code: def get_dummy_dataset(self):
      dataset = Dataset.from_dict(
          {
              "id": ["0", "1"],
              "text": ["foo", "bar"],
              "title": ["Foo", "Bar"],
              "embeddings": [
                  np.ones(self.retrieval_vector_size),
                  2 * np.ones(self.retrieval_vector_size),
              ],
          }
      )
      dataset.add_faiss_index(
          "embeddings",
          string_factory="Flat",
          metric_type=faiss.METRIC_INNER_PRODUCT,
      )
      return dataset
  
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 6 for calling the RagRetrieverTest obj's underlying member method code with example usage: obj.get_dummy_dataset() and returns: dataset