code: def testSetsQuantizeWeights(self):
      layer = self._simple_dense_layer()
      quantize_kernel = K.variable(
          np.ones(layer.kernel.shape.as_list())
      )
  
      quantize_config = n_bit_registry.DefaultNBitQuantizeConfig(
          ["kernel"],
          ["activation"],
          False,
          num_bits_weight=4,
          num_bits_activation=4,
      )
      quantize_config.set_quantize_weights(layer, [quantize_kernel])
  
      self._assert_kernel_equality(layer.kernel, quantize_kernel)
  
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.experimental.default_n_bit import default_n_bit_quantize_registry
label_desc: Use image node_id 4 for calling the DefaultNBitQuantizeConfigTest obj's underlying member method code with example usage: obj.testSetsQuantizeWeights() without return types