code: def test_quasi_newton_sr1(self):
      x_train, x_test, y_train, y_test = simple_classification()
  
      qnnet = algorithms.QuasiNewton(
          network=[
              layers.Input(10),
              layers.Sigmoid(30, weight=init.Orthogonal()),
              layers.Sigmoid(1, weight=init.Orthogonal()),
          ],
          shuffle_data=True,
          show_epoch=20,
          verbose=False,
          update_function="sr1",
          h0_scale=2,
      )
      qnnet.train(x_train, y_train, x_test, y_test, epochs=10)
      result = qnnet.predict(x_test).round()
  
      roc_curve_score = metrics.roc_auc_score(result, y_test)
      self.assertAlmostEqual(0.92, roc_curve_score, places=2)
  
imports: from functools import partial
  from collections import namedtuple
  import numpy
  from sklearn import metrics
  from neupy.utils import asfloat
  from neupy import algorithms, layers, init
  from neupy.algorithms.gd import quasi_newton
  from helpers import simple_classification
  from base import BaseTestCase
label_desc: Use image node_id 5 for calling the QuasiNewtonTestCase obj's underlying member method code with example usage: obj.test_quasi_newton_sr1() without return types