e95455b7d7300e3b9fe13cf0827a7ec0f5ea5332,python/ray/util/sgd/torch/examples/dcgan.py,,train_example,#Any#Any#Any#,226

Before Change

        backend="nccl" if use_gpu else "gloo")

    from tabulate import tabulate
    for itr in range(5):
        stats = trainer.train()
        formatted = tabulate([stats], headers="keys")
        if itr > 0:  // Get the last line of the stats.

After Change

        tqdm=True)

    from tabulate import tabulate
    pbar = trange(5, unit="epoch")
    for itr in pbar:
        stats = trainer.train(info=dict(epoch_idx=itr, num_epochs=5))
        pbar.set_postfix(
            dict(loss_g=stats["mean_loss_g"], loss_d=stats["mean_loss_d"]))

Instances