code: def test_gpu_faiss_nearest_neighbors_execution(setup_gpu):
      rs = np.random.RandomState(0)
  
      raw_X = rs.rand(10, 5)
      raw_Y = rs.rand(8, 5)
  
      # test faiss execution
      X = mt.tensor(raw_X, chunk_size=7).to_gpu()
      Y = mt.tensor(raw_Y, chunk_size=8).to_gpu()
  
      nn = NearestNeighbors(
          n_neighbors=3, algorithm="faiss", metric="l2"
      )
      nn.fit(X)
  
      ret = nn.kneighbors(Y)
  
      snn = SkNearestNeighbors(
          n_neighbors=3, algorithm="auto", metric="l2"
      )
      snn.fit(raw_X)
      expected = snn.kneighbors(raw_Y)
  
      result = [r.fetch() for r in ret]
      np.testing.assert_almost_equal(
          result[0].get(), expected[0], decimal=6
      )
      np.testing.assert_almost_equal(result[1].get(), expected[1])
  
file_path: mars/mars/learn/neighbors/tests/test_nearest_neighbors.py
imports: import numpy
  import scipy.sparse
  import pytest
  from ....None import tensor
  from ....core import tile
  from ....lib.sparse import SparseNDArray
  from ....tests.core import require_cupy
  from ....utils import lazy_import
  from ...proxima.core import proxima
  from ..None import NearestNeighbors
label_desc: Use image node_id 6 for calling a global function with example usage: test_gpu_faiss_nearest_neighbors_execution(setup_gpu) without return types