


"""simple docstring"""


import random



class 	_a   :
    @staticmethod
    def   _UpperCamelCase							(			SCREAMING_SNAKE_CASE__				:       str					):
          lowerCamelCase__							     =		[ord(_lowerCAmelCase					) for i in text]
          lowerCamelCase__							     =		[]
          lowerCamelCase__							     =		[]
          for i in plain:
                lowerCamelCase__							     =		random.randint(1				,       3_00					)
                lowerCamelCase__							     =		(i + k) * k
                cipher.append(_lowerCAmelCase					)
                key.append(_lowerCAmelCase					)
          return cipher, key


    @staticmethod
    def   _UpperCamelCase							(			SCREAMING_SNAKE_CASE__				:       list[int]				,       SCREAMING_SNAKE_CASE__				:       list[int]					):
          lowerCamelCase__							     =		[]
          for i in range(len(_lowerCAmelCase					)					):
                lowerCamelCase__							     =		int((cipher[i] - (key[i]) ** 2) / key[i]					)
                plain.append(chr(_lowerCAmelCase					)					)
          return "".join(_lowerCAmelCase					)


if __name__ == "__main__":
   _snake_case        =				Onepad().encrypt("Hello")
   print(c, k)
   print(Onepad().decrypt(c, k))







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE						:str			=  {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechConfig''']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE						:List[str]			=  [
       '''UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''UniSpeechForCTC''',
       '''UniSpeechForPreTraining''',
       '''UniSpeechForSequenceClassification''',
       '''UniSpeechModel''',
       '''UniSpeechPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_unispeech import (
          UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
          UniSpeechForCTC,
          UniSpeechForPreTraining,
          UniSpeechForSequenceClassification,
          UniSpeechModel,
          UniSpeechPreTrainedModel,
      )

else:
   import sys

   SCREAMING_SNAKE_CASE						:List[str]			=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




