code: def checkpoint_mode_when_chunks_1(pipe_class):
      model = nn.Sequential(nn.Linear(1, 1))
  
      # All checkpoint modes are fine.
      pipe_class(
          model,
          balance=[1],
          worker_map=get_worker_map(),
          chunks=1,
          checkpoint="except_last",
      )
      pipe_class(
          model,
          balance=[1],
          worker_map=get_worker_map(),
          chunks=1,
          checkpoint="always",
      )
      pipe_class(
          model,
          balance=[1],
          worker_map=get_worker_map(),
          chunks=1,
          checkpoint="never",
      )
  
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 16 for calling a global function with example usage: checkpoint_mode_when_chunks_1(pipe_class) without return types