code: def mxnet_training_job(
      sagemaker_session,
      cpu_instance_type,
      mxnet_training_latest_version,
      mxnet_training_latest_py_version,
  ):
      with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
          script_path = os.path.join(
              DATA_DIR, "mxnet_mnist", "mnist_neo.py"
          )
          data_path = os.path.join(DATA_DIR, "mxnet_mnist")
  
          mx = MXNet(
              entry_point=script_path,
              role="SageMakerRole",
              framework_version=mxnet_training_latest_version,
              py_version=mxnet_training_latest_py_version,
              instance_count=1,
              instance_type=cpu_instance_type,
              sagemaker_session=sagemaker_session,
          )
  
          train_input = mx.sagemaker_session.upload_data(
              path=os.path.join(data_path, "train"),
              key_prefix="integ-test-data/mxnet_mnist/train",
          )
          test_input = mx.sagemaker_session.upload_data(
              path=os.path.join(data_path, "test"),
              key_prefix="integ-test-data/mxnet_mnist/test",
          )
  
          mx.fit({"train": train_input, "test": test_input})
          return mx.latest_training_job.name
  
imports: from __future__ import absolute_import
  import os
  import pytest
  from sagemaker.mxnet.estimator import MXNet
  from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES
  from tests.integ.timeout import timeout
label_desc: Use image node_id 1 for calling a global function with example usage: mxnet_training_job(sagemaker_session, cpu_instance_type, mxnet_training_latest_version, mxnet_training_latest_py_version) and returns: mx