



from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
 from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline










def 					__snake_case     (      _UpperCAmelCase    ):
    if not isinstance(_UpperCAmelCase       ,			_UpperCAmelCase    ):
        raise TypeError('''Input value must be an \'int\' type'''    )

    __a							=    0
    while number:
        position += 1
        number >>= 1

    return position


if __name__ == "__main__":
 import doctest

 doctest.testmod()





