code: def convert_bayes_configs(config):
      selected_features = []
      new_config = {}
      for config_name, config_value in config.items():
          if config_name.startswith("bayes_feature"):
              # print(config_name, config_value)
              if config_value >= 0.5:
                  feature_name = config_name.replace(
                      "bayes_feature_", ""
                  )
                  selected_features.append(feature_name)
          elif config_name == "batch_size_log":
              batch_size = int(2**config_value)
              new_config["batch_size"] = batch_size
          elif config_name.endswith("float"):
              int_config_name = config_name.replace("_float", "")
              int_config_value = int(config_value)
              new_config[int_config_name] = int_config_value
          else:
              new_config[config_name] = config_value
      if selected_features:
          new_config["selected_features"] = json.dumps(
              selected_features
          )
      # print("config after bayes conversion is ", new_config)
      return new_config
  
label_desc: Use image node_id 1 for calling a global function with example usage: convert_bayes_configs(config) and returns: new_config