code: def test_only_red(self, device, dtype):
      torch.manual_seed(0)  # For reproducibility of random processes
  
      camera: PinholeCamera = create_one_camera(5, 9, device, dtype)
      img: list[Tensor] = create_red_images_for_cameras(camera, device)
  
      # train the model
      nerf_obj = NerfSolver(device=device, dtype=dtype)
      nerf_obj.setup_solver(
          camera,
          1.0,
          3.0,
          False,
          img,
          num_img_rays=15,
          batch_size=5,
          num_ray_points=10,
          lr=1e-2,
      )
      nerf_obj.run(num_epochs=10)
  
      # render the actual image
      renderer = NerfModelRenderer(
          nerf_obj.nerf_model, (5, 9), device, dtype
      )
      img_rendered = renderer.render_view(camera).permute(
          2, 0, 1
      )  # CxHxW
  
      assert_close(
          img_rendered.to(device, dtype),
          img[0].to(device, dtype) / 255.0,
      )
  
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 4 for calling the TestNerfSolver obj's underlying member method code with example usage: obj.test_only_red(device, dtype) without return types