code: def pubdev_2041():
      iris = h2o.import_file(
          pyunit_utils.locate("smalldata/iris/iris.csv")
      )
      s = iris.runif(seed=12345)
      train1 = iris[s >= 0.5]
      train2 = iris[s < 0.5]
  
      m1 = H2ODeepLearningEstimator(epochs=100)
      m1.train(x=list(range(4)), y=4, training_frame=train1)
  
      # update m1 with new training data
      m2 = H2ODeepLearningEstimator(checkpoint=m1.model_id, epochs=200)
      m2.train(x=list(range(4)), y=4, training_frame=train2)
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.deeplearning import H2ODeepLearningEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: pubdev_2041() without return types