code: def test_interpret_works_with_custom_embedding_layer(self):
      inputs = {"sentence": "I always write unit tests for my code"}
      vocab = Vocabulary()
      vocab.add_tokens_to_namespace(
          [w for w in inputs["sentence"].split(" ")]
      )
      model = FakeModelForTestingInterpret(
          vocab, max_tokens=len(inputs["sentence"].split(" "))
      )
      predictor = FakePredictorForTestingInterpret(
          model, TextClassificationJsonReader()
      )
  
      hotflipper = Hotflip(predictor)
      hotflipper.initialize()
      attack = hotflipper.attack_from_json(
          inputs, "tokens", "grad_input_1"
      )
      assert attack is not None
      assert "final" in attack
      assert "original" in attack
      assert "outputs" in attack
      assert len(attack["final"][0]) == len(attack["original"])
  
file_path: allennlp/tests/interpret/hotflip_test.py
imports: from pytest import raises
  import torch
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.data.token_indexers import TokenCharactersIndexer
  from allennlp.interpret.attackers import Hotflip
  from allennlp.models.archival import load_archive
  from allennlp.modules.token_embedders import EmptyEmbedder
  from allennlp.predictors import Predictor, TextClassifierPredictor
  from allennlp.data.dataset_readers import TextClassificationJsonReader
  from allennlp.data.vocabulary import Vocabulary
  from allennlp.common.testing.interpret_test import FakeModelForTestingInterpret, FakePredictorForTestingInterpret
label_desc: Use image node_id 4 for calling the TestHotflip obj's underlying member method code with example usage: obj.test_interpret_works_with_custom_embedding_layer() without return types