code: def test_convert_predict_list_of_array(self):
      tf.reset_default_graph()
  
      sc = init_nncontext()
      sqlcontext = SQLContext(sc)
      rdd = sc.parallelize([(1, 2, 3), (4, 5, 6), (7, 8, 9)])
      df = rdd.toDF(["feature", "label", "c"])
      predict_rdd = df.rdd.map(
          lambda row: [np.array([1, 2]), np.array(0)]
      )
      resultDF = convert_predict_rdd_to_dataframe(df, predict_rdd)
      resultDF.printSchema()
      print(resultDF.collect()[0])
      predict_rdd = df.rdd.map(lambda row: np.array(1))
      resultDF = convert_predict_rdd_to_dataframe(df, predict_rdd)
      resultDF.printSchema()
      print(resultDF.collect()[0])
  
imports: import shutil
  from unittest import TestCase
  import tensorflow
  from bigdl.orca import OrcaContext
  from bigdl.orca.learn.trigger import SeveralIteration
  from bigdl.orca.learn.tf.estimator import Estimator
  from bigdl.dllib.nncontext import *
  from bigdl.orca.learn.utils import convert_predict_rdd_to_dataframe
  from bigdl.orca.learn.tf.estimator import save_model_dir
label_desc: Use image node_id 13 for calling the TestEstimatorForKeras obj's underlying member method code with example usage: obj.test_convert_predict_list_of_array() without return types