code: def override_pipeline_parameter_var(func):
      """A decorator to override pipeline Parameters passed into a function
  
      This is a temporary decorator to override pipeline Parameter objects with their default value
      and display warning information to instruct users to update their code.
  
      This decorator can help to give a grace period for users to update their code when
      we make changes to explicitly prevent passing any pipeline variables to a function.
  
      We should remove this decorator after the grace period.
      """
      warning_msg_template = (
          "The input argument %s of function (%s) is a pipeline variable (%s), "
          "which is interpreted in pipeline execution time only. "
          "As the function needs to evaluate the argument value in SDK compile time, "
          "the default_value of this Parameter object will be used to override it. "
          "Please make sure the default_value is valid."
      )
  
      @wraps(func)
      def wrapper(*args, **kwargs):
          func_name = "{}.{}".format(func.__module__, func.__name__)
          params = inspect.signature(func).parameters
          args = list(args)
          for i, (arg_name, _) in enumerate(params.items()):
              if i >= len(args):
                  break
              if isinstance(args[i], Parameter):
                  logger.warning(
                      warning_msg_template,
                      arg_name,
                      func_name,
                      type(args[i]),
                  )
                  args[i] = args[i].default_value
          args = tuple(args)
  
          for arg_name, value in kwargs.items():
              if isinstance(value, Parameter):
                  logger.warning(
                      warning_msg_template,
                      arg_name,
                      func_name,
                      type(value),
                  )
                  kwargs[arg_name] = value.default_value
          return func(*args, **kwargs)
  
      return wrapper
  
imports: from __future__ import absolute_import
  import inspect
  import logging
  from functools import wraps
  from pathlib import Path
  from typing import List, Sequence, Union, Set, TYPE_CHECKING, Optional
  import hashlib
  from urllib.parse import unquote, urlparse
  from contextlib import contextmanager
  from _hashlib import HASH
  from sagemaker.utils import base_from_name
  from sagemaker.workflow.parameters import Parameter
  from sagemaker.workflow.pipeline_context import _StepArguments, _PipelineConfig
  from sagemaker.workflow.entities import Entity, RequestType
  from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
label_desc: Use image node_id 16 for calling a global function with example usage: override_pipeline_parameter_var(func) and returns: wrapper, func