code: def test_raises(self):
      with self.assertRaises(ValueError):
          nei_finder = MultiscaleRadiusNeighbourFinder([1], [3, 4])
  
      x = torch.Tensor([[-1, -1], [-1, 1], [1, -1], [1, 1]])
      batch_x = torch.tensor([0, 0, 0, 0])
      y = torch.Tensor([[-1, 0], [1, 0]])
      batch_y = torch.tensor([0, 0])
      nei_finder = MultiscaleRadiusNeighbourFinder([1, 2], [3, 4])
      with self.assertRaises(ValueError):
          nei_finder(x, y, batch_x, batch_y, 10)
  
file_path: torch-points3d/test/test_sampler.py
imports: import unittest
  import torch
  from torch_geometric.data import Data
  from torch_points3d.core.spatial_ops import FPSSampler, RandomSampler, RadiusNeighbourFinder, MultiscaleRadiusNeighbourFinder
  from torch_points3d.modules.VoteNet.dense_samplers import FPSSamplerToDense
label_desc: Use image node_id 5 for calling the TestNeighboorhoodSearch obj's underlying member method code with example usage: obj.test_raises() without return types