code: def too_few_devices(pipe_class):
      model = nn.Sequential(
          nn.Linear(1, 1),
          nn.Linear(1, 1),
          nn.Linear(1, 1),
          nn.Linear(1, 1),
      )
  
      with pytest.raises(IndexError):
          # len(balance) > len(group.size())
          model = pipe_class(
              model, balance=[1, 1, 1, 1], worker_map=get_worker_map()
          )
  
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 11 for calling a global function with example usage: too_few_devices(pipe_class) without return types