






def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	Tuple    )  ->			List[str]:

   """simple docstring"""
   __a				     =    ''
   for ch in key:
      if ch == " " or ch not in key_no_dups and ch.isalpha():
         key_no_dups += ch
   return key_no_dups



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	int    )  ->			Optional[int]:

   """simple docstring"""
   __a				     =    [chr(i + 65    ) for i in range(26    )]
   # Remove duplicate characters from key
   __a				     =    remove_duplicates(key.upper()    )
   __a				     =    len(SCREAMING_SNAKE_CASE__    )
   # First fill cipher with key characters
   __a				     =    {alphabet[i]: char for i, char in enumerate(SCREAMING_SNAKE_CASE__    )}
   # Then map remaining characters in alphabet to
   # the alphabet from the beginning
   for i in range(len(SCREAMING_SNAKE_CASE__    ),					26    ):
      __a				     =    alphabet[i - offset]
      # Ensure we are not mapping letters to letters previously mapped
      while char in key:
         offset -= 1
         __a				     =    alphabet[i - offset]
      __a				     =    char
   return cipher_alphabet



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	Union[str, Any],					SCREAMING_SNAKE_CASE__:	Dict    )  ->			List[str]:

   """simple docstring"""
   return "".join(cipher_map.get(SCREAMING_SNAKE_CASE__,					SCREAMING_SNAKE_CASE__    ) for ch in message.upper()    )



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	Union[str, Any],					SCREAMING_SNAKE_CASE__:	Optional[int]    )  ->			Any:

   """simple docstring"""
   __a				     =    {v: k for k, v in cipher_map.items()}
   return "".join(rev_cipher_map.get(SCREAMING_SNAKE_CASE__,					SCREAMING_SNAKE_CASE__    ) for ch in message.upper()    )



def    __UpperCAmelCase	(				)  ->			Optional[Any]:

   """simple docstring"""
   __a				     =    input('Enter message to encode or decode: '    ).strip()
   __a				     =    input('Enter keyword: '    ).strip()
   __a				     =    input('Encipher or decipher? E/D:'    ).strip()[0].lower()
   try:
      __a				     =    {'e': encipher, 'd': decipher}[option]
   except KeyError:
      raise KeyError('invalid input option'    )
   __a				     =    create_cipher_map(SCREAMING_SNAKE_CASE__    )
   print(func(SCREAMING_SNAKE_CASE__,					SCREAMING_SNAKE_CASE__    )    )


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 main()







'''simple docstring'''



from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_torch_available():
 import torch

if is_torch_tpu_available(check_device=False):
 import torch_xla.core.xla_model as xm


__UpperCamelCase      :       Optional[Any]      			=      logging.get_logger(__name__)
@dataclass
class 							__SCREAMING_SNAKE_CASE       (							_lowerCAmelCase     ):
      __a  					=[
          "no_inference",
          "no_cuda",
          "no_tpu",
          "no_speed",
          "no_memory",
          "no_env_print",
          "no_multi_process",
      ]




      def __init__(  self ,   **lowerCamelCase      )							->List[Any]:



         '''simple docstring'''
         for deprecated_arg in self.deprecated_args:
            if deprecated_arg in kwargs:
               __a				     =    deprecated_arg[3:]
               setattr(self ,   lowerCamelCase ,   not kwargs.pop(lowerCamelCase      )      )
               logger.warning(
                   F"""{deprecated_arg} is depreciated. Please use --no_{positive_arg} or"""
                   F""" {positive_arg}={kwargs[positive_arg]}"""      )

         __a				     =    kwargs.pop('torchscript' ,   self.torchscript      )
         __a				     =    kwargs.pop('torch_xla_tpu_print_metrics' ,   self.torch_xla_tpu_print_metrics      )
         __a				     =    kwargs.pop('fp16_opt_level' ,   self.fpaa_opt_level      )
         super().__init__(**lowerCamelCase      )

      __a  					=field(default=_lowerCAmelCase      ,      metadata={"help": "Trace the models using torchscript"}     )
      __a  					=field(default=_lowerCAmelCase      ,      metadata={"help": "Print Xla/PyTorch tpu metrics"}     )
      __a  					=field(
          default="O1"      ,      metadata={
              "help": (
                  "For fp16: Apex AMP optimization level selected in ['O0', 'O1', 'O2', and 'O3']. "
                  "See details at https://nvidia.github.io/apex/amp.html"
              )
          }      ,      )




      @cached_property
      def  __UpperCamelCase							(  self      )							->Tuple["torch.device", int]:



         '''simple docstring'''
         requires_backends(self ,   ['torch']      )
         logger.info('PyTorch: setting up devices'      )
         if not self.cuda:
            __a				     =    torch.device('cpu'      )
            __a				     =    0
         elif is_torch_tpu_available():
            __a				     =    xm.xla_device()
            __a				     =    0
         else:
            __a				     =    torch.device('cuda' if torch.cuda.is_available() else 'cpu'      )
            __a				     =    torch.cuda.device_count()
         return device, n_gpu




      @property
      def  __UpperCamelCase							(  self      )							->Optional[Any]:



         '''simple docstring'''
         return is_torch_tpu_available() and self.tpu




      @property
      def  __UpperCamelCase							(  self      )							->int:



         '''simple docstring'''
         requires_backends(self ,   ['torch']      )
         # TODO(PVP): currently only single GPU is supported
         return torch.cuda.current_device()




      @property
      def  __UpperCamelCase							(  self      )							->"torch.device":



         '''simple docstring'''
         requires_backends(self ,   ['torch']      )
         return self._setup_devices[0]




      @property
      def  __UpperCamelCase							(  self      )							->List[Any]:



         '''simple docstring'''
         requires_backends(self ,   ['torch']      )
         return self._setup_devices[1]






      @property
      def  __UpperCamelCase							(  self      )							->List[str]:



         '''simple docstring'''
         return self.n_gpu > 0