code: def test_pinhole_camera_attributes(self, device, dtype):
      batch_size = 1
      height, width = 4, 6
      fx, fy, cx, cy = 1, 2, width / 2, height / 2
      tx, ty, tz = 1, 2, 3
  
      intrinsics = self._create_intrinsics(
          batch_size, fx, fy, cx, cy, device=device, dtype=dtype
      )
      extrinsics = self._create_extrinsics(
          batch_size, tx, ty, tz, device=device, dtype=dtype
      )
      height = (
          torch.ones(batch_size, device=device, dtype=dtype) * height
      )
      width = torch.ones(batch_size, device=device, dtype=dtype) * width
  
      pinhole = kornia.geometry.camera.PinholeCamera(
          intrinsics, extrinsics, height, width
      )
  
      assert pinhole.batch_size == batch_size
      assert pinhole.fx.item() == fx
      assert pinhole.fy.item() == fy
      assert pinhole.cx.item() == cx
      assert pinhole.cy.item() == cy
      assert pinhole.tx.item() == tx
      assert pinhole.ty.item() == ty
      assert pinhole.tz.item() == tz
      assert pinhole.height.item() == height
      assert pinhole.width.item() == width
      assert pinhole.rt_matrix.shape == (batch_size, 3, 4)
      assert pinhole.camera_matrix.shape == (batch_size, 3, 3)
      assert pinhole.rotation_matrix.shape == (batch_size, 3, 3)
      assert pinhole.translation_vector.shape == (batch_size, 3, 1)
  
imports: import math
  import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  from kornia.testing import assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 5 for calling the TestPinholeCamera obj's underlying member method code with example usage: obj.test_pinhole_camera_attributes(device, dtype) without return types