code: def test_model_quantize_openvino_with_only_x(self):
      model = MobileNetV2(
          weights=None, input_shape=[40, 40, 3], classes=10
      )
      model = Model(inputs=model.inputs, outputs=model.outputs)
      # test numpy array
      train_examples = np.random.random((100, 40, 40, 3))
      openvino_quantized_model = InferenceOptimizer.quantize(
          model, accelerator="openvino", x=train_examples, y=None
      )
  
      preds = model.predict(train_examples)
      openvino_preds = openvino_quantized_model.predict(train_examples)
      np.testing.assert_allclose(preds, openvino_preds, rtol=1e-2)
  
      # test tf tensor
      train_examples = tf.convert_to_tensor(train_examples)
      openvino_quantized_model = InferenceOptimizer.quantize(
          model, accelerator="openvino", x=train_examples, y=None
      )
  
      preds = model.predict(train_examples)
      openvino_preds = openvino_quantized_model.predict(train_examples)
      np.testing.assert_allclose(preds, openvino_preds, rtol=1e-2)
  
      # test dataset
      train_examples = np.random.random((100, 40, 40, 3))
      train_dataset = tf.data.Dataset.from_tensor_slices(train_examples)
      openvino_quantized_model = InferenceOptimizer.quantize(
          model, accelerator="openvino", x=train_dataset, y=None
      )
  
      preds = model.predict(train_examples)
      openvino_preds = openvino_quantized_model.predict(train_examples)
      np.testing.assert_allclose(preds, openvino_preds, rtol=1e-2)
  
file_path: BigDL/python/nano/test/openvino/tf/test_openvino_quantize.py
imports: from unittest import TestCase
  import tensorflow
  import pytest
  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_quantize_openvino_with_only_x() without return types