code: def __repr__(self) -> str:
      import yaml
  
      return yaml.dump(
          {
              "trainer_name": self.__class__.__name__,
              "p_optimizer": self.p_optimizer,
              "p_learning_rate": self.p_lr,
              "p_max_epoch": self.p_epoch,
              "p_early_stopping_round": self.p_early_stopping_round,
              "encoder": repr(self.encoder),
              "decoder": repr(self.decoder),
          }
      )
  
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 37 for calling the BaseContrastiveTrainer obj's underlying member method code with example usage: obj.__repr__() and returns: yaml