code: def test_svd_flip_1d():
      # Make sure svd_flip_1d is equivalent to svd_flip
      u = np.array([1, -4, 2])
      v = np.array([1, 2, 3])
  
      u_expected, v_expected = svd_flip(
          u.reshape(-1, 1), v.reshape(1, -1)
      )
      _svd_flip_1d(u, v)  # inplace
  
      assert_allclose(u, u_expected.ravel())
      assert_allclose(u, [-1, 4, -2])
  
      assert_allclose(v, v_expected.ravel())
      assert_allclose(v, [-1, -2, -3])
  
imports: import warnings
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from sklearn.cross_decomposition import CCA, PLSSVD, PLSCanonical, PLSRegression
  from sklearn.cross_decomposition._pls import _center_scale_xy, _get_first_singular_vectors_power_method, _get_first_singular_vectors_svd, _svd_flip_1d
  from sklearn.datasets import load_linnerud, make_regression
  from sklearn.ensemble import VotingRegressor
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.linear_model import LinearRegression
  from sklearn.utils import check_random_state
  from sklearn.utils.extmath import svd_flip
label_desc: Use image node_id 16 for calling a global function with example usage: test_svd_flip_1d() without return types