code: def _noam_optimizer(c: OptimizerConfigs):
      from labml_nn.optimizers.noam import Noam
  
      return Noam(
          c.parameters,
          lr=c.learning_rate,
          betas=c.betas,
          eps=c.eps,
          weight_decay=c.weight_decay_obj,
          amsgrad=c.amsgrad,
          warmup=c.warmup,
          d_model=c.d_model,
      )
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/optimizers/configs.py
imports: from typing import Tuple
  import torch
  from labml.configs import BaseConfigs, option, meta_config
  from labml_nn.optimizers import WeightDecay
label_desc: Use image node_id 7 for calling a global function with example usage: _noam_optimizer(c) and returns: Noam