code: def test_smoke(self, batch_size, device, dtype):
      H, W = 250, 500
      fx, fy = W, H
      cx, cy = W / 2, H / 2
      eps = 1e-12
      seed = 77
      low, high = -500, 500
  
      intrinsics = self._create_intrinsics(
          batch_size, fx, fy, cx, cy, device=device, dtype=dtype
      )
  
      # Setting the projection matrix to the intrinsic matrix for
      # simplicity (i.e. assuming that the RT matrix is an identity matrix)
      proj_mat = intrinsics
  
      torch.manual_seed(seed)
      cam_coords_src = self._get_samples(
          (batch_size, H, W, 3), low, high, device, dtype
      )
  
      pixel_coords_dst = kornia.geometry.camera.cam2pixel(
          cam_coords_src=cam_coords_src, dst_proj_src=proj_mat, eps=eps
      )
      assert pixel_coords_dst.shape == (batch_size, H, W, 2)
  
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 4 for calling the TestCam2Pixel obj's underlying member method code with example usage: obj.test_smoke(batch_size, device, dtype) without return types