code: def test_non_smallvocab_non_target_auto_mode(self):
      priming_data = generate_sentences(2, 6, vocab_size=101)
      test_data = random.sample(priming_data, len(priming_data) // 5)
  
      enc = ShortTextEncoder(is_target=False)
      enc.prepare(priming_data)
  
      assert enc.is_target is False
  
      # _combine is expected to be 'mean' when is_target is False
      assert enc._mode == "mean"
  
      encoded_data = enc.encode(test_data)
  
      assert len(test_data) == len(encoded_data)
  
      with self.assertRaises(ValueError):
          enc.decode(encoded_data)
  
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 4 for calling the TestShortTextEncoder obj's underlying member method code with example usage: obj.test_non_smallvocab_non_target_auto_mode() without return types