code: def test(self, client_parameters):
      ds_config = {
          "train_batch_size": 1,
          "optimizer": {"type": "Adam", "params": {"lr": 0.001}},
      }
  
      hidden_dim = 10
      model = SimpleModel(hidden_dim)
  
      if client_parameters:
          model_parameters = list(model.parameters())
      else:
          model_parameters = None
  
      _, ds_optimizer, _, _ = deepspeed.initialize(
          config=ds_config,
          model=model,
          model_parameters=model_parameters,
      )
  
      assert isinstance(ds_optimizer, FusedAdam)
  
imports: import pytest
  from typing import Callable
  import torch
  from torch.optim import Optimizer, Adam, AdamW
  from torch.optim.lr_scheduler import _LRScheduler, LambdaLR
  from unit.simple_model import SimpleModel, random_dataloader
  from unit.common import DistributedTest
  from unit.util import required_torch_version, bf16_required_version_check, required_amp_check
  import deepspeed
  from deepspeed.ops.adam import FusedAdam
  from deepspeed.runtime.lr_schedules import WARMUP_LR, WarmupLR
  from deepspeed.runtime.config import ADAM_OPTIMIZER
  from deepspeed.runtime.utils import see_memory_usage
label_desc: Use image node_id 1 for calling the TestConfigOptimizer obj's underlying member method code with example usage: obj.test(client_parameters) without return types