docstr: Train index.
docstr_tok: ["Train","index","."]
code: def train(self):
      """Train index."""
  
      # Single process only.
      if torch.distributed.get_rank() == 0:
          self._train()
  
      torch.distributed.barrier()
  
file_path: megatron-lm/tools/retro/index/indexes/faiss_base.py
imports: from datetime import timedelta
  import numpy
  import os
  import torch
  from tqdm import tqdm
  from megatron import get_retro_args, print_rank_0
  from tools.bert_embedding import BertEmbedder
  from tools.retro.external_libs import faiss
  from tools.retro.index.index import Index
  from tools.retro.index.utils import get_training_data_merged_path, num_samples_to_block_ranges
label_desc: Use image node_id 2 for calling the FaissBaseIndex obj's underlying member method code with example usage: obj.train() without return types