code: def pubdev_5352():
      mnist_original = h2o.import_file(
          pyunit_utils.locate(
              "smalldata/flow_examples/mnist/test.csv.gz"
          )
      )
      predictors = mnist_original.columns[0:-1]
      target = "C785"
      train, new_data = mnist_original.split_frame(
          ratios=[0.5], seed=1234
      )
      drf = H2ORandomForestEstimator(
          model_id="drf", ntrees=3, seed=1234
      )
      drf.train(x=predictors, y=target, training_frame=train)
      drf_checkpoint = H2ORandomForestEstimator(
          model_id="drf_checkpoint",
          checkpoint=drf.model_id,
          ntrees=4,
          seed=1234,
      )
      drf_checkpoint.train(
          x=predictors, y=target, training_frame=new_data
      )
  
      assert drf_checkpoint.ntrees == 4
  
imports: import sys
  import h2o
  from h2o.estimators.random_forest import H2ORandomForestEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: pubdev_5352() without return types