def METHOD_NAME(mxnet_training, example_only):
    """
    Run MXNet distributed training on EKS using docker images with MNIST dataset (parameter server)
    """
    random.seed(f"{mxnet_training}-{datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')}")
    unique_id = random.randint(1, 6000)
    namespace = "mxnet"
    job_name = f"kubeflow-mxnet-gpu-dist-job-{unique_id}"
    # TODO: This should either be dynamic or at least global variables
    num_workers = "3"
    num_servers = "2"
    gpu_limit = "1"
    epochs = '"20"'
    layers = '"2"'
    gpus = '"0"'
    local_template_file_path = os.path.join(
        "eks", "eks_manifest_templates", "mxnet", "training", "multi_node_gpu_training.yaml"
    )
    remote_yaml_file_path = os.path.join(
        os.sep, "tmp", f"mxnet_multi_node_training_{unique_id}.yaml"
    )
    replace_dict = {
        "<JOB_NAME>": job_name,
        "<NUM_SERVERS>": num_servers,
        "<NUM_WORKERS>": num_workers,
        "<CONTAINER_IMAGE>": mxnet_training,
        "<EPOCHS>": epochs,
        "<LAYERS>": layers,
        "<GPUS>": gpus,
        "<GPU_LIMIT>": gpu_limit,
    }
    eks_utils.write_eks_yaml_file_from_template(
        local_template_file_path, remote_yaml_file_path, replace_dict
    )
    training_result = _run_eks_mxnet_multi_node_training(namespace, job_name, remote_yaml_file_path)
    assert training_result, "EKS multinode training failed"