code: def __init__(self, **kwargs):
      super().__init__(
          kwargs["vis_processor"],
          kwargs["text_processor"],
          kwargs["vis_root"],
          kwargs["ann_paths"],
      )
  
      self.non_binary_cls = kwargs.get("non_bin", False)
      self.unanimous = kwargs.get("unanimous", False)
  
      annotation = []
      for i in range(0, len(self.annotation), 3):
          new_ann = self.annotation[i]
          new_ann["question"] = new_ann["QuestionText"]
          del new_ann["QuestionText"]
          new_ann["answer"] = [
              self.annotation[i + off]["answer"] for off in range(3)
          ]
          if (
              self.unanimous
              and Counter(new_ann["answer"])[new_ann["answer"][0]] != 3
          ):
              continue
          if self.non_binary_cls and (
              "yes" in new_ann["answer"] or "no" in new_ann["answer"]
          ):
              continue
          new_ann["question_id"] = new_ann["instance_id"]
          annotation.append(new_ann)
      self.modalities = kwargs["modalities"]
      for modality in self.modalities:
          setattr(self, f"{modality}_root", kwargs[f"{modality}_root"])
          setattr(
              self,
              f"{modality}_processor",
              kwargs[f"{modality}_processor"],
          )
      self.annotation = annotation
  
file_path: lavis/lavis/datasets/datasets/audio_qa_datasets.py
imports: import copy
  import os
  from lavis.datasets.datasets.audio_captioning_datasets import AudioCapsDataset
  from lavis.datasets.datasets.base_dataset import BaseDataset
  import torch
  import random
  from collections import Counter
label_desc: Use image node_id 1 to create a new ClothoQADataset object from inherited base classes: BaseDataset with example: obj = ClothoQADataset()