code: def from_compressor(
      cls,
      compressor: Compressor,
      new_config_list: List[Dict],
      evaluator: Evaluator | None = None,
  ):
      return super().from_compressor(
          compressor, new_config_list, evaluator=evaluator
      )
  
imports: from __future__ import annotations
  import logging
  from typing import Dict, List, Literal, Tuple, overload
  import torch
  from .tools import _DATA, _METRICS, _MASKS, active_sparse_targets_filter, norm_metrics, fpgm_metrics, generate_sparsity
  from ..base.compressor import Compressor, Pruner
  from ..base.target_space import PruningTargetSpace
  from ..base.wrapper import ModuleWrapper
  from ..utils.evaluator import Evaluator
label_desc: Use image node_id 4 for calling the _NormPruner obj's underlying member method code with example usage: obj.from_compressor(cls, compressor, new_config_list, evaluator) and returns: super