code: def search(self):
      logging.info(f"search: {self.knn_dir}")
      slurm_job_id = os.environ.get("SLURM_JOB_ID")
  
      ngpu = faiss.get_num_gpus()
      logging.info(f"number of gpus: {ngpu}")
      self.all_gpu_resources = [
          faiss.StandardGpuResources() for _ in range(ngpu)
      ]
      self._knn_function(
          np.zeros((10, 10), dtype=np.float16),
          np.zeros((10, 10), dtype=np.float16),
          self.k,
          metric=self.metric,
          thread_id=0,
      )
  
      index = self._open_sharded_index()
      index_ivf = faiss.downcast_index(faiss.extract_index_ivf(index))
      logging.info(f"setting nprobe to {self.nprobe}")
      index_ivf.nprobe = self.nprobe
      # quantizer = faiss.index_cpu_to_all_gpus(index_ivf.quantizer)
      for i in range(0, self.xq_ds.size, self.xq_bs):
          Ifn = (
              f"{self.knn_dir}/I{(i):010}_{self.knn_output_file_suffix}"
          )
          Dfn = f"{self.knn_dir}/D_approx{(i):010}_{self.knn_output_file_suffix}"
          CPfn = f"{self.knn_dir}/CP{(i):010}_{self.knn_output_file_suffix}"
  
          if slurm_job_id:
              worker_record = (
                  self.knn_dir
                  + f"/record_{(i):010}_{self.knn_output_file_suffix}.txt"
              )
              if not os.path.exists(worker_record):
                  logging.info(
                      f"creating record file {worker_record} and saving job"
                      f" id: {slurm_job_id}"
                  )
                  with open(worker_record, "w") as h:
                      h.write(slurm_job_id)
              else:
                  old_slurm_id = open(worker_record, "r").read()
                  logging.info(
                      f"old job slurm id {old_slurm_id} and current job id:"
                      f" {slurm_job_id}"
                  )
                  if old_slurm_id == slurm_job_id:
                      if os.path.getsize(Ifn) == 0:
                          logging.info(
                              f"cleaning up zero length files {Ifn} and"
                              f" {Dfn}"
                          )
                          os.remove(Ifn)
                          os.remove(Dfn)
  
          try:  # TODO: modify shape for pretransform case
              with open(Ifn, "xb") as f, open(Dfn, "xb") as g:
                  xq_i = np.empty(
                      shape=(self.xq_bs, self.input_d), dtype=np.float16
                  )
                  q_assign = np.empty(
                      (self.xq_bs, self.nprobe), dtype=np.int32
                  )
                  j = 0
                  quantizer = faiss.index_cpu_to_all_gpus(
                      index_ivf.quantizer
                  )
                  for xq_i_j in tqdm(
                      self._iterate_transformed(
                          self.xq_ds,
                          i,
                          min(100_000, self.xq_bs),
                          np.float16,
                      ),
                      file=sys.stdout,
                  ):
                      xq_i[j : j + xq_i_j.shape[0]] = xq_i_j
                      (
                          _,
                          q_assign[j : j + xq_i_j.shape[0]],
                      ) = quantizer.search(xq_i_j, self.nprobe)
                      j += xq_i_j.shape[0]
                      assert j <= xq_i.shape[0]
                      if j == xq_i.shape[0]:
                          break
                  xq_i = xq_i[:j]
                  q_assign = q_assign[:j]
  
                  assert q_assign.shape == (
                      xq_i.shape[0],
                      index_ivf.nprobe,
                  )
                  del quantizer
                  logging.info(f"computing: {Ifn}")
                  logging.info(f"computing: {Dfn}")
                  prefetch_threads = faiss.get_num_gpus()
                  D_ann, I = big_batch_search(
                      index_ivf,
                      xq_i,
                      self.k,
                      verbose=10,
                      method="knn_function",
                      knn=self._knn_function,
                      threaded=faiss.get_num_gpus() * 8,
                      use_float16=True,
                      prefetch_threads=prefetch_threads,
                      computation_threads=faiss.get_num_gpus(),
                      q_assign=q_assign,
                      checkpoint=CPfn,
                      checkpoint_freq=7200,  # in seconds
                  )
                  assert (
                      np.amin(I) >= 0
                  ), f"{I}, there exists negative indices, check"
                  logging.info(f"saving: {Ifn}")
                  np.save(f, I)
                  logging.info(f"saving: {Dfn}")
                  np.save(g, D_ann)
  
                  if os.path.exists(CPfn):
                      logging.info(f"removing: {CPfn}")
                      os.remove(CPfn)
  
          except FileExistsError:
              logging.info(f"skipping {Ifn}, already exists")
              logging.info(f"skipping {Dfn}, already exists")
              continue
  
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 17 for calling the OfflineIVF obj's underlying member method code with example usage: obj.search() without return types