code: def test_lr_scheduler_asserts():
      err_msg = r"Argument lr_scheduler should be a subclass of torch.optim.lr_scheduler.(_LRScheduler|LRScheduler)"
      with pytest.raises(TypeError, match=err_msg):
          LRScheduler(123)
  
      with pytest.raises(TypeError, match=err_msg):
          LRScheduler.simulate_values(1, None)
  
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 12 for calling a global function with example usage: test_lr_scheduler_asserts() without return types