docstr: The function of getting the valid score.
  
  Parameters
  ----------
  return_major: ``bool``.
      If True, then return only consists of the major result.
      If False, then return consists of the all results.
  
  Returns
  -------
  result: The valid score in training stage.
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code: def get_valid_score(self, return_major=True):
      """
      The function of getting the valid score.
  
      Parameters
      ----------
      return_major: ``bool``.
          If True, then return only consists of the major result.
          If False, then return consists of the all results.
  
      Returns
      -------
      result: The valid score in training stage.
      """
      if isinstance(self.feval, list):
          if return_major:
              return (
                  self.valid_score[0],
                  self.feval[0].is_higher_better(),
              )
          else:
              return self.valid_score, [
                  f.is_higher_better() for f in self.feval
              ]
      else:
          return self.valid_score, self.feval.is_higher_better()
  
imports: import os
  import torch
  import torch_geometric
  import logging
  import numpy
  import typing
  from tqdm import trange
  from typing import Union, Tuple, Sequence, Type, Callable
  import torch.nn.functional
  import torch.utils.data
  from torch.optim.lr_scheduler import StepLR, MultiStepLR, ExponentialLR, ReduceLROnPlateau
  from .losses import NTXent_loss
  from .utils import get_view_by_name
  from autogl.module.model.encoders.base_encoder import AutoHomogeneousEncoderMaintainer
  from ..base import BaseTrainer, EarlyStopping, _DummyModel
  from ..evaluation import Evaluation, get_feval, Acc
  from ...model import BaseAutoModel, BaseEncoderMaintainer, BaseDecoderMaintainer, EncoderUniversalRegistry, DecoderUniversalRegistry
  from ....utils import get_logger
  from ....datasets import utils
label_desc: Use image node_id 36 for calling the BaseContrastiveTrainer obj's underlying member method code with example usage: obj.get_valid_score(return_major) and returns: self,  self, self,  self, self,  unknown