code: def testPrestoToExample(self):
      with beam.Pipeline() as pipeline:
          examples = (
              pipeline
              | "ToTFExample"
              >> executor._PrestoToExample(
                  exec_properties={
                      "input_config": proto_utils.proto_to_json(
                          example_gen_pb2.Input()
                      ),
                      "custom_config": proto_utils.proto_to_json(
                          example_gen_pb2.CustomConfig()
                      ),
                  },
                  split_pattern="SELECT i, f, s FROM `fake`",
              )
          )
  
          feature = {}
          feature["i"] = tf.train.Feature(
              int64_list=tf.train.Int64List(value=[1])
          )
          feature["f"] = tf.train.Feature(
              float_list=tf.train.FloatList(value=[2.0])
          )
          feature["s"] = tf.train.Feature(
              bytes_list=tf.train.BytesList(
                  value=[tf.compat.as_bytes("abc")]
              )
          )
          example_proto = tf.train.Example(
              features=tf.train.Features(feature=feature)
          )
          util.assert_that(examples, util.equal_to([example_proto]))
  
imports: import os
  import random
  from unittest import mock
  import apache_beam
  from apache_beam.testing import util
  import prestodb
  import tensorflow
  from tfx.dsl.io import fileio
  from tfx.examples.custom_components.presto_example_gen.presto_component import executor
  from tfx.examples.custom_components.presto_example_gen.proto import presto_config_pb2
  from tfx.proto import example_gen_pb2
  from tfx.types import artifact_utils
  from tfx.types import standard_artifacts
  from tfx.utils import proto_utils
label_desc: Use image node_id 2 for calling the ExecutorTest obj's underlying member method code with example usage: obj.testPrestoToExample() without return types