code: def get_config():
      logger.auto_set_dir()
  
      ds_train = get_data("train")
      ds_test = get_data("test")
  
      return TrainConfig(
          model=Model(),
          data=QueueInput(ds_train),
          callbacks=[
              ModelSaver(),
              InferenceRunner(ds_test, [ScalarStats("total_costs")]),
          ],
          steps_per_epoch=len(ds_train),
          max_epoch=100,
      )
  
file_path: tensorpack/examples/boilerplate.py
imports: import argparse
  import os
  import tensorflow
  from tensorpack import *
label_desc: Use image node_id 2 for calling a global function with example usage: get_config() and returns: TrainConfig