code: def test_estimator_graph_predict_dataset(self):
      tf.reset_default_graph()
  
      model = SimpleModel()
      file_path = os.path.join(resource_path, "orca/learn/ncf.csv")
      data_shard = zoo.orca.data.pandas.read_csv(file_path)
  
      est = Estimator.from_graph(
          inputs=[model.user, model.item], outputs=[model.logits]
      )
  
      def transform(df):
          result = {
              "x": (df["user"].to_numpy(), df["item"].to_numpy()),
          }
          return result
  
      data_shard = data_shard.transform_shard(transform)
      dataset = Dataset.from_tensor_slices(data_shard)
      predictions = est.predict(dataset).collect()
      assert len(predictions) == 48
  
imports: import os
  import shutil
  import tempfile
  from unittest import TestCase
  import numpy
  import tensorflow
  from zoo.orca.learn.trigger import SeveralIteration
  from pyspark.sql.context import SQLContext
  import zoo.orca.data.pandas
  from zoo import init_nncontext
  from zoo.orca import OrcaContext
  from zoo.orca.data.tf.data import Dataset
  from zoo.orca.learn.tf.estimator import Estimator
  from zoo.util.tf import save_tf_checkpoint, load_tf_checkpoint, get_checkpoint_state
label_desc: Use image node_id 10 for calling the TestEstimatorForGraph obj's underlying member method code with example usage: obj.test_estimator_graph_predict_dataset() and returns: result