code: def estimate_keypoints_norm_type(keypoints):
      type_str = estimate_normalization_type(keypoints)
      valid_type_strs = [
          "None",
          "array[float]",
          "array[int]",
          "array[uint]",
          "tuple[number,size=2]",
          "Keypoint",
          "KeypointsOnImage",
          "iterable[empty]",
          "iterable-array[float]",
          "iterable-array[int]",
          "iterable-array[uint]",
          "iterable-tuple[number,size=2]",
          "iterable-Keypoint",
          "iterable-KeypointsOnImage",
          "iterable-iterable[empty]",
          "iterable-iterable-tuple[number,size=2]",
          "iterable-iterable-Keypoint",
      ]
      _assert_is_of_norm_type(type_str, valid_type_strs, "keypoints")
      return type_str
  
imports: from __future__ import print_function, division, absolute_import
  import functools
  import numpy
  from ..None import imgaug
  from ..None import dtypes
  from .base import IAugmentable
label_desc: Use image node_id 26 for calling a global function with example usage: estimate_keypoints_norm_type(keypoints) and returns: type_str