code: def _ada_belief_optimizer(c: OptimizerConfigs):
      from labml_nn.optimizers.ada_belief import AdaBelief
  
      return AdaBelief(
          c.parameters,
          lr=c.learning_rate,
          betas=c.betas,
          eps=c.eps,
          weight_decay=c.weight_decay_obj,
          amsgrad=c.amsgrad,
          degenerate_to_sgd=c.degenerate_to_sgd,
          rectify=c.rectify,
      )
  
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 6 for calling a global function with example usage: _ada_belief_optimizer(c) and returns: AdaBelief