code: def approximation_parameters(
      method: str,
  ) -> Tuple[
      Callable[[int], List[float]], Callable[[int], List[float]]
  ]:
      r"""Retrieves parameters for the input approximation `method`
  
      Args:
          method (str): The name of the approximation method. Currently only `riemann`
                  and gauss legendre are
      """
      if method in SUPPORTED_RIEMANN_METHODS:
          return riemann_builders(method=Riemann[method.split("_")[-1]])
      if method == "gausslegendre":
          return gauss_legendre_builders()
      raise ValueError(
          "Invalid integral approximation method name: {}".format(
              method
          )
      )
  
file_path: captum/captum/attr/_utils/approximation_methods.py
imports: from enum import Enum
  from typing import Callable, List, Tuple
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: approximation_parameters(method) and returns: riemann_builders, gauss_legendre_builders