code: def test_set_converter_with_quantization_from_int8_config(self):
      representative_data = test_util.create_dataset(
          data_size=10, input_shape=[4], num_classes=3
      )
      config = quantization.QuantizationConfig.for_int8(
          representative_data=representative_data
      )
      model = test_util.build_model(input_shape=[4], num_classes=3)
      saved_model_dir = self.get_temp_dir()
      model.save(saved_model_dir)
      converter = tf.lite.TFLiteConverter.from_saved_model(
          saved_model_dir
      )
      converter = config.set_converter_with_quantization(
          converter=converter
      )
      self.assertEqual(config.optimizations, [tf.lite.Optimize.DEFAULT])
      self.assertEqual(config.inference_input_type, tf.uint8)
      self.assertEqual(config.inference_output_type, tf.uint8)
      self.assertEqual(
          config.supported_ops, [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
      )
      tflite_model = converter.convert()
      interpreter = tf.lite.Interpreter(model_content=tflite_model)
      self.assertEqual(
          interpreter.get_input_details()[0]["dtype"], tf.uint8
      )
      self.assertEqual(
          interpreter.get_output_details()[0]["dtype"], tf.uint8
      )
  
file_path: mediapipe/mediapipe/model_maker/python/core/utils/quantization_test.py
imports: from absl.testing import parameterized
  import tensorflow
  from mediapipe.model_maker.python.core.utils import quantization
  from mediapipe.model_maker.python.core.utils import test_util
label_desc: Use image node_id 3 for calling the QuantizationTest obj's underlying member method code with example usage: obj.test_set_converter_with_quantization_from_int8_config() without return types