code: def testReturnsConfig_KerasLayer(self):
      model = keras.Sequential([(l.Dense(2, input_shape=(3,)))])
      layer = model.layers[0]
  
      quantize_config = self.quantize_registry.get_quantize_config(
          layer
      )
  
      (weights, weight_quantizers) = self._convert_list(
          quantize_config.get_weights_and_quantizers(layer)
      )
      (activations, activation_quantizers) = self._convert_list(
          quantize_config.get_activations_and_quantizers(layer)
      )
  
      self._assert_weight_quantizers(weight_quantizers)
      self.assertEqual([layer.kernel], weights)
  
      self._assert_activation_quantizers(activation_quantizers)
      self.assertEqual([layer.activation], activations)
  
      quantize_kernel = keras.backend.variable(
          np.ones(layer.kernel.shape.as_list())
      )
      quantize_activation = keras.activations.relu
      quantize_config.set_quantize_weights(layer, [quantize_kernel])
      quantize_config.set_quantize_activations(
          layer, [quantize_activation]
      )
  
      self._assert_kernel_equality(layer.kernel, quantize_kernel)
      self.assertEqual(layer.activation, quantize_activation)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import unittest
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
  from tensorflow_model_optimization.python.core.quantization.keras import utils
  from tensorflow_model_optimization.python.core.quantization.keras.default_8bit import default_8bit_quantize_registry
label_desc: Use image node_id 9 for calling the QuantizeRegistryTest obj's underlying member method code with example usage: obj.testReturnsConfig_KerasLayer() without return types