code: def test_transform_without_ignore(self):
      track_results = self.pack_track_inputs(self.results_1)
      assert isinstance(track_results, dict)
  
      inputs = track_results["inputs"]
      assert isinstance(inputs, torch.Tensor)
      assert inputs.shape == (3, 3, self.H, self.W)
  
      track_data_sample = track_results["data_samples"]
      assert len(track_data_sample) == 3
      assert (
          "key_frames_inds" in track_data_sample.metainfo
          and track_data_sample.key_frames_inds == [1]
      )
      assert (
          "ref_frames_inds" in track_data_sample.metainfo
          and track_data_sample.ref_frames_inds == [0, 2]
      )
      for i, data_sample in enumerate(track_data_sample):
          assert data_sample.gt_instances.bboxes.shape == (2, 4)
          assert len(data_sample.gt_instances.masks) == 2
          assert (
              data_sample.gt_instances.labels.numpy()
              == self.gt_bboxes_labels[i]
          ).all()
          assert (
              data_sample.gt_instances.instances_ids.numpy()
              == self.gt_instances_ids[i]
          ).all()
          for key in self.meta_keys:
              assert data_sample.metainfo[key] == getattr(self, key)[i]
  
imports: import copy
  import os.path
  import unittest
  import numpy
  import torch
  from mmengine.structures import InstanceData, LabelData, PixelData
  from mmdet.datasets.transforms import PackDetInputs, PackReIDInputs, PackTrackInputs
  from mmdet.structures import DetDataSample, ReIDDataSample
  from mmdet.structures.mask import BitmapMasks
label_desc: Use image node_id 2 for calling the TestPackTrackInputs obj's underlying member method code with example usage: obj.test_transform_without_ignore() without return types