code: def _get_mirrored_strategy(self):
      device_type = "GPU" if tf.test.is_gpu_available() else "CPU"
      devices = [
          "{}:{}".format(device_type, i) for i in range(NUM_REPLICAS)
      ]
      return tf.distribute.MirroredStrategy(devices)
  
file_path: neural-structured-learning/neural_structured_learning/keras/adversarial_regularization_multi_device_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import neural_structured_learning.configs
  from neural_structured_learning.keras import adversarial_regularization
  import numpy
  import tensorflow
label_desc: Use image node_id 3 for calling the AdversarialRegularizationMultiDeviceTest obj's underlying member method code with example usage: obj._get_mirrored_strategy() and returns: tf