class_docstr: DatasetBuilder for glove_100_angular 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(
              {
                  "index": tfds.features.Scalar(
                      dtype=np.int64, doc="Index within the split."
                  ),
                  "embedding": tfds.features.Tensor(
                      shape=(100,), dtype=np.float32
                  ),
                  "neighbors": tfds.features.Sequence(
                      {
                          "index": tfds.features.Scalar(
                              dtype=np.int64, doc="Neighbor index."
                          ),
                          "distance": tfds.features.Scalar(
                              dtype=np.float32, doc="Neighbor distance."
                          ),
                      },
                      doc=(
                          "The computed neighbors, which is only available for"
                          " the test split."
                      ),
                  ),
              }
          ),
          homepage="https://nlp.stanford.edu/projects/glove/",
          citation=_CITATION,
          disable_shuffling=True,
      )
  
file_path: datasets/tensorflow_datasets/nearest_neighbors/glove_100_angular/glove_100_angular.py
imports: import h5py
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the Glove100Angular obj's underlying member method code with example usage: obj._info() and returns: tfds