code: def __init__(
      self,
      model: torch.nn.Module,
      config_list: List[Dict],
      evaluator: Evaluator,
      training_steps: int,
      regular_scale: float = 1.0,
  ):
      ...
  
imports: from __future__ import annotations
  from collections import defaultdict
  import logging
  from typing import Dict, List, Literal, Tuple, overload
  import torch
  from torch.optim import Adam
  from .tools import _METRICS, _MASKS, generate_sparsity, is_active_target
  from ..base.compressor import Compressor, Pruner
  from ..base.target_space import TargetType
  from ..base.wrapper import ModuleWrapper
  from ..utils import Evaluator, _EVALUATOR_DOCSTRING
label_desc: Use image node_id 1 to create a new SlimPruner object from inherited base classes: Pruner with example: obj = SlimPruner(model, config_list, evaluator, training_steps, regular_scale)