




import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import (
    TaBlock,
    TaConfig,
    TaLayerNorm,
)

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class      _UpperCamelCase (			__lowerCAmelCase		,    __lowerCAmelCase		,    __lowerCAmelCase						):
      @register_to_config
      def __init__(     self				:Optional[Any]	, lowerCamelCase				:Dict	, lowerCamelCase				:Dict	, lowerCamelCase				:Dict	, lowerCamelCase				:List[str]	, lowerCamelCase				:Optional[Any]	, lowerCamelCase				:str	, lowerCamelCase				:Any	, lowerCamelCase				:Tuple	, lowerCamelCase				:Tuple	, lowerCamelCase				:int = False	, )       ->     Optional[Any]:
       super().__init__()

       UpperCAmelCase__								=  nn.Linear(__SCREAMING_SNAKE_CASE	, __SCREAMING_SNAKE_CASE	, bias=__SCREAMING_SNAKE_CASE )

       UpperCAmelCase__								=  nn.Embedding(__SCREAMING_SNAKE_CASE	, __SCREAMING_SNAKE_CASE )
       UpperCAmelCase__								=  False

       UpperCAmelCase__								=  nn.Dropout(p=__SCREAMING_SNAKE_CASE )

       UpperCAmelCase__								=  TaConfig(
           d_model=__SCREAMING_SNAKE_CASE	, num_heads=__SCREAMING_SNAKE_CASE	, d_kv=__SCREAMING_SNAKE_CASE	, d_ff=__SCREAMING_SNAKE_CASE	, feed_forward_proj=__SCREAMING_SNAKE_CASE	, dropout_rate=__SCREAMING_SNAKE_CASE	, is_decoder=__SCREAMING_SNAKE_CASE	, is_encoder_decoder=__SCREAMING_SNAKE_CASE	, )
       UpperCAmelCase__								=  nn.ModuleList()
       for lyr_num in range(__SCREAMING_SNAKE_CASE ):
        UpperCAmelCase__								=  TaBlock(__SCREAMING_SNAKE_CASE )
        self.encoders.append(__SCREAMING_SNAKE_CASE )

       UpperCAmelCase__								=  TaLayerNorm(__SCREAMING_SNAKE_CASE )
       UpperCAmelCase__								=  nn.Dropout(p=__SCREAMING_SNAKE_CASE )







      def 		UpperCAmelCase_  (     self				:Tuple	, lowerCamelCase				:List[Any]	, lowerCamelCase				:List[str] )       ->     Optional[int]:
       UpperCAmelCase__								=  self.input_proj(__SCREAMING_SNAKE_CASE )

       # terminal relative positional encodings
       UpperCAmelCase__								=  encoder_inputs.shape[1]
       UpperCAmelCase__								=  torch.arange(__SCREAMING_SNAKE_CASE	, device=encoder_inputs.device )

       UpperCAmelCase__								=  encoder_inputs_mask.sum(-1 )
       UpperCAmelCase__								=  torch.roll(input_positions.unsqueeze(0 )	, tuple(seq_lens.tolist() )	, dims=0 )
       x += self.position_encoding(__SCREAMING_SNAKE_CASE )

       UpperCAmelCase__								=  self.dropout_pre(__SCREAMING_SNAKE_CASE )

       # inverted the attention mask
       UpperCAmelCase__								=  encoder_inputs.size()
       UpperCAmelCase__								=  self.get_extended_attention_mask(__SCREAMING_SNAKE_CASE	, __SCREAMING_SNAKE_CASE )

       for lyr in self.encoders:
        UpperCAmelCase__								=  lyr(__SCREAMING_SNAKE_CASE	, __SCREAMING_SNAKE_CASE )[0]
       UpperCAmelCase__								=  self.layer_norm(__SCREAMING_SNAKE_CASE )

       return self.dropout_post(__SCREAMING_SNAKE_CASE ), encoder_inputs_mask











from __future__ import annotations

from string import ascii_letters



def   lowerCAmelCase						(						_lowerCAmelCase							:				str  ,							_lowerCAmelCase							:				int  ,							_lowerCAmelCase							:				str | None = None		):




 """simple docstring"""







 UpperCAmelCase__								=  alphabet or ascii_letters

 # The final result string
 UpperCAmelCase__								=  ""

 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__								=  (alpha.index(_lowerCAmelCase		) + key) % len(_lowerCAmelCase		)

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

 return result



def   lowerCAmelCase						(						_lowerCAmelCase							:				str  ,							_lowerCAmelCase							:				int  ,							_lowerCAmelCase							:				str | None = None		):




 """simple docstring"""







 key *= -1

 return encrypt(_lowerCAmelCase  ,							_lowerCAmelCase  ,							_lowerCAmelCase		)



def   lowerCAmelCase						(						_lowerCAmelCase							:				str  ,							_lowerCAmelCase							:				str | None = None		):




 """simple docstring"""







 UpperCAmelCase__								=  alphabet or ascii_letters

 # To store data on all the combinations
 UpperCAmelCase__								=  {}

 # Cycle through each combination
 for key in range(1  ,							len(_lowerCAmelCase		) + 1		):
  # Decrypt the message and store the result in the data
  UpperCAmelCase__								=  decrypt(_lowerCAmelCase  ,							_lowerCAmelCase  ,							_lowerCAmelCase		)

 return brute_force_data


if __name__ == "__main__":
  while True:
    print(F'''\n{"-" * 1_0}\n Menu\n{"-" * 1_0}''')
    print(*["1.Encrypt", "2.Decrypt", "3.BruteForce", "4.Quit"], sep="\n")

    # get user input
    _lowerCAmelCase  :				List[Any]						=				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":
      _lowerCAmelCase  :				Any						=				input("Please enter the string to be encrypted: ")
      _lowerCAmelCase  :				str						=				int(input("Please enter off-set: ").strip())

      print(encrypt(input_string, key))
    elif choice == "2":
      _lowerCAmelCase  :				Optional[Any]						=				input("Please enter the string to be decrypted: ")
      _lowerCAmelCase  :				Any						=				int(input("Please enter off-set: ").strip())

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

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

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





