code: def _transfer_googlenet(src, dst):
      # 1 #################################################################
      dst.conv1.W.array[:] = src["conv1/7x7_s2"].W.array
      dst.conv1.b.array[:] = src["conv1/7x7_s2"].b.array
  
      # 2 #################################################################
      dst.conv2_reduce.W.array[:] = src["conv2/3x3_reduce"].W.array
      dst.conv2_reduce.b.array[:] = src["conv2/3x3_reduce"].b.array
      dst.conv2.W.array[:] = src["conv2/3x3"].W.array
      dst.conv2.b.array[:] = src["conv2/3x3"].b.array
  
      # 3, 4, 5 ###########################################################
      _transfer_inception(
          src,
          dst,
          ["3a", "3b", "4a", "4b", "4c", "4d", "4e", "5a", "5b"],
      )
  
      # outputs ############################################################
      dst.loss1_conv.W.array[:] = src["loss1/conv"].W.array
      dst.loss1_conv.b.array[:] = src["loss1/conv"].b.array
      dst.loss1_fc1.W.array[:] = src["loss1/fc"].W.array
      dst.loss1_fc1.b.array[:] = src["loss1/fc"].b.array
      dst.loss1_fc2.W.array[:] = src["loss1/classifier"].W.array
      dst.loss1_fc2.b.array[:] = src["loss1/classifier"].b.array
  
      dst.loss2_conv.W.array[:] = src["loss2/conv"].W.array
      dst.loss2_conv.b.array[:] = src["loss2/conv"].b.array
      dst.loss2_fc1.W.array[:] = src["loss2/fc"].W.array
      dst.loss2_fc1.b.array[:] = src["loss2/fc"].b.array
      dst.loss2_fc2.W.array[:] = src["loss2/classifier"].W.array
      dst.loss2_fc2.b.array[:] = src["loss2/classifier"].b.array
  
      dst.loss3_fc.W.array[:] = src["loss3/classifier"].W.array
      dst.loss3_fc.b.array[:] = src["loss3/classifier"].b.array
  
imports: import collections
  import os
  import sys
  import numpy
  import chainer
  from chainer.dataset.convert import concat_examples
  from chainer.dataset import download
  from chainer import function
  from chainer.functions.activation.relu import relu
  from chainer.functions.activation.softmax import softmax
  from chainer.functions.array.reshape import reshape
  from chainer.functions.math.average import average
  from chainer.functions.noise.dropout import dropout
  from chainer.functions.normalization.local_response_normalization import local_response_normalization
  from chainer.functions.pooling.average_pooling_2d import average_pooling_2d
  from chainer.functions.pooling.max_pooling_nd import max_pooling_2d
  from chainer.initializers import constant
  from chainer.initializers import uniform
  from chainer import link
  from chainer.links.connection.convolution_2d import Convolution2D
  from chainer.links.connection.inception import Inception
  from chainer.links.connection.linear import Linear
  from chainer.serializers import npz
  from chainer.utils import argument
  from chainer.utils import imgproc
  from chainer.variable import Variable
label_desc: Use image node_id 3 for calling a global function with example usage: _transfer_googlenet(src, dst) without return types