code: def test_catboost_quantile(fit_helper):
      fit_args = dict(
          hyperparameters={"CAT": {}},
          time_limit=10,  # CatBoost trains for a very long time on ames (many iterations)
      )
      dataset_name = "ames"
      init_args = dict(
          problem_type="quantile",
          quantile_levels=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],
      )
      fit_helper.fit_and_validate_dataset(
          dataset_name=dataset_name,
          fit_args=fit_args,
          init_args=init_args,
      )
  
imports: import sys
  import pytest
  from autogluon.tabular.models.catboost.catboost_model import CatBoostModel
label_desc: Use image node_id 4 for calling a global function with example usage: test_catboost_quantile(fit_helper) without return types