src/indicies/flat.py

import os
import json
import pickle
import faiss
import numpy as np
import torch

from src.indicies.index_utils import convert_pkl_to_jsonl, get_passage_pos_ids


os.environ["TOKENIZERS_PARALLELISM"] = "true"

device = "cuda" if torch.cuda.is_available() else "cpu"


class FlatIndexer(object):
    def __init__(
        self,
        index_path,
        meta_file,
        passage_dir=None,
        pos_map_save_path=None,
    ):
        self.index_path = index_path  # path to store the final index
        self.meta_file = meta_file  # path to save the index id to db id map
        self.passage_dir = passage_dir
        self.pos_map_save_path = pos_map_save_path
        self.cuda = False

        if os.path.exists(index_path) and os.path.exists(self.meta_file):
            print("Loading index...")
            self.index = faiss.read_index(index_path)
            self.index_id_to_db_id = self.load_index_id_to_db_id()
        else:
            raise NotImplementedError

        if self.pos_map_save_path is not None:
            self.psg_pos_id_map = self.load_psg_pos_id_map()

    def load_index_id_to_db_id(
        self,
    ):
        with open(self.meta_file, "rb") as reader:
            index_id_to_db_id = pickle.load(reader)
        return index_id_to_db_id

    def build_passage_pos_id_map(
        self,
    ):
        convert_pkl_to_jsonl(self.passage_dir)
        passage_pos_ids = get_passage_pos_ids(self.passage_dir, self.pos_map_save_path)
        return passage_pos_ids

    def load_psg_pos_id_map(
        self,
    ):
        if os.path.exists(self.pos_map_save_path):
            with open(self.pos_map_save_path, "rb") as f:
                psg_pos_id_map = pickle.load(f)
        else:
            psg_pos_id_map = self.build_passage_pos_id_map()
        return psg_pos_id_map

    def _id2psg(self, shard_id, chunk_id):
        filename, position = self.psg_pos_id_map[shard_id][chunk_id]
        with open(filename, "r") as file:
            file.seek(position)
            line = file.readline()
        return json.loads(line)

    def _get_passage(self, index_id):
        try:
            shard_id, chunk_id = self.index_id_to_db_id[index_id]
        except:
            shard_id, chunk_id = 0, self.index_id_to_db_id[index_id]
        return self._id2psg(shard_id, chunk_id)

    def get_retrieved_passages(self, all_indices):
        passages, db_ids = [], []
        for query_indices in all_indices:
            passages_per_query = [
                self._get_passage(int(index_id))["text"] for index_id in query_indices
            ]
            db_ids_per_query = [
                self.index_id_to_db_id[int(index_id)] for index_id in query_indices
            ]
            passages.append(passages_per_query)
            db_ids.append(db_ids_per_query)
        return passages, db_ids

    def search(self, query_embs, k=4096):
        all_scores, all_indices = self.index.search(query_embs.astype(np.float32), k)
        all_passages, db_ids = self.get_retrieved_passages(all_indices)
        return all_scores.tolist(), all_passages, db_ids