class_docstr: Unit tests for the cluster_wrapper module.
docstr: Verifies that ClusterWeights can be initialized with a custom clusterable layer.
docstr_tok: ["Verifies","that","ClusterWeights","can","be","initialized","with","a","custom","clusterable","layer","."]
code: def testCanBeInitializedWithAlreadyClusterableLayer(self):
      """Verifies that ClusterWeights can be initialized with a custom clusterable layer."""
      layer = AlreadyClusterableLayer(10)
      l = cluster_wrapper.ClusterWeights(
          layer,
          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 8 for calling the ClusterWeightsTest obj's underlying member method code with example usage: obj.testCanBeInitializedWithAlreadyClusterableLayer() without return types