code: def test_training_with_l2_regularization(self):
      x_train, x_test, y_train, y_test = simple_classification()
      mnet = algorithms.Momentum(
          [layers.Input(10), layers.Sigmoid(20), layers.Sigmoid(1)],
          step=0.35,
          momentum=0.99,
          batch_size=None,
          verbose=False,
          nesterov=True,
          regularizer=algorithms.l2(0.001),
      )
      mnet.train(x_train, y_train, x_test, y_test, epochs=40)
      self.assertGreater(0.15, mnet.errors.valid[-1])
  
file_path: neupy/tests/algorithms/test_regularizers.py
imports: import numpy
  from neupy import algorithms, layers
  from base import BaseTestCase
  from helpers import simple_classification
label_desc: Use image node_id 4 for calling the L2RegularizationTestCase obj's underlying member method code with example usage: obj.test_training_with_l2_regularization() without return types