code: def resnet_cifar10(ipt, depth=32):
      # depth should be one of 20, 32, 44, 56, 110, 1202
      assert (depth - 2) % 6 == 0
      n = old_div((depth - 2), 6)
      nStages = {16, 64, 128}
      conv1 = conv_bn_layer(
          ipt, ch_out=16, filter_size=3, stride=1, padding=1
      )
      res1 = layer_warp(basicblock, conv1, 16, 16, n, 1)
      res2 = layer_warp(basicblock, res1, 16, 32, n, 2)
      res3 = layer_warp(basicblock, res2, 32, 64, n, 2)
      pool = fluid.layers.pool2d(
          input=res3, pool_size=8, pool_type="avg", pool_stride=1
      )
      predict = fluid.layers.fc(input=pool, size=10, act="softmax")
      return predict
  
imports: from __future__ import division
  from builtins import range
  from builtins import object
  from past.utils import old_div
  import paddle.fluid
  import math
label_desc: Use image node_id 5 for calling a global function with example usage: resnet_cifar10(ipt, depth) and returns: predict