code: def huber_loss(e, d):
      """Huber loss function"""
      a = (abs(e) <= d).float()
      b = (e > d).float()
      return a * e**2 / 2 + b * d * (abs(e) - d / 2)
  
imports: import torch
  import torch.nn
  from torch.distributions import Categorical
  import numpy
  import parl
label_desc: Use image node_id 1 for calling a global function with example usage: huber_loss(e, d) and returns: unknown