code: def test_GenWarpFields_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          bias_field_correction=dict(
              argstr="-n 1",
          ),
          dimension=dict(
              argstr="-d %d",
              position=1,
              usedefault=True,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          force_proceed=dict(
              argstr="-f 1",
          ),
          input_image=dict(
              argstr="-i %s",
              copyfile=False,
              extensions=None,
              mandatory=True,
          ),
          inverse_warp_template_labels=dict(
              argstr="-l",
          ),
          max_iterations=dict(
              argstr="-m %s",
              sep="x",
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          out_prefix=dict(
              argstr="-o %s",
              usedefault=True,
          ),
          quality_check=dict(
              argstr="-q 1",
          ),
          reference_image=dict(
              argstr="-r %s",
              copyfile=True,
              extensions=None,
              mandatory=True,
          ),
          similarity_metric=dict(
              argstr="-s %s",
          ),
          transformation_model=dict(
              argstr="-t %s",
              usedefault=True,
          ),
      )
      inputs = GenWarpFields.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_GenWarpFields_inputs() without return types