code: def log_prob(self, x, cond):
      u, sum_log_abs_det_jacobians = self.forward(x, cond)
      return torch.sum(
          self.base_dist.log_prob(u) + sum_log_abs_det_jacobians, dim=-1
      )
  
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 7 for calling the Flow obj's underlying member method code with example usage: obj.log_prob(x, cond) and returns: torch