code: def forward(self, obs, act=None):
      mu = self.mu_net(obs)
      pi = DiagonalGaussianDistribution(mu, self.log_std)
      logp_a = None
      if act is not None:
          logp_a = pi.log_prob(act)
      return pi, logp_a
  
file_path: spinningup/spinup/exercises/pytorch/problem_set_1_solutions/exercise1_2_soln.py
imports: import torch
  import torch.nn
  import numpy
label_desc: Use image node_id 2 for calling the MLPGaussianActor obj's underlying member method code with example usage: obj.forward(obs, act) and returns: pi,  logp_a