code: def test_model_quantize_without_dataset(self):
      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))
      train_labels = np.random.randint(0, 10, size=(100,))
      train_labels = to_categorical(train_labels, num_classes=10)
  
      q_model = InferenceOptimizer.quantize(
          model, x=train_examples, y=train_labels
      )
      assert q_model(train_examples[0:10]).shape == (10, 10)
  
file_path: BigDL/python/nano/test/inc/tf/test_keras_quantize.py
imports: import pytest
  import operator
  import tempfile
  from unittest import TestCase
  import tensorflow
  from tensorflow.keras.applications.mobilenet_v2 import MobileNetV2
  from keras.utils.np_utils import to_categorical
  import numpy
  from bigdl.nano.tf.keras import Model, InferenceOptimizer
  from bigdl.nano.utils.common import compare_version
label_desc: Use image node_id 2 for calling the TestModelQuantize obj's underlying member method code with example usage: obj.test_model_quantize_without_dataset() without return types