class_docstr: Online Retrieval Predictor for Clips (used by RetriTask).
  TODO: merge this with VisPredictor?
class_docstr_tok: ["Online","Retrieval","Predictor","for","Clips","(","used","by","RetriTask",")",".","TODO",":","merge","this","with","VisPredictor","?"]
code: def predict_loop(self, model, retriver, epoch, early_stop=-1):
      # a fake loop that only try to recover video vector
      # from video_id.
      batched_videos = []
      # obtain available video_ids.
      video_ids = list(retriver.videoid_to_vectoridx.keys())
  
      dataloader = random.sample(
          video_ids, len(video_ids) // self.num_video_per_batch
      )
  
      if get_local_rank() == 0:
          dataloader = tqdm(dataloader)
      for batch_idx, batch in enumerate(dataloader):
          # batch is one video id.
          if batch_idx == early_stop:
              break
          video_ids = retriver.search_by_video_ids(
              [batch], self.num_cands
          )[0]
          if len(video_ids) > self.num_video_per_batch:
              # we moved the center to make cluster robust.
              video_ids = random.sample(
                  video_ids, self.num_video_per_batch
              )
          batched_videos.append(video_ids)
      return self.finalize(batched_videos, epoch)
  
imports: import os
  import torch
  import pickle
  import random
  from tqdm import tqdm
  from torch.utils.data import DataLoader
  from torch.utils.data.distributed import DistributedSampler
  from ..processors import ShardedHow2MetaProcessor, ShardedVideoProcessor, ShardedTextProcessor, VariedLenAligner
  from ..datasets import MMDataset
  from .task import Task
  from ..modules import vectorpool
  from ..evaluators.predictor import Predictor
  from ..utils import set_seed, get_local_rank, get_world_size
label_desc: Use image node_id 2 for calling the VideoRetriPredictor obj's underlying member method code with example usage: obj.predict_loop(model, retriver, epoch, early_stop) and returns: self