code: def optimizer_kwargs(cfg):
      """cfg/argparse to kwargs helper
      Convert optimizer args in argparse args or cfg like object to keyword args for updated create fn.
      """
      kwargs = dict(
          opt=cfg.opt,
          lr=cfg.lr,
          weight_decay=cfg.weight_decay,
          momentum=cfg.momentum,
      )
      if getattr(cfg, "opt_eps", None) is not None:
          kwargs["eps"] = cfg.opt_eps
      if getattr(cfg, "opt_betas", None) is not None:
          kwargs["betas"] = cfg.opt_betas
      if getattr(cfg, "layer_decay", None) is not None:
          kwargs["layer_decay"] = cfg.layer_decay
      if getattr(cfg, "opt_args", None) is not None:
          kwargs.update(cfg.opt_args)
      if getattr(cfg, "opt_foreach", None) is not None:
          kwargs["foreach"] = cfg.opt_foreach
      return kwargs
  
imports: import logging
  from itertools import islice
  from typing import Optional, Callable, Tuple
  import torch
  import torch.nn
  import torch.optim
  from timm.models import group_parameters
  from .adabelief import AdaBelief
  from .adafactor import Adafactor
  from .adahessian import Adahessian
  from .adamp import AdamP
  from .adan import Adan
  from .lamb import Lamb
  from .lars import Lars
  from .lion import Lion
  from .lookahead import Lookahead
  from .madgrad import MADGRAD
  from .nadam import Nadam
  from .nadamw import NAdamW
  from .nvnovograd import NvNovoGrad
  from .radam import RAdam
  from .rmsprop_tf import RMSpropTF
  from .sgdp import SGDP
  from .sgdw import SGDW
label_desc: Use image node_id 5 for calling a global function with example usage: optimizer_kwargs(cfg) and returns: kwargs