code: def test_forward_tensor_mode(self, device, cfg_path):
      with_semantic = "panoptic" in cfg_path
      model_cfg = self._create_model_cfg(cfg_path)
      detector = MODELS.build(model_cfg)
      if device == "cuda" and not torch.cuda.is_available():
          return unittest.skip("test requires GPU and torch+cuda")
      detector = detector.to(device)
  
      packed_inputs = demo_mm_inputs(
          2,
          [[3, 128, 128], [3, 125, 130]],
          sem_seg_output_strides=1,
          with_mask=True,
          with_semantic=with_semantic,
      )
      data = detector.data_preprocessor(packed_inputs, False)
      out = detector.forward(**data, mode="tensor")
      self.assertIsInstance(out, tuple)
  
imports: import unittest
  import torch
  from parameterized import parameterized
  from mmdet.registry import MODELS
  from mmdet.structures import DetDataSample
  from mmdet.testing._utils import demo_mm_inputs, get_detector_cfg
  from mmdet.utils import register_all_modules
label_desc: Use image node_id 6 for calling the TestMask2Former obj's underlying member method code with example usage: obj.test_forward_tensor_mode(device, cfg_path) and returns: unittest