code: def get_feature_to_metric_names_map_from_feature_collection(
      output_features: "FeatureCollection",  # noqa
  ) -> Dict[str, List[str]]:
      """Returns a dict of output_feature_name -> list of metric names."""
      metrics_names = {
          output_feature.name: get_metric_names_for_type(
              output_feature.type
          )
          for output_feature in output_features
      }
      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 8 for calling a global function with example usage: get_feature_to_metric_names_map_from_feature_collection(output_features) and returns: metrics_names