old_contents: import tensorflow as tf
  import sys
  
  
  def get_cluster_spec():
      return tf.train.ClusterSpec({
          "worker": [
              # "139.30.31.218:2222",  # citlab
              "139.30.31.13:2222", # citlab 2
              "139.30.31.13:2224", # citlab 2
              # "139.30.31.187:8888:2222", # citlab 3
          ],
          "ps": [
              "139.30.31.13:2223", # citlab 2
              # "139.30.31.176:2222"  # gundram
          ]})
  
  
  if __name__ == '__main__':
      spec = get_cluster_spec()
      for arg in sys.argv[1:]:
          print arg
      jobname = sys.argv[1]
      taskindex = int(sys.argv[2])
      print("job_name = '{}'".format(jobname))
      print("task_index = '{}'".format(taskindex))
      server = tf.train.Server(spec, job_name=jobname, task_index=taskindex)
  
new_contents: import tensorflow as tf
  import sys
  
  
  def get_cluster_spec():
      return tf.train.ClusterSpec({
          "worker": [
              # "139.30.31.218:2222",  # citlab
              # "139.30.31.13:2222", # citlab 2
              "139.30.31.176:2222", # gundram
              "139.30.31.13:2222", # citlab 2
              # "139.30.31.187:8888:2222", # citlab 3
          ],
          "ps": [
              "139.30.31.181:2222", # tobi
              # "139.30.31.176:2222"  # gundram
          ]})
  
  
  if __name__ == '__main__':
      spec = get_cluster_spec()
      for arg in sys.argv[1:]:
          print arg
      jobname = sys.argv[1]
      taskindex = int(sys.argv[2])
      print("job_name = '{}'".format(jobname))
      print("task_index = '{}'".format(taskindex))
      server = tf.train.Server(spec, job_name=jobname, task_index=taskindex)
  
subject: add tobi