code: def add_intercept(X):
      """Add intercept column to X"""
      intercept = np.ones((X.shape[0], 1))
      if sp.issparse(X):
          return sp.hstack([X, intercept]).tocsr()
      else:
          return np.hstack([X, intercept])
  
imports: from __future__ import absolute_import
  from distutils.version import LooseVersion
  from typing import Any, Optional, List, Tuple
  import numpy
  import scipy.sparse
  from sklearn.multiclass import OneVsRestClassifier
  from eli5.sklearn.unhashing import invert_hashing_and_fit, handle_hashing_vec
  from eli5._feature_names import FeatureNames
label_desc: Use image node_id 15 for calling a global function with example usage: add_intercept(X) and returns: sp, np