code: def test_cumsum_still_not_supported():
      """Make sure that cumsum on gpu and deterministic mode still fails.
  
      If this test begins to passes, it means newer Pytorch versions support this and we can drop internal support.
  
      """
      torch.use_deterministic_algorithms(True)
      with pytest.raises(
          RuntimeError,
          match="cumsum_cuda_kernel does not have a deterministic implementation.*",
      ):
          torch.arange(10).float().cuda().cumsum(0)
      torch.use_deterministic_algorithms(False)
  
imports: import sys
  import numpy
  import pytest
  import torch
  from torch import tensor
  from torchmetrics.regression import MeanSquaredError, PearsonCorrCoef
  from torchmetrics.utilities import check_forward_full_state_property, rank_zero_debug, rank_zero_info, rank_zero_warn
  from torchmetrics.utilities.checks import _allclose_recursive
  from torchmetrics.utilities.data import _bincount, _cumsum, _flatten, _flatten_dict, select_topk, to_categorical, to_onehot
  from torchmetrics.utilities.distributed import class_reduce, reduce
  from torchmetrics.utilities.exceptions import TorchMetricsUserWarning
  from torchmetrics.utilities.imports import _TORCH_GREATER_EQUAL_1_13
label_desc: Use image node_id 11 for calling a global function with example usage: test_cumsum_still_not_supported() without return types