code: def __init__(
      self,
      criterion,
      pruned_params,
      pruned_ratios,
      print_prune_params,
      quant_config,
      print_qat_model,
  ):
      super(PrunerQAT, self).__init__()
      assert criterion in [
          "l1_norm",
          "fpgm",
      ], "unsupported prune criterion: {}".format(criterion)
      # Pruner hyperparameter
      self.criterion = criterion
      self.pruned_params = pruned_params
      self.pruned_ratios = pruned_ratios
      self.print_prune_params = print_prune_params
      # QAT hyperparameter
      self.quant_config = quant_config
      self.print_qat_model = print_qat_model
  
file_path: PaddleDetection/ppdet/slim/prune.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from paddle.utils import try_import
  from ppdet.core.workspace import register, serializable
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 1 to create a new PrunerQAT object from inherited base classes: object with example: obj = PrunerQAT(criterion, pruned_params, pruned_ratios, print_prune_params, quant_config, print_qat_model)