code: def test_merge_points_small():
      points = torch.tensor(
          [
              [0.0, 0.0],
              [0.0, 1.0],
              [2.0, 0.0],
              [2.0, 0.5],
              [2.0, 1.0],
          ]
      )
      merged_points, groups = merge_points(points, radius=1.0)
  
      assert len(merged_points) == 3
      assert set(map(frozenset, groups)) == set(
          map(frozenset, [[0], [1], [2, 3, 4]])
      )
      assert_equal(merged_points[0], points[0])
      assert_equal(merged_points[1], points[1])
      assert merged_points[2, 0] == 2
      assert 0.325 <= merged_points[2, 1] <= 0.625
  
file_path: pyro/tests/contrib/tracking/test_hashing.py
imports: import logging
  import pytest
  import torch
  from pyro.contrib.tracking.hashing import LSH, ApproxSet, merge_points
  from tests.common import assert_equal
label_desc: Use image node_id 9 for calling a global function with example usage: test_merge_points_small() without return types