code: def get_distribution_strategy(num_gpus, all_reduce_alg="nccl"):
      """Return a DistributionStrategy for running the model.
  
      Args:
        num_gpus: Number of GPUs to run this model.
        all_reduce_alg: Specify which algorithm to use when performing all-reduce.
          See tf.distribute.NcclAllReduce for available algorithms.
          If None, Strategy will using nccl as default.
  
      Returns:
        tf.distribute.Strategy object.
      """
      if num_gpus == 0:  # pylint: disable=no-else-return
          return tf.distribute.OneDeviceStrategy("device:CPU:0")
      elif num_gpus == 1:
          return tf.distribute.OneDeviceStrategy("device:GPU:0")
      else:
          return tf.distribute.MirroredStrategy(
              devices=None, cross_device_ops=None
          )
  
imports: import os
  from absl import logging
  import numpy
  import delta.compat
  from tensorflow.python.client import device_lib
  from tensorflow.python.estimator.canned import metric_keys
  from tensorflow.python.util import nest
  from delta.utils.register import registers
label_desc: Use image node_id 10 for calling a global function with example usage: get_distribution_strategy(num_gpus, all_reduce_alg) and returns: tf, tf, tf