code: def get(name: str) -> Type[Optimizer]:
      r"""Returns an optimizer class from its name. Case insensitive.
  
      Args:
          name: the optimizer name.
      """
      optimizer_class = _NAME_OPTIM_MAP.get(name.lower())
      if optimizer_class is None:
          raise ValueError("Optimizer {} not found".format(name))
      return optimizer_class
  
imports: from typing import Dict, List, Type
  from pytorch_ranger import Ranger, RangerQH, RangerVA
  from torch.optim.optimizer import Optimizer
  from .a2grad import A2GradExp, A2GradInc, A2GradUni
  from .accsgd import AccSGD
  from .adabelief import AdaBelief
  from .adabound import AdaBound
  from .adafactor import Adafactor
  from .adahessian import Adahessian
  from .adamod import AdaMod
  from .adamp import AdamP
  from .aggmo import AggMo
  from .apollo import Apollo
  from .diffgrad import DiffGrad
  from .lamb import Lamb
  from .lars import LARS
  from .lion import Lion
  from .lookahead import Lookahead
  from .madgrad import MADGRAD
  from .novograd import NovoGrad
  from .pid import PID
  from .qhadam import QHAdam
  from .qhm import QHM
  from .radam import RAdam
  from .sgdp import SGDP
  from .sgdw import SGDW
  from .shampoo import Shampoo
  from .swats import SWATS
  from .yogi import Yogi
label_desc: Use image node_id 1 for calling a global function with example usage: get(name) and returns: optimizer_class