code: def test_median_strategy_regressor(global_random_seed):
      random_state = np.random.RandomState(seed=global_random_seed)
  
      X = [[0]] * 5  # ignored
      y = random_state.randn(5)
  
      reg = DummyRegressor(strategy="median")
      reg.fit(X, y)
      assert_array_equal(reg.predict(X), [np.median(y)] * len(X))
  
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 18 for calling a global function with example usage: test_median_strategy_regressor(global_random_seed) without return types