code: def simple_config():
      config_dict = {
          "train_batch_size": 2,
          "train_micro_batch_size_per_gpu": 1,
          "steps_per_print": 1,
          "optimizer": {
              "type": "Adam",
              "params": {
                  "lr": 0.001,
                  "betas": [0.9, 0.999],
                  "eps": 1e-8,
                  "weight_decay": 3e-7,
              },
          },
          "pipeline": {"activation_checkpoint_interval": 1},
      }
      return config_dict
  
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 2 for calling a global function with example usage: simple_config() and returns: config_dict