code: def infiniband():
      if torch.distributed.get_rank() == 0:
          t = torch.Tensor(range(100)).cuda()
          torch.distributed.broadcast(t, 0)
      else:
          t = torch.empty(100).cuda()
          torch.distributed.broadcast(t, 0)
  
      assert torch.equal(t, torch.Tensor(range(100)).cuda())
      print(f"t on {torch.distributed.get_rank()} is {t}")
  
imports: from collections import OrderedDict
  from copy import deepcopy
  import os
  import time
  import pytest
  import torch
  from torch import nn
  from fairscale.fair_dev.testing.testing import get_worker_map, torch_spawn
  from fairscale.internal import torch_version
  from fairscale.nn.model_parallel.initialize import get_pipeline_parallel_group
  from fairscale.nn.pipe import AsyncPipe
  from fairscale.nn.pipe.types import LazyModule
label_desc: Use image node_id 2 for calling a global function with example usage: infiniband() without return types