class_docstr: Maps a feature path to its weight feature.
  
  This map can be created with a "global" weight feature and path-specific
  overrides. For any given FeaturePath, its weight column is the override, if
  specified, or the "global" one.
code: def __init__(
      self,
      weight_feature: Optional[types.FeatureName] = None,
      per_feature_override: Optional[
          Mapping[types.FeaturePath, types.FeatureName]
      ] = None,
  ):
      self._weight_feature = weight_feature
      self._per_feature_override = per_feature_override
      all_weight_features = []
      if self._per_feature_override is not None:
          all_weight_features.extend(
              self._per_feature_override.values()
          )
      if self._weight_feature is not None:
          all_weight_features.append(self._weight_feature)
      self._all_weight_features = frozenset(all_weight_features)
  
imports: from typing import FrozenSet, Mapping, Optional
  from tensorflow_data_validation import types
label_desc: Use image node_id 1 to create a new ExampleWeightMap object from inherited base classes: object with example: obj = ExampleWeightMap(weight_feature, per_feature_override)