code: def bernoulli_likelihood(x, x_pred, dim=None):
      """Compute Bernoulli likelihood."""
      assert x_pred.min() >= 0.0
      assert x_pred.max() <= 1.0
      lik = td.Bernoulli(probs=x_pred).log_prob(x)
      if torch.isnan(lik.sum()):
          print(lik.sum())
      if dim:
          return lik.sum(dim=dim)
      else:
          return lik.sum()
  
imports: import matplotlib
  import matplotlib.pyplot
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  from torch.nn import Linear
  import os
label_desc: Use image node_id 5 for calling a global function with example usage: bernoulli_likelihood(x, x_pred, dim) and returns: lik, lik