TEST: increase timeout for gradient_boosted_classification (uxlfounda…

…tion#2118)

* [refactor] sort tests and fix typo in print statement

* increase timeout of gradient_boosted_classification to 240

tests/test_daal4py_examples.py

@@ -146,7 +146,7 @@ def run_test(self):
 
             duration_seconds = time.process_time() - start
             timeout_msg = (
-                "Runtime (in seconds too long). Test timeout. "
+                "Runtime (in seconds) too long. Test timeout. "
                 "Decrease workload or increase `timeout_cpu_seconds`"
             )
             self.assertLessEqual(
@@ -250,13 +250,14 @@ def low_order_moms_getter(result):
     Config("association_rules", "association_rules.csv", "confidence"),
     Config("bacon_outlier", "multivariate_outlier.csv", lambda r: r[1].weights),
     Config("brownboost", required_version=(2020, "P", 0)),
+    Config("cholesky", "cholesky.csv", "choleskyFactor"),
     Config(
         "correlation_distance", "correlation_distance.csv", correlation_distance_getter
     ),
     Config("cosine_distance", "cosine_distance.csv", cosine_distance_getter),
-    Config("cholesky", "cholesky.csv", "choleskyFactor"),
-    Config("covariance", "covariance.csv", "covariance"),
     Config("covariance_streaming", "covariance.csv", "covariance"),
+    Config("covariance", "covariance.csv", "covariance"),
+    Config("dbscan", "dbscan.csv", "assignments", (2019, "P", 5)),
     Config(
         "decision_forest_classification_default_dense",
         result_attribute=lambda r: r[1].prediction,
@@ -289,43 +290,43 @@ def low_order_moms_getter(result):
         "decision_tree_regression.csv",
         result_attribute=lambda r: r[1].prediction,
     ),
+    Config("elastic_net", required_version=((2020, "P", 1), (2021, "B", 105))),
     Config("em_gmm", "em_gmm.csv", lambda r: r.covariances[0]),
+    Config("gradient_boosted_classification", timeout_cpu_seconds=240),
     Config("implicit_als", "implicit_als.csv", "prediction"),
     Config("kdtree_knn_classification"),
     Config("kmeans", "kmeans.csv", "centroids"),
+    Config("lasso_regression", required_version=(2019, "P", 5)),
     Config("lbfgs_cr_entr_loss", "lbfgs_cr_entr_loss.csv", "minimum"),
     Config("lbfgs_mse", "lbfgs_mse.csv", "minimum"),
-    Config("linear_regression", "linear_regression.csv", lambda r: r[1].prediction),
     Config(
         "linear_regression_streaming", "linear_regression.csv", lambda r: r[1].prediction
     ),
+    Config("linear_regression", "linear_regression.csv", lambda r: r[1].prediction),
     Config("log_reg_binary_dense", "log_reg_binary_dense.csv", lambda r: r[1].prediction),
     Config("logitboost", required_version=(2020, "P", 0)),
     Config("low_order_moms_dense", "low_order_moms_dense.csv", low_order_moms_getter),
     Config("low_order_moms_streaming", "low_order_moms_dense.csv", low_order_moms_getter),
     Config("multivariate_outlier", "multivariate_outlier.csv", lambda r: r[1].weights),
-    Config("naive_bayes", "naive_bayes.csv", lambda r: r[0].prediction),
     Config("naive_bayes_streaming", "naive_bayes.csv", lambda r: r[0].prediction),
+    Config("naive_bayes", "naive_bayes.csv", lambda r: r[0].prediction),
     Config("normalization_minmax", "normalization_minmax.csv", "normalizedData"),
     Config("normalization_zscore", "normalization_zscore.csv", "normalizedData"),
-    Config("pca", "pca.csv", "eigenvectors"),
     Config("pca_transform", "pca_transform.csv", lambda r: r[1].transformedData),
+    Config("pca", "pca.csv", "eigenvectors"),
     Config("pivoted_qr", "pivoted_qr.csv", "matrixR"),
     Config("quantiles", "quantiles.csv", "quantiles"),
-    Config("ridge_regression", "ridge_regression.csv", lambda r: r[0].prediction),
     Config(
         "ridge_regression_streaming", "ridge_regression.csv", lambda r: r[0].prediction
     ),
+    Config("ridge_regression", "ridge_regression.csv", lambda r: r[0].prediction),
     Config("saga", required_version=(2019, "P", 3)),
     Config("sgd_logistic_loss", "sgd_logistic_loss.csv", "minimum"),
     Config("sgd_mse", "sgd_mse.csv", "minimum"),
     Config("stump_classification", required_version=(2020, "P", 0)),
     Config("stump_regression", required_version=(2020, "P", 0)),
     Config("svm_multiclass", "svm_multiclass.csv", lambda r: r[0].prediction),
     Config("univariate_outlier", "univariate_outlier.csv", lambda r: r[1].weights),
-    Config("dbscan", "dbscan.csv", "assignments", (2019, "P", 5)),
-    Config("lasso_regression", required_version=(2019, "P", 5)),
-    Config("elastic_net", required_version=((2020, "P", 1), (2021, "B", 105))),
 ]
 
 module_names_with_configs = [cfg.module_name for cfg in examples]