class_docstr: CrossTaskPredictor needs to compute the average of logits
  for overlapped sliding-window.
class_docstr_tok: ["CrossTaskPredictor","needs","to","compute","the","average","of","logits","for","overlapped","sliding-window","."]
code: def __init__(self, config):
      super().__init__(config)
      self.lsm = torch.nn.LogSoftmax(dim=1)
      self.max_video_len = config.dataset.max_video_len
      self.sliding_window = config.dataset.sliding_window
      self.sliding_window_size = config.dataset.sliding_window_size
      self.annotation_path = config.dataset.annotation_path
  
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 1 to create a new CrossTaskPredictor object from inherited base classes: Predictor with example: obj = CrossTaskPredictor(config)