code: def test_lvq_step_reduction(self):
      lvqnet = algorithms.LVQ(
          n_inputs=2,
          n_subclasses=4,
          n_classes=2,
          minstep=0.1,
          step=1.1,
          n_updates_to_stepdrop=200,
      )
  
      n_expected_updates = 0
      for i in range(10):
          n_expected_updates += len(self.data)
          lvqnet.train(self.data, self.target, epochs=1)
          expected_step = 1.1 - (i + 1) * 0.1
          self.assertAlmostEqual(lvqnet.training_step, expected_step)
  
      self.assertEqual(n_expected_updates, lvqnet.n_updates)
      self.assertEqual(lvqnet.training_step, lvqnet.minstep)
  
imports: from functools import partial
  import numpy
  from sklearn import datasets
  from neupy import algorithms, init
  from neupy.exceptions import NotTrained
  from base import BaseTestCase
  from helpers import compare_networks
label_desc: Use image node_id 7 for calling the LVQTestCase obj's underlying member method code with example usage: obj.test_lvq_step_reduction() without return types