code: def run_keras_single_device(device="cpu", device_id=0):
      with tf.device("/{0}:{1}".format(device, device_id)):
          model = keras_model()
          train_dataset = get_dataset(device, device_id)
  
          model.fit(
              train_dataset, epochs=EPOCHS, steps_per_epoch=ITERATIONS
          )
  
          assert (
              model.evaluate(train_dataset, steps=ITERATIONS)[1]
              > TARGET
          )
  
imports: import nvidia.dali.plugin.tf
  import os
  from nvidia.dali.pipeline import Pipeline
  import nvidia.dali.fn
  import nvidia.dali.types
  from test_utils_tensorflow import num_available_gpus
  from shutil import rmtree
  import tensorflow
  import tensorflow.compat.v1
label_desc: Use image node_id 5 for calling a global function with example usage: run_keras_single_device(device, device_id) without return types