code: def test_log_model_allowlist_from_url():
      allowlist_file_path = "https://raw.githubusercontent.com/mlflow/mlflow/v1.26.0/mlflow/pyspark/ml/log_model_allowlist.txt"
  
      with (
          SparkSession.builder.config(
              "spark.mlflow.pysparkml.autolog.logModelAllowlistFile",
              allowlist_file_path,
          )
          .master("local[*]")
          .getOrCreate()
      ):
          mlflow.pyspark.ml.autolog()
  
          assert mlflow.pyspark.ml._log_model_allowlist == {
              "pyspark.ml.classification.LinearSVCModel",
              "pyspark.ml.classification.DecisionTreeClassificationModel",
              "pyspark.ml.classification.GBTClassificationModel",
              "pyspark.ml.classification.LogisticRegressionModel",
              "pyspark.ml.classification.RandomForestClassificationModel",
              "pyspark.ml.classification.NaiveBayesModel",
              "pyspark.ml.clustering.BisectingKMeansModel",
              "pyspark.ml.clustering.KMeansModel",
              "pyspark.ml.clustering.GaussianMixtureModel",
              "pyspark.ml.regression.AFTSurvivalRegressionModel",
              "pyspark.ml.regression.DecisionTreeRegressionModel",
              "pyspark.ml.regression.GBTRegressionModel",
              "pyspark.ml.regression.GeneralizedLinearRegressionModel",
              "pyspark.ml.regression.LinearRegressionModel",
              "pyspark.ml.regression.RandomForestRegressionModel",
              "pyspark.ml.feature.BucketedRandomProjectionLSHModel",
              "pyspark.ml.feature.ChiSqSelectorModel",
              "pyspark.ml.feature.CountVectorizerModel",
              "pyspark.ml.feature.IDFModel",
              "pyspark.ml.feature.ImputerModel",
              "pyspark.ml.feature.MaxAbsScalerModel",
              "pyspark.ml.feature.MinHashLSHModel",
              "pyspark.ml.feature.MinMaxScalerModel",
              "pyspark.ml.feature.OneHotEncoderModel",
              "pyspark.ml.feature.RobustScalerModel",
              "pyspark.ml.feature.RFormulaModel",
              "pyspark.ml.feature.StandardScalerModel",
              "pyspark.ml.feature.StringIndexerModel",
              "pyspark.ml.feature.VarianceThresholdSelectorModel",
              "pyspark.ml.feature.VectorIndexerModel",
              "pyspark.ml.feature.UnivariateFeatureSelectorModel",
              "pyspark.ml.classification.OneVsRestModel",
              "pyspark.ml.pipeline.PipelineModel",
              "pyspark.ml.tuning.CrossValidatorModel",
              "pyspark.ml.tuning.TrainValidationSplitModel",
          }
  
imports: import os
  from pyspark.sql import SparkSession
  import mlflow
label_desc: Use image node_id 2 for calling a global function with example usage: test_log_model_allowlist_from_url() without return types