code: def conv_nets():
      net = gluon.nn.HybridSequential()
      with net.name_scope():
          net.add(
              gluon.nn.Conv2D(
                  channels=20, kernel_size=5, activation="relu"
              )
          )
          net.add(gluon.nn.MaxPool2D(pool_size=2, strides=2))
          net.add(
              gluon.nn.Conv2D(
                  channels=50, kernel_size=5, activation="relu"
              )
          )
          net.add(gluon.nn.MaxPool2D(pool_size=2, strides=2))
          net.add(gluon.nn.Flatten())
          net.add(gluon.nn.Dense(512, activation="relu"))
          net.add(gluon.nn.Dense(10))
      return net
  
file_path: mxnet/example/distributed_training-horovod/gluon_mnist.py
imports: import argparse
  import logging
  import os
  import zipfile
  import time
  import mxnet
  import horovod.mxnet
  from mxnet import autograd, gluon, nd
  from mxnet.test_utils import download
label_desc: Use image node_id 2 for calling a global function with example usage: conv_nets() and returns: net