code: def store_many_vectors(self, vs, data=None):
          
          # We will store the normalized vector (used during retrieval)
          nvs = [unitvec(i) for i in vs]
          # Store vector in each bucket of all hashes
          for lshash in self.lshashes:
              bucket_keys = [lshash.hash_vector(i)[0] for i in vs]
              self.storage.store_many_vectors(lshash.hash_name, bucket_keys,
                                              nvs, data)
docs: Store a batch of vectors.
          Hashes vector vs and stores them in all matching buckets in the storage.
          The data argument must be either None or a list of JSON-serializable
          object. It is stored with the vector and will be returned in search
          results.