'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


lowerCAmelCase_	:		Tuple			=     {
    """configuration_speecht5""": [
        """SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP""",
        """SpeechT5Config""",
        """SpeechT5HifiGanConfig""",
    ],
    """feature_extraction_speecht5""": ["""SpeechT5FeatureExtractor"""],
    """processing_speecht5""": ["""SpeechT5Processor"""],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCAmelCase_	:		Union[str, Any]			=     ["""SpeechT5Tokenizer"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCAmelCase_	:		Tuple			=     [
       """SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """SpeechT5ForSpeechToText""",
       """SpeechT5ForSpeechToSpeech""",
       """SpeechT5ForTextToSpeech""",
       """SpeechT5Model""",
       """SpeechT5PreTrainedModel""",
       """SpeechT5HifiGan""",
   ]

if TYPE_CHECKING:
   from .configuration_speechta import (
       SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
       SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
       SpeechTaConfig,
       SpeechTaHifiGanConfig,
   )
   from .feature_extraction_speechta import SpeechTaFeatureExtractor
   from .processing_speechta import SpeechTaProcessor

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_speechta import SpeechTaTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_speechta import (
          SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
          SpeechTaForSpeechToSpeech,
          SpeechTaForSpeechToText,
          SpeechTaForTextToSpeech,
          SpeechTaHifiGan,
          SpeechTaModel,
          SpeechTaPreTrainedModel,
      )

else:
   import sys

   lowerCAmelCase_	:		Any			=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



'''simple docstring'''





import random




class 		SCREAMING_SNAKE_CASE     :







				'''simple docstring'''





				@staticmethod
				def  snake_case__				(						lowercase__					:						str					)							->tuple[list[int], list[int]]:


										'''simple docstring'''




										_UpperCamelCase			:			List[str]   			=						[ord(lowercase__					) for i in text]
										_UpperCamelCase			:			Dict   			=						[]
										_UpperCamelCase			:			Optional[int]   			=						[]
										for i in plain:
																_UpperCamelCase			:			Tuple   			=						random.randint(1       ,		300					)
																_UpperCamelCase			:			Any   			=						(i + k) * k
																cipher.append(lowercase__					)
																key.append(lowercase__					)
										return cipher, key







				@staticmethod
				def  snake_case__				(						lowercase__					:						list[int]       ,		lowercase__					:						list[int]					)							->str:


										'''simple docstring'''




										_UpperCamelCase			:			int   			=						[]
										for i in range(len(lowercase__					)					):
																_UpperCamelCase			:			List[Any]   			=						int((cipher[i] - (key[i]) ** 2) / key[i]					)
																plain.append(chr(lowercase__					)					)
										return "".join(lowercase__					)


if __name__ == "__main__":
			lowerCAmelCase_	,	lowerCAmelCase_	:		Optional[int]			=     Onepad().encrypt("""Hello""")
			print(c, k)
			print(Onepad().decrypt(c, k))


