code: def testFloat(self, enable_mlir):
      input_data = constant_op.constant(1.0, shape=[1])
      root = autotrackable.AutoTrackable()
      root.v1 = variables.Variable(3.0)
      root.v2 = variables.Variable(2.0)
      root.f = def_function.function(lambda x: root.v1 * root.v2 * x)
      concrete_func = root.f.get_concrete_function(input_data)
  
      # Convert model.
      converter = lite.TFLiteConverterV2.from_concrete_functions(
          [concrete_func], root
      )
      converter.target_spec.supported_ops = set(
          [lite.OpsSet.SELECT_TF_OPS]
      )
      converter.experimental_new_converter = enable_mlir
      tflite_model = converter.convert()
  
      # Check the model works with TensorFlow ops.
      interpreter = Interpreter(model_content=tflite_model)
      interpreter.allocate_tensors()
      input_details = interpreter.get_input_details()
      test_input = np.array([4.0], dtype=np.float32)
      interpreter.set_tensor(input_details[0]["index"], test_input)
      interpreter.invoke()
  
      output_details = interpreter.get_output_details()
      expected_output = np.array([24.0], dtype=np.float32)
      output_data = interpreter.get_tensor(output_details[0]["index"])
      self.assertTrue((expected_output == output_data).all())
  
imports: import os
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow.core.framework import graph_pb2
  from tensorflow.lite.python import lite
  from tensorflow.lite.python import test_util
  from tensorflow.lite.python.convert import register_custom_opdefs
  from tensorflow.lite.python.interpreter import Interpreter
  from tensorflow.lite.python.testdata import double_op
  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 list_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.saved_model import saved_model
  from tensorflow.python.trackable import autotrackable
label_desc: Use image node_id 1 for calling the FromConcreteFunctionTest obj's underlying member method code with example usage: obj.testFloat(enable_mlir) without return types