class_docstr: Shapes3d data set.
code: def _info(self):
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "image": tfds.features.Image(shape=(64, 64, 3)),
                  "label_floor_hue": tfds.features.ClassLabel(
                      num_classes=10
                  ),
                  "label_wall_hue": tfds.features.ClassLabel(
                      num_classes=10
                  ),
                  "label_object_hue": tfds.features.ClassLabel(
                      num_classes=10
                  ),
                  "label_scale": tfds.features.ClassLabel(
                      num_classes=8
                  ),
                  "label_shape": tfds.features.ClassLabel(
                      num_classes=4
                  ),
                  "label_orientation": tfds.features.ClassLabel(
                      num_classes=15
                  ),
                  "value_floor_hue": tfds.features.Tensor(
                      shape=[], dtype=np.float32
                  ),
                  "value_wall_hue": tfds.features.Tensor(
                      shape=[], dtype=np.float32
                  ),
                  "value_object_hue": tfds.features.Tensor(
                      shape=[], dtype=np.float32
                  ),
                  "value_scale": tfds.features.Tensor(
                      shape=[], dtype=np.float32
                  ),
                  "value_shape": tfds.features.Tensor(
                      shape=[], dtype=np.float32
                  ),
                  "value_orientation": tfds.features.Tensor(
                      shape=[], dtype=np.float32
                  ),
              }
          ),
          homepage="https://github.com/deepmind/3d-shapes",
      )
  
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