code: def train_network(epochs=2, **kwargs):
      network = algorithms.GradientDescent(
          [
              layers.Input(10),
              layers.Sigmoid(3),
              layers.Sigmoid(1),
          ],
          **kwargs,
      )
  
      data, target = make_classification(30, n_features=10, n_classes=2)
      network.train(data, target, data, target, epochs=epochs)
  
      return network
  
imports: from __future__ import unicode_literals
  from collections import namedtuple
  import numpy
  import progressbar
  from sklearn.datasets import make_classification
  from neupy import algorithms, layers
  from neupy.exceptions import StopTraining
  from neupy.algorithms.signals import format_time
  from base import BaseTestCase
  from helpers import catch_stdout
label_desc: Use image node_id 1 for calling a global function with example usage: train_network(epochs) and returns: network