code: def test_forward(
      self,
      shape,
      padding,
      patchwise_apply,
      same_on_batch,
      keepdim,
      random_apply,
      device,
      dtype,
  ):
      torch.manual_seed(11)
      try:  # skip wrong param settings.
          seq = K.PatchSequential(
              K.color.RgbToBgr(),
              K.ColorJiggle(0.1, 0.1, 0.1, 0.1),
              K.ImageSequential(
                  K.ColorJiggle(0.1, 0.1, 0.1, 0.1, p=0.5),
                  K.RandomPerspective(0.2, p=0.5),
                  K.RandomSolarize(0.1, 0.1, p=0.5),
              ),
              K.RandomMixUpV2(p=1.0),
              grid_size=(2, 2),
              padding=padding,
              patchwise_apply=patchwise_apply,
              same_on_batch=same_on_batch,
              keepdim=keepdim,
              random_apply=random_apply,
          )
      # TODO: improve me and remove the exception.
      except Exception:
          return
  
      input = torch.randn(*shape, device=device, dtype=dtype)
      out = seq(input)
      assert out.shape[-3:] == input.shape[-3:]
  
      reproducibility_test(input, seq)
  
imports: from functools import partial
  from unittest.mock import patch
  import pytest
  import torch
  import kornia
  import kornia.augmentation
  from kornia.augmentation.container.base import ParamItem
  from kornia.constants import BorderType
  from kornia.geometry.bbox import bbox_to_mask
  from kornia.testing import assert_close
label_desc: Use image node_id 2 for calling the TestPatchSequential obj's underlying member method code with example usage: obj.test_forward(shape, padding, patchwise_apply, same_on_batch, keepdim, random_apply, device, dtype) without return types