text: from builtins import range
  import sys
  sys.path.insert(1,"../../../")
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
  
  def mnist_many_cols_gbm_large():
    train = h2o.import_file(path=pyunit_utils.locate("bigdata/laptop/mnist/train.csv.gz"))
    train.tail()
  
  
    gbm_mnist = H2OGradientBoostingEstimator(ntrees=1,
                                             max_depth=1,
                                             min_rows=10,
                                             learn_rate=0.01)
    gbm_mnist.train(x=list(range(784)), y=784, training_frame=train)
    gbm_mnist.show()
  
  
  if __name__ == "__main__":
    pyunit_utils.standalone_test(mnist_many_cols_gbm_large)
  else:
    mnist_many_cols_gbm_large()
  