code: def test_tensor_life_without_checkpointing():
      skip_layout = SkipLayout(
          num_partitions=2, skip_routes={(None, "test"): (0, 1)}
      )
      skip_tracker = SkipTrackerThroughPotals(skip_layout)
  
      batch = Batch(torch.tensor([1.0]))
      tensor = torch.tensor([2.0])
  
      skip_tracker.save(batch, None, "test", tensor)
      assert skip_tracker.portals[(None, "test")].tensor_life == 1
  
      skip_tracker.load(batch, None, "test")
      assert skip_tracker.portals[(None, "test")].tensor_life == 0
  
file_path: pytorch/test/distributed/pipeline/sync/skip/test_tracker.py
imports: from queue import Queue
  import threading
  import pytest
  import torch
  from torch import nn
  from torch.distributed.pipeline.sync.checkpoint import enable_checkpointing, enable_recomputing
  from torch.distributed.pipeline.sync.microbatch import Batch
  from torch.distributed.pipeline.sync.skip import pop, skippable, stash
  from torch.distributed.pipeline.sync.skip.layout import SkipLayout
  from torch.distributed.pipeline.sync.skip.tracker import SkipTracker, SkipTrackerThroughPotals, current_skip_tracker
  from torch.testing._internal.common_utils import run_tests
label_desc: Use image node_id 5 for calling a global function with example usage: test_tensor_life_without_checkpointing() without return types