code: def test_digits_euclidean_two_stage():
      model = GraphCutSelection(100, "euclidean", optimizer="two-stage")
      model.fit(X_digits)
      assert_array_equal(model.ranking, digits_euclidean_ranking)
      assert_array_almost_equal(model.gains, digits_euclidean_gains, 4)
      assert_array_almost_equal(model.subset, X_digits[model.ranking])
  
imports: import scipy
  import numpy
  from apricot import GraphCutSelection
  from apricot.optimizers import *
  from sklearn.datasets import load_digits
  from sklearn.metrics import pairwise_distances
  from numpy.testing import assert_almost_equal
  from numpy.testing import assert_array_equal
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 3 for calling a global function with example usage: test_digits_euclidean_two_stage() without return types