code: def check_y_valid_values_for_pairs(y):
      """Checks that y values are in [-1, 1]"""
      if not np.array_equal(np.abs(y), np.ones_like(y)):
          raise ValueError(
              "When training on pairs, the labels (y) should contain "
              "only values in [-1, 1]. Found an incorrect value."
          )
  
imports: import numpy
  from numpy.linalg import LinAlgError
  from sklearn.datasets import make_spd_matrix
  from sklearn.decomposition import PCA
  from sklearn.utils import check_array
  from sklearn.utils.validation import check_X_y, check_random_state
  from .exceptions import PreprocessorError, NonPSDError
  from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
  from scipy.linalg import pinvh, eigh
  import sys
  import time
  import warnings
label_desc: Use image node_id 10 for calling a global function with example usage: check_y_valid_values_for_pairs(y) without return types