code: def test_quantile_aggregation_multi():
      x = torch.tensor(
          [
              [0.0, 1.0, 2.0],
              [3.0, 4.0, 5.0],
              [6.0, 7.0, 8.0],
              [9.0, 0.0, 1.0],
              [2.0, 3.0, 4.0],
              [5.0, 6.0, 7.0],
              [8.0, 9.0, 0.0],
              [1.0, 2.0, 3.0],
              [4.0, 5.0, 6.0],
              [7.0, 8.0, 9.0],
          ]
      )
      index = torch.tensor([0, 0, 0, 0, 1, 1, 1, 2, 2, 2])
  
      qs = [0.25, 0.5, 0.75]
  
      assert torch.allclose(
          QuantileAggregation(qs)(x, index),
          torch.cat(
              [QuantileAggregation(q)(x, index) for q in qs], dim=-1
          ),
      )
  
imports: import pytest
  import torch
  from torch_geometric.nn import MedianAggregation, QuantileAggregation
label_desc: Use image node_id 3 for calling a global function with example usage: test_quantile_aggregation_multi() without return types