class_docstr: SSD model is like a Tree, except with additional handling for the output layer, and
  for the prior boxes
class_docstr_tok: ["SSD","model","is","like","a","Tree",",","except","with","additional","handling","for","the","output","layer",",","and","for","the","prior","boxes"]
code: def _prior_box_fprop(self):
      # fprop and stack all the prior boxes
  
      if self.all_prior_boxes is None:
          priors = [
              prior_box.fprop(None).get()
              for prior_box in self.prior_boxes
          ]
  
          self.all_prior_boxes = np.vstack(priors)
          self.all_prior_boxes_dev = self.be.array(self.all_prior_boxes)
  
imports: from neon.initializers import Constant, Xavier
  from neon.transforms import Rectlin
  from neon.layers import Conv, Pooling, BranchNode
  from layer import Normalize, PriorBox, DetectionOutput, ConcatTranspose
  import numpy
  from neon.util.persist import load_obj
  from neon.layers.container import Tree
  from neon.layers.layer import Layer
  from collections import OrderedDict
  import inspect
  import re
  from neon.data.datasets import Dataset
  import os
label_desc: Use image node_id 17 for calling the SSD obj's underlying member method code with example usage: obj._prior_box_fprop() without return types