code: def _train_model(self, model):
      model.compile(
          loss="categorical_crossentropy",
          optimizer="sgd",
          metrics=["accuracy"],
      )
      model.fit(
          np.random.rand(20, 10),
          tf.keras.utils.to_categorical(
              np.random.randint(5, size=(20, 1)), 5
          ),
          batch_size=20,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tempfile
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import compat
  from tensorflow_model_optimization.python.core.keras import test_utils
  from tensorflow_model_optimization.python.core.quantization.keras import quantize
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_config
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
label_desc: Use image node_id 4 for calling the QuantizeIntegrationTest obj's underlying member method code with example usage: obj._train_model(model) without return types