code: def forward(self, data):
      zg = self.encoder(data)
      out = self.pred_head(zg)
  
      return nn.functional.log_softmax(out, dim=-1)
  
imports: import copy
  import torch
  import numpy
  import torch.nn
  from tqdm import trange
  from sklearn.model_selection import StratifiedKFold
  from torch_geometric.loader import DataLoader
  from sklearn.svm import SVC
  from sklearn import preprocessing
  from sklearn.metrics import accuracy_score
  from sklearn.model_selection import GridSearchCV
label_desc: Use image node_id 2 for calling the PredictionModel obj's underlying member method code with example usage: obj.forward(data) and returns: nn