



"""simple docstring"""







def   a_	(			__a      ):
     if not isinstance(__a		,							__a      ):
          raise ValueError('''Input series is not valid, valid series - [1, 2/3, 2]'''      )
     if len(__a      ) == 0:
          raise ValueError('''Input list must be a non empty list'''      )
     if len(__a      ) == 1 and series[0] != 0:
          return True
     A__				=   []
     A__				=   len(__a      )
     for i in range(0		,							__a      ):
          if series[i] == 0:
               raise ValueError('''Input series cannot have 0 as an element'''      )
          rec_series.append(1 / series[i]      )
     A__				=   rec_series[1] - rec_series[0]
     for index in range(2		,							__a      ):
          if rec_series[index] - rec_series[index - 1] != common_diff:
               return False
     return True



def   a_	(			__a      ):
     if not isinstance(__a		,							__a      ):
          raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''      )
     if len(__a      ) == 0:
          raise ValueError('''Input list must be a non empty list'''      )
     A__				=   0
     for val in series:
          answer += 1 / val
     return len(__a      ) / answer


if __name__ == "__main__":
 import doctest

 doctest.testmod()








"""simple docstring"""







from typing import TYPE_CHECKING

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


__snake_case	:				List[Any]  					=			{
    'configuration_unispeech_sat': ['UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechSatConfig'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __snake_case	:				str  					=			[
     'UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'UniSpeechSatForAudioFrameClassification',
     'UniSpeechSatForCTC',
     'UniSpeechSatForPreTraining',
     'UniSpeechSatForSequenceClassification',
     'UniSpeechSatForXVector',
     'UniSpeechSatModel',
     'UniSpeechSatPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_unispeech_sat import (
      UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
      UniSpeechSatForAudioFrameClassification,
      UniSpeechSatForCTC,
      UniSpeechSatForPreTraining,
      UniSpeechSatForSequenceClassification,
      UniSpeechSatForXVector,
      UniSpeechSatModel,
      UniSpeechSatPreTrainedModel,
  )

else:
 import sys

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



