


from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
  if not (is_transformers_available() and is_torch_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_objects import (
      ImageTextPipelineOutput,
      UniDiffuserPipeline,
  )
else:
  from .modeling_text_decoder import UniDiffuserTextDecoder
  from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
  from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline







def      a	(							SCREAMING_SNAKE_CASE_      :		int       ):






       """simple docstring"""





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


if __name__ == "__main__":
  import doctest

  doctest.testmod()

