code: def get_train_data_iter(config, kv):
      train_data = np.random.rand(200, 30)
      train_label = np.random.randint(0, 10, (200,))
      train = mx.io.NDArrayIter(
          {"input": train_data},
          {"label": train_label},
          batch_size=config["batch_size"],
          shuffle=True,
      )
      return train
  
file_path: analytics-zoo/pyzoo/test/zoo/orca/learn/ray/mxnet/test_mxnet_symbol.py
imports: from unittest import TestCase
  import numpy
  import pytest
  import mxnet
  from zoo.orca.learn.mxnet import Estimator, create_config
label_desc: Use image node_id 1 for calling a global function with example usage: get_train_data_iter(config, kv) and returns: train