class_docstr: LSMDC dataset.
class_docstr_tok: ["LSMDC","dataset","."]
code: def __getitem__(self, idx):
      face_ind = 1
  
      if idx >= self.n_lsmdc:
          flow = th.zeros(self.flow_features_size)
          face = th.zeros(self.face_features_size)
          audio = th.zeros(
              self.audio_features.size()[1], self.audio_features_size
          )
          audio_size = 1
          face_ind = 0
      else:
          flow = self.flow_features[idx]
          face = self.face_features[idx]
          audio = self.audio_features[idx]
          audio_size = self.audio_sizes[idx]
  
          if th.sum(face) == 0:
              face_ind = 0
      return {
          "video": self.visual_features[idx],
          "flow": flow,
          "face": face,
          "text": self.text_features[idx],
          "audio": audio,
          "audio_size": audio_size,
          "coco_ind": self.coco_ind[idx],
          "face_ind": face_ind,
          "text_size": self.text_sizes[idx],
      }
  
imports: import torch
  from torch.utils.data import Dataset
  import numpy
  import os
  import math
  import random
label_desc: Use image node_id 3 for calling the LSMDC obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: dict