code: def predict_test_data(self):
      data = [
          dict(
              X_train=gs.array([[0.0], [1.0], [2.0], [3.0]]),
              y_train=gs.array([0, 0, 1, 1]),
              X_test=gs.array([[1.1]]),
              y_test=gs.array([0]),
          )
      ]
      return self.generate_tests(data)
  
imports: import geomstats.backend
  from geomstats.test.data import TestData
label_desc: Use image node_id 1 for calling the KNearestNeighborsClassifierEuclideanTestData obj's underlying member method code with example usage: obj.predict_test_data() and returns: self