code: def training_step(self, batch, batch_idx):
      outputs = self(**batch)
      loss = outputs[0]
      return loss
  
imports: from typing import Any, List
  import inspect
  import torch
  import hydra
  from pytorch_lightning import LightningModule, LightningDataModule
  from torchmetrics import MetricCollection
  from einops import rearrange
  from omegaconf import OmegaConf
  from src.utils.utils import get_logger
  from src.optim.param_grouping import group_parameters_for_optimizer
  from src.utils.checkpoint import load_checkpoint
  import datasets
label_desc: Use image node_id 2 for calling the GLUETransformerHfMetrics obj's underlying member method code with example usage: obj.training_step(batch, batch_idx) and returns: loss