code: def encode_candidate(
      reranker,
      candidate_pool,
      encode_batch_size,
      silent,
      logger,
      is_zeshel,
  ):
      if is_zeshel:
          src = 0
          cand_encode_dict = {}
          for src, cand_pool in candidate_pool.items():
              logger.info("Encoding candidate pool %s" % WORLDS[src])
              cand_pool_encode = encode_candidate(
                  reranker,
                  cand_pool,
                  encode_batch_size,
                  silent,
                  logger,
                  is_zeshel=False,
              )
              cand_encode_dict[src] = cand_pool_encode
          return cand_encode_dict
  
      reranker.model.eval()
      device = reranker.device
      sampler = SequentialSampler(candidate_pool)
      data_loader = DataLoader(
          candidate_pool, sampler=sampler, batch_size=encode_batch_size
      )
      if silent:
          iter_ = data_loader
      else:
          iter_ = tqdm(data_loader)
  
      cand_encode_list = None
      for step, batch in enumerate(iter_):
          cands = batch
          cands = cands.to(device)
          cand_encode = reranker.encode_candidate(cands)
          if cand_encode_list is None:
              cand_encode_list = cand_encode
          else:
              cand_encode_list = torch.cat(
                  (cand_encode_list, cand_encode)
              )
  
      return cand_encode_list
  
imports: import argparse
  import json
  import logging
  import os
  import torch
  from tqdm import tqdm
  from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
  from pytorch_transformers.tokenization_bert import BertTokenizer
  from blink.biencoder.biencoder import BiEncoderRanker
  import blink.biencoder.data_process
  import blink.biencoder.nn_prediction
  import blink.candidate_ranking.utils
  from blink.biencoder.zeshel_utils import WORLDS, load_entity_dict_zeshel, Stats
  from blink.common.params import BlinkParser
label_desc: Use image node_id 5 for calling a global function with example usage: encode_candidate(reranker, candidate_pool, encode_batch_size, silent, logger, is_zeshel) and returns: cand_encode_list, cand_encode_dict