text: import unittest
  import torch
  import avalanche as avl
  from strategies.utils import create_default_args, get_average_metric, get_target_result
  
  
  class StrategyName(unittest.TestCase):
      def test_benchmarkname(self, override_args=None):
          #####################
          # Create arguments  #
          #####################
          # add as many parameters as you want in the input dictionary
          args = create_default_args({'cuda': 0}, override_args)
          device = torch.device(f"cuda:{args.cuda}"
                                if torch.cuda.is_available() and
                                args.cuda >= 0 else "cpu")
  
          #####################
          # FILL HERE         #
          #####################
          # Create your experiment with Avalanche and get the final results into the res variable
          # (e.g. res = strategy.eval(benchmark.test_stream)
  
          #####################
          # Process results   #
          #####################
          # you may find useful the already imported functions
          # `get_average_metric` and `get_target_result`
          if args.check:
              pass
              # check that your current result meets the expected result
              # e.g., self.assertAlmostEqual(target_acc, expected_acc, delta=0.02)
  