code: def forward(self, hidden: Tensor) -> Tuple[Tensor, Tensor]:
      mu = self.mean(hidden)
      sigma = self.var(hidden)
      return mu, sigma
  
file_path: gluonts/src/gluonts/nursery/daf/tslib/nn/distributions.py
imports: from typing import List, Tuple
  import torch
  from torch import Tensor
  from torch import nn
  from torch.distributions import Distribution
  from .activations import PositiveSoftplus
label_desc: Use image node_id 2 for calling the GaussianLayer obj's underlying member method code with example usage: obj.forward(hidden) and returns: mu,  sigma