code: def test_parameter_change_after_one_epoch(self, device, dtype):
      nerf_obj = NerfSolver(device, dtype)
      cameras: PinholeCamera = create_four_cameras(device, dtype)
      imgs: list[Tensor] = create_random_images_for_cameras(cameras)
      nerf_obj.setup_solver(
          cameras,
          1.0,
          3.0,
          True,
          imgs,
          num_img_rays=45,
          batch_size=1,
          num_ray_points=10,
      )
  
      params_before_update = [
          torch.clone(param).detach()
          for param in nerf_obj.nerf_model.parameters()
      ]
  
      nerf_obj.run(num_epochs=5)
  
      params_after_update = [
          torch.clone(param).detach()
          for param in nerf_obj.nerf_model.parameters()
      ]
  
      assert all(
          not torch.equal(param_before_update, param_after_update)
          for param_before_update, param_after_update in zip(
              params_before_update, params_after_update
          )
      )
  
file_path: kornia/test/nerf/test_nerf_solver.py
imports: import pytest
  import torch
  from kornia.core import Tensor
  from kornia.geometry.camera import PinholeCamera
  from kornia.nerf.nerf_model import NerfModelRenderer
  from kornia.nerf.nerf_solver import NerfSolver
  from kornia.testing import assert_close
  from test.nerf.test_data_utils import create_random_images_for_cameras, create_red_images_for_cameras
  from test.nerf.test_rays import create_four_cameras, create_one_camera
label_desc: Use image node_id 1 for calling the TestNerfSolver obj's underlying member method code with example usage: obj.test_parameter_change_after_one_epoch(device, dtype) without return types