code: def aug_ratio(self, aug_ratio):
      # set augmentation methods
      if isinstance(self.views_fn, list):
          if isinstance(aug_ratio, float):
              aug_ratio = [aug_ratio] * len(self.views_fn)
          assert len(aug_ratio) >= len(self.views_fn)
      self._aug_ratio = aug_ratio
      self._views_fn = self._get_views_fn(
          self.views_fn_opt, self.aug_ratio
      )
  
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 16 for calling the BaseContrastiveTrainer obj's underlying member method code with example usage: obj.aug_ratio(aug_ratio) without return types