code: def testPruneValidLayersListSuccessful(self):
      model_layers = [
          self.keras_prunable_layer,
          self.keras_non_prunable_layer,
          self.custom_prunable_layer,
      ]
      pruned_layers = prune.prune_low_magnitude(
          model_layers, **self.params
      )
  
      self.assertEqual(len(model_layers), len(pruned_layers))
      for layer, pruned_layer in zip(model_layers, pruned_layers):
          self._validate_pruned_layer(layer, pruned_layer)
  
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 14 for calling the PruneTest obj's underlying member method code with example usage: obj.testPruneValidLayersListSuccessful() without return types