code: def _optimizer(c: MNISTConfigs):
      """
      ### Default optimizer configurations
      """
      opt_conf = OptimizerConfigs()
      opt_conf.parameters = c.model.parameters()
      opt_conf.optimizer = "Adam"
      return opt_conf
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/experiments/mnist.py
imports: import torch.nn
  import torch.utils.data
  from labml_helpers.module import Module
  from labml import tracker
  from labml.configs import option
  from labml_helpers.datasets.mnist import MNISTConfigs
  from labml_helpers.device import DeviceConfigs
  from labml_helpers.metrics.accuracy import Accuracy
  from labml_helpers.train_valid import TrainValidConfigs, BatchIndex, hook_model_outputs
  from labml_nn.optimizers.configs import OptimizerConfigs
label_desc: Use image node_id 1 for calling a global function with example usage: _optimizer(c) and returns: opt_conf