code: def test_random_erasing(self, device, dtype):
      fill_value = 0.5
      input = torch.randn(3, 3, 100, 100, device=device, dtype=dtype)
      aug = K.AugmentationSequential(
          K.RandomErasing(p=1.0, value=fill_value),
          data_keys=["image", "mask"],
      )
  
      reproducibility_test((input, input), aug)
  
      out = aug(input, input)
      assert torch.all(out[1][out[0] == fill_value] == 0.0)
  
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 8 for calling the TestAugmentationSequential obj's underlying member method code with example usage: obj.test_random_erasing(device, dtype) without return types