code: def test_quantile():
      quantile_levels = [0.01, 0.02, 0.05, 0.98, 0.99]
      dataset = {
          "url": "https://autogluon.s3.amazonaws.com/datasets/toyRegression.zip",
          "name": "toyRegression",
          "problem_type": QUANTILE,
          "label": "y",
      }
      directory_prefix = "./datasets/"
      train_file = "train_data.csv"
      test_file = "test_data.csv"
      train_data, test_data = load_data(
          directory_prefix=directory_prefix,
          train_file=train_file,
          test_file=test_file,
          name=dataset["name"],
          url=dataset["url"],
      )
      print(f"Evaluating Benchmark Dataset {dataset['name']}")
      directory = directory_prefix + dataset["name"] + "/"
      savedir = directory + "AutogluonOutput/"
      shutil.rmtree(
          savedir, ignore_errors=True
      )  # Delete AutoGluon output directory to ensure previous runs' information has been removed.
      fit_args = {"time_limit": 40}
      predictor = TabularPredictor(
          label=dataset["label"],
          path=savedir,
          problem_type=dataset["problem_type"],
          quantile_levels=quantile_levels,
      ).fit(train_data, **fit_args)
      ldr = predictor.leaderboard(test_data)
      perf = predictor.evaluate(test_data)
  
imports: import os
  import shutil
  import sys
  import tempfile
  import warnings
  from random import seed
  import numpy
  import pandas
  import pytest
  from networkx.exception import NetworkXError
  from autogluon.common import space
  from autogluon.common.utils.simulation_utils import convert_simulation_artifacts_to_tabular_predictions_dict
  from autogluon.core.constants import BINARY, MULTICLASS, PROBLEM_TYPES_CLASSIFICATION, QUANTILE, REGRESSION
  from autogluon.core.utils import download, unzip
  from autogluon.tabular import TabularDataset, TabularPredictor
  from autogluon.tabular.configs.hyperparameter_configs import get_hyperparameter_config
label_desc: Use image node_id 19 for calling a global function with example usage: test_quantile() without return types