class_docstr: Top-Level Indexer.
  
  Provides an interface for interacting with FAISS Indexes.
docstr: Given array of query vectors, return the vectors used for search.
  
  Allows subclasses to modify the vectors at their discretion.
  
  :param query_vectors:
      q vecs to modify
  
  :return search vectors:
      return vectors used for FAISS.
docstr_tok: ["Given","array","of","query","vectors",",","return","the","vectors","used","for","search",".","Allows","subclasses","to","modify","the","vectors","at","their","discretion",".",":","param","query_vectors",":","q","vecs","to","modify",":","return","search","vectors",":","return","vectors","used","for","FAISS","."]
code: def get_search_vectors(self, query_vectors: np.array) -> np.array:
      """
      Given array of query vectors, return the vectors used for search.
  
      Allows subclasses to modify the vectors at their discretion.
  
      :param query_vectors:
          q vecs to modify
  
      :return search vectors:
          return vectors used for FAISS.
      """
      return query_vectors
  
imports: from parlai.core.build_data import modelzoo_path
  from parlai.core.opt import Opt
  import parlai.utils.logging
  from abc import ABC, abstractmethod
  import math
  import numpy
  import os
  import random
  import time
  import torch
  import torch.cuda
  from typing import List, Tuple, Optional
  from parlai.agents.rag.args import WIKIPEDIA_COMPRESSED_INDEX, WIKIPEDIA_EXACT_INDEX
label_desc: Use image node_id 3 for calling the BaseIndexer obj's underlying member method code with example usage: obj.get_search_vectors(query_vectors) and returns: query_vectors