code: def get_run_args():
      """Builds a dict of run arguments from flags."""
      run_args = {}
      if FLAGS.num_iterations:
          run_args["num_iterations"] = FLAGS.num_iterations
      if FLAGS.initial_collect_steps:
          run_args[
              "initial_collect_steps"
          ] = FLAGS.initial_collect_steps
      if FLAGS.replay_buffer_capacity:
          run_args[
              "replay_buffer_capacity"
          ] = FLAGS.replay_buffer_capacity
      if FLAGS.train_steps_per_iteration:
          run_args[
              "train_steps_per_iteration"
          ] = FLAGS.train_steps_per_iteration
      if FLAGS.n_step_update:
          run_args["n_step_update"] = FLAGS.n_step_update
      if FLAGS.eval_steps_per_iteration:
          run_args[
              "eval_steps_per_iteration"
          ] = FLAGS.eval_steps_per_iteration
      return run_args
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import app
  from absl import flags
  from absl import logging
  import gin
  import numpy
  import tensorflow
  from tf_agents.agents.categorical_dqn import categorical_dqn_agent
  from tf_agents.environments import batched_py_environment
  from tf_agents.environments import suite_atari
  from tf_agents.eval import metric_utils
  from tf_agents.metrics import py_metric
  from tf_agents.metrics import py_metrics
  from tf_agents.networks import categorical_q_network
  from tf_agents.networks import network
  from tf_agents.policies import epsilon_greedy_policy
  from tf_agents.policies import py_tf_policy
  from tf_agents.policies import random_py_policy
  from tf_agents.replay_buffers import py_hashed_replay_buffer
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
  from tf_agents.utils import timer
label_desc: Use image node_id 2 for calling a global function with example usage: get_run_args() and returns: run_args