code: def test_table_roundtrip(self, exported_in_tf1):
      input_specs = {"input": tf.TensorSpec([], dtype=tf.string)}
  
      def preprocessing_fn(inputs):
          table_keys = ["cat", "dog", "giraffe"]
          initializer = tf.lookup.KeyValueTensorInitializer(
              keys=table_keys,
              values=tf.cast(tf.range(len(table_keys)), tf.int64),
              key_dtype=tf.string,
              value_dtype=tf.int64,
          )
          table = tf.lookup.StaticHashTable(
              initializer, default_value=-1
          )
          return {"output": table.lookup(inputs["input"])}
  
      export_path = _create_test_saved_model(
          exported_in_tf1,
          input_specs,
          preprocessing_fn,
          base_dir=self.get_temp_dir(),
      )
  
      # Using a computed input gives confidence that the graphs are fused.
      input_string = tf.constant("dog")
      inputs = {"input": input_string}
      saved_model_loader = saved_transform_io_v2.SavedModelLoader(
          export_path
      )
      outputs = saved_model_loader.apply_transform_model(inputs)
      self.assertEqual(1, outputs["output"].numpy())
  
imports: import os
  import shutil
  import tempfile
  import numpy
  import tensorflow
  from tensorflow_transform import graph_context
  from tensorflow_transform import impl_helper
  from tensorflow_transform import tf_utils
  from tensorflow_transform import test_case
  from tensorflow_transform.py_func.api import apply_pyfunc
  from tensorflow_transform.saved import constants
  from tensorflow_transform.saved import saved_transform_io
  from tensorflow_transform.saved import saved_transform_io_v2
  from tensorflow.core.protobuf import meta_graph_pb2
  from tensorflow.python.lib.io import file_io
  from tensorflow.python.ops import script_ops
label_desc: Use image node_id 11 for calling the SavedTransformIOV2Test obj's underlying member method code with example usage: obj.test_table_roundtrip(exported_in_tf1) and returns: dict