code: def svm_smoke():
      splice = h2o.import_file(
          pyunit_utils.locate("smalldata/splice/splice.svm")
      )
      svm = H2OSupportVectorMachineEstimator(
          gamma=0.01, rank_ratio=0.1, disable_training_metrics=False
      )
      svm.train(y="C1", training_frame=splice)
  
      pred = svm.predict(test_data=splice)
      assert len(pred) == len(splice)
  
      accuracy = svm.model_performance(train=True).accuracy()[0][1]
      print("Accuracy (on train): %s" % accuracy)
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.psvm import H2OSupportVectorMachineEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: svm_smoke() without return types