A PyTorch training loop

trainingloop.py

criterion = nn.CrossEntropyLoss()
optimizer = optim.SGD(m.parameters(), lr=0.01)
for epoch in range(0,300):
    gen = DataGenerator([words[word.lower()] for word in ' '.join(sentences).replace('?',' <unk>').split(' ')])
    for x, y in gen:
        m.zero_grad()
        output = m(x)
        loss = criterion(output, y)
        loss.backward()
        optimizer.step()
print(loss)