code: def __getitem__(self, idx):
      if len(self.video_clips) == 0:
          self.load_df()
      video, audio, info = self.video_clips.get_clip(idx)
      text = self.text_list[idx]
      actual_idx = self.ids_list[idx]
      label = [
          self.class_to_idx[class_name]
          for class_name in self.labels[idx]
      ]
      one_hot_label = torch.zeros(len(self.class_to_idx))
      one_hot_label[label] = 1
  
      if self.video_processor is not None:
          video = self.video_processor(video)
  
      if self.audio_processor is not None:
          audio = self.audio_processor(audio)
  
      sample = Sample()
      sample.id = object_to_byte_tensor(actual_idx)
      sample.video = video
      sample.audio = audio
      sample.update(self.text_processor({"text": text}))
      sample.targets = one_hot_label
      return sample
  
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 10 for calling the CharadesDataset obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: sample