code: def get_feature_to_metric_names_map(
      output_features: List[FeatureConfigDict],
  ) -> Dict[str, List[str]]:
      """Returns a dict of output_feature_name -> list of metric names."""
      metrics_names = {}
      for output_feature in output_features:
          output_feature_name = output_feature[NAME]
          output_feature_type = output_feature[TYPE]
          metrics_names[
              output_feature_name
          ] = get_metric_names_for_type(output_feature_type)
      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 7 for calling a global function with example usage: get_feature_to_metric_names_map(output_features) and returns: metrics_names