCase   :      str										=     (alpha.index(lowerCAmelCase__ ) + key) % len(lowerCAmelCase__ )

									# Append the encoded character to the alphabet
									result += alpha[new_key]

			return result


def   lowercase_	(   lowerCAmelCase__	:  str			,							lowerCAmelCase__	:  int			,							lowerCAmelCase__	:  str | None = None ):

			"""simple docstring"""





			key *= -1

			return encrypt(lowerCAmelCase__			,							lowerCAmelCase__			,							lowerCAmelCase__ )


def   lowercase_	(   lowerCAmelCase__	:  str			,							lowerCAmelCase__	:  str | None = None ):

			"""simple docstring"""





			__UpperCAmelCase   :      Optional[int]										=     alphabet or ascii_letters

			# To store data on all the combinations
			__UpperCAmelCase   :      List[Any]										=     {}

			# Cycle through each combination
			for key in range(1			,							len(lowerCAmelCase__ ) + 1 ):
						# Decrypt the message and store the result in the data
						__UpperCAmelCase   :      Union[str, Any]										=     decrypt(lowerCAmelCase__			,							lowerCAmelCase__			,							lowerCAmelCase__ )

			return brute_force_data


if __name__ == "__main__":
					while True:
										print(F'\n{"-" * 10}\n Menu\n{"-" * 10}')
										print(*['''1.Encrypt''', '''2.Decrypt''', '''3.BruteForce''', '''4.Quit'''], sep='''\n''')

										# get user input
										_UpperCamelCase											=			input('''\nWhat would you like to do?: ''').strip() or '''4'''

										# run functions based on what the user chose
										if choice not in ("1", "2", "3", "4"):
															print('''Invalid choice, please enter a valid choice''')
										elif choice == "1":
															_UpperCamelCase											=			input('''Please enter the string to be encrypted: ''')
															_UpperCamelCase											=			int(input('''Please enter off-set: ''').strip())

															print(encrypt(input_string, key))
										elif choice == "2":
															_UpperCamelCase											=			input('''Please enter the string to be decrypted: ''')
															_UpperCamelCase											=			int(input('''Please enter off-set: ''').strip())

															print(decrypt(input_string, key))
										elif choice == "3":
															_UpperCamelCase											=			input('''Please enter the string to be decrypted: ''')
															_UpperCamelCase											=			brute_force(input_string)

															for key, value in brute_force_data.items():
																				print(F'Key: {key} | Message: {value}')

										elif choice == "4":
															print('''Goodbye.''')
															break









'''simple docstring'''
import torch

from transformers import AutoTokenizer



class _A  (    __SCREAMING_SNAKE_CASE    ):





		def __init__(     self ,       __UpperCAmelCase				)       ->     Union[str, Any]:

					'''simple docstring'''
					__UpperCAmelCase   :      Any										=     AutoTokenizer.from_pretrained(__UpperCAmelCase				)





		def 							__A       (     self ,       __UpperCAmelCase				)       ->     Any:

					'''simple docstring'''

					if isinstance(__UpperCAmelCase ,       __UpperCAmelCase				) and all(isinstance(_x ,       __UpperCAmelCase				) for _x in x				):
								__UpperCAmelCase   :      Dict										=     None
								for l in x:
											__UpperCAmelCase   :      Dict										=     self.tokenizer(
											    __UpperCAmelCase ,       padding="""max_length""" ,       max_length=384 ,       truncation=__UpperCAmelCase ,       return_tensors="""pt""" ,       )
											__UpperCAmelCase   :      Union[str, Any]										=     torch.tensor([len(__UpperCAmelCase				)]				)
											if d is not None:
														for k in d.keys():
																	__UpperCAmelCase   :      Dict										=     torch.cat((d[k], t[k]) ,       0				)
											else:
														__UpperCAmelCase   :      List[str]										=     t

								__UpperCAmelCase   :      Union[str, Any]										=     torch.tensor(self.tokenizer.convert_tokens_to_ids("""[E]"""				)				)
								__UpperCAmelCase   :      Any										=     torch.tensor(self.tokenizer.convert_tokens_to_ids("""[/E]"""				)				)

					elif isinstance(__UpperCAmelCase ,       __UpperCAmelCase				) and all(isinstance(_x ,       __UpperCAmelCase				) for _x in x				):
								__UpperCAmelCase   :      int										=     self.tokenizer(
								    __UpperCAmelCase ,       padding="""max_length""" ,       max_length=384 ,       truncation=__UpperCAmelCase ,       return_tensors="""pt""" ,       )

					else:
								raise Exception(
								    """Type of parameter x was not recognized! Only `list of strings` for query or `list of lists of"""
								    """ strings` for supports are supported."""				)

					return d





		def 							__A       (     self ,       __UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase=0.70				)       ->     Dict:

					'''simple docstring'''
					__UpperCAmelCase   :      Tuple										=     []
					for idx in range(len(W_query["""input_ids"""]				)				):
								__UpperCAmelCase   :      Optional[int]										=     range(p_start.shape[1]				)

								__UpperCAmelCase   :      Union[str, Any]										=     []
								for start_id in start_indexes:
											for end_id in end_indexes:
														if start_id < end_id:
																	output.append(
																	    (
																	        start_id,
																	        end_id,
																	        p_start[idx][start_id].item(),
																	        p_end[idx][end_id].item(),
																	    )				)

								output.sort(key=lambda __UpperCAmelCase				: (tup[2] * tup[3]) ,       reverse=__UpperCAmelCase				)
								__UpperCAmelCase   :      Optional[Any]										=     []
								for k in range(len(__UpperCAmelCase				)				):
											if output[k][2] * output[k][3] >= thresh:
														__UpperCAmelCase				,  __UpperCAmelCase   :      Tuple										=     output[k][0], output[k][1]
														__UpperCAmelCase   :      int										=     self.tokenizer.decode(W_query["""input_ids"""][idx][c_start_pos:c_end_pos]				)
														temp.append((decoded, output[k][2] * output[k][3])				)

								final_outputs.append(__UpperCAmelCase				)

					return final_outputs




