code: def test_tfdataset_with_string_rdd(self):
      string_rdd = self.sc.parallelize(["123", "456"], 1)
      ds = TFDataset.from_string_rdd(string_rdd, batch_per_thread=1)
      input_tensor = tf.placeholder(dtype=tf.string, shape=(None,))
      output_tensor = tf.string_to_number(input_tensor)
      with tf.Session() as sess:
          tfnet = TFNet.from_session(
              sess, inputs=[input_tensor], outputs=[output_tensor]
          )
      result = tfnet.predict(ds).collect()
      assert result[0] == 123
      assert result[1] == 456
  
imports: import pytest
  from pyspark.ml.linalg import DenseVector
  from bigdl.dllib.feature.common import ChainedPreprocessing, FeatureSet
  from bigdl.dllib.feature.image import *
  from bigdl.orca.test_zoo_utils import ZooTestCase
  from bigdl.dllib.keras.optimizers import Adam
  from bigdl.orca.tfpark import TFNet, TFOptimizer
  import tensorflow
  import numpy
  import os
  from bigdl.orca.tfpark import KerasModel, TFDataset
label_desc: Use image node_id 15 for calling the TestTFDataset obj's underlying member method code with example usage: obj.test_tfdataset_with_string_rdd() without return types