code: def forward(self, *inputs):
      # apply mask to weight, bias
      self.module.weight.data = self.module.weight.data.mul_(
          self.weight_mask
      )
      if hasattr(self.module, "bias") and self.module.bias is not None:
          self.module.bias.data = self.module.bias.data.mul_(
              self.bias_mask
          )
      return self.module(*inputs)
  
imports: import types
  import logging
  import torch
  from .None import default_layers
label_desc: Use image node_id 2 for calling the PrunerModuleWrapper obj's underlying member method code with example usage: obj.forward() and returns: self