class_docstr: Dense index using Faiss. It is used to index vectors.
  Faiss is a library for efficient similarity search and clustering of dense vectors.
  It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM.
  You can find more information about Faiss here:
  - For index types and the string factory: https://github.com/facebookresearch/faiss/wiki/The-index-factory
  - For GPU settings: https://github.com/facebookresearch/faiss/wiki/Faiss-on-the-GPU
class_docstr_tok: ["Dense","index","using","Faiss",".","It","is","used","to","index","vectors",".","Faiss","is","a","library","for","efficient","similarity","search","and","clustering","of","dense","vectors",".","It","contains","algorithms","that","search","in","sets","of","vectors","of","any","size",",","up","to","ones","that","possibly","do","not","fit","in","RAM",".","You","can","find","more","information","about","Faiss","here",":","-","For","index","types","and","the","string","factory",":","https",":","\/\/github.com\/facebookresearch\/faiss\/wiki\/The-index-factory","-","For","GPU","settings",":","https",":","\/\/github.com\/facebookresearch\/faiss\/wiki\/Faiss-on-the-GPU"]
docstr: Deserialize the FaissIndex from disk
docstr_tok: ["Deserialize","the","FaissIndex","from","disk"]
code: def load(
      cls,
      file: Union[str, PurePath],
      device: Optional[Union[int, List[int]]] = None,
      storage_options: Optional[Dict] = None,
  ) -> "FaissIndex":
      """Deserialize the FaissIndex from disk"""
      import faiss  # noqa: F811
  
      # Instances of FaissIndex is essentially just a wrapper for faiss indices.
      faiss_index = cls(device=device)
      with fsspec.open(str(file), "rb", **(storage_options or {})) as f:
          index = faiss.read_index(
              faiss.BufferedIOReader(faiss.PyCallbackIOReader(f.read))
          )
      faiss_index.faiss_index = faiss_index._faiss_index_to_device(
          index, faiss_index.device
      )
      return faiss_index
  
imports: import importlib.util
  import os
  import tempfile
  from pathlib import PurePath
  from typing import TYPE_CHECKING, Dict, List, NamedTuple, Optional, Union
  import fsspec
  import numpy
  from .utils import logging
  from .utils import tqdm
label_desc: Use image node_id 7 for calling the FaissIndex obj's underlying member method code with example usage: obj.load(cls, file, device, storage_options) and returns: faiss_index