code: def test_estimator_keras_dataframe_no_fit(self):
      tf.reset_default_graph()
  
      model = self.create_model()
      sc = init_nncontext()
      sqlcontext = SQLContext(sc)
      file_path = os.path.join(self.resource_path, "orca/learn/ncf.csv")
      df = sqlcontext.read.csv(file_path, header=True, inferSchema=True)
      from pyspark.sql.functions import array
  
      df = df.withColumn("user", array("user")).withColumn(
          "item", array("item")
      )
  
      est = Estimator.from_keras(keras_model=model)
  
      eval_result = est.evaluate(
          df, feature_cols=["user", "item"], label_cols=["label"]
      )
      assert "acc Top1Accuracy" in eval_result
  
      prediction_df = est.predict(
          df, batch_size=4, feature_cols=["user", "item"]
      )
      assert "prediction" in prediction_df.columns
      predictions = prediction_df.collect()
      assert len(predictions) == 48
  
imports: import shutil
  from unittest import TestCase
  import tensorflow
  from zoo.orca import OrcaContext
  from zoo.orca.learn.trigger import SeveralIteration
  from zoo.orca.learn.tf.estimator import Estimator
  from zoo.common.nncontext import *
  from zoo.orca.learn.utils import convert_predict_rdd_to_dataframe
label_desc: Use image node_id 10 for calling the TestEstimatorForKeras obj's underlying member method code with example usage: obj.test_estimator_keras_dataframe_no_fit() without return types