code: def _validate_pruned_layer(self, original_layer, wrapped_layer):
      self.assertIsInstance(
          wrapped_layer, pruning_wrapper.PruneLowMagnitude
      )
      self.assertEqual(original_layer, wrapped_layer.layer)
      self.assertEqual(
          self.params["pruning_schedule"],
          wrapped_layer.pruning_schedule,
      )
      self.assertEqual(
          self.params["block_size"], wrapped_layer.block_size
      )
      self.assertEqual(
          self.params["block_pooling_type"],
          wrapped_layer.block_pooling_type,
      )
  
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 3 for calling the PruneTest obj's underlying member method code with example usage: obj._validate_pruned_layer(original_layer, wrapped_layer) without return types