code: def test_feature_hasher_dicts():
      feature_hasher = FeatureHasher(n_features=16)
      assert "dict" == feature_hasher.input_type
  
      raw_X = [
          {"foo": "bar", "dada": 42, "tzara": 37},
          {"foo": "baz", "gaga": "string1"},
      ]
      X1 = FeatureHasher(n_features=16).transform(raw_X)
      gen = (iter(d.items()) for d in raw_X)
      X2 = FeatureHasher(n_features=16, input_type="pair").transform(
          gen
      )
      assert_array_equal(X1.toarray(), X2.toarray())
  
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 1 for calling a global function with example usage: test_feature_hasher_dicts() without return types