code: def test_smoke_no_transform(self, device):
      x_data = torch.rand(1, 2, 8, 9).to(device)
      aug = kornia.augmentation.RandomShear((10.0, 10.0))
      out = aug(x_data)
      assert out.shape == x_data.shape
      assert aug.inverse(out).shape == x_data.shape
      assert aug.inverse(out, aug._params).shape == x_data.shape
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 1 for calling the TestRandomShear obj's underlying member method code with example usage: obj.test_smoke_no_transform(device) without return types