code: def to_device(
      self,
      model: Union["BaseModel", DDP],
      device: Optional[torch.device] = None,
  ) -> nn.Module:
      try:
          return model.to_device(
              device if device is not None else get_torch_device()
          )
      except AttributeError:
          # Model is already wrapped in DistributedDataParallel, so it has already been moved to device
          return model
  
imports: import contextlib
  import logging
  import os
  import socket
  from typing import Any, Callable, Dict, Optional, Tuple, Type, TYPE_CHECKING, Union
  import torch
  import torch.distributed
  from ray.train.backend import BackendConfig
  from ray.train.data_parallel_trainer import DataParallelTrainer
  from ray.train.torch import TorchTrainer
  from torch import nn
  from torch.nn.parallel import DistributedDataParallel
  from torch.optim import Optimizer
  from torchmetrics.utilities.distributed import gather_all_tensors
  from ludwig.distributed.base import DistributedStrategy
  from ludwig.modules.optimization_modules import create_optimizer
  from ludwig.utils.torch_utils import get_torch_device
label_desc: Use image node_id 23 for calling the DDPStrategy obj's underlying member method code with example usage: obj.to_device(model, device) and returns: model, model