code: def prune_cluster_preserve_quantize_model(
      clustered_model, preserve_sparsity
  ):
      """Prune_cluster_preserve QAT model."""
  
      pcqat_epoch = 1
      quant_aware_annotate_model = quantize.quantize_annotate_model(
          clustered_model
      )
      quant_aware_model = quantize.quantize_apply(
          quant_aware_annotate_model,
          scheme=default_8bit_cluster_preserve_quantize_scheme.Default8BitClusterPreserveQuantizeScheme(
              preserve_sparsity
          ),
      )
  
      callbacks = []
      quant_aware_model = _train_model(
          quant_aware_model, callbacks, pcqat_epoch
      )
      pcqat_stripped = cluster_utils.strip_clustering_cqat(
          quant_aware_model
      )
  
      return quant_aware_model, pcqat_stripped
  
imports: import numpy
  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.experimental import cluster
  from tensorflow_model_optimization.python.core.quantization.keras import quantize
  from tensorflow_model_optimization.python.core.quantization.keras.collab_opts.cluster_preserve import cluster_utils
  from tensorflow_model_optimization.python.core.quantization.keras.collab_opts.cluster_preserve import default_8bit_cluster_preserve_quantize_scheme
  from tensorflow_model_optimization.python.core.sparsity.keras import prune
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_callbacks
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_schedule
label_desc: Use image node_id 8 for calling a global function with example usage: prune_cluster_preserve_quantize_model(clustered_model, preserve_sparsity) and returns: quant_aware_model,  pcqat_stripped