code: def test_sequence_preproc_module_bad_tokenizer():
      metadata = {
          "preprocessing": {
              "lowercase": True,
              "tokenizer": "dutch_lemmatize",
              "unknown_symbol": "<UNK>",
              "padding_symbol": "<PAD>",
              "computed_fill_value": "<UNK>",
          },
          "max_sequence_length": SEQ_SIZE,
          "str2idx": {
              "<EOS>": 0,
              "<SOS>": 1,
              "<PAD>": 2,
              "<UNK>": 3,
              "▁hell": 4,
              "o": 5,
              "▁world": 6,
          },
      }
  
      with pytest.raises(ValueError):
          _SequencePreprocessing(metadata)
  
imports: from typing import List, Tuple
  import numpy
  import pytest
  import torch
  import torchtext
  from ludwig.constants import ENCODER_OUTPUT, LAST_HIDDEN, LOGITS, SEQUENCE, TEXT, TYPE
  from ludwig.features.sequence_feature import _SequencePreprocessing, SequenceInputFeature, SequenceOutputFeature
  from ludwig.features.text_feature import TextInputFeature, TextOutputFeature
  from ludwig.schema.features.sequence_feature import SequenceInputFeatureConfig, SequenceOutputFeatureConfig
  from ludwig.schema.features.text_feature import ECDTextInputFeatureConfig, ECDTextOutputFeatureConfig
  from ludwig.utils.torch_utils import get_torch_device
  from tests.integration_tests.utils import ENCODERS, sequence_feature
label_desc: Use image node_id 4 for calling a global function with example usage: test_sequence_preproc_module_bad_tokenizer() without return types