
from typing import TYPE_CHECKING

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


lowercase__       ={
    '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:
      lowercase__       =[
          '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:
      lowercase__       =[
          '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:
      lowercase__       =[
          '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

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


from __future__ import annotations




def    __UpperCamelCase     (				lowerCAmelCase__							:				list[float]  ,   lowerCAmelCase__							:				list[float]  ):
 __a :  Dict						=  sorted(numsa + numsa  )
 __a				,       __a :  Optional[Any]						=  divmod(len(lowerCAmelCase__  )  ,   2  )
 if mod == 1:
  return all_numbers[div]
 else:
  return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      lowercase__       =[float(x) for x in input('Enter the elements of first array: ').split()]
      lowercase__       =[float(x) for x in input('Enter the elements of second array: ').split()]
      print(F"""The median of two arrays is: {median_of_two_arrays(array_a, array_a)}""")
