code: def test_two_stage_forward_loss_mode(self, cfg_file):
      model = get_detector_cfg(cfg_file)
      # backbone convert to ResNet18
      model.backbone.depth = 18
      model.neck.in_channels = [64, 128, 256, 512]
      model.backbone.init_cfg = None
  
      from mmdet.registry import MODELS
  
      detector = MODELS.build(model)
  
      if not torch.cuda.is_available():
          return unittest.skip("test requires GPU and torch+cuda")
      detector = detector.cuda()
  
      packed_inputs = demo_mm_inputs(
          2, [[3, 128, 128], [3, 125, 130]], with_mask=True
      )
      data = detector.data_preprocessor(packed_inputs, True)
      # Test loss mode
      losses = detector.forward(**data, mode="loss")
      self.assertIsInstance(losses, dict)
  
file_path: mmdetection/tests/test_models/test_detectors/test_two_stage.py
imports: import unittest
  from unittest import TestCase
  import torch
  from parameterized import parameterized
  from mmdet.structures import DetDataSample
  from mmdet.testing import demo_mm_inputs, get_detector_cfg
  from mmdet.utils import register_all_modules
label_desc: Use image node_id 3 for calling the TestTwoStageMask obj's underlying member method code with example usage: obj.test_two_stage_forward_loss_mode(cfg_file) and returns: unittest