loss.backward()
optimizer.step()
log_string('train_loss {:d} {:f}'.format(e + 1, acc_loss))
- dt = (time.time() - t) / (e + 1)
+ 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