code: def check_loss(ref_loss, res_loss):
      assert len(ref_loss) == len(res_loss)
      length = len(ref_loss)
      x = min(length, 10)
      if sum(res_loss[-x:]) / 10 <= sum(ref_loss[-x:]) / 10 + 1e-1:
          return True
      else:
          return False
  
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 4 for calling a global function with example usage: check_loss(ref_loss, res_loss) and returns: True, False