code: def get_specified_metrics(metric_names: list):
      ensembles = MetricEnsemble()
      available_metrics = get_metric_names([classi, reg])
      for metric_name in metric_names:
          if metric_name in available_metrics:
              ensembles.add_metric(
                  get_metric_names([classi, reg])[metric_name]()
              )
          else:
              raise ValueError(
                  f"metric {metric_name} is not supported yet, supported metrics are \n {list(available_metrics.keys())}"
              )
      return ensembles
  
file_path: FATE/python/fate/ml/evaluation/tool.py
imports: import inspect
  from fate.ml.evaluation import classification
  from fate.ml.evaluation import regression
  from fate.ml.evaluation.metric_base import Metric, MetricEnsemble
label_desc: Use image node_id 8 for calling a global function with example usage: get_specified_metrics(metric_names) and returns: ensembles