code: def main():
      opt = parse_args()
      mx.random.seed(128)
      random.seed(12)
      np.random.seed(2)
  
      context = mx.cpu() if opt.context.lower() == "cpu" else mx.gpu()
      # Create a Gluon Model.
      net = create_gluon_model()
  
      # Start the training.
      train_data, val_data = prepare_data(opt.batch_size)
  
      train_model(
          net=net,
          epochs=opt.epochs,
          ctx=context,
          learning_rate=opt.learning_rate,
          momentum=0.9,
          train_data=train_data,
          val_data=val_data,
      )
  
file_path: sagemaker-python-sdk/tests/data/mxnet_mnist/mnist_gluon.py
imports: import argparse
  import random
  import mxnet
  import numpy
  from mxnet import autograd, gluon
  from mxnet.gluon import nn
label_desc: Use image node_id 7 for calling a global function with example usage: main() without return types