code: def test_model_trace_openvino_gpu_save_load(self):
      # test whether contains GPU
      from openvino.runtime import Core
  
      core = Core()
      devices = core.available_devices
      gpu_avaliable = any("GPU" in x for x in devices)
  
      if gpu_avaliable is False:
          return
  
      model = MobileNetV2(
          weights=None, input_shape=[40, 40, 3], classes=10
      )
      model = Model(inputs=model.inputs, outputs=model.outputs)
      train_examples = np.random.random((100, 40, 40, 3))
  
      # trace a Keras model
      openvino_model = InferenceOptimizer.trace(
          model, accelerator="openvino", thread_num=4, device="GPU"
      )
      y_hat = openvino_model(train_examples[:10])
      assert y_hat.shape == (10, 10)
  
      with tempfile.TemporaryDirectory() as tmp_dir_name:
          InferenceOptimizer.save(openvino_model, tmp_dir_name)
          load_model = InferenceOptimizer.load(
              tmp_dir_name, model
          )  # GPU model
          load_model = InferenceOptimizer.load(
              tmp_dir_name, model, device="CPU"
          )
  
file_path: BigDL/python/nano/test/openvino/tf/test_openvino.py
imports: from unittest import TestCase
  import tensorflow
  from tensorflow.keras.applications.mobilenet_v2 import MobileNetV2
  import numpy
  from bigdl.nano.tf.keras import Model, InferenceOptimizer
  import tempfile
  from bigdl.nano.deps.openvino.tf.model import KerasOpenVINOModel
label_desc: Use image node_id 3 for calling the TestOpenVINO obj's underlying member method code with example usage: obj.test_model_trace_openvino_gpu_save_load() without return types