{
    "device": "$torch.device(f'cuda:{dist.get_rank()}')",
    "gnetwork": {
        "_target_": "torch.nn.parallel.DistributedDataParallel",
        "module": "$@autoencoder_def.to(@device)",
        "device_ids": [
            "@device"
        ]
    },
    "dnetwork": {
        "_target_": "torch.nn.parallel.DistributedDataParallel",
        "module": "$@discriminator_def.to(@device)",
        "device_ids": [
            "@device"
        ]
    },
    "train#sampler": {
        "_target_": "DistributedSampler",
        "dataset": "@train#dataset",
        "even_divisible": true,
        "shuffle": true
    },
    "train#dataloader#sampler": "@train#sampler",
    "train#dataloader#shuffle": false,
    "train#trainer#train_handlers": "$@train#handlers[: -2 if dist.get_rank() > 0 else None]",
    "initialize": [
        "$import torch.distributed as dist",
        "$dist.is_initialized() or dist.init_process_group(backend='nccl')",
        "$torch.cuda.set_device(@device)",
        "$monai.utils.set_determinism(seed=123)",
        "$import logging",
        "$@train#trainer.logger.setLevel(logging.WARNING if dist.get_rank() > 0 else logging.INFO)"
    ],
    "run": [
        "$@train#trainer.run()"
    ],
    "finalize": [
        "$dist.is_initialized() and dist.destroy_process_group()"
    ]
}