code: def main():
      conf = Configs()
      experiment.create(name="configs")
      experiment.configs(conf, {"optimizer": "sgd_optimizer"})
  
      torch.manual_seed(conf.seed)
  
      with experiment.start():
          conf.run()
  
      # save the model
      experiment.save_checkpoint()
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torch.utils.data
  from torchvision import datasets, transforms
  from labml import experiment, lab, tracker, logger
  from labml.configs import BaseConfigs, option
  from labml.internal.configs.dynamic_hyperparam import FloatDynamicHyperParam, IntDynamicHyperParam
label_desc: Use image node_id 7 for calling a global function with example usage: main() without return types