code: def test_poutyne():
      callback = PlotLossesPoutyne(outputs=(CheckOutput(),))
      network = Network()
      optimizer = optim.Adam(params=network.parameters(), lr=0.001)
      loss_fn = nn.CrossEntropyLoss()
  
      train_dataloader = get_random_data()
  
      model = Model(network, optimizer, loss_fn)
      model.fit_generator(
          train_dataloader, epochs=2, callbacks=[callback]
      )
  
file_path: livelossplot/tests/external_test_poutyne.py
imports: import torch
  from torch import nn, optim
  from torch.utils.data import TensorDataset, DataLoader
  from poutyne import Model
  from livelossplot import MainLogger, PlotLossesPoutyne
  from livelossplot.outputs import BaseOutput
label_desc: Use image node_id 2 for calling a global function with example usage: test_poutyne() without return types