code: def test_with_mosaic(self, device, dtype):
      width, height = 100, 100
      crop_width, crop_height = 3, 3
      input = torch.randn(
          3, 3, width, height, device=device, dtype=dtype
      )
      bbox = torch.tensor(
          [
              [
                  [1.0, 1.0, 2.0, 2.0],
                  [0.0, 0.0, 1.0, 2.0],
                  [0.0, 0.0, 2.0, 1.0],
              ]
          ],
          device=device,
          dtype=dtype,
      ).expand(3, -1, -1)
      aug = K.AugmentationSequential(
          K.RandomCrop(
              (crop_width, crop_height),
              padding=1,
              cropping_mode="resample",
              fill=0,
          ),
          K.RandomHorizontalFlip(p=1.0),
          K.RandomMosaic(p=1.0),
          data_keys=["input", "bbox_xyxy"],
      )
  
      reproducibility_test((input, bbox), aug)
  
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 6 for calling the TestAugmentationSequential obj's underlying member method code with example usage: obj.test_with_mosaic(device, dtype) without return types