code: def calc_mask(self, sparsity, wrapper, wrapper_idx=None):
      """
      Calculate the mask of given layer.
      Parameters
      ----------
      sparsity: float
          pruning ratio,  preserved weight ratio is `1 - sparsity`
      wrapper: PrunerModuleWrapper
          layer wrapper of this layer
      wrapper_idx: int
          index of this wrapper in pruner's all wrappers
      Returns
      -------
      dict
          dictionary for storing masks, keys of the dict:
          'weight_mask':  weight mask tensor
          'bias_mask': bias mask tensor (optional)
      """
  
      raise NotImplementedError(
          "{} calc_mask is not implemented".format(
              self.__class__.__name__
          )
      )
  
label_desc: Use image node_id 2 for calling the WeightMasker obj's underlying member method code with example usage: obj.calc_mask(sparsity, wrapper, wrapper_idx) without return types