code: def test_regressor_prediction_independent_of_X(strategy):
      y = [0, 2, 1, 1]
      X1 = [[0]] * 4
      reg1 = DummyRegressor(strategy=strategy, constant=0, quantile=0.7)
      reg1.fit(X1, y)
      predictions1 = reg1.predict(X1)
  
      X2 = [[1]] * 4
      reg2 = DummyRegressor(strategy=strategy, constant=0, quantile=0.7)
      reg2.fit(X2, y)
      predictions2 = reg2.predict(X2)
  
      assert_array_equal(predictions1, predictions2)
  
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 42 for calling a global function with example usage: test_regressor_prediction_independent_of_X(strategy) without return types