code: def _default_optimizer(c: SimpleTrainValidConfigs):
      from labml_helpers.optimizer import OptimizerConfigs
  
      opt_conf = OptimizerConfigs()
      opt_conf.parameters = c.model.parameters()
      return opt_conf
  
imports: from typing import Optional, Dict, List, Callable, Any
  import torch.optim
  import torch.optim
  import torch.utils.data
  import torch.utils.data
  from torch import nn
  import labml.utils.pytorch
  from labml import tracker, monit
  from labml.configs import option, meta_config
  from .device import DeviceConfigs
  from .metrics import StateModule
  from .training_loop import TrainingLoopConfigs
label_desc: Use image node_id 5 for calling a global function with example usage: _default_optimizer(c) and returns: opt_conf