code: def test_hashing_transform_seed():
      # check the influence of the seed when computing the hashes
      raw_X = [
          ["foo", "bar", "baz", "foo".encode("ascii")],
          ["bar".encode("ascii"), "baz", "quux"],
      ]
  
      raw_X_ = (((f, 1) for f in x) for x in raw_X)
      indices, indptr, _ = _hashing_transform(
          raw_X_, 2**7, str, False
      )
  
      raw_X_ = (((f, 1) for f in x) for x in raw_X)
      indices_0, indptr_0, _ = _hashing_transform(
          raw_X_, 2**7, str, False, seed=0
      )
      assert_array_equal(indices, indices_0)
      assert_array_equal(indptr, indptr_0)
  
      raw_X_ = (((f, 1) for f in x) for x in raw_X)
      indices_1, _, _ = _hashing_transform(
          raw_X_, 2**7, str, False, seed=1
      )
      with pytest.raises(AssertionError):
          assert_array_equal(indices, indices_1)
  
file_path: scikit-learn/sklearn/feature_extraction/tests/test_feature_hasher.py
imports: import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from sklearn.feature_extraction import FeatureHasher
  from sklearn.feature_extraction._hashing_fast import transform
label_desc: Use image node_id 4 for calling a global function with example usage: test_hashing_transform_seed() without return types