code: def test_keras_multi_gpu_mirrored_strategy():
      # due to compatibility problems between the driver, cuda version and
      # TensorFlow 2.12 test_keras_multi_gpu_mirrored_strategy doesn't work.
      if LooseVersion(tf.__version__) >= LooseVersion("2.12.0"):
          raise SkipTest(
              "This test is not supported for TensorFlow 2.12"
          )
      strategy = tf.distribute.MirroredStrategy(
          devices=available_gpus()
      )
  
      with strategy.scope():
          model = mnist.keras_model()
  
      train_dataset = mnist.get_dataset_multi_gpu(strategy)
  
      model.fit(
          train_dataset,
          epochs=mnist.EPOCHS,
          steps_per_epoch=mnist.ITERATIONS,
      )
  
      assert (
          model.evaluate(train_dataset, steps=mnist.ITERATIONS)[1]
          > mnist.TARGET
      )
  
file_path: DALI/dali/test/python/test_dali_tf_dataset_mnist_eager.py
imports: import tensorflow
  from nose.tools import with_setup
  import test_dali_tf_dataset_mnist
  from test_utils_tensorflow import skip_for_incompatible_tf, available_gpus
  from nose_utils import raises
  from nose import SkipTest
  from distutils.version import LooseVersion
label_desc: Use image node_id 6 for calling a global function with example usage: test_keras_multi_gpu_mirrored_strategy() without return types