code: def tearDown(self):
      interesting = []
      for o in gc.get_objects():
          if (
              isinstance(o, (torch.Tensor, Dim, Tensor, DimList))
              and id(o) not in self.interesting
          ):
              interesting.append(o)
  
      extra_memory = 0
      if "cuda" in self._testMethodName:
          extra_memory += (
              torch.cuda.memory_allocated() - self.mem_allocated
          )
  
      #  nolevels = _n_levels_in_use() == 0
      if extra_memory != 0 or len(interesting) != 0:
          import refcycle
  
          refcycle.garbage().export_image("garbage.pdf")
      gc.collect()
      # assert nolevels, f"cleanup failed? {_n_levels_in_use()}"
      assert (
          extra_memory == 0
      ), f"extra cuda memory left allocated: {extra_memory}"
      assert len(interesting) == 0, (
          f"extra torch.Tensor, Dim, or Tensor left allocated: {len(interesting)} objects of types:"
          f" { [type(t) for t in interesting] }"
      )
  
imports: from functorch.dim import Tensor, Dim, dims, dimlists, stack, DimensionBindError, DimList
  from attn_ft import BertSelfAttention, Linear
  from attn_positional import BertSelfAttention
  from torch.testing._internal.common_utils import TestCase, run_tests, TEST_CUDA
  from unittest import skip, skipIf
  import torch
  import gc
  from functorch._C import dim
  from contextlib import contextmanager
  from time import perf_counter
label_desc: Use image node_id 2 for calling the TestMin obj's underlying member method code with example usage: obj.tearDown() without return types