code: def get_metric_names(
      output_features: Dict[str, "OutputFeature"]
  ) -> Dict[str, List[str]]:  # noqa
      """Returns a dict of output_feature_name -> list of metric names."""
      metrics_names = {}
      for (
          output_feature_name,
          output_feature,
      ) in output_features.items():
          metrics_names[output_feature_name] = sorted(
              list(get_metric_names_for_type(output_feature.type()))
          )
      # Add combined loss.
      metrics_names[COMBINED] = [LOSS]
      return metrics_names
  
file_path: ludwig/ludwig/utils/metric_utils.py
imports: from collections import defaultdict, namedtuple
  from typing import Dict, List, Optional
  import torch
  from torch import Tensor
  from torchmetrics.metric import Metric
  from ludwig.constants import COMBINED, LOSS, NAME, TYPE
  from ludwig.modules.metric_registry import get_metric_names_for_type
  from ludwig.types import FeatureConfigDict
label_desc: Use image node_id 6 for calling a global function with example usage: get_metric_names(output_features) and returns: metrics_names