class_docstr: CelebA dataset. Aligned and cropped. With metadata.
class_docstr_tok: ["CelebA","dataset",".","Aligned","and","cropped",".","With","metadata","."]
code: def _info(self):
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "image": tfds.features.Image(
                      shape=(218, 178, 3), encoding_format="jpeg"
                  ),
                  "landmarks": {
                      name: np.int64 for name in LANDMARK_HEADINGS
                  },
                  # Attributes could be some special MultiLabel FeatureConnector
                  "attributes": {
                      name: np.bool_ for name in ATTR_HEADINGS
                  },
                  "identity": {
                      name: np.int64 for name in IDENTITY_HEADINGS
                  },
              }
          ),
          homepage="http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html",
      )
  
file_path: datasets/tensorflow_datasets/datasets/celeb_a/celeb_a_dataset_builder.py
imports: from __future__ import annotations
  import os
  from typing import Sequence, Union
  from etils import epath
  import numpy
  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