code: def test_rag_token_inference(self):
      rag_config = self.get_rag_config()
      rag_decoder_tokenizer = BartTokenizer.from_pretrained(
          "facebook/bart-large-cnn"
      )
      rag_question_encoder_tokenizer = (
          DPRQuestionEncoderTokenizer.from_pretrained(
              "facebook/dpr-question_encoder-single-nq-base"
          )
      )
      rag_retriever = RagRetriever(
          rag_config,
          question_encoder_tokenizer=rag_question_encoder_tokenizer,
          generator_tokenizer=rag_decoder_tokenizer,
      )
  
      rag_token = self.token_model
      rag_token.set_retriever(rag_retriever)
  
      input_ids = rag_question_encoder_tokenizer(
          "who sings does he love me with reba", return_tensors="pt"
      ).input_ids
      decoder_input_ids = rag_decoder_tokenizer(
          "Linda Davis", return_tensors="pt"
      ).input_ids
  
      input_ids = input_ids.to(torch_device)
      decoder_input_ids = decoder_input_ids.to(torch_device)
  
      with torch.no_grad():
          output = rag_token(
              input_ids,
              labels=decoder_input_ids,
          )
  
      expected_shape = torch.Size([5, 5, 50264])
      self.assertEqual(output.logits.shape, expected_shape)
  
      expected_doc_scores = torch.tensor(
          [[75.0286, 74.4998, 74.0804, 74.0306, 73.9504]]
      ).to(torch_device)
      _assert_tensors_equal(
          expected_doc_scores, output.doc_scores, atol=TOLERANCE
      )
  
      expected_loss = torch.tensor([36.3557]).to(torch_device)
      _assert_tensors_equal(expected_loss, output.loss, atol=TOLERANCE)
  
imports: import gc
  import json
  import os
  import shutil
  import tempfile
  import unittest
  from unittest.mock import patch
  import numpy
  from transformers import BartTokenizer, T5Tokenizer
  from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
  from transformers.models.dpr.tokenization_dpr import DPRContextEncoderTokenizer, DPRQuestionEncoderTokenizer
  from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
  from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, require_torch_non_multi_gpu, slow, torch_device
  from transformers.utils import cached_property, is_datasets_available, is_faiss_available, is_torch_available
  from ..bart.test_modeling_bart import BartModelTester
  from ..dpr.test_modeling_dpr import DPRModelTester
  from ..t5.test_modeling_t5 import T5ModelTester
label_desc: Use image node_id 6 for calling the RagModelIntegrationTests obj's underlying member method code with example usage: obj.test_rag_token_inference() without return types