Auto.ML: Fix issue when parsing float string fails on pl-PL culture set using Regression Experiment

src/Microsoft.ML.AutoML/Sweepers/Parameters.cs

@@ -83,7 +83,7 @@ public LongParameterValue(string name, long value)
         {
             _name = name;
             _value = value;
-            _valueText = _value.ToString("D");
+            _valueText = _value.ToString("D", CultureInfo.InvariantCulture);
         }
 
         public bool Equals(IParameterValue other)

src/Microsoft.ML.AutoML/Sweepers/SweeperProbabilityUtils.cs

@@ -4,6 +4,7 @@
 
 using System;
 using System.Collections.Generic;
+using System.Globalization;
 using Microsoft.ML.Internal.CpuMath;
 
 namespace Microsoft.ML.AutoML
@@ -98,13 +99,15 @@ public static float[] ParameterSetAsFloatArray(IValueGenerator[] sweepParams, Pa
                 }
                 else if (sweepParam is LongValueGenerator lvg)
                 {
+                    var longValue = GetIfIParameterValueOfT<long>(pset) ?? long.Parse(pset.ValueText, CultureInfo.InvariantCulture);
                     // Normalizing all numeric parameters to [0,1] range.
-                    result.Add(lvg.NormalizeValue(new LongParameterValue(pset.Name, long.Parse(pset.ValueText))));
+                    result.Add(lvg.NormalizeValue(new LongParameterValue(pset.Name, longValue)));
                 }
                 else if (sweepParam is FloatValueGenerator fvg)
                 {
+                    var floatValue = GetIfIParameterValueOfT<float>(pset) ?? float.Parse(pset.ValueText, CultureInfo.InvariantCulture);
                     // Normalizing all numeric parameters to [0,1] range.
-                    result.Add(fvg.NormalizeValue(new FloatParameterValue(pset.Name, float.Parse(pset.ValueText))));
+                    result.Add(fvg.NormalizeValue(new FloatParameterValue(pset.Name, floatValue)));
                 }
                 else
                 {
@@ -115,6 +118,10 @@ public static float[] ParameterSetAsFloatArray(IValueGenerator[] sweepParams, Pa
             return result.ToArray();
         }
 
+        private static T? GetIfIParameterValueOfT<T>(IParameterValue parameterValue)
+            where T : struct =>
+            parameterValue is IParameterValue<T> pvt ? pvt.Value : default(T?);
+
         public static ParameterSet FloatArrayAsParameterSet(IValueGenerator[] sweepParams, float[] array, bool expandedCategoricals = true)
         {
             Runtime.Contracts.Assert(array.Length == sweepParams.Length);

test/Microsoft.ML.AutoML.Tests/AutoFitTests.cs

@@ -2,7 +2,9 @@
 // The .NET Foundation licenses this file to you under the MIT license.
 // See the LICENSE file in the project root for more information.
 
+using System.Globalization;
 using System.Linq;
+using System.Threading;
 using Microsoft.ML.Data;
 using Microsoft.ML.TestFramework;
 using Microsoft.ML.TestFramework.Attributes;
@@ -102,9 +104,33 @@ private void Context_Log(object sender, LoggingEventArgs e)
             //throw new NotImplementedException();
         }
 
-        [Fact]
-        public void AutoFitRegressionTest()
+        [Theory]
+        [InlineData("en-US")]
+        [InlineData("ar-SA")]
+        [InlineData("pl-PL")]
+        public void AutoFitRegressionTest(string culture)
         {
+            var originalCulture = Thread.CurrentThread.CurrentCulture;
+            Thread.CurrentThread.CurrentCulture = new CultureInfo(culture);
+
+            uint experimentTime = 0;
+
+            if (culture == "ar-SA")
+            {
+                // If users run AutoML with a different local, sometimes
+                // the sweeper encounters problems when parsing some strings.
+                // So testing in another culture is necessary.
+                // Furthermore, these issues might only occur after several
+                // iterations, so more experiment time is needed for this to
+                // occur.
+                experimentTime = 30;
+
+            }
+            else if(culture == "pl-PL")
+            {
+                experimentTime = 100;
+            }
+
             var context = new MLContext(1);
             var dataPath = DatasetUtil.GetMlNetGeneratedRegressionDataset();
             var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.MlNetGeneratedRegressionLabel);
@@ -113,11 +139,13 @@ public void AutoFitRegressionTest()
             var validationData = context.Data.TakeRows(trainData, 20);
             trainData = context.Data.SkipRows(trainData, 20);
             var result = context.Auto()
-                .CreateRegressionExperiment(0)
+                .CreateRegressionExperiment(experimentTime)
                 .Execute(trainData, validationData,
                     new ColumnInformation() { LabelColumnName = DatasetUtil.MlNetGeneratedRegressionLabel });
 
             Assert.True(result.RunDetails.Max(i => i.ValidationMetrics.RSquared > 0.9));
+
+            Thread.CurrentThread.CurrentCulture = originalCulture;
         }
 
         [LightGBMFact]
@@ -351,4 +379,4 @@ private TextLoader.Options GetLoaderArgsRank(string labelColumnName, string grou
             };
         }
     }
-}
+}