class_docstr: DatasetBuilder for pass dataset.
docstr: Returns the dataset metadata.
docstr_tok: ["Returns","the","dataset","metadata","."]
code: def _info(self):
      """Returns the dataset metadata."""
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "image": tfds.features.Image(
                      shape=(None, None, 3)
                  ),  # The image.
                  "image/creator_uname": (
                      tfds.features.Text()
                  ),  # The photographer/creator.
                  "image/hash": (
                      tfds.features.Text()
                  ),  # The hash, as computed from YFCC-100M.
                  "image/gps_lon": tfds.features.Tensor(
                      shape=(), dtype=np.float32
                  ),  # Longitude of image if existent, otw. NaN.
                  "image/gps_lat": tfds.features.Tensor(
                      shape=(), dtype=np.float32
                  ),  # Latitude of image if existent, otw. NaN.
                  "image/date_taken": (
                      tfds.features.Text()
                  ),  # Datetime of image if not NaN, else empty string.
              }
          ),
          supervised_keys=None,
          homepage="https://www.robots.ox.ac.uk/~vgg/data/pass/",
      )
  
imports: 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 Builder obj's underlying member method code with example usage: obj._info() and returns: self