code: def test_scatter_any(device):
      src = torch.randn(6, 4, device=device)
      index = torch.tensor([0, 0, 1, 1, 2, 2], device=device)
  
      out = scatter(src, index, dim=0, reduce="any")
  
      for i in range(3):
          for j in range(4):
              assert (
                  float(out[i, j]) in src[2 * i : 2 * i + 2, j].tolist()
              )
  
file_path: pytorch_geometric/test/utils/test_scatter.py
imports: from itertools import product
  import pytest
  import torch
  import torch_geometric.typing
  from torch_geometric.profile import benchmark
  from torch_geometric.testing import withCUDA, withPackage
  from torch_geometric.utils import group_argsort, scatter
  from torch_geometric.utils._scatter import scatter_argmax
label_desc: Use image node_id 4 for calling a global function with example usage: test_scatter_any(device) without return types