61228f3243eaee39cba31a9abd2afc6ead9612a8,implementations/bicyclegan/bicyclegan.py,,,#,136

Before Change

        //  Log Progress
        // --------------

        logger.log({"loss_D_VAE": loss_D_VAE, "loss_D_LR": loss_D_LR,
                    "loss_G": loss_GE, "loss_pixel": loss_pixel, "loss_latent": loss_latent},
                    images={"real_B": real_B, "fake_B": fake_B, "real_A": real_A},
                    epoch=epoch, batch=i)

After Change

        // --------------

        // Determine approximate time left
        batches_done = epoch * len(dataloader) + i
        batches_left = opt.n_epochs * len(dataloader) - batches_done
        time_left = datetime.timedelta(seconds=batches_left * (time.time() - start_time)/ (batches_done + 1))

        // Print log
        sys.stdout.write("\r[Epoch %d/%d] [Batch %d/%d] [D VAE_loss: %f, LR_loss: %f] [G loss: %f, pixel: %f, latent: %f] ETA: %s" %
                                                        (epoch, opt.n_epochs,
                                                        i, len(dataloader),
                                                        loss_D_VAE.item(), loss_D_LR.item(),
                                                        loss_GE.item(), loss_pixel.item(),
                                                        loss_latent.item(), time_left))

        if batches_done % opt.sample_interval == 0:
            sample_images(batches_done)

Instances