code: def average_gradients(model):
      """Gradient averaging."""
      size = float(dist.get_world_size())
      for param in model.parameters():
          dist.all_reduce(param.grad.data, op=dist.ReduceOp.SUM)
          param.grad.data /= size
  
imports: import math
  import random
  import time
  import torch
  import torch.distributed
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torchvision.datasets
  import torchvision.transforms
  import fiber
  from fiber.experimental import Ring
label_desc: Use image node_id 2 for calling a global function with example usage: average_gradients(model) without return types