code: def test_train_resume(self):
      train_generator = SomeDataGeneratorWithLen(32, 10, 0)
      valid_generator = SomeDataGeneratorWithLen(32, 10, 0)
      lr_schedulers = [ExponentialLR(0.9), ExponentialLR(0.8)]
      logs = self.test_experiment.train(
          train_generator,
          valid_generator,
          epochs=self.NUM_EPOCHS,
          callbacks=[self.metric_callback],
          lr_schedulers=lr_schedulers,
      )
      self._test_train_integration(logs, num_lr_schedulers=2)
  
      epochs = self.NUM_EPOCHS + 10
      logs = self.test_experiment.train(
          train_generator,
          valid_generator,
          epochs=epochs,
          lr_schedulers=lr_schedulers,
      )
      self._test_train_integration(
          logs,
          epochs=epochs,
          initial_epoch=self.NUM_EPOCHS + 1,
          num_lr_schedulers=2,
      )
  
imports: import os
  from tempfile import TemporaryDirectory
  from unittest import TestCase
  import numpy
  import pandas
  import torch
  from torch import nn
  from torch.utils.data import TensorDataset
  from poutyne import Experiment, ExponentialLR
  from tests.framework.experiment.utils import ConstantMetric, ConstantMetricCallback
  from tests.framework.tools import SomeDataGeneratorWithLen
label_desc: Use image node_id 8 for calling the BaseExperimentTest obj's underlying member method code with example usage: obj.test_train_resume() without return types