code: def preact_bottleneck(l, ch_out, stride, preact):
      # stride is applied on the second conv, following fb.resnet.torch
      l, shortcut = apply_preactivation(l, preact)
      l = Conv2D("conv1", l, ch_out, 1, activation=BNReLU)
      l = Conv2D(
          "conv2", l, ch_out, 3, strides=stride, activation=BNReLU
      )
      l = Conv2D("conv3", l, ch_out * 4, 1)
      return l + resnet_shortcut(shortcut, ch_out * 4, stride)
  
file_path: tensorpack/examples/Saliency/resnet_model.py
imports: import tensorflow
  from tensorpack import tfv1
  from tensorpack.models import BatchNorm, BNReLU, Conv2D, FullyConnected, GlobalAvgPooling, MaxPooling
  from tensorpack.tfutils.argscope import argscope, get_arg_scope
label_desc: Use image node_id 5 for calling a global function with example usage: preact_bottleneck(l, ch_out, stride, preact) and returns: unknown