code: def test_compatible_with_v1_savedmodel(self):
      p1 = Part([1, 4])
      p2 = Part([2, 5])
      p3 = Part([3, 6])
      s = Stack([p1, p2, p3])
      save_path = os.path.join(self.get_temp_dir(), "savedmodel")
  
      @def_function.function(input_signature=[])
      def serve():
          return {"value": s.value()}
  
      exported_value = serve()["value"]
  
      save.save(s, save_path, signatures=serve)
      with ops.Graph().as_default(), session.Session() as sess:
          metagraph = loader.load(sess, ["serve"], save_path)
          value_output = metagraph.signature_def[
              "serving_default"
          ].outputs["value"]
          self.assertAllEqual(
              exported_value, sess.run(value_output.name)
          )
  
imports: import os
  import tempfile
  from absl.testing import parameterized
  from google.protobuf import wrappers_pb2
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.client import session
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import test
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import io_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import gfile
  from tensorflow.python.saved_model import load
  from tensorflow.python.saved_model import loader
  from tensorflow.python.saved_model import registration
  from tensorflow.python.saved_model import save
  from tensorflow.python.trackable import autotrackable
label_desc: Use image node_id 3 for calling the SingleCycleTest obj's underlying member method code with example usage: obj.test_compatible_with_v1_savedmodel() and returns: dict