code: def training_iter_fn(batch, model, optimizer):
      outputs = model(**batch)
      loss = outputs.loss
      loss.backward()
      optimizer.step()
      optimizer.zero_grad()
      return loss
  
file_path: pytorch/benchmarks/dynamo/training_loss.py
imports: import argparse
  import inspect
  import os
  import sys
  import time
  from datetime import timedelta
  import torch
  import torch._dynamo
  from datasets import load_dataset, load_metric
  from torch.utils.data import DataLoader
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
label_desc: Use image node_id 2 for calling a global function with example usage: training_iter_fn(batch, model, optimizer) and returns: loss