code: def test_tokens(self):
      model = Seq2SeqModel.from_config(
          Seq2SeqModel.Config(
              source_embedding=WordEmbedding.Config(embed_dim=512),
              target_embedding=WordEmbedding.Config(embed_dim=512),
          ),
          get_tensorizers(),
      )
      model.eval()
      ts_model = model.torchscriptify()
      res = ts_model(["call", "mom"])
      assert res is not None
  
imports: import unittest
  import torch
  from pytext.common.constants import Stage
  from pytext.data import Batcher
  from pytext.data.data import Data
  from pytext.data.sources.data_source import Gazetteer
  from pytext.data.sources.tsv import TSVDataSource
  from pytext.data.tensorizers import ByteTokenTensorizer, GazetteerTensorizer, initialize_tensorizers, TokenTensorizer
  from pytext.models.embeddings import ContextualTokenEmbedding, DictEmbedding, WordEmbedding
  from pytext.models.seq_models.rnn_encoder import LSTMSequenceEncoder
  from pytext.models.seq_models.rnn_encoder_decoder import RNNModel
  from pytext.models.seq_models.seq2seq_model import Seq2SeqModel
  from pytext.utils.test import import_tests_module
label_desc: Use image node_id 1 for calling the Seq2SeqModelExportTests obj's underlying member method code with example usage: obj.test_tokens() without return types