code: def get_config():
      logger.auto_set_dir()
  
      ds = CharRNNData(param.corpus, 100000)
      ds = BatchData(ds, param.batch_size)
  
      return TrainConfig(
          data=QueueInput(ds),
          callbacks=[
              ModelSaver(),
              ScheduledHyperParamSetter("learning_rate", [(25, 2e-4)]),
          ],
          model=Model(),
          max_epoch=50,
      )
  
imports: import argparse
  import numpy
  import operator
  import os
  import sys
  from collections import Counter
  import tensorflow
  from tensorpack import *
  from tensorpack.tfutils import optimizer, summary
  from tensorpack.tfutils.gradproc import GlobalNormClip
label_desc: Use image node_id 1 for calling a global function with example usage: get_config() and returns: TrainConfig