code: def get_data():
      d1 = dataset.SVHNDigit("train")
      d2 = dataset.SVHNDigit("extra")
      data_train = RandomMixData([d1, d2])
      data_test = dataset.SVHNDigit("test", shuffle=False)
  
      augmentors = [
          imgaug.Resize((40, 40)),
          imgaug.Brightness(30),
          imgaug.Contrast((0.5, 1.5)),
      ]
      data_train = AugmentImageComponent(data_train, augmentors)
      data_train = BatchData(data_train, 128)
      data_train = MultiProcessRunner(data_train, 5, 5)
  
      augmentors = [imgaug.Resize((40, 40))]
      data_test = AugmentImageComponent(data_test, augmentors)
      data_test = BatchData(data_test, 128, remainder=True)
      return data_train, data_test
  
file_path: tensorpack/examples/basics/svhn-digit-convnet.py
imports: import argparse
  import os
  from tensorpack import tfv1
  from tensorpack import *
  from tensorpack.dataflow import dataset
  from tensorpack.tfutils.summary import *
label_desc: Use image node_id 1 for calling a global function with example usage: get_data() and returns: data_train,  data_test