


"""simple docstring"""





from typing import TYPE_CHECKING

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


snake_case__		:     Optional[Any]    				=				{
    '''configuration_speech_to_text''': ['''SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Speech2TextConfig'''],
    '''processing_speech_to_text''': ['''Speech2TextProcessor'''],
}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__		:     Union[str, Any]    				=				['''Speech2TextTokenizer''']

try:
 if not is_speech_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__		:     Tuple    				=				['''Speech2TextFeatureExtractor''']

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__		:     Dict    				=				[
     '''TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TFSpeech2TextForConditionalGeneration''',
     '''TFSpeech2TextModel''',
     '''TFSpeech2TextPreTrainedModel''',
 ]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__		:     Dict    				=				[
     '''SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''Speech2TextForConditionalGeneration''',
     '''Speech2TextModel''',
     '''Speech2TextPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_speech_to_text import SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextConfig
 from .processing_speech_to_text import SpeechaTextProcessor

 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_speech_to_text import SpeechaTextTokenizer

 try:
  if not is_speech_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_speech_to_text import SpeechaTextFeatureExtractor

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_speech_to_text import (
      TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFSpeechaTextForConditionalGeneration,
      TFSpeechaTextModel,
      TFSpeechaTextPreTrainedModel,
  )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_speech_to_text import (
      SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
      SpeechaTextForConditionalGeneration,
      SpeechaTextModel,
      SpeechaTextPreTrainedModel,
  )

else:
 import sys

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






"""simple docstring"""





def      _snake_case						(						_snake_case				:			int ,   _snake_case				:			int			):
      return base * power(_snake_case ,   (exponent - 1)			) if exponent else 1


if __name__ == "__main__":
 print('''Raise base to the power of exponent using recursion...''')
 snake_case__		:     Union[str, Any]    				=				int(input('''Enter the base: ''').strip())
 snake_case__		:     Optional[Any]    				=				int(input('''Enter the exponent: ''').strip())
 snake_case__		:     Any    				=				power(base, abs(exponent))
 if exponent < 0:  # power() does not properly deal w/ negative exponents
  snake_case__		:     Dict    				=				1 / result
 print(f"""{base} to the power of {exponent} is {result}""")


