code: def _optimizer(c: NLPClassificationConfigs):
      """
      ### Default [optimizer configurations](../optimizers/configs.html)
      """
  
      optimizer = OptimizerConfigs()
      optimizer.parameters = c.model.parameters()
      optimizer.optimizer = "Adam"
      optimizer.d_model = c.d_model
  
      return optimizer
  
imports: from collections import Counter
  from typing import Callable
  import torch
  import torchtext
  from torch import nn
  from torch.utils.data import DataLoader
  import torchtext.vocab
  from torchtext.vocab import Vocab
  from labml import lab, tracker, monit
  from labml.configs import option
  from labml_helpers.device import DeviceConfigs
  from labml_helpers.metrics.accuracy import Accuracy
  from labml_helpers.module import Module
  from labml_helpers.train_valid import TrainValidConfigs, hook_model_outputs, BatchIndex
  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: optimizer