code: def test_unsupported():
      vec = CountVectorizer()
      clf = BaseEstimator()
      res = explain_prediction(clf, "hello, world", vec=vec)
      assert "BaseEstimator" in res.error
      for expl in format_as_all(res, clf):
          assert "Error" in expl
          assert "BaseEstimator" in expl
  
imports: from __future__ import absolute_import
  from pprint import pprint
  import attr
  import pytest
  from sklearn.base import BaseEstimator
  from sklearn.feature_extraction import DictVectorizer
  from sklearn.feature_extraction.text import CountVectorizer, HashingVectorizer
  from sklearn.linear_model import LinearRegression
  from sklearn.linear_model import LogisticRegression
  from sklearn.pipeline import FeatureUnion
  from eli5 import explain_prediction, explain_weights
  from eli5.formatters import format_as_html
  from eli5.sklearn import invert_hashing_and_fit, InvertableHashingVectorizer
  from .utils import format_as_all, get_all_features, get_names_coefs, write_html
label_desc: Use image node_id 6 for calling a global function with example usage: test_unsupported() without return types