code: def get_dummy_custom_hf_index_retriever(self, from_disk: bool):
      dataset = self.get_dummy_dataset()
      config = RagConfig(
          retrieval_vector_size=self.retrieval_vector_size,
          question_encoder=DPRConfig().to_dict(),
          generator=BartConfig().to_dict(),
          index_name="custom",
      )
      if from_disk:
          config.passages_path = os.path.join(
              self.tmpdirname, "dataset"
          )
          config.index_path = os.path.join(
              self.tmpdirname, "index.faiss"
          )
          dataset.get_index("embeddings").save(
              os.path.join(self.tmpdirname, "index.faiss")
          )
          dataset.drop_index("embeddings")
          dataset.save_to_disk(os.path.join(self.tmpdirname, "dataset"))
          del dataset
          retriever = RagRetriever(
              config,
              question_encoder_tokenizer=self.get_dpr_tokenizer(),
              generator_tokenizer=self.get_bart_tokenizer(),
          )
      else:
          retriever = RagRetriever(
              config,
              question_encoder_tokenizer=self.get_dpr_tokenizer(),
              generator_tokenizer=self.get_bart_tokenizer(),
              index=CustomHFIndex(
                  config.retrieval_vector_size, dataset
              ),
          )
      return retriever
  
imports: import json
  import os
  import shutil
  import tempfile
  from unittest import TestCase
  from unittest.mock import patch
  import numpy
  from datasets import Dataset
  from transformers import is_faiss_available
  from transformers.models.bart.configuration_bart import BartConfig
  from transformers.models.bart.tokenization_bart import BartTokenizer
  from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
  from transformers.models.dpr.configuration_dpr import DPRConfig
  from transformers.models.dpr.tokenization_dpr import DPRContextEncoderTokenizer, DPRQuestionEncoderTokenizer
  from transformers.models.rag.configuration_rag import RagConfig
  from transformers.models.rag.retrieval_rag import CustomHFIndex, RagRetriever
  from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
  from transformers.testing_utils import require_faiss, require_sentencepiece, require_tokenizers, require_torch
label_desc: Use image node_id 8 for calling the RagRetrieverTest obj's underlying member method code with example usage: obj.get_dummy_custom_hf_index_retriever(from_disk) and returns: retriever