class_docstr: ClusterPreserveQuantizeRegistry is for built-in keras layers.
code: def __init__(self, preserve_sparsity):
      self._config_quantizer_map = {
          "Default8BitQuantizeConfig": ClusterPreserveDefault8BitWeightsQuantizer(
              preserve_sparsity
          ),
          "Default8BitConvQuantizeConfig": ClusterPreserveDefault8BitConvWeightsQuantizer(
              preserve_sparsity
          ),
      }
  
imports: import logging
  import warnings
  import tensorflow
  from tensorflow_model_optimization.python.core.clustering.keras import cluster_config
  from tensorflow_model_optimization.python.core.clustering.keras import clustering_registry
  from tensorflow_model_optimization.python.core.quantization.keras import quant_ops
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
  from tensorflow_model_optimization.python.core.quantization.keras.default_8bit import default_8bit_quantize_registry
  from tensorflow_model_optimization.python.core.quantization.keras.default_8bit import default_8bit_quantizers
label_desc: Use image node_id 1 to create a new ClusterPreserveQuantizeRegistry object from inherited base classes: object with example: obj = ClusterPreserveQuantizeRegistry(preserve_sparsity)