code: def _r(self):  # output is of size 1 by input_dim
      return (
          (self.m / np.sqrt(self.target_dim))
          * torch.exp(0.5 * self.gamma)
          / torch.sqrt(torch.sum(torch.exp(self.gamma)))
      )
  
file_path: gluonts/src/gluonts/nursery/robust-mts-attack/sparse_layer.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  import torch.distributions
  from torch.distributions import Normal
  from abc import ABC
  import numpy
  import warnings
  import os, pickle
label_desc: Use image node_id 2 for calling the SparseNet obj's underlying member method code with example usage: obj._r() and returns: unknown