code: def model(c: Configs):
      return Net().to(c.device)
  
imports: import datetime
  import torch.distributed
  import torch.nn
  import torch.nn.functional
  import torch.utils.data
  from labml import experiment, monit
  from labml import tracker
  from labml.configs import option
  from labml.logger import inspect
  from labml.utils import pytorch
  from labml_helpers.datasets.mnist import MNISTConfigs
  from labml_helpers.device import DeviceConfigs
  from labml_helpers.metrics.accuracy import Accuracy
  from labml_helpers.module import Module
  from labml_helpers.seed import SeedConfigs
  from labml_helpers.train_valid import TrainValidConfigs, BatchIndex
  from torch.nn.parallel import DistributedDataParallel
label_desc: Use image node_id 1 for calling a global function with example usage: model(c) and returns: Net