code: def get_data(train_or_test):
      isTrain = train_or_test == "train"
      augs = fbresnet_augmentor(isTrain)
  
      meta = dataset.ILSVRCMeta()
      pp_mean = meta.get_per_pixel_mean()
      augs.append(
          imgaug.MapImage(lambda x: x - pp_mean[16:-16, 16:-16])
      )
  
      ds = get_imagenet_dataflow(
          args.data, train_or_test, BATCH_SIZE, augs
      )
      return ds
  
file_path: tensorpack/examples/ImageNetModels/inception-bn.py
imports: import argparse
  import os
  from tensorpack import tfv1
  from tensorpack import *
  from tensorpack.dataflow import dataset
  from tensorpack.tfutils.summary import add_moving_summary
  from tensorpack.utils.gpu import get_num_gpu
  from imagenet_utils import fbresnet_augmentor, get_imagenet_dataflow
label_desc: Use image node_id 1 for calling a global function with example usage: get_data(train_or_test) and returns: ds