code: def train_language_understanding_atis_for_eval(
      test_device, output_dir
  ):
      abs_path = os.path.dirname(os.path.abspath(__file__))
      data_path = os.path.join(
          os.path.join(
              abs_path,
              "..",
              "..",
              "..",
              "..",
              "Examples",
              "LanguageUnderstanding",
              "ATIS",
              "Data",
          )
      )
      reader = LanguageUnderstanding.create_reader(
          data_path + "/atis.train.ctf", True
      )
      model = LanguageUnderstanding.create_model_function()
  
      # train
      LanguageUnderstanding_train(reader, model, max_epochs=1)
      model.save(os.path.join(output_dir, "atis" + "_0.dnn"))
  
file_path: CNTK/Tests/EndToEndTests/EvalClientTests/CNTKLibraryCSEvalExamplesTest/train_models_for_evaluation.py
imports: import os
  import sys
  import argparse
  import zipfile
  import math
  import cntk
  import prepare_test_data
  import TrainResNet_CIFAR10
  import LanguageUnderstanding
  from cntk.layers.typing import *
  from cntk import *
  from cntk.logging import *
label_desc: Use image node_id 5 for calling a global function with example usage: train_language_understanding_atis_for_eval(test_device, output_dir) without return types