optimizer = optim.SGD(model.parameters(), lr = 1e-2)
+ start_t = time.time()
+
for e in range(0, args.nb_epochs):
acc_loss = 0.0
for b in range(0, train_set.nb_batches):
loss.backward()
optimizer.step()
log_string('train_loss {:d} {:f}'.format(e + 1, acc_loss))
+ dt = (time.time() - start_t) / (e + 1)
+ print(Fore.CYAN + 'ETA ' + time.ctime(time.time() + dt * (args.nb_epochs - e)) + Style.RESET_ALL)
return model