90a753c9d419597530ae36aebc10653e4ea15f1d,examples/contrib/cifar10_qat/main.py,,training,#Any#Any#,20

Before Change

    if rank == 0:
        now = datetime.now().strftime("%Y%m%d-%H%M%S")

        folder_name = "{}_backend-{}-{}_{}".format(config["model"], idist.backend(), idist.get_world_size(), now)
        output_path = Path(output_path) / folder_name
        if not output_path.exists():
            output_path.mkdir(parents=True)

After Change

                "learning_rate",
                "num_warmup_epochs",
            ]
            task.connect({k: config[k] for k in hyper_params})

    // Setup dataflow, model, optimizer, criterion
    train_loader, test_loader = get_dataflow(config)

Instances