code: def forward(self, x):
      action_mean = self.fc_mean(x)
  
      zeros = torch.zeros(action_mean.size())
  
      if x.is_cuda:
          zeros = zeros.cuda()
  
      action_logstd = self.logstd(zeros)
  
      return FixedNormal(action_mean, action_logstd.exp())
  
file_path: SerpentAI/serpent/machine_learning/reinforcement_learning/ppo/distributions.py
imports: import math
  import torch
label_desc: Use image node_id 2 for calling the DiagGaussian obj's underlying member method code with example usage: obj.forward(x) and returns: FixedNormal