code: def __loss__(self, logits, labels):
      return F.cross_entropy(logits, labels)
  
imports: import os
  import hydra
  import torch
  import shutil
  import warnings
  from torch.optim import Adam
  from omegaconf import OmegaConf
  from benchmarks.xgraph.utils import check_dir
  from benchmarks.xgraph.gnnNets import get_gnnNets
  from benchmarks.xgraph.dataset import get_dataset, get_dataloader
  import torch.nn.functional
  from torch.optim.lr_scheduler import MultiStepLR
  from utils import fix_random_seed
label_desc: Use image node_id 2 for calling the TrainModel obj's underlying member method code with example usage: obj.__loss__(logits, labels) and returns: F