code: def forward(self, x):
      y_hat = self.model(x)
      return y_hat
  
imports: import warnings
  from typing import Dict, List, Optional, Union, Type
  import torch.nn
  import torch.optim
  import torchmetrics
  from torch.utils.data import DataLoader
  import nni
  from ..lightning import LightningModule, _AccuracyWithLogits, Lightning
  from .trainer import Trainer
label_desc: Use image node_id 3 for calling the _MultiModelSupervisedLearningModule obj's underlying member method code with example usage: obj.forward(x) and returns: y_hat