code: def prediction_head(
      self, head: _typing.Union[BaseDecoderMaintainer, str, None]
  ):
      if isinstance(self.encoder, BaseAutoModel):
          raise ValueError(
              "Encoder shouldn't be a `BaseAutoModel` in GraphCLSemisupervisedTrainer."
          )
      if isinstance(head, str):
          self._prediction_head = DecoderUniversalRegistry.get_decoder(
              head
          )(
              self.num_classes,
              input_dim=self.last_dim,
              num_graph_features=self.num_graph_features,
              device=self.device,
              init=self.initialized,
          )
      elif (
          isinstance(head, BaseDecoderMaintainer)
          or head is None
          or (hasattr(head, "fit") and hasattr(head, "predict"))
      ):
          self._prediction_head = head
      else:
          raise NotImplementedError(
              f"Sorry. The head {head} is not supported yet."
          )
      self.num_features = self.num_features
      self.last_dim = self.last_dim
      self.num_graph_features = self.num_graph_features
      self.num_classes = self.num_classes
  
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 18 for calling the BaseContrastiveTrainer obj's underlying member method code with example usage: obj.prediction_head(head) without return types