code: def sequential_model():
      model = torch.nn.Sequential(
          *[nn.Linear(HIDDEN_DIM, HIDDEN_DIM) for _ in range(LAYERS)],
          nn.Linear(HIDDEN_DIM, 1),
      )
      return model
  
file_path: deepspeed/tests/unit/pipe/test_pipe_module.py
imports: import copy
  import torch
  import torch.nn
  import deepspeed.comm
  import pytest
  import deepspeed
  from deepspeed.pipe import PipelineModule
  from deepspeed.utils import RepeatingLoader
  from deepspeed.accelerator import get_accelerator
  from unit.common import DistributedTest
label_desc: Use image node_id 1 for calling a global function with example usage: sequential_model() and returns: model