code: def test_early_stop_min_delta_on_gpu(self) -> None:
      device = torch.device("cuda:0")
  
      # Loss decreases beyond 0.25 but not more than min_delta
      losses = [
          torch.tensor([0.4], device=device),
          torch.tensor([0.38], device=device),
          torch.tensor([0.31], device=device),
          torch.tensor([0.25], device=device),
          torch.tensor([0.27], device=device),
          torch.tensor([0.24], device=device),
      ]
      es1 = EarlyStopChecker("min", 3, min_delta=0.05)
      es2 = EarlyStopChecker("min", 4, min_delta=0.05)
  
      for loss in losses:
          should_stop = es1.check(torch.tensor(loss))
          self.assertFalse(should_stop)
          should_stop = es2.check(torch.tensor(loss))
          self.assertFalse(should_stop)
  
      # Patience should run out
      should_stop = es1.check(torch.tensor(0.25))
      self.assertTrue(should_stop)
  
      # es2 has more patience than es1
      should_stop = es2.check(torch.tensor(0.25))
      self.assertFalse(should_stop)
      should_stop = es2.check(torch.tensor(0.26))
      self.assertTrue(should_stop)
  
imports: import unittest
  import torch
  from torchtnt.utils.early_stop_checker import EarlyStopChecker
label_desc: Use image node_id 4 for calling the EarlyStopCheckerTest obj's underlying member method code with example usage: obj.test_early_stop_min_delta_on_gpu() without return types