code: def _tf_setup_from_flags():
      """Processes TensorFlow-relevant flags."""
      if FLAGS.enable_eager_execution:
          tf.compat.v1.enable_eager_execution()
      if FLAGS.tf_xla:
          tf.config.optimizer.set_jit(True)
          fastmath.tf.set_tf_xla_forced_compile(
              FLAGS.tf_xla_forced_compile
          )
      tf.config.optimizer.set_experimental_options(
          {
              "pin_to_host_optimization": FLAGS.tf_opt_pin_to_host,
              "layout_optimizer": FLAGS.tf_opt_layout,
          }
      )
      tf_np.set_allow_float64(FLAGS.tf_allow_float64)
  
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 1 for calling a global function with example usage: _tf_setup_from_flags() without return types