94a995defe223eed0898f25d2332ba6178a92abe,ssd/engine/trainer.py,,do_train,#Any#Any#Any#Any#Any#Any#Any#,46

Before Change

        if iteration % args.log_step == 0:
            eta_seconds = int((trained_time / iteration) * (max_iter - iteration))
            logger.info(
                "Iter: {:06d}, Lr: {:.5f}, Cost: {:.2f}s, Eta: {}, ".format(iteration, optimizer.param_groups[0]["lr"],
                                                                            time.time() - tic,
                                                                            str(datetime.timedelta(seconds=eta_seconds))) +
                "Loss: {:.3f}, ".format(losses_reduced.item()) +
                "Regression Loss {:.3f}, ".format(loss_dict_reduced["regression_loss"].item()) +
                "Classification Loss: {:.3f}".format(loss_dict_reduced["classification_loss"].item()))

            if summary_writer:
                global_step = iteration

After Change

                                                                          time.time() - tic, str(datetime.timedelta(seconds=eta_seconds))),
                "total_loss: {:.3f}".format(losses_reduced.item())
            ]
            for loss_name, loss_item in loss_dict_reduced.items():
                log_str.append("{}: {:.3f}".format(loss_name, loss_item.item()))
            log_str = ", ".join(log_str)
            logger.info(log_str)
            if summary_writer:
                global_step = iteration

Instances