code: def test_step_routine(self, op: OperationBase):
      op = op.eval()
      op = op.train()
      if op.magnitude is not None:
          init_mag = op.magnitude.item()
      init_prob = op.probability.item()
  
      optimizer = torch.optim.SGD(op.parameters(), lr=10, momentum=0.9)
  
      for _ in range(5):
          in_tensor = torch.rand(10, 3, 50, 50, requires_grad=True)
          optimizer.zero_grad()
          x = op(in_tensor)
          loss = (x - 0).mean()
          loss.backward()
          optimizer.step()
  
      if op.magnitude is not None:
          assert init_mag != op.magnitude.item()
      if isinstance(op, ops.Equalize):
          # NOTE: Equalize is somehow not working yet to update the probabilities.
          return
      assert init_prob != op.probability.item()
  
imports: import inspect
  from typing import List
  import pytest
  import torch
  from kornia.augmentation.auto.autoaugment import AutoAugment
  from kornia.augmentation.auto.operations import OperationBase, ops
  from kornia.augmentation.auto.rand_augment.rand_augment import RandAugment
  from kornia.augmentation.auto.rand_augment.rand_augment import default_policy
  from kornia.augmentation.auto.trivial_augment import TrivialAugment
  from kornia.augmentation.container import AugmentationSequential
  from kornia.geometry.bbox import bbox_to_mask
  from kornia.testing import assert_close
  from kornia.utils._compat import torch_version
  from test.augmentation.test_container import reproducibility_test
label_desc: Use image node_id 1 for calling the TestOperations obj's underlying member method code with example usage: obj.test_step_routine(op) without return types