code: def load_caffe_weights(model, file_path):
      pdict = load_obj(file_path)["params"]
  
      #  we match by name with the caffe blobs
      for pos, layer in enumerate(model.layers.layers):
          if pos == 1:  # skip conv4_3
              continue
          load_weights(layer.layers, pdict)
  
      # we handle the tree-in-tree next
      conv4_3_loc = model.layers.layers[1].layers[1].layers[0].layers
      conv4_3_conf = model.layers.layers[1].layers[1].layers[1].layers
      load_weights(conv4_3_loc, pdict)
      load_weights(conv4_3_conf, pdict)
  
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 2 for calling a global function with example usage: load_caffe_weights(model, file_path) without return types