code: def test_closure_result_deepcopy():
      closure_loss = torch.tensor(123.45)
      result = ClosureResult(closure_loss)
  
      assert closure_loss.data_ptr() == result.closure_loss.data_ptr()
      # the `loss` is cloned so the storage is different
      assert closure_loss.data_ptr() != result.loss.data_ptr()
  
      copy = result.asdict()
      assert result.loss == copy["loss"]
      assert copy.keys() == {"loss"}
  
      # no copy
      assert id(result.loss) == id(copy["loss"])
      assert result.loss.data_ptr() == copy["loss"].data_ptr()
  
file_path: pytorch-lightning/tests/tests_pytorch/loops/optimization/test_optimizer_loop.py
imports: from typing import Dict, Generic, Iterator, Mapping, TypeVar
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.loops.optimization.automatic import ClosureResult
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
label_desc: Use image node_id 1 for calling a global function with example usage: test_closure_result_deepcopy() without return types