
'''simple docstring'''

snake_case									=    """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""


def        UpperCAmelCase_ (  ):







 """simple docstring"""


 lowerCAmelCase__     :   List[Any]     		=	input("Enter message: "			)
 lowerCAmelCase__     :   List[str]     		=	input("Enter key [alphanumeric]: "			)
 lowerCAmelCase__     :   List[str]     		=	input("Encrypt/Decrypt [e/d]: "			)

 if mode.lower().startswith("e"			):
  lowerCAmelCase__     :   Any     		=	"encrypt"
  lowerCAmelCase__     :   Any     		=	encrypt_message(lowerCamelCase_      ,			lowerCamelCase_			)
 elif mode.lower().startswith("d"			):
  lowerCAmelCase__     :   str     		=	"decrypt"
  lowerCAmelCase__     :   str     		=	decrypt_message(lowerCamelCase_      ,			lowerCamelCase_			)

 print(f'''\n{mode.title()}ed message:'''			)
 print(lowerCamelCase_			)


def        UpperCAmelCase_ (  lowerCamelCase_      ,			lowerCamelCase_			):







 """simple docstring"""


 return translate_message(lowerCamelCase_      ,			lowerCamelCase_      ,			"encrypt"			)


def        UpperCAmelCase_ (  lowerCamelCase_      ,			lowerCamelCase_			):







 """simple docstring"""


 return translate_message(lowerCamelCase_      ,			lowerCamelCase_      ,			"decrypt"			)


def        UpperCAmelCase_ (  lowerCamelCase_      ,			lowerCamelCase_      ,			lowerCamelCase_			):







 """simple docstring"""


 lowerCAmelCase__     :   int     		=	[]
 lowerCAmelCase__     :   Union[str, Any]     		=	0
 lowerCAmelCase__     :   Optional[int]     		=	key.upper()

 for symbol in message:
  lowerCAmelCase__     :   int     		=	LETTERS.find(symbol.upper()			)
  if num != -1:
   if mode == "encrypt":
    num += LETTERS.find(key[key_index]			)
   elif mode == "decrypt":
    num -= LETTERS.find(key[key_index]			)

   num %= len(lowerCamelCase_			)

   if symbol.isupper():
    translated.append(LETTERS[num]			)
   elif symbol.islower():
    translated.append(LETTERS[num].lower()			)

   key_index += 1
   if key_index == len(lowerCamelCase_			):
    lowerCAmelCase__     :   Dict     		=	0
  else:
   translated.append(lowerCamelCase_			)
 return "".join(lowerCamelCase_			)


if __name__ == "__main__":
     main()







'''simple docstring'''

import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel

from ...models.attention import BasicTransformerBlock
from ...utils import logging


snake_case									=    logging.get_logger(__name__)  # pylint: disable=invalid-name




class    lowerCAmelCase       (     UpperCamelCase_  ):


 def __init__(    self  : Union[str, Any]			,							a__  : int			,							a__  : List[Any]=768    ):
  '''simple docstring'''

  super().__init__(a__    )
  lowerCAmelCase__     :   int     		=	proj_size

  lowerCAmelCase__     :   str     		=	CLIPVisionModel(a__    )
  lowerCAmelCase__     :   int     		=	PaintByExampleMapper(a__    )
  lowerCAmelCase__     :   Optional[int]     		=	nn.LayerNorm(config.hidden_size    )
  lowerCAmelCase__     :   Optional[Any]     		=	nn.Linear(config.hidden_size			,							self.proj_size    )

  # uncondition for scaling
  lowerCAmelCase__     :   Dict     		=	nn.Parameter(torch.randn((1, 1, self.proj_size)    )    )


 def    _A	(    self  : Tuple			,							a__  : int			,							a__  : Optional[Any]=False    ):
  '''simple docstring'''

  lowerCAmelCase__     :   List[Any]     		=	self.model(pixel_values=a__    )
  lowerCAmelCase__     :   Any     		=	clip_output.pooler_output
  lowerCAmelCase__     :   Union[str, Any]     		=	self.mapper(latent_states[:, None]    )
  lowerCAmelCase__     :   List[Any]     		=	self.final_layer_norm(a__    )
  lowerCAmelCase__     :   Optional[int]     		=	self.proj_out(a__    )
  if return_uncond_vector:
   return latent_states, self.uncond_vector

  return latent_states




class    lowerCAmelCase       (     nn.Module  ):


 def __init__(    self  : Optional[Any]			,							a__  : Optional[Any]    ):
  '''simple docstring'''

  super().__init__()
  lowerCAmelCase__     :   Optional[Any]     		=	(config.num_hidden_layers + 1) // 5
  lowerCAmelCase__     :   str     		=	config.hidden_size
  lowerCAmelCase__     :   Dict     		=	1
  lowerCAmelCase__     :   int     		=	nn.ModuleList(
      [
          BasicTransformerBlock(a__			,							a__			,							a__			,							activation_fn="gelu"			,							attention_bias=a__    )
          for _ in range(a__    )
      ]    )


 def    _A	(    self  : int			,							a__  : Union[str, Any]    ):
  '''simple docstring'''

  for block in self.blocks:
   lowerCAmelCase__     :   List[Any]     		=	block(a__    )

  return hidden_states





