code: def test_MNIBiasCorrection_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          distance=dict(
              argstr="--distance %d",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          in_file=dict(
              argstr="--i %s",
              extensions=None,
              mandatory=True,
          ),
          iterations=dict(
              argstr="--n %d",
              usedefault=True,
          ),
          mask=dict(
              argstr="--mask %s",
              extensions=None,
          ),
          no_rescale=dict(
              argstr="--no-rescale",
          ),
          out_file=dict(
              argstr="--o %s",
              extensions=None,
              hash_files=False,
              keep_extension=True,
              name_source=["in_file"],
              name_template="%s_output",
          ),
          protocol_iterations=dict(
              argstr="--proto-iters %d",
          ),
          shrink=dict(
              argstr="--shrink %d",
          ),
          stop=dict(
              argstr="--stop %f",
          ),
          subjects_dir=dict(),
          transform=dict(
              argstr="--uchar %s",
              extensions=None,
          ),
      )
      inputs = MNIBiasCorrection.input_spec()
  
      for key, metadata in list(input_map.items()):
          for metakey, value in list(metadata.items()):
              assert getattr(inputs.traits()[key], metakey) == value
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_MNIBiasCorrection_inputs() without return types