class_docstr: A basic feature store to manage multiple features for access.
class_docstr_tok: ["A","basic","feature","store","to","manage","multiple","features","for","access","."]
docstr: Get the metadata of the specified feature in the feature store.
  
  Parameters
  ----------
  domain : str
      The domain of the feature such as "node", "edge" or "graph".
  type_name : str
      The node or edge type name.
  feature_name : str
      The feature name.
  Returns
  -------
  Dict
      The metadata of the feature.
docstr_tok: ["Get","the","metadata","of","the","specified","feature","in","the","feature","store",".","Parameters","--","--","--","--","--","domain",":","str","The","domain","of","the","feature","such","as","``","node","''",",","``","edge","''","or","``","graph","''",".","type_name",":","str","The","node","or","edge","type","name",".","feature_name",":","str","The","feature","name",".","Returns","--","--","--","-","Dict","The","metadata","of","the","feature","."]
code: def metadata(
      self,
      domain: str,
      type_name: str,
      feature_name: str,
  ):
      """Get the metadata of the specified feature in the feature store.
  
      Parameters
      ----------
      domain : str
          The domain of the feature such as "node", "edge" or "graph".
      type_name : str
          The node or edge type name.
      feature_name : str
          The feature name.
      Returns
      -------
      Dict
          The metadata of the feature.
      """
      return self._features[
          (domain, type_name, feature_name)
      ].metadata()
  
file_path: dgl/python/dgl/graphbolt/impl/basic_feature_store.py
imports: from typing import Dict, Tuple
  import torch
  from ..feature_store import Feature, FeatureStore
label_desc: Use image node_id 4 for calling the BasicFeatureStore obj's underlying member method code with example usage: obj.metadata(domain, type_name, feature_name) and returns: self