code: def _feature_description():
      return {
          "checkpoint_idx": tf.io.FixedLenFeature([], tf.int64),
          "episode_idx": tf.io.FixedLenFeature([], tf.int64),
          "episode_return": tf.io.FixedLenFeature([], tf.float32),
          "clipped_episode_return": tf.io.FixedLenFeature(
              [], tf.float32
          ),
          "observations": tf.io.FixedLenSequenceFeature(
              [], tf.string, allow_missing=True
          ),
          "actions": tf.io.FixedLenSequenceFeature(
              [], tf.int64, allow_missing=True
          ),
          "unclipped_rewards": tf.io.FixedLenSequenceFeature(
              [], tf.float32, allow_missing=True
          ),
          "clipped_rewards": tf.io.FixedLenSequenceFeature(
              [], tf.float32, allow_missing=True
          ),
          "discounts": tf.io.FixedLenSequenceFeature(
              [], tf.float32, allow_missing=True
          ),
      }
  
file_path: datasets/tensorflow_datasets/rl_unplugged/atari_utils.py
imports: from __future__ import annotations
  import dataclasses
  from typing import Any, Dict
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 3 for calling a global function with example usage: _feature_description() and returns: dict