class_docstr: generated `pooled_video` and `pooled_text`.
class_docstr_tok: ["generated","`","pooled_video","`","and","`","pooled_text","`","."]
code: def _append_scores(self, scores, answers, full_scores):
      if len(full_scores) == 0:
          full_scores.append([])
          full_scores.append([])
      full_scores[0].append(scores.cpu().detach().numpy())
      full_scores[1].append(answers.cpu().detach().numpy())
  
imports: import os
  import random
  import json
  import numpy
  import torch
  import pickle
  import math
  from tqdm import tqdm
label_desc: Use image node_id 5 for calling the QAPredictor obj's underlying member method code with example usage: obj._append_scores(scores, answers, full_scores) without return types