code: def inverse(self, u, y=None, sum_log_abs_det_jacobians=None):
      # MAF eq 3
      # D = u.shape[-1]
      x = torch.zeros_like(u)
      # run through reverse model
      for i in self.input_degrees:
          m, loga = self.net(self.net_input(x, y)).chunk(
              chunks=2, dim=-1
          )
          x[..., i] = u[..., i] * torch.exp(loga[..., i]) + m[..., i]
      log_abs_det_jacobian = loga
      return x, 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 4 for calling the MADE obj's underlying member method code with example usage: obj.inverse(u, y, sum_log_abs_det_jacobians) and returns: x,  log_abs_det_jacobian