code: def test_quantile_invalid():
      X = [[0]] * 5  # ignored
      y = [0] * 5  # ignored
  
      est = DummyRegressor(strategy="quantile", quantile=None)
      err_msg = "When using `strategy='quantile', you have to specify the desired quantile"
      with pytest.raises(ValueError, match=err_msg):
          est.fit(X, y)
  
imports: import numpy
  import pytest
  import scipy.sparse
  from sklearn.base import clone
  from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.exceptions import NotFittedError
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal, ignore_warnings
  from sklearn.utils.fixes import CSC_CONTAINERS
  from sklearn.utils.stats import _weighted_percentile
label_desc: Use image node_id 22 for calling a global function with example usage: test_quantile_invalid() without return types