code: def test_inferentia_deploy_model(
      mxnet_training_job,
      sagemaker_session,
      inf_instance_type,
      inf_instance_family,
      inferentia_mxnet_latest_version,
      inferentia_mxnet_latest_py_version,
  ):
      endpoint_name = unique_name_from_base("test-neo-deploy-model")
  
      with timeout_and_delete_endpoint_by_name(
          endpoint_name, sagemaker_session
      ):
          desc = (
              sagemaker_session.sagemaker_client.describe_training_job(
                  TrainingJobName=mxnet_training_job
              )
          )
          model_data = desc["ModelArtifacts"]["S3ModelArtifacts"]
          script_path = os.path.join(
              DATA_DIR, "mxnet_mnist", "mnist_neo.py"
          )
          role = "SageMakerRole"
          model = MXNetModel(
              model_data,
              role,
              entry_point=script_path,
              framework_version=inferentia_mxnet_latest_version,
              py_version=inferentia_mxnet_latest_py_version,
              sagemaker_session=sagemaker_session,
          )
  
          model.compile(
              target_instance_family=inf_instance_family,
              input_shape={"data": [1, 1, 28, 28]},
              role=role,
              job_name=unique_name_from_base(
                  "test-deploy-model-compilation-job"
              ),
              output_path="/".join(model_data.split("/")[:-1]),
          )
  
          serializer = JSONSerializer(
              content_type="application/vnd+python.numpy+binary"
          )
  
          predictor = model.deploy(
              1,
              inf_instance_type,
              serializer=serializer,
              endpoint_name=endpoint_name,
          )
  
          data = numpy.zeros(shape=(1, 1, 28, 28))
          predictor.predict(data)
  
file_path: sagemaker-python-sdk/tests/integ/test_neo_mxnet.py
imports: from __future__ import absolute_import
  import os
  import numpy
  import pytest
  from sagemaker.mxnet.estimator import MXNet
  from sagemaker.mxnet.model import MXNetModel
  from sagemaker.serializers import JSONSerializer
  from sagemaker.utils import unique_name_from_base
  from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES
  from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
label_desc: Use image node_id 4 for calling a global function with example usage: test_inferentia_deploy_model(mxnet_training_job, sagemaker_session, inf_instance_type, inf_instance_family, inferentia_mxnet_latest_version, inferentia_mxnet_latest_py_version) without return types