code: def test_boosting_type_null_invalid(
      tree_learner, tmpdir, local_backend
  ):
      """Test that the null boosting type is disabled.
  
      `boosting_type: null` defaults to "gbdt", and it was removed to avoid confusing GBM trainer settings.
      """
      input_features = [number_feature()]
      output_features = [binary_feature()]
  
      with pytest.raises(ConfigValidationError):
          _train_and_predict_gbm(
              input_features,
              output_features,
              tmpdir,
              local_backend,
              boosting_type=None,
              tree_learner=tree_learner,
          )
  
imports: import os
  import numpy
  import pytest
  from ludwig.api import LudwigModel
  from ludwig.constants import INPUT_FEATURES, MODEL_TYPE, OUTPUT_FEATURES, TRAINER
  from ludwig.error import ConfigValidationError
  from ludwig.schema.model_types.base import ModelConfig
  from tests.integration_tests import synthetic_test_data
  from tests.integration_tests.utils import binary_feature
  from tests.integration_tests.utils import category_feature
  from tests.integration_tests.utils import generate_data, number_feature, text_feature
label_desc: Use image node_id 25 for calling a global function with example usage: test_boosting_type_null_invalid(tree_learner, tmpdir, local_backend) without return types