code: def test_gpr_predict_input_not_modified():
      """
      Check that the input X is not modified by the predict method of the
      GaussianProcessRegressor when setting return_std=True.
  
      Non-regression test for:
      https://github.com/scikit-learn/scikit-learn/issues/24340
      """
      gpr = GaussianProcessRegressor(kernel=CustomKernel()).fit(X, y)
  
      X2_copy = np.copy(X2)
      _, _ = gpr.predict(X2, return_std=True)
  
      assert_allclose(X2, X2_copy)
  
imports: import re
  import sys
  import warnings
  import numpy
  import pytest
  from scipy.optimize import approx_fprime
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.gaussian_process import GaussianProcessRegressor
  from sklearn.gaussian_process.kernels import RBF, DotProduct, ExpSineSquared, WhiteKernel
  from sklearn.gaussian_process.kernels import ConstantKernel
  from sklearn.gaussian_process.tests._mini_sequence_kernel import MiniSeqKernel
  from sklearn.utils._testing import assert_allclose, assert_almost_equal, assert_array_almost_equal, assert_array_less
label_desc: Use image node_id 35 for calling a global function with example usage: test_gpr_predict_input_not_modified() without return types