code: def output_fn(predictions, content_type):
      """
      After invoking predict_fn, the model server invokes `output_fn`.
      """
      if (
          content_type == "text/csv"
          or content_type == "application/json"
      ):
          return ",".join(str(x) for x in predictions[0])
      else:
          raise ValueError(
              "Content type {} is not supported.".format(content_type)
          )
  
file_path: sagemaker-python-sdk/tests/data/experiment/inference.py
imports: import os
  import json
  import logging
  import pickle
  import boto3
  import numpy
  import sagemaker_xgboost_container.encoder
  from sagemaker.session import Session
  from sagemaker.experiments import load_run
label_desc: Use image node_id 5 for calling a global function with example usage: output_fn(predictions, content_type) and returns: str