code: def testSetsQuantizeWeights_ErrorOnWrongNumberOfWeights(self):
      with self.assertRaises(ValueError):
          self.quantize_config.set_quantize_weights(self.layer, [])
  
      quantize_weights = [
          self._dummy_weights(self.cell1.kernel),
          self._dummy_weights(self.cell1.recurrent_kernel),
      ]
      with self.assertRaises(ValueError):
          self.quantize_config.set_quantize_weights(
              self.layer, quantize_weights
          )
  
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 Default8BitQuantizeConfigRNNTest obj's underlying member method code with example usage: obj.testSetsQuantizeWeights_ErrorOnWrongNumberOfWeights() without return types