class_docstr: DatasetBuilder for RLDS datasets which proxies data files from GCS.
  
  RLDS datasets are already converted to TFDS format. This
  builder just effectively downloads them from GCS.
class_docstr_tok: ["DatasetBuilder","for","RLDS","datasets","which","proxies","data","files","from","GCS",".","RLDS","datasets","are","already","converted","to","TFDS","format",".","This","builder","just","effectively","downloads","them","from","GCS","."]
docstr: Returns the dataset metadata.
docstr_tok: ["Returns","the","dataset","metadata","."]
code: def _info(self) -> tfds.core.DatasetInfo:
      """Returns the dataset metadata."""
      description = self.get_description()
      features = self.get_ds_builder().info.features
  
      tmp = dict(features)
  
      for key in self.KEYS_TO_STRIP:
          if key in tmp:
              del tmp[key]
      features = tfds.features.FeaturesDict(tmp)
  
      return tfds.core.DatasetInfo(
          builder=self,
          description=description,
          features=features,
          supervised_keys=None,
          homepage=self.get_homepage(),
          citation=self.get_citation(),
      )
  
imports: from __future__ import annotations
  import abc
  import os
  from typing import Any
  from tensorflow_datasets.core import beam_utils
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import dataset_utils
  from tensorflow_datasets.core import splits
  from tensorflow_datasets.core.utils import read_config
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 6 for calling the DatasetImporterBuilder obj's underlying member method code with example usage: obj._info() and returns: tfds