code: def __init__(
      self, config, dataset_type, imdb_file_index, *args, **kwargs
  ):
      super().__init__("charades", config, dataset_type)
      self.imdb_file_index = imdb_file_index
      self.load_df()
      self.length = len(self.video_clips)
      self.audio_processor = None
      self.video_processor = None
      self.video_train_processor = None
      self.video_test_processor = None
      self.prediction_threshold = self.config.get(
          "prediction_threshold", 0.5
      )
  
imports: import os
  import PIL
  import torch
  from mmf.common.sample import Sample
  from mmf.datasets.base_dataset import BaseDataset
  from mmf.datasets.builders.charades._utils import CharadesVideoClips, img2gif, make_charades_df
  from mmf.utils.distributed import byte_tensor_to_object, object_to_byte_tensor
  from mmf.utils.file_io import PathManager
label_desc: Use image node_id 1 to create a new CharadesDataset object from inherited base classes: BaseDataset with example: obj = CharadesDataset(config, dataset_type, imdb_file_index)