code: def feature_loss(fmap_r, fmap_g):
      loss = 0
      for dr, dg in zip(fmap_r, fmap_g):
          for rl, gl in zip(dr, dg):
              loss += torch.mean(torch.abs(rl - gl))
  
      return loss * 2
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
  from torch.nn.utils import remove_weight_norm, spectral_norm, weight_norm
label_desc: Use image node_id 3 for calling a global function with example usage: feature_loss(fmap_r, fmap_g) and returns: unknown