code: def _steps_features():
      return tfds.features.FeaturesDict(
          {
              "action": tfds.features.FeaturesDict(
                  {
                      "close_gripper": np.bool_,
                      "open_gripper": np.bool_,
                      "target_pose": tfds.features.Tensor(
                          shape=(7,),
                          dtype=np.float32,
                          encoding=tfds.features.Encoding.ZLIB,
                      ),
                      "terminate": np.bool_,
                  }
              ),
              "is_first": np.bool_,
              "is_last": np.bool_,
              "is_terminal": np.bool_,
              "observation": tfds.features.FeaturesDict(
                  {
                      "gripper_closed": np.bool_,
                      "height_to_bottom": np.float32,
                      "image": tfds.features.Image(
                          shape=(512, 640, 3), dtype=np.uint8
                      ),
                      "state_dense": tfds.features.Tensor(
                          shape=(7,),
                          dtype=np.float32,
                          encoding=tfds.features.Encoding.ZLIB,
                      ),
                  }
              ),
          }
      )
  
file_path: datasets/tensorflow_datasets/robotics/mt_opt/mt_opt.py
imports: from __future__ import annotations
  import os
  from typing import Any, Dict, Generator, Tuple
  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 a global function with example usage: _steps_features() and returns: tfds