code: def test_mmhash3_int_array():
      rng = np.random.RandomState(42)
      keys = rng.randint(-5342534, 345345, size=3 * 2 * 1).astype(
          np.int32
      )
      keys = keys.reshape((3, 2, 1))
  
      for seed in [0, 42]:
          expected = np.array(
              [murmurhash3_32(int(k), seed) for k in keys.flat]
          )
          expected = expected.reshape(keys.shape)
          assert_array_equal(murmurhash3_32(keys, seed), expected)
  
      for seed in [0, 42]:
          expected = np.array(
              [
                  murmurhash3_32(k, seed, positive=True)
                  for k in keys.flat
              ]
          )
          expected = expected.reshape(keys.shape)
          assert_array_equal(
              murmurhash3_32(keys, seed, positive=True), expected
          )
  
file_path: scikit-learn/sklearn/utils/tests/test_murmurhash.py
imports: import numpy
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  from sklearn.utils.murmurhash import murmurhash3_32
label_desc: Use image node_id 2 for calling a global function with example usage: test_mmhash3_int_array() without return types