code: def pckh(preds, gts, scales):
      t_range = np.arange(0, 0.51, 0.01)
      dists = (
          tf.sqrt(
              tf.reduce_sum(
                  tf.pow(preds - gts, 2), reduction_indices=-1
              )
          )
          / scales
      )
      # pckh = [ced_accuracy(t, dists) for t in t_range]
      # return pckh[-1]
      return ced_accuracy(0.5, dists)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  import menpo.io
  from menpo.image import Image
  from menpo.shape import PointCloud
  import cv2
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.contrib.framework.python.ops import variables
  from tensorflow.python.training import optimizer
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import variables
  from menpo.transform import Translation, Scale
  from menpo.shape import PointCloud
label_desc: Use image node_id 14 for calling a global function with example usage: pckh(preds, gts, scales) and returns: ced_accuracy