class_docstr: Unit tests for the cluster_wrapper module.
docstr: Verifies that the ClusterWeights instance created from a layer that has a batch shape attribute, will also have this attribute.
docstr_tok: ["Verifies","that","the","ClusterWeights","instance","created","from","a","layer","that","has","a","batch","shape","attribute",",","will","also","have","this","attribute","."]
code: def testIfLayerHasBatchShapeClusterWeightsMustHaveIt(self):
      """Verifies that the ClusterWeights instance created from a layer that has a batch shape attribute, will also have this attribute."""
      l = cluster_wrapper.ClusterWeights(
          layers.Dense(10, input_shape=(10,)),
          number_of_clusters=13,
      )
      self.assertTrue(hasattr(l, "_batch_input_shape"))
  
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 9 for calling the ClusterWeightsTest obj's underlying member method code with example usage: obj.testIfLayerHasBatchShapeClusterWeightsMustHaveIt() without return types