class_docstr: Weight clustering compression module config.
class_docstr_tok: ["Weight","clustering","compression","module","config","."]
code: def get_compressible_weights(
      self, original_layer: tf.keras.layers.Layer
  ) -> List[str]:
      if isinstance(
          original_layer, tf.keras.layers.Conv2D
      ) or isinstance(original_layer, tf.keras.layers.Dense):
          return [original_layer.kernel]
      return []
  
file_path: model-optimization/tensorflow_model_optimization/python/core/common/keras/compression/algorithms/weight_clustering.py
imports: from typing import List
  import tensorflow
  from tensorflow_model_optimization.python.core.clustering.keras import clustering_centroids
  from tensorflow_model_optimization.python.core.clustering.keras import clustering_registry
  from tensorflow_model_optimization.python.core.clustering.keras.cluster_config import GradientAggregation
  from tensorflow_model_optimization.python.core.common.keras.compression import algorithm
label_desc: Use image node_id 5 for calling the WeightClustering obj's underlying member method code with example usage: obj.get_compressible_weights(original_layer) and returns: list, list