class_docstr: CLEVR dataset.
code: def _info(self):
      features = {
          "image": tfds.features.Image(),
          "file_name": tfds.features.Text(),
          "objects": tfds.features.Sequence(
              {
                  "color": tfds.features.ClassLabel(
                      names=[
                          "gray",
                          "blue",
                          "brown",
                          "yellow",
                          "red",
                          "green",
                          "purple",
                          "cyan",
                      ]
                  ),
                  "material": tfds.features.ClassLabel(
                      names=["rubber", "metal"]
                  ),
                  "shape": tfds.features.ClassLabel(
                      names=["cube", "sphere", "cylinder"]
                  ),
                  "size": tfds.features.ClassLabel(
                      names=["small", "large"]
                  ),
                  "rotation": tfds.features.Tensor(
                      shape=(), dtype=np.float32
                  ),
                  "3d_coords": tfds.features.Tensor(
                      shape=(3,), dtype=np.float32
                  ),
                  "pixel_coords": tfds.features.Tensor(
                      shape=(3,), dtype=np.float32
                  ),
              }
          ),
      }
      if self.version > "3.0.0":
          features["question_answer"] = tfds.features.Sequence(
              {
                  "question": tfds.features.Text(),
                  "answer": tfds.features.Text(),
              }
          )
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(features),
          homepage=_BASE_URL,
      )
  
file_path: datasets/tensorflow_datasets/datasets/clevr/clevr_dataset_builder.py
imports: import collections
  import json
  import os
  from etils import epath
  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