


from typing import TYPE_CHECKING

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


UpperCAmelCase_				:			Any   =	{
    '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:
   UpperCAmelCase_				:			Optional[int]   =	['SpeechT5Tokenizer']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase_				:			Dict   =	[
       '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

   UpperCAmelCase_				:			Tuple   =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






def 	SCREAMING_SNAKE_CASE_						(      __A			:      int  ,   __A			:      int    )     ->		int:

       """simple docstring"""

       while b:
              a_							,		a_ :		int							=  b, a % b
       return a







def 	SCREAMING_SNAKE_CASE_						(      __A			:      int  ,   __A			:      int    )     ->		int:

       """simple docstring"""

       return a if b == 0 else euclidean_gcd_recursive(__A  ,   a % b    )







def 	SCREAMING_SNAKE_CASE_						(      )     ->		str:

       """simple docstring"""

       print(F"""euclidean_gcd(3, 5) = {euclidean_gcd(3  ,   5    )}"""    )
       print(F"""euclidean_gcd(5, 3) = {euclidean_gcd(5  ,   3    )}"""    )
       print(F"""euclidean_gcd(1, 3) = {euclidean_gcd(1  ,   3    )}"""    )
       print(F"""euclidean_gcd(3, 6) = {euclidean_gcd(3  ,   6    )}"""    )
       print(F"""euclidean_gcd(6, 3) = {euclidean_gcd(6  ,   3    )}"""    )

       print(F"""euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3  ,   5    )}"""    )
       print(F"""euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5  ,   3    )}"""    )
       print(F"""euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1  ,   3    )}"""    )
       print(F"""euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3  ,   6    )}"""    )
       print(F"""euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6  ,   3    )}"""    )


if __name__ == "__main__":
   main()


