scripts/train_instance_seg.py [64:109]:
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    log_debug("\n%s", config_to_string(conf))
    return conf


def make_dataloader(args, config, rank, world_size):
    config = config["dataloader"]
    log_debug("Creating dataloaders for dataset in %s", args.data)

    # Training dataloader
    train_tf = ISSTransform(config.getint("shortest_size"),
                            config.getint("longest_max_size"),
                            config.getstruct("rgb_mean"),
                            config.getstruct("rgb_std"),
                            config.getboolean("random_flip"),
                            config.getstruct("random_scale"))
    train_db = ISSDataset(args.data, config["train_set"], train_tf)
    train_sampler = DistributedARBatchSampler(
        train_db, config.getint("train_batch_size"), world_size, rank, True)
    train_dl = data.DataLoader(train_db,
                               batch_sampler=train_sampler,
                               collate_fn=iss_collate_fn,
                               pin_memory=True,
                               num_workers=config.getint("num_workers"))

    # Validation dataloader
    val_tf = ISSTransform(config.getint("shortest_size"),
                          config.getint("longest_max_size"),
                          config.getstruct("rgb_mean"),
                          config.getstruct("rgb_std"))
    val_db = ISSDataset(args.data, config["val_set"], val_tf)
    val_sampler = DistributedARBatchSampler(
        val_db, config.getint("val_batch_size"), world_size, rank, False)
    val_dl = data.DataLoader(val_db,
                             batch_sampler=val_sampler,
                             collate_fn=iss_collate_fn,
                             pin_memory=True,
                             num_workers=config.getint("num_workers"))

    return train_dl, val_dl


def make_model(config, num_thing, num_stuff):
    body_config = config["body"]
    fpn_config = config["fpn"]
    rpn_config = config["rpn"]
    roi_config = config["roi"]
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scripts/train_panoptic.py [74:119]:
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    log_debug("\n%s", config_to_string(conf))
    return conf


def make_dataloader(args, config, rank, world_size):
    config = config["dataloader"]
    log_debug("Creating dataloaders for dataset in %s", args.data)

    # Training dataloader
    train_tf = ISSTransform(config.getint("shortest_size"),
                            config.getint("longest_max_size"),
                            config.getstruct("rgb_mean"),
                            config.getstruct("rgb_std"),
                            config.getboolean("random_flip"),
                            config.getstruct("random_scale"))
    train_db = ISSDataset(args.data, config["train_set"], train_tf)
    train_sampler = DistributedARBatchSampler(
        train_db, config.getint("train_batch_size"), world_size, rank, True)
    train_dl = data.DataLoader(train_db,
                               batch_sampler=train_sampler,
                               collate_fn=iss_collate_fn,
                               pin_memory=True,
                               num_workers=config.getint("num_workers"))

    # Validation dataloader
    val_tf = ISSTransform(config.getint("shortest_size"),
                          config.getint("longest_max_size"),
                          config.getstruct("rgb_mean"),
                          config.getstruct("rgb_std"))
    val_db = ISSDataset(args.data, config["val_set"], val_tf)
    val_sampler = DistributedARBatchSampler(
        val_db, config.getint("val_batch_size"), world_size, rank, False)
    val_dl = data.DataLoader(val_db,
                             batch_sampler=val_sampler,
                             collate_fn=iss_collate_fn,
                             pin_memory=True,
                             num_workers=config.getint("num_workers"))

    return train_dl, val_dl


def make_model(config, num_thing, num_stuff):
    body_config = config["body"]
    fpn_config = config["fpn"]
    rpn_config = config["rpn"]
    roi_config = config["roi"]
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