code: def assertCanNetworkOverfit(
      self, network_class, epochs=100, min_accepted_loss=0.001
  ):
      x_train = 2 * np.random.random((10, 2)) - 1  # zero centered
      y_train = np.random.random((10, 1))
  
      relu_xavier_normal = init.XavierNormal(gain=4)
      relu_weight = relu_xavier_normal.sample(
          (2, 20), return_array=True
      )
  
      xavier_normal = init.XavierNormal(gain=2)
      sigmoid_weight = xavier_normal.sample((20, 1), return_array=True)
  
      optimizer = network_class(
          [
              layers.Input(2),
              layers.Relu(20, weight=relu_weight),
              layers.Sigmoid(1, weight=sigmoid_weight),
          ]
      )
  
      optimizer.train(x_train, y_train, epochs=epochs)
      self.assertLess(optimizer.errors.train[-1], min_accepted_loss)
  
imports: import pickle
  import inspect
  import logging
  import unittest
  import numpy
  import tensorflow
  from neupy import utils, layers, init
  from neupy.utils import tensorflow_eval, tensorflow_session, shape_to_tuple
  from neupy.layers.base import format_name_if_specified_as_pattern
  from helpers import vectors_for_testing
label_desc: Use image node_id 8 for calling the BaseTestCase obj's underlying member method code with example usage: obj.assertCanNetworkOverfit(network_class, epochs, min_accepted_loss) without return types