code: def testPruneModelUnsupportedKerasLayerRaisesError(self):
      with self.assertRaises(ValueError):
          prune.prune_low_magnitude(
              keras.Sequential(
                  [
                      self.keras_prunable_layer,
                      self.keras_non_prunable_layer,
                      self.custom_prunable_layer,
                      self.keras_unsupported_layer,
                  ]
              ),
              **self.params,
          )
  
imports: import json
  import tempfile
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import test_utils
  from tensorflow_model_optimization.python.core.sparsity.keras import prunable_layer
  from tensorflow_model_optimization.python.core.sparsity.keras import prune
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_schedule
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_wrapper
label_desc: Use image node_id 11 for calling the PruneTest obj's underlying member method code with example usage: obj.testPruneModelUnsupportedKerasLayerRaisesError() without return types