code: def print_all_variables(train_only=False):
      
      # tvar = tf.trainable_variables() if train_only else tf.all_variables()
      if train_only:
          t_vars = tf.trainable_variables()
          logging.info("  [*] printing trainable variables")
  
      else:
          t_vars = tf.global_variables()
          logging.info("  [*] printing global variables")
  
      for idx, v in enumerate(t_vars):
          logging.info("  var {:3}: {:15}   {}".format(idx, str(v.get_shape()), v.name))
docs: Print information of trainable or all variables,
      without ``tl.layers.initialize_global_variables(sess)``.
  
      Parameters
      ----------
      train_only : boolean
          Whether print trainable variables only.
              - If True, print the trainable variables.
              - If False, print all variables.