code: def _transform_terms(hasher, terms):
      return hasher.transform(np.array(terms).reshape(-1, 1))
  
imports: from __future__ import absolute_import
  from collections import defaultdict, Counter
  from itertools import chain
  from typing import List, Iterable, Any, Dict, Tuple, Union
  import numpy
  import six
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.feature_extraction.text import HashingVectorizer, FeatureHasher
  from sklearn.pipeline import FeatureUnion
  from eli5._feature_names import FeatureNames
label_desc: Use image node_id 3 for calling a global function with example usage: _transform_terms(hasher, terms) and returns: hasher