code: def uniformly_subsampled_atari_data(dataset_name, data_percent):
      """Load `data_percent` sampled from rlu tfds `dataset_name` dataset."""
      ds_builder = tfds.builder(dataset_name)
      data_splits = []
      for split, info in ds_builder.info.splits.items():
          # Convert `data_percent` to number of episodes to allow
          # for fractional percentages.
          num_episodes = int((data_percent / 100) * info.num_examples)
          if num_episodes == 0:
              raise ValueError(
                  f"{data_percent}% leads to 0 episodes in {split}!"
              )
          # Sample first `data_percent` episodes from each of the data split
          data_splits.append(f"{split}[:{num_episodes}]")
      return load_data_splits(dataset_name, data_splits)
  
file_path: dopamine/dopamine/labs/offline_rl/rlu_tfds/tfds_atari_utils.py
imports: import rlds
  import tensorflow
  import tensorflow_datasets
label_desc: Use image node_id 3 for calling a global function with example usage: uniformly_subsampled_atari_data(dataset_name, data_percent) and returns: load_data_splits