Auto.ML: Fix issue when parsing float string fails on pl-PL culture s…

…et using Regression Experiment (#5163)

* Fix issue when parsing float string fails on pl-PL culture set

* Added InvariantCulture float parsing as per CodeReview request

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

Co-authored-by: Justin Ormont <justinormont@users.noreply.github.com>

* Update Parameters.cs

* Added PL test

* Added multiple cultures

* debugging CI failure

* Debug runSpecific

* Revert "Debug runSpecific"

This reverts commit 95b7280.

* Removed LightGBM and addressed comments

* Increased time

* Increase time

* Increased time

Co-authored-by: Justin Ormont <justinormont@users.noreply.github.com>
Co-authored-by: Antonio Velazquez <anvelazq@microsoft.com>

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 +2,10 @@
 // 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;
+using System.Globalization;
 using System.Linq;
+using System.Threading;
 using Microsoft.ML.Data;
 using Microsoft.ML.TestFramework;
 using Microsoft.ML.TestFramework.Attributes;
@@ -102,22 +105,55 @@ 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 context = new MLContext(1);
-            var dataPath = DatasetUtil.GetMlNetGeneratedRegressionDataset();
-            var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.MlNetGeneratedRegressionLabel);
-            var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions);
-            var trainData = textLoader.Load(dataPath);
-            var validationData = context.Data.TakeRows(trainData, 20);
-            trainData = context.Data.SkipRows(trainData, 20);
-            var result = context.Auto()
-                .CreateRegressionExperiment(0)
-                .Execute(trainData, validationData,
-                    new ColumnInformation() { LabelColumnName = DatasetUtil.MlNetGeneratedRegressionLabel });
+            var originalCulture = Thread.CurrentThread.CurrentCulture;
+            try
+            {
+                Thread.CurrentThread.CurrentCulture = new CultureInfo(culture);
+
+                // If users run AutoML with a different locale, sometimes
+                // the sweeper encounters problems when parsing some strings.
+                // So testing in another culture is necessary.
+                // Furthermore, these issues might only occur after ~70
+                // iterations, so more experiment time is needed for this to
+                // occur.
+                uint experimentTime = (uint) (culture == "en-US" ? 0 : 180);
+
+                var experimentSettings = new RegressionExperimentSettings { MaxExperimentTimeInSeconds = experimentTime};
+                if (!Environment.Is64BitProcess)
+                {
+                    // LightGBM isn't available on x86 machines
+                    experimentSettings.Trainers.Remove(RegressionTrainer.LightGbm);
+                }
+
+                var context = new MLContext(1);
+                var dataPath = DatasetUtil.GetMlNetGeneratedRegressionDataset();
+                var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.MlNetGeneratedRegressionLabel);
+                var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions);
+                var trainData = textLoader.Load(dataPath);
+                var validationData = context.Data.TakeRows(trainData, 20);
+                trainData = context.Data.SkipRows(trainData, 20);
+                var result = context.Auto()
+                    .CreateRegressionExperiment(experimentSettings)
+                    .Execute(trainData, validationData,
+                        new ColumnInformation() { LabelColumnName = DatasetUtil.MlNetGeneratedRegressionLabel });
+
+                Assert.True(result.RunDetails.Max(i => i.ValidationMetrics.RSquared > 0.9));
+
+                // Ensure experimentTime allows enough iterations to fully test the internationalization code
+                // If the below assertion fails, increase the experiment time so the number of iterations is met
+                Assert.True(culture == "en-US" || result.RunDetails.Count() >= 75, $"RunDetails.Count() = {result.RunDetails.Count()}, below 75");
 
-            Assert.True(result.RunDetails.Max(i => i.ValidationMetrics.RSquared > 0.9));
+            }
+            finally
+            {
+                Thread.CurrentThread.CurrentCulture = originalCulture;
+            }
         }
 
         [LightGBMFact]
@@ -351,4 +387,4 @@ private TextLoader.Options GetLoaderArgsRank(string labelColumnName, string grou
             };
         }
     }
-}
+}