code: def commands():
      """
      Serve models on SageMaker.
  
      To serve a model associated with a run on a tracking server, set the MLFLOW_TRACKING_URI
      environment variable to the URL of the desired server.
      """
      pass
  
file_path: mlflow/mlflow/sagemaker/cli.py
imports: import json
  import os
  import click
  import mlflow
  import mlflow.models.docker_utils
  import mlflow.sagemaker
  from mlflow.sagemaker import DEFAULT_IMAGE_NAME
  from mlflow.utils import cli_args
  from mlflow.utils import env_manager
label_desc: Use image node_id 1 for calling a global function with example usage: commands() without return types