class_docstr: ClusterPreserveWeightsQuantizer for default 8bit Conv2D weights.
code: def build(self, tensor_shape, name, layer):
      result = ClusterPreserveDefaultWeightsQuantizer._build_clusters(
          self, name, layer
      )
      result.update(
          default_8bit_quantizers.Default8BitConvWeightsQuantizer.build(
              self, tensor_shape, name, layer
          )
      )
      return result
  
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 2 for calling the ClusterPreserveDefault8BitConvWeightsQuantizer obj's underlying member method code with example usage: obj.build(tensor_shape, name, layer) and returns: result