




from typing import TYPE_CHECKING

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


UpperCamelCase								=					{
    'configuration_wav2vec2': ['WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Wav2Vec2Config'],
    'feature_extraction_wav2vec2': ['Wav2Vec2FeatureExtractor'],
    'processing_wav2vec2': ['Wav2Vec2Processor'],
    'tokenization_wav2vec2': ['Wav2Vec2CTCTokenizer', 'Wav2Vec2Tokenizer'],
}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase								=					[
         'WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST',
         'Wav2Vec2ForAudioFrameClassification',
         'Wav2Vec2ForCTC',
         'Wav2Vec2ForMaskedLM',
         'Wav2Vec2ForPreTraining',
         'Wav2Vec2ForSequenceClassification',
         'Wav2Vec2ForXVector',
         'Wav2Vec2Model',
         'Wav2Vec2PreTrainedModel',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase								=					[
         'TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST',
         'TFWav2Vec2ForCTC',
         'TFWav2Vec2Model',
         'TFWav2Vec2PreTrainedModel',
         'TFWav2Vec2ForSequenceClassification',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase								=					[
         'FlaxWav2Vec2ForCTC',
         'FlaxWav2Vec2ForPreTraining',
         'FlaxWav2Vec2Model',
         'FlaxWav2Vec2PreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_wavaveca import WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, WavaVecaConfig
     from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
     from .processing_wavaveca import WavaVecaProcessor
     from .tokenization_wavaveca import WavaVecaCTCTokenizer, WavaVecaTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_wavaveca import (
              WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
              WavaVecaForAudioFrameClassification,
              WavaVecaForCTC,
              WavaVecaForMaskedLM,
              WavaVecaForPreTraining,
              WavaVecaForSequenceClassification,
              WavaVecaForXVector,
              WavaVecaModel,
              WavaVecaPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_wavaveca import (
              TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFWavaVecaForCTC,
              TFWavaVecaForSequenceClassification,
              TFWavaVecaModel,
              TFWavaVecaPreTrainedModel,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_wavaveca import (
              FlaxWavaVecaForCTC,
              FlaxWavaVecaForPreTraining,
              FlaxWavaVecaModel,
              FlaxWavaVecaPreTrainedModel,
          )


else:
     import sys

     UpperCamelCase								=					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






from maths.prime_factors import prime_factors



def 							_A       (						lowerCAmelCase_					: int      ):
     """simple docstring"""

     if not isinstance(lowerCAmelCase_       ,    lowerCAmelCase_      ):
          lowerCAmelCase__          =			F'Input value of [number={number}] must be an integer'
          raise TypeError(lowerCAmelCase_      )
     if number < 1:
          raise ValueError("Input must be a positive integer"      )
     return -1 if len(prime_factors(lowerCAmelCase_      )      ) % 2 else 1


if __name__ == "__main__":
     import doctest

     doctest.testmod()
