code: def test_smallvocab_target_auto_mode(self):
      priming_data = generate_sentences(2, 6, vocab_size=99)
      test_data = random.sample(priming_data, len(priming_data) // 5)
  
      enc = ShortTextEncoder(is_target=True)
      enc.prepare(priming_data)
  
      assert enc.is_target is True
  
      # _combine is expected to be 'concat' when is_target is True
      assert enc._mode == "concat"
  
      encoded_data = enc.encode(test_data)
      decoded_data = enc.decode(encoded_data)
  
      assert len(test_data) == len(encoded_data) == len(decoded_data)
  
      for x_sent, y_sent in zip(
          [" ".join(tokenize_text(x)) for x in test_data],
          [" ".join(x) for x in decoded_data],
      ):
          assert x_sent == y_sent
  
file_path: lightwood/tests/unit_tests/encoder/text/test_short.py
imports: import random
  import unittest
  from lightwood.encoder.text.short import ShortTextEncoder
  from type_infer.rule_based.helpers import tokenize_text
  import torch
label_desc: Use image node_id 1 for calling the TestShortTextEncoder obj's underlying member method code with example usage: obj.test_smallvocab_target_auto_mode() without return types