code: def get_training_stats(stats):
      stats["wall"] = round(
          metrics.get_meter("default", "wall").elapsed_time, 0
      )
      return stats
  
imports: import argparse
  import logging
  import math
  import os
  import random
  import sys
  import numpy
  import torch
  from fairseq import checkpoint_utils, distributed_utils, options, quantization_utils, tasks, utils
  from fairseq.data import iterators
  from fairseq.logging import meters, metrics, progress_bar
  from fairseq.model_parallel.megatron_trainer import MegatronTrainer
  from .ls_fs_gcq_trainer import LSTrainer
label_desc: Use image node_id 5 for calling a global function with example usage: get_training_stats(stats) and returns: stats