code: def split_predict_cols(y):
      if not isinstance(y, (list, tuple)):
          return {"prediction": y}
      output_cols = [f"output_{i}" for i in range(len(y))]
  
      # Multi-output in a list format
      invalidInputError(
          len(output_cols) == len(y),
          f"The length of output_cols ({len(output_cols)}) "
          f"does not match the length of model output ({len(y)}).",
      )
  
      return dict(zip(output_cols, y))
  
imports: import time
  import numbers
  import socket
  import collections
  import numpy
  from contextlib import closing, contextmanager
  import torch
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 10 for calling a global function with example usage: split_predict_cols(y) and returns: dict, dict