class_docstr: ## Gaussian Distribution
code: def sample(self):
      # Sample from the distribution
      return self.mean + self.std * torch.randn_like(self.std)
  
imports: from typing import List
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 2 for calling the GaussianDistribution obj's underlying member method code with example usage: obj.sample() and returns: unknown