code: def _make_jax_gpu_cluster(
      host_id, server_ip, n_hosts, server_port=5005
  ):
      """Make JAX GPU Cluster."""
  
      addr = f"{server_ip}:{server_port}"
      if host_id == 0:
          logging.info("starting service on %s", addr)
          service = xc.get_distributed_runtime_service(addr, n_hosts)
          # We add an explicit call to shutdown the service via atexit as Python
          # interpreter may not call the service destructor on process termination.
          atexit.register(service.shutdown)
  
      logging.info("connecting to service on %s", addr)
      dist_client = xc.get_distributed_runtime_client(addr, host_id)
      dist_client.connect()
      atexit.register(dist_client.shutdown)
  
      # register dist gpu backend
      factory = functools.partial(
          jax.lib.xla_client.make_gpu_client, dist_client, host_id
      )
      jax.lib.xla_bridge.register_backend_factory(
          "gpu", factory, priority=300
      )
  
imports: import atexit
  import datetime
  import functools
  import os
  from absl import app
  from absl import flags
  from absl import logging
  import gin
  import jax
  from jax.lib import xla_extension
  import tensorflow.compat.v2
  from trax import fastmath
  from trax import trainer_flags
  from trax.supervised import trainer_lib
  from trax.tf_numpy import numpy
label_desc: Use image node_id 7 for calling a global function with example usage: _make_jax_gpu_cluster(host_id, server_ip, n_hosts, server_port) without return types