code: def test_loss_multi_task(self):
      metric = TaskAwareLoss()
      self.assertEqual(metric.result(), {})
      metric.update(torch.tensor(1.0), 1, 0)
      metric.update(torch.tensor(2.0), 1, 1)
      out = metric.result()
      for k, v in out.items():
          self.assertIn(k, [0, 1])
          if k == 0:
              self.assertEqual(v, 1)
          else:
              self.assertEqual(v, 2)
      metric.reset()
      self.assertEqual(metric.result(), {})
  
imports: import unittest
  import torch
  from avalanche.evaluation.metrics import TaskAwareAccuracy, TopkAccuracy, AverageMeanClassAccuracy, MultiStreamAMCA, ClassAccuracy, TaskAwareLoss, ConfusionMatrix, DiskUsage, MAC, CPUUsage, MaxGPU, MaxRAM, Mean, Sum, ElapsedTime, Forgetting, ForwardTransfer, CumulativeAccuracy, LabelsRepartition
  from tests.unit_tests_utils import FAST_TEST, is_github_action
label_desc: Use image node_id 14 for calling the GeneralMetricTests obj's underlying member method code with example usage: obj.test_loss_multi_task() without return types