





from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
   from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore




class  __UpperCamelCase						(       A__						):
     __A  :     Dict            =      c_float





     @property
     def 		UpperCamelCase(    self				):
        return sizeof(self.value				)




def     A__					(						SCREAMING_SNAKE_CASE_      :			int							,  SCREAMING_SNAKE_CASE_      :			int							,  SCREAMING_SNAKE_CASE_      :			int = 0	)     ->     int:






   """simple docstring"""







   if dimension <= 0:
      _UpperCAmelCase											=      fixed_dimension

   dimension -= num_token_to_add
   return dimension
def     A__					(						SCREAMING_SNAKE_CASE_      :			int							,  SCREAMING_SNAKE_CASE_      :			ParameterFormat	)     ->     int:






   """simple docstring"""







   return num_parameters * dtype.size
def     A__					(						SCREAMING_SNAKE_CASE_      :			str	)     ->     Optional[Union["AutoTokenizer", "AutoFeatureExtractor", "AutoProcessor"]]:






   """simple docstring"""







   from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

   try:
      return AutoProcessor.from_pretrained(SCREAMING_SNAKE_CASE_	)
   except (ValueError, OSError, KeyError):
      _UpperCAmelCase					,			_UpperCAmelCase											=      None, None
      try:
         _UpperCAmelCase											=      AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_	)
      except (OSError, KeyError):
         pass
      try:
         _UpperCAmelCase											=      AutoFeatureExtractor.from_pretrained(SCREAMING_SNAKE_CASE_	)
      except (OSError, KeyError):
         pass

      if tokenizer is not None and feature_extractor is not None:
         raise ValueError(
             F'''Couldn\'t auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor.'''	)
      elif tokenizer is None and feature_extractor is None:
         return None
      elif tokenizer is not None:
         return tokenizer
      else:
         return feature_extractor






import os
import sys
import time

from . import transposition_cipher as trans_cipher
def     A__					(						)     ->     None:






   """simple docstring"""







   _UpperCAmelCase											=      '''Prehistoric Men.txt'''
   _UpperCAmelCase											=      '''Output.txt'''
   _UpperCAmelCase											=      int(input('''Enter key: '''	)	)
   _UpperCAmelCase											=      input('''Encrypt/Decrypt [e/d]: '''	)

   if not os.path.exists(SCREAMING_SNAKE_CASE_	):
      print(F'''File {input_file} does not exist. Quitting...'''	)
      sys.exit()
   if os.path.exists(SCREAMING_SNAKE_CASE_	):
      print(F'''Overwrite {output_file}? [y/n]'''	)
      _UpperCAmelCase											=      input('''> '''	)
      if not response.lower().startswith('''y'''	):
         sys.exit()

   _UpperCAmelCase											=      time.time()
   if mode.lower().startswith('''e'''	):
      with open(SCREAMING_SNAKE_CASE_	) as f:
         _UpperCAmelCase											=      f.read()
      _UpperCAmelCase											=      trans_cipher.encrypt_message(SCREAMING_SNAKE_CASE_							,  SCREAMING_SNAKE_CASE_	)
   elif mode.lower().startswith('''d'''	):
      with open(SCREAMING_SNAKE_CASE_	) as f:
         _UpperCAmelCase											=      f.read()
      _UpperCAmelCase											=      trans_cipher.decrypt_message(SCREAMING_SNAKE_CASE_							,  SCREAMING_SNAKE_CASE_	)

   with open(SCREAMING_SNAKE_CASE_							,  '''w'''	) as output_obj:
      output_obj.write(SCREAMING_SNAKE_CASE_	)

   _UpperCAmelCase											=      round(time.time() - start_time							,  2	)
   print(('''Done (''', total_time, '''seconds )''')	)


if __name__ == "__main__":
   main()