class_docstr: DatasetBuilder for QReCC dataset.
docstr: Returns the dataset metadata.
docstr_tok: ["Returns","the","dataset","metadata","."]
code: def _info(self) -> tfds.core.DatasetInfo:
      """Returns the dataset metadata."""
      return tfds.core.DatasetInfo(
          builder=self,
          description=_DESCRIPTION,
          features=tfds.features.FeaturesDict(
              {
                  "context": tfds.features.Sequence(
                      tfds.features.Text()
                  ),
                  "question": tfds.features.Text(),
                  "question_rewrite": tfds.features.Text(),
                  "answer": tfds.features.Text(),
                  "answer_url": tfds.features.Text(),
                  "conversation_id": tfds.features.Scalar(
                      np.int32, doc="The id of the conversation."
                  ),
                  "turn_id": tfds.features.Scalar(
                      np.int32,
                      doc="The id of the conversation turn, within a conversation.",
                  ),
                  "source": tfds.features.Text(
                      doc=(
                          "The original source of the data -- either QuAC, CAsT or"
                          " Natural Questions"
                      )
                  ),
              }
          ),
          supervised_keys=None,
          homepage="https://github.com/apple/ml-qrecc",
          citation=_CITATION,
      )
  
file_path: datasets/tensorflow_datasets/text/qrecc/qrecc.py
imports: import json
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the QReCC obj's underlying member method code with example usage: obj._info() and returns: tfds