code: def tf_init_tpu(worker="", protocol=None):
      """Initializes TPU for TensorFlow.
  
      Args:
        worker: The BNS address of the remote TPU worker. If it's empty (the default
          value), TF will assume the TPU devices are connected to the local host.
        protocol: The network protocol used to connect to the TPU worker.
      Returns:
        The device name of the TPU worker's CPU.
      """
      protocol = protocol or "grpc"
      is_local = worker in ("", "local")
      resolver = tf.distribute.cluster_resolver.TPUClusterResolver(
          tpu=worker
      )
      if not is_local:
          tf.config.experimental_connect_to_cluster(
              resolver, protocol=protocol
          )
      tf.tpu.experimental.initialize_tpu_system(resolver)
      if is_local:
          return ""
      else:
          return "/job:worker"
  
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 6 for calling a global function with example usage: tf_init_tpu(worker, protocol) and returns: str, str