code: def dedupe(self):
      logging.info(self.deduper)
      if self.deduper is None:
          logging.info("No deduper configured")
          return
      codecs = []
      codesets = []
      idxs = []
      for factory, filename in zip(self.deduper, self.deduper_codec_fn):
          if os.path.exists(filename):
              logging.info(f"loading trained dedupe codec: {filename}")
              codec = faiss.read_index(filename)
          else:
              logging.info(f"training dedupe codec: {factory}")
              codec = faiss.index_factory(self.input_d, factory)
              xb_sample = np.unique(
                  self.xb_ds.get_first_n(100_000, np.float32), axis=0
              )
              faiss.ParameterSpace().set_index_parameter(
                  codec, "verbose", 1
              )
              codec.train(xb_sample)
              logging.info(f"writing trained dedupe codec: {filename}")
              faiss.write_index(codec, filename)
          codecs.append(codec)
          codesets.append(faiss.CodeSet(codec.sa_code_size()))
          idxs.append(np.empty((0,), dtype=np.uint32))
      bs = 1_000_000
      i = 0
      for buffer in tqdm(self.xb_ds.iterate(0, bs, np.float32)):
          for j in range(len(codecs)):
              codec, codeset, idx = codecs[j], codesets[j], idxs[j]
              uniq = codeset.insert(codec.sa_encode(buffer))
              idxs[j] = np.append(
                  idx,
                  np.arange(i, i + buffer.shape[0], dtype=np.uint32)[
                      uniq
                  ],
              )
          i += buffer.shape[0]
      for idx, filename in zip(idxs, self.deduper_idx_fn):
          logging.info(f"writing {filename}, shape: {idx.shape}")
          np.save(filename, idx)
      logging.info("done")
  
imports: import faiss
  import numpy
  import os
  from tqdm import tqdm, trange
  import sys
  import logging
  from faiss.contrib.ondisk import merge_ondisk
  from faiss.contrib.big_batch_search import big_batch_search
  from faiss.contrib.exhaustive_search import knn_ground_truth
  from faiss.contrib.evaluation import knn_intersection_measure
  from utils import get_intersection_cardinality_frequencies, margin, is_pretransform_index
  from dataset import create_dataset_from_oivf_config
label_desc: Use image node_id 3 for calling the OfflineIVF obj's underlying member method code with example usage: obj.dedupe() without return types