code: def _get_tensorizers(self):
      schema = {"source_sequence": str, "target_sequence": str}
      data_source = TSVDataSource.from_config(
          TSVDataSource.Config(
              train_filename=tests_module.test_file(
                  "compositional_seq2seq_unit.tsv"
              ),
              field_names=["source_sequence", "target_sequence"],
          ),
          schema,
      )
      src_tensorizer = TokenTensorizer.from_config(
          TokenTensorizer.Config(
              column="source_sequence",
              add_eos_token=True,
              add_bos_token=True,
          )
      )
      tgt_tensorizer = TokenTensorizer.from_config(
          TokenTensorizer.Config(
              column="target_sequence",
              add_eos_token=True,
              add_bos_token=True,
          )
      )
      tensorizers = {
          "src_seq_tokens": src_tensorizer,
          "trg_seq_tokens": tgt_tensorizer,
      }
      initialize_tensorizers(tensorizers, data_source.train)
      return tensorizers
  
file_path: pytext/pytext/models/test/scripted_seq2seq_generator_test.py
imports: import unittest
  import numpy
  import torch
  from pytext.data.sources.tsv import TSVDataSource
  from pytext.data.tensorizers import initialize_tensorizers, TokenTensorizer
  from pytext.models.embeddings.word_embedding import WordEmbedding
  from pytext.models.seq_models.seq2seq_model import Seq2SeqModel
  from pytext.torchscript.seq2seq.scripted_seq2seq_generator import ScriptedSequenceGenerator
  from pytext.utils.test import import_tests_module
label_desc: Use image node_id 1 for calling the ScriptedSeq2SeqGeneratorTest obj's underlying member method code with example usage: obj._get_tensorizers() and returns: tensorizers