code: def get_xgboost_objective_metric(objective):
      """
      Get the xgboost version-compatible objective and evaluation metric from a potentially version-incompatible input.
  
      Args
      ----
  
      objective : string
          An xgboost objective that may be incompatible with the installed version.
  
      Returns
      -------
      A tuple with the translated objective and evaluation metric.
      """
  
      def clean_dict_keys(orig):
          return {
              clean_xgboost_objective(k): v for (k, v) in orig.items()
          }
  
      metric_mapping = clean_dict_keys(
          {"rank:pairwise": "auc", "reg:squarederror": "rmse"}
      )
  
      objective = clean_xgboost_objective(objective)
  
      assert (
          objective in metric_mapping
      ), "Effect learner objective must be one of: " + ", ".join(
          metric_mapping
      )
      return objective, metric_mapping[objective]
  
file_path: causalml/causalml/inference/meta/utils.py
imports: import pandas
  import numpy
  from packaging import version
  from xgboost import __version__
label_desc: Use image node_id 6 for calling a global function with example usage: get_xgboost_objective_metric(objective) and returns: objective,  metric_mapping, unknown