code: def num_graph_features(self, num_graph_featues):
      self._num_graph_features = num_graph_featues
      if self.graph_level:
          if self.encoder is not None:
              self.encoder.num_graph_features = self._num_graph_features
          if self.decoder is not None:
              self.decoder.num_graph_features = self._num_graph_features
  
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 8 for calling the BaseContrastiveTrainer obj's underlying member method code with example usage: obj.num_graph_features(num_graph_featues) without return types