code: def test_create_lr_scheduler_with_warmup_asserts():
      with pytest.raises(
          TypeError,
          match=r"Argument lr_scheduler should be a subclass of",
      ):
          create_lr_scheduler_with_warmup(
              12,
              warmup_start_value=0.0,
              warmup_end_value=0.1,
              warmup_duration=10,
          )
  
      t1 = torch.zeros([1], requires_grad=True)
      # A) opt lr != warmup_end_value
      optimizer = torch.optim.SGD([t1], lr=0.2)
      torch_lr_scheduler = torch.optim.lr_scheduler.ExponentialLR(
          optimizer=optimizer, gamma=0.98
      )
  
      with pytest.raises(
          ValueError,
          match=r"Argument warmup_duration should be at least 2 events",
      ):
          create_lr_scheduler_with_warmup(
              torch_lr_scheduler,
              warmup_start_value=0.0,
              warmup_end_value=0.1,
              warmup_duration=1,
          )
  
      with pytest.raises(
          TypeError, match=r"Argument warmup_duration should be integer"
      ):
          create_lr_scheduler_with_warmup(
              torch_lr_scheduler,
              warmup_start_value=0.0,
              warmup_end_value=0.1,
              warmup_duration="abc",
          )
  
      with pytest.raises(
          TypeError,
          match=r"Argument output_simulated_values should be a list of None",
      ):
          simulated_values = ()
          create_lr_scheduler_with_warmup(
              torch_lr_scheduler,
              warmup_start_value=0.0,
              warmup_end_value=0.1,
              warmup_duration=10,
              output_simulated_values=simulated_values,
          )
  
imports: from unittest.mock import MagicMock, patch
  import numpy
  import pytest
  import torch
  from torch.optim.lr_scheduler import CosineAnnealingWarmRestarts, ExponentialLR, StepLR
  from ignite.engine import Engine, Events
  from ignite.handlers.param_scheduler import ConcatScheduler, CosineAnnealingScheduler, create_lr_scheduler_with_warmup, LinearCyclicalScheduler, LRScheduler, ParamGroupScheduler, ParamScheduler, PiecewiseLinear, ReduceLROnPlateauScheduler
  from tests.ignite.contrib.handlers import MockFP16DeepSpeedZeroOptimizer
label_desc: Use image node_id 17 for calling a global function with example usage: test_create_lr_scheduler_with_warmup_asserts() without return types