code: def get_feval(feval):
      if isinstance(feval, str):
          return EVALUATE_DICT[feval]
      if isinstance(feval, type) and issubclass(feval, Evaluation):
          return feval
      if isinstance(feval, list):
          return [get_feval(f) for f in feval]
      raise ValueError(
          "feval argument of type", type(feval), "is not supported!"
      )
  
imports: from .None import register_trainer, Evaluation
  import torch
  from torch.optim.lr_scheduler import StepLR, MultiStepLR, ExponentialLR, ReduceLROnPlateau
  import torch.nn.functional
  from ..model import BaseEncoderMaintainer, BaseDecoderMaintainer, BaseAutoModel
  from .evaluation import Auc, EVALUATE_DICT
  from .base import EarlyStopping, BaseLinkPredictionTrainer
  from typing import Union, Tuple
  from copy import deepcopy
  from ...utils import get_logger
  from ...backend import DependentBackend
label_desc: Use image node_id 1 for calling a global function with example usage: get_feval(feval) and returns: EVALUATE_DICT, feval, unknown