code: def _optimizer(c: Configs):
      from labml_helpers.optimizer import OptimizerConfigs
  
      opt_conf = OptimizerConfigs()
      opt_conf.parameters = c.model.parameters()
      return opt_conf
  
imports: import torch.nn
  import torch.nn.functional
  import torch.utils.data
  from labml import experiment, tracker
  from labml.configs import option
  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, hook_model_outputs
label_desc: Use image node_id 2 for calling a global function with example usage: _optimizer(c) and returns: opt_conf