scripts/train_instance_seg.py [312:323]:
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    coco_struct = []
    img_list = []

    data_time = time.time()
    for it, batch in enumerate(dataloader):
        with torch.no_grad():
            idxs = batch["idx"]
            batch_sizes = [img.shape[-2:] for img in batch["img"]]
            original_sizes = batch["size"]

            # Upload batch
            batch = {k: batch[k].cuda(device=varargs["device"], non_blocking=True) for k in NETWORK_INPUTS}
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scripts/train_panoptic.py [361:372]:
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    coco_struct = []
    img_list = []

    data_time = time.time()
    for it, batch in enumerate(dataloader):
        with torch.no_grad():
            idxs = batch["idx"]
            batch_sizes = [img.shape[-2:] for img in batch["img"]]
            original_sizes = batch["size"]

            # Upload batch
            batch = {k: batch[k].cuda(device=varargs["device"], non_blocking=True) for k in NETWORK_INPUTS}
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