code: def forward(self, x, y=None):
      # MAF eq 4 -- return mean and log std
      m, loga = self.net(self.net_input(x, y)).chunk(chunks=2, dim=-1)
      u = (x - m) * torch.exp(-loga)
      # MAF eq 5
      log_abs_det_jacobian = -loga
      return u, log_abs_det_jacobian
  
imports: import copy
  import math
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.distributions import Normal
label_desc: Use image node_id 3 for calling the MADE obj's underlying member method code with example usage: obj.forward(x, y) and returns: u,  log_abs_det_jacobian