code: def test_ConvertXFM_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          concat_xfm=dict(
              argstr="-concat",
              position=-3,
              requires=["in_file2"],
              xor=["invert_xfm", "concat_xfm", "fix_scale_skew"],
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          fix_scale_skew=dict(
              argstr="-fixscaleskew",
              position=-3,
              requires=["in_file2"],
              xor=["invert_xfm", "concat_xfm", "fix_scale_skew"],
          ),
          in_file=dict(
              argstr="%s",
              extensions=None,
              mandatory=True,
              position=-1,
          ),
          in_file2=dict(
              argstr="%s",
              extensions=None,
              position=-2,
          ),
          invert_xfm=dict(
              argstr="-inverse",
              position=-3,
              xor=["invert_xfm", "concat_xfm", "fix_scale_skew"],
          ),
          out_file=dict(
              argstr="-omat %s",
              extensions=None,
              genfile=True,
              hash_files=False,
              position=1,
          ),
          output_type=dict(),
      )
      inputs = ConvertXFM.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_ConvertXFM_inputs() without return types