class_docstr: dSprites data set.
code: def _info(self):
      features_dict = {
          "image": tfds.features.Image(shape=(64, 64, 1)),
          "label_shape": tfds.features.ClassLabel(num_classes=3),
          "label_scale": tfds.features.ClassLabel(num_classes=6),
          "label_orientation": tfds.features.ClassLabel(num_classes=40),
          "label_x_position": tfds.features.ClassLabel(num_classes=32),
          "label_y_position": tfds.features.ClassLabel(num_classes=32),
          "value_shape": tfds.features.Tensor(
              shape=[], dtype=np.float32
          ),
          "value_scale": tfds.features.Tensor(
              shape=[], dtype=np.float32
          ),
          "value_orientation": tfds.features.Tensor(
              shape=[], dtype=np.float32
          ),
          "value_x_position": tfds.features.Tensor(
              shape=[], dtype=np.float32
          ),
          "value_y_position": tfds.features.Tensor(
              shape=[], dtype=np.float32
          ),
      }
      if self.version > "2.0.0":
          features_dict["id"] = tfds.features.Text()
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(features_dict),
          homepage="https://github.com/deepmind/dsprites-dataset",
      )
  
imports: 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