code: def testSavedModel(self):
      saved_model_dir = self._getFilepath("model")
      with ops.Graph().as_default():
          with session.Session() as sess:
              in_tensor = array_ops.placeholder(
                  shape=[1, 16, 16, 3],
                  dtype=dtypes.float32,
                  name="inputB",
              )
              out_tensor = in_tensor + in_tensor
              inputs = {"x": in_tensor}
              outputs = {"z": out_tensor}
              saved_model.simple_save(
                  sess, saved_model_dir, inputs, outputs
              )
  
      flags_str = "--saved_model_dir={}".format(saved_model_dir)
      self._run(flags_str, should_succeed=True)
  
imports: import os
  from absl.testing import parameterized
  import numpy
  from tensorflow import keras
  from tensorflow.core.framework import graph_pb2
  from tensorflow.lite.python import test_util
  from tensorflow.lite.python import tflite_convert
  from tensorflow.lite.python.convert import register_custom_opdefs
  from tensorflow.python import tf2
  from tensorflow.python.client import session
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.framework.importer import import_graph_def
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.platform import gfile
  from tensorflow.python.platform import resource_loader
  from tensorflow.python.platform import test
  from tensorflow.python.saved_model import saved_model
  from tensorflow.python.saved_model.save import save
  from tensorflow.python.trackable import autotrackable
  from tensorflow.python.training.training_util import write_graph
label_desc: Use image node_id 7 for calling the TfLiteConvertV1Test obj's underlying member method code with example usage: obj.testSavedModel() without return types