code: def test_include_known_frames(self):
      if inside_re_worker:
          return
      expand_args_fields(LlffDatasetMapProvider)
  
      provider = LlffDatasetMapProvider(
          base_dir="manifold://co3d/tree/nerf_data/nerf_llff_data/fern",
          object_name="fern",
          n_known_frames_for_test=2,
      )
      dataset_map = provider.get_dataset_map()
  
      for name, types in [
          ("train", ["known"] * 17),
          ("val", ["unseen"] * 3 + ["known"] * 17),
          ("test", ["unseen"] * 3 + ["known"] * 17),
      ]:
          dataset = getattr(dataset_map, name)
          self.assertEqual(len(dataset), len(types))
          for i, frame_type in enumerate(types):
              value = dataset[i]
              self.assertEqual(value.frame_type, frame_type)
              self.assertIsNone(value.fg_probability)
  
      self.assertEqual(len(dataset_map.test.get_eval_batches()), 3)
      for batch in dataset_map.test.get_eval_batches():
          self.assertEqual(len(batch), 3)
          self.assertEqual(
              dataset_map.test[batch[0]].frame_type, "unseen"
          )
          for i in batch[1:]:
              self.assertEqual(dataset_map.test[i].frame_type, "known")
  
file_path: pytorch3d/tests/implicitron/test_data_llff.py
imports: import os
  import unittest
  import torch
  from pytorch3d.implicitron.dataset.blender_dataset_map_provider import BlenderDatasetMapProvider
  from pytorch3d.implicitron.dataset.data_source import ImplicitronDataSource
  from pytorch3d.implicitron.dataset.dataset_base import FrameData
  from pytorch3d.implicitron.dataset.llff_dataset_map_provider import LlffDatasetMapProvider
  from pytorch3d.implicitron.tools.config import expand_args_fields, get_default_args
  from pytorch3d.renderer import PerspectiveCameras
  from tests.common_testing import TestCaseMixin
label_desc: Use image node_id 3 for calling the TestDataLlff obj's underlying member method code with example usage: obj.test_include_known_frames() without return types