code: def test_forward(self, device):
      if device == "cuda":
          if not torch.cuda.is_available():
              return unittest.skip("test requires GPU and torch+cuda")
      num_classes = 6
      mask_head = HTCMaskHead(
          with_conv_res=True,
          num_convs=1,
          in_channels=1,
          conv_out_channels=1,
          num_classes=num_classes,
      )
  
      x = torch.rand((1, 1, 10, 10))
      res_feat = torch.rand((1, 1, 10, 10))
  
      with self.assertRaises(AssertionError):
          mask_head(x, return_logits=False, return_feat=False)
  
      results = mask_head(x)
      self.assertEqual(len(results), 2)
      results = mask_head(x, res_feat=res_feat)
      self.assertEqual(len(results), 2)
  
      results = mask_head(x, return_logits=False)
      self.assertIsInstance(results, Tensor)
      results = mask_head(x, return_feat=False)
      self.assertIsInstance(results, Tensor)
  
      results = mask_head(x, res_feat=res_feat, return_logits=False)
      self.assertIsInstance(results, Tensor)
      results = mask_head(x, res_feat=res_feat, return_feat=False)
      self.assertIsInstance(results, Tensor)
  
file_path: mmdetection/tests/test_models/test_roi_heads/test_mask_heads/test_htc_mask_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 HTCMaskHead
label_desc: Use image node_id 1 for calling the TestHTCMaskHead obj's underlying member method code with example usage: obj.test_forward(device) and returns: unittest