code: def test_lr_warmup_schedule(self, warmup_num_steps, warmup_type):
      config_dict = {
          "train_batch_size": 2,
          "steps_per_print": 1,
          "optimizer": {
              "type": "Adam",
              "params": {"lr": 0.00015},
          },
          "scheduler": {
              "type": WARMUP_LR,
              "params": {
                  WARMUP_MIN_LR: 0.1,
                  WARMUP_MAX_LR: 0.2,
                  WARMUP_NUM_STEPS: warmup_num_steps,
                  WARMUP_TYPE: warmup_type,
              },
          },
          "gradient_clipping": 1.0,
      }
      schedule_params = config_dict["scheduler"]["params"]
      total_num_steps = 2 * warmup_num_steps
      hidden_dim = 10
  
      model = SimpleModel(hidden_dim, empty_grad=False)
      model, _, _, lr_scheduler = deepspeed.initialize(
          config=config_dict,
          model=model,
          model_parameters=model.parameters(),
      )
  
      data_loader = random_dataloader(
          model=model,
          total_samples=total_num_steps * 2,
          hidden_dim=hidden_dim,
          device=model.device,
          dtype=torch.float,
      )
      step_lrs = []
      for n, batch in enumerate(data_loader):
          loss = model(batch[0], batch[1])
          model.backward(loss)
          model.step()
          step_lrs.append(lr_scheduler.get_lr())
  
      # Verify initial lr
      assert step_lrs[0] == [schedule_params[WARMUP_MIN_LR]]
  
      # Verify warmup completion
      warmup_num_steps = schedule_params[WARMUP_NUM_STEPS]
      warmup_max_lr = [schedule_params[WARMUP_MAX_LR]]
      assert step_lrs[warmup_num_steps] == warmup_max_lr
  
      # Verify post-warmup completion
      assert all(
          [warmup_max_lr == lr for lr in step_lrs[warmup_num_steps:]]
      )
  
imports: import torch
  import deepspeed
  import pytest
  from unit.common import DistributedTest
  from unit.simple_model import SimpleModel, random_dataloader
  from deepspeed.runtime.lr_schedules import LR_RANGE_TEST, LR_RANGE_TEST_MIN_LR, LR_RANGE_TEST_STEP_RATE, LR_RANGE_TEST_STEP_SIZE, LR_RANGE_TEST_STAIRCASE
  from deepspeed.runtime.lr_schedules import WARMUP_LR, WARMUP_MIN_LR, WARMUP_MAX_LR, WARMUP_NUM_STEPS, WARMUP_TYPE, WARMUP_LOG_RATE, WARMUP_LINEAR_RATE
  from deepspeed.runtime.lr_schedules import ONE_CYCLE, CYCLE_MIN_LR, CYCLE_MAX_LR, CYCLE_FIRST_STEP_SIZE, DECAY_LR_RATE, DECAY_STEP_SIZE
  from deepspeed.runtime.lr_schedules import CYCLE_MIN_MOM, CYCLE_MAX_MOM, DECAY_MOM_RATE
  from deepspeed.runtime.lr_schedules import WARMUP_DECAY_LR, TOTAL_NUM_STEPS
label_desc: Use image node_id 1 for calling the TestLrSchedule obj's underlying member method code with example usage: obj.test_lr_warmup_schedule(warmup_num_steps, warmup_type) without return types