class_docstr: Unit tests for the cluster_wrapper module.
docstr: Verifies that ClusterWeights can be initialized with a built-in clusterable layer.
docstr_tok: ["Verifies","that","ClusterWeights","can","be","initialized","with","a","built-in","clusterable","layer","."]
code: def testCanBeInitializedWithClusterableLayer(self):
      """Verifies that ClusterWeights can be initialized with a built-in clusterable layer."""
      l = cluster_wrapper.ClusterWeights(
          layers.Dense(10),
          number_of_clusters=13,
      )
      self.assertIsInstance(l, cluster_wrapper.ClusterWeights)
  
imports: import itertools
  import os
  import tempfile
  from absl.testing import parameterized
  import tensorflow
  from tensorflow_model_optimization.python.core.clustering.keras import cluster
  from tensorflow_model_optimization.python.core.clustering.keras import cluster_config
  from tensorflow_model_optimization.python.core.clustering.keras import cluster_wrapper
  from tensorflow_model_optimization.python.core.clustering.keras import clusterable_layer
label_desc: Use image node_id 3 for calling the ClusterWeightsTest obj's underlying member method code with example usage: obj.testCanBeInitializedWithClusterableLayer() without return types