code: def init_tf(config_dict: dict = None) -> None:
      """Initialize TensorFlow session using good default settings."""
      # Skip if already initialized.
      if tf.get_default_session() is not None:
          return
  
      # Setup config dict and random seeds.
      cfg = _sanitize_tf_config(config_dict)
      np_random_seed = cfg["rnd.np_random_seed"]
      if np_random_seed is not None:
          np.random.seed(np_random_seed)
      tf_random_seed = cfg["rnd.tf_random_seed"]
      if tf_random_seed == "auto":
          tf_random_seed = np.random.randint(1 << 31)
      if tf_random_seed is not None:
          tf.set_random_seed(tf_random_seed)
  
      # Setup environment variables.
      for key, value in cfg.items():
          fields = key.split(".")
          if fields[0] == "env":
              assert len(fields) == 2
              os.environ[fields[1]] = str(value)
  
      # Create default TensorFlow session.
      create_session(cfg, force_as_default=True)
  
imports: import os
  import numpy
  import tensorflow
  import logging
  import tensorflow.contrib
  from typing import Any, Iterable, List, Union
label_desc: Use image node_id 12 for calling a global function with example usage: init_tf(config_dict) without return types