code: def testQuantizeSingleLayer_ProducesFullIntegerModel_TF1(
      self, layer_type, kwargs
  ):
      if not compat.is_v1_apis():
          return
  
      if "input_shape" not in kwargs:
          kwargs["input_shape"] = (5,)
  
      layer = layer_type(**kwargs)
      model = tf.keras.Sequential([layer])
      quantized_model = quantize.quantize_model(model)
  
      with quantize.quantize_scope():
          test_utils.convert_keras_to_tflite(
              model=quantized_model,
              output_path=None,
              is_quantized=True,
              inference_type=tf.uint8,
              inference_input_type=tf.uint8,
              input_quant_params=(0.0, 1.0),
          )
  
file_path: model-optimization/tensorflow_model_optimization/python/core/quantization/keras/quantize_functional_test.py
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.testing import test_utils_mnist
  from tensorflow_model_optimization.python.core.quantization.keras import quantize
  from tensorflow_model_optimization.python.core.quantization.keras import utils
label_desc: Use image node_id 2 for calling the QuantizeFullIntegerModelTest obj's underlying member method code with example usage: obj.testQuantizeSingleLayer_ProducesFullIntegerModel_TF1(layer_type, kwargs) without return types