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 configure(self, in_obj):
      # configure the base model
      super(SSD, self).configure(in_obj)
  
      self.leafs = self.unnest(self.get_terminal())
  
      self.prior_boxes = []
      for _, config in self.output_config.items():
          conv_layer = config["conv_layer"]
          mbox_prior = config["layers"]["mbox_prior"]
          mbox_prior.configure([in_obj, conv_layer])
          self.prior_boxes.append(mbox_prior)
  
      self.concat_loc.configure(self.leafs["mbox_loc"])
      self.concat_conf.configure(self.leafs["mbox_conf"])
  
      # configure the output layer
      self.prior_boxes = [
          config["layers"]["mbox_prior"]
          for _, config in self.output_config.items()
      ]
  
      self.output_layer.configure((self.leafs, self.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 4 for calling the SSD obj's underlying member method code with example usage: obj.configure(in_obj) without return types