code: def test_shape(self, batch_size, device, dtype):
      B: int = batch_size
      focal: float = 100.0
      image = torch.rand(B, 3, 4, 4, device=device, dtype=dtype)
      camera_matrix = epi.intrinsics_like(focal, image)
      assert camera_matrix.shape == (B, 3, 3)
      assert camera_matrix.device == image.device
      assert camera_matrix.dtype == image.dtype
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia.geometry.epipolar
  from kornia.testing import assert_close
label_desc: Use image node_id 2 for calling the TestIntrinsicsLike obj's underlying member method code with example usage: obj.test_shape(batch_size, device, dtype) without return types