code: def test_shape(self, batch_shape, device, dtype):
      E_mat = torch.rand(batch_shape, device=device, dtype=dtype)
      R1, R2, t = epi.decompose_essential_matrix(E_mat)
      assert R1.shape == batch_shape
      assert R2.shape == batch_shape
      assert t.shape == batch_shape[:-1] + (1,)
  
imports: import pytest
  import test_common
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.geometry.epipolar
  from kornia.testing import assert_close
label_desc: Use image node_id 2 for calling the TestDecomposeEssentialMatrix obj's underlying member method code with example usage: obj.test_shape(batch_shape, device, dtype) without return types