code: def main(_):
      assert tf.version.VERSION.startswith("2.")
  
      if not FLAGS.model_dir:
          FLAGS.model_dir = "/tmp/bert/"
  
      #########################################################################
      # Construct AutoDist with ResourceSpec for Different Strategies
      if FLAGS.autodist_patch_tf:
          os.environ["AUTODIST_PATCH_TF"] = "True"
      else:
          os.environ["AUTODIST_PATCH_TF"] = "False"
      resource_spec_file = os.path.join(
          os.path.dirname(__file__), "../resource_spec.yml"
      )
  
      if FLAGS.autodist_strategy == "PS":
          strategy = AutoDist(
              resource_spec_file, PS(local_proxy_variable=FLAGS.proxy)
          )
      elif FLAGS.autodist_strategy == "PSLoadBalancing":
          strategy = AutoDist(
              resource_spec_file,
              PSLoadBalancing(local_proxy_variable=FLAGS.proxy),
          )
      elif FLAGS.autodist_strategy == "PartitionedPS":
          strategy = AutoDist(
              resource_spec_file,
              PartitionedPS(local_proxy_variable=FLAGS.proxy),
          )
      elif FLAGS.autodist_strategy == "AllReduce":
          strategy = AutoDist(
              resource_spec_file, AllReduce(chunk_size=FLAGS.chunk_size)
          )
      elif FLAGS.autodist_strategy == "Parallax":
          strategy = AutoDist(
              resource_spec_file,
              Parallax(
                  chunk_size=FLAGS.chunk_size,
                  local_proxy_variable=FLAGS.proxy,
              ),
          )
      else:
          raise ValueError(
              "the strategy can be only from PS, PSLoadBalancing, PartitionedPS, AllReduce, Parallax"
          )
  
      strategy.num_replicas_in_sync = strategy._resource_spec.num_gpus
  
      if strategy:
          print(
              "***** Number of cores used : ",
              strategy.num_replicas_in_sync,
          )
  
      resource_info = yaml.safe_load(open(resource_spec_file, "r"))
      try:
          node_num = len(resource_info["nodes"])
      except ValueError:
          print("nodes need to be set in specficiation file")
  
      try:
          gpu_num = len(resource_info["nodes"][0]["gpus"])
      except ValueError:
          print("gpus need to be set in specficiation file")
      #########################################################################
  
      logdir = "/tmp/logs"
      if not os.path.exists(logdir):
          os.makedirs(logdir)
  
      logname = (
          "bert_strategy_{}_node_{}_gpu_{}_patch_{}_proxy_{}".format(
              FLAGS.autodist_strategy,
              node_num,
              gpu_num,
              FLAGS.autodist_patch_tf,
              FLAGS.proxy,
          )
      )
  
      logging.get_absl_handler().use_absl_log_file(logname, logdir)
      # start running
      run_bert_pretrain(strategy, gpu_num, node_num)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import yaml
  import os
  import sys
  import tensorflow
  from absl import app
  from absl import flags
  from absl import logging
  from utils.logs import logger
  from utils.misc import keras_utils
  from utils import bert_modeling
  from utils import bert_models
  from utils import common_flags
  from utils import input_pipeline
  from utils import bert_utils
  from autodist import AutoDist
  from autodist.strategy.all_reduce_strategy import AllReduce
  from autodist.strategy.ps_strategy import PS
  from autodist.strategy.ps_lb_strategy import PSLoadBalancing
  from autodist.strategy.parallax_strategy import Parallax
  from autodist.strategy.partitioned_ps_strategy import PartitionedPS
label_desc: Use image node_id 5 for calling a global function with example usage: main(_) without return types