code: def test_single_custom_layer_is_reduced(self):
      num_units = 5
      num_dims = 3
      reduced_model = get_reduced_model(
          tf.keras.Input(num_dims),
          [DoubleDense(num_units)],
      )
      # Ignore the input layer.
      for l in reduced_model.layers[1:]:
          self.assertIsInstance(l, tf.keras.layers.Dense)
  
imports: from typing import Any
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_privacy.privacy.fast_gradient_clipping import gradient_clipping_utils
label_desc: Use image node_id 1 for calling the GenerateOutputsUsingCoreKerasLayers obj's underlying member method code with example usage: obj.test_single_custom_layer_is_reduced() without return types