code: def main():
      if opt.builtin_profiler > 0:
          profiler.set_config(profile_all=True, aggregate_stats=True)
          profiler.set_state("run")
      if opt.mode == "hybrid":
          net.hybridize()
      train(opt, device)
      if opt.builtin_profiler > 0:
          profiler.set_state("stop")
          print(profiler.dumps())
  
file_path: mxnet/example/gluon/image_classification.py
imports: from __future__ import division
  import argparse, time, os
  import logging
  import mxnet
  from mxnet import gluon
  from mxnet import profiler
  from mxnet.gluon import nn
  from mxnet.gluon.model_zoo import vision
  from mxnet import autograd
  from mxnet.test_utils import get_mnist_iterator
  from mxnet.gluon.metric import Accuracy, TopKAccuracy, CompositeEvalMetric
  import numpy
  from data import get_cifar10_iterator, get_imagenet_iterator, get_caltech101_iterator, dummy_iterator
label_desc: Use image node_id 7 for calling a global function with example usage: main() without return types