why does imagenet need drop blox size 5 but cifar need dropbox size 2?

[brando90]

def get_resnet_rfs_model_mi(model_opt: str,
                            avg_pool=True,
                            drop_rate=0.1,
                            dropblock_size=5,
                            num_classes=64,
                            ) -> tuple[nn.Module, dict]:
    """
    Get resnet_rfs model according to the string model_opt
        e.g. model_opt = resnet12

    ref:
        - https://github.com/WangYueFt/rfs/blob/f8c837ba93c62dd0ac68a2f4019c619aa86b8421/models/util.py#L7
    """
    model_hps: dict = {'avg_pool': avg_pool,
                       'drop_rate': drop_rate,
                       'dropblock_size': dropblock_size,
                       'num_classes': num_classes}
    model: nn.Module = model_dict[model_opt](avg_pool=avg_pool,
                                             drop_rate=drop_rate,
                                             dropblock_size=dropblock_size,
                                             num_classes=num_classes)
    return model, model_hps


def get_resnet_rfs_model_cifarfs_fc100(model_opt: str,
                                       num_classes,
                                       avg_pool=True,
                                       drop_rate=0.1,
                                       dropblock_size=2,
                                       ) -> tuple[nn.Module, dict]:
    """
    ref:
        - https://github.com/WangYueFt/rfs/blob/f8c837ba93c62dd0ac68a2f4019c619aa86b8421/models/util.py#L7
    """
    model_hps: dict = {'avg_pool': avg_pool,
                       'drop_rate': drop_rate,
                       'dropblock_size': dropblock_size,
                       'num_classes': num_classes}
    model: nn.Module = model_dict[model_opt](avg_pool=avg_pool,
                                             drop_rate=drop_rate,
                                             dropblock_size=dropblock_size,
                                             num_classes=num_classes)
    return model, model_hps