





def 							__snake_case							(    lowerCAmelCase_	)				->						str:
    if number > 0:
        raise ValueError('''input must be a negative integer'''	)
    SCREAMING_SNAKE_CASE__											=			len(bin(lowerCAmelCase_	)[3:]	)
    SCREAMING_SNAKE_CASE__											=			bin(abs(lowerCAmelCase_	) - (1 << binary_number_length)	)[3:]
    SCREAMING_SNAKE_CASE__											=			(
        (
            '''1'''
            + '''0''' * (binary_number_length - len(lowerCAmelCase_	))
            + twos_complement_number
        )
        if number < 0
        else '''0'''
    )
    return "0b" + twos_complement_number


if __name__ == "__main__":
  import doctest

  doctest.testmod()







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A					:				List[str]				=			{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _A					:				Dict				=			[
      """WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """WavLMForAudioFrameClassification""",
      """WavLMForCTC""",
      """WavLMForSequenceClassification""",
      """WavLMForXVector""",
      """WavLMModel""",
      """WavLMPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_wavlm import (
        WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        WavLMForAudioFrameClassification,
        WavLMForCTC,
        WavLMForSequenceClassification,
        WavLMForXVector,
        WavLMModel,
        WavLMPreTrainedModel,
    )

else:
  import sys

  _A					:				List[Any]				=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
