class_docstr: Registry responsible for built-in keras layers.
code: def _weight_names(cls, layer):
      # For layers with zero trainable weights, like Reshape, Pooling.
      if not layer.trainable_weights:
          return []
  
      return cls._LAYERS_WEIGHTS_MAP[layer.__class__]
  
file_path: model-optimization/tensorflow_model_optimization/python/core/clustering/keras/clustering_registry.py
imports: import tensorflow
  from tensorflow_model_optimization.python.core.clustering.keras import clusterable_layer
  from tensorflow_model_optimization.python.core.clustering.keras import clustering_algorithm
label_desc: Use image node_id 3 for calling the ClusteringRegistry obj's underlying member method code with example usage: obj._weight_names(cls, layer) and returns: cls, list