code: def __init__(
      self, model, pruner, statistics_batch_num=1, activation="relu"
  ):
      super().__init__(model, pruner)
      self.statistics_batch_num = statistics_batch_num
      self.pruner.hook_id = self._add_activation_collector(self.pruner)
  
      assert activation in ["relu", "relu6"]
      if activation == "relu":
          self.pruner.activation = torch.nn.functional.relu
      elif activation == "relu6":
          self.pruner.activation = torch.nn.functional.relu6
      else:
          self.pruner.activation = None
  
imports: import logging
  import math
  import numpy
  import torch
  from .weight_masker import WeightMasker
label_desc: Use image node_id 1 to create a new ActivationFilterPrunerMasker object from inherited base classes: StructuredWeightMasker with example: obj = ActivationFilterPrunerMasker(model, pruner, statistics_batch_num, activation)