code: def test_simulate_lrs_epoch_step(self, policy):
      lr_sch = LRScheduler(policy, step_size=2)
      lrs = lr_sch.simulate(6, 1)
      expected = np.array([1.0, 1.0, 0.1, 0.1, 0.01, 0.01])
      assert np.allclose(expected, lrs)
  
imports: from unittest.mock import Mock
  import numpy
  import pytest
  from sklearn.base import clone
  from torch.optim import SGD
  from torch.optim.lr_scheduler import CosineAnnealingLR
  from torch.optim.lr_scheduler import ExponentialLR
  from torch.optim.lr_scheduler import LambdaLR
  from torch.optim.lr_scheduler import MultiStepLR
  from torch.optim.lr_scheduler import ReduceLROnPlateau
  from torch.optim.lr_scheduler import StepLR
  from torch.optim.lr_scheduler import CyclicLR
  from skorch import NeuralNetClassifier
  from skorch.callbacks.lr_scheduler import WarmRestartLR, LRScheduler
label_desc: Use image node_id 1 for calling the TestLRCallbacks obj's underlying member method code with example usage: obj.test_simulate_lrs_epoch_step(policy) without return types