code: def test_SVMTrain_inputs():
      input_map = dict(
          alphas=dict(
              argstr="-alpha %s",
              extensions=None,
              name_source="in_file",
              name_template="%s_alphas",
              suffix="_alphas",
          ),
          args=dict(
              argstr="%s",
          ),
          censor=dict(
              argstr="-censor %s",
              extensions=None,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          in_file=dict(
              argstr="-trainvol %s",
              copyfile=False,
              extensions=None,
              mandatory=True,
          ),
          kernel=dict(
              argstr="-kernel %s",
          ),
          mask=dict(
              argstr="-mask %s",
              copyfile=False,
              extensions=None,
              position=-1,
          ),
          max_iterations=dict(
              argstr="-max_iterations %d",
          ),
          model=dict(
              argstr="-model %s",
              extensions=None,
              name_source="in_file",
              name_template="%s_model",
              suffix="_model",
          ),
          nomodelmask=dict(
              argstr="-nomodelmask",
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          options=dict(
              argstr="%s",
          ),
          out_file=dict(
              argstr="-bucket %s",
              extensions=None,
              name_source="in_file",
              name_template="%s_vectors",
              suffix="_bucket",
          ),
          outputtype=dict(),
          trainlabels=dict(
              argstr="-trainlabels %s",
              extensions=None,
          ),
          ttype=dict(
              argstr="-type %s",
              mandatory=True,
          ),
          w_out=dict(
              argstr="-wout",
          ),
      )
      inputs = SVMTrain.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_SVMTrain_inputs() without return types