code: def test_forward_loss(self, device):
      if device == "cuda":
          if not torch.cuda.is_available():
              return unittest.skip("test requires GPU and torch+cuda")
  
      head = GlobalContextHead(
          num_convs=1,
          in_channels=4,
          conv_out_channels=4,
          num_classes=10,
      )
      feats = [
          torch.rand((1, 4, 64 // 2 ** (i + 1), 64 // 2 ** (i + 1)))
          for i in range(5)
      ]
      mc_pred, x = head(feats)
  
      labels = [torch.randint(0, 10, (10,))]
      loss = head.loss(mc_pred, labels)
      self.assertIsInstance(loss, Tensor)
  
file_path: mmdetection/tests/test_models/test_roi_heads/test_mask_heads/test_global_context_head.py
imports: import unittest
  from unittest import TestCase
  import torch
  from parameterized import parameterized
  from torch import Tensor
  from mmdet.models.roi_heads.mask_heads import GlobalContextHead
label_desc: Use image node_id 1 for calling the TestGlobalContextHead obj's underlying member method code with example usage: obj.test_forward_loss(device) and returns: unittest