class_docstr: This class provides a way to pickle a function and its arguments.
  It also provides a way to create a script that can run a
  function with arguments if they have them pickled to a file.
  It also provides a way of extracting the conents of a pickle file.
docstr: Given a path to a file with pickled output, this function
  will unpickle the output and return it to the user.
  
  Parameters
  ----------
  fn_output_path: str
      The path to the file containing the pickled output of a function.
  
  Returns
  -------
  Any
      The unpickled output stored in func_output_path
docstr_tok: ["Given","a","path","to","a","file","with","pickled","output",",","this","function","will","unpickle","the","output","and","return","it","to","the","user",".","Parameters","--","--","--","--","--","fn_output_path",":","str","The","path","to","the","file","containing","the","pickled","output","of","a","function",".","Returns","--","--","--","-","Any","The","unpickled","output","stored","in","func_output_path"]
code: def get_fn_output(fn_output_path: str) -> Any:
      """
      Given a path to a file with pickled output, this function
      will unpickle the output and return it to the user.
  
      Parameters
      ----------
      fn_output_path: str
          The path to the file containing the pickled output of a function.
  
      Returns
      -------
      Any
          The unpickled output stored in func_output_path
      """
      with open(fn_output_path, "rb") as f:
          return cloudpickle.load(f)
  
file_path: spark/python/pyspark/ml/dl_util.py
imports: import os
  import tempfile
  import textwrap
  from typing import Any, Callable
  from pyspark import cloudpickle
label_desc: Use image node_id 3 for calling the FunctionPickler obj's underlying member method code with example usage: obj.get_fn_output(fn_output_path) and returns: cloudpickle