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Auto.ML: Fix issue when parsing float string fails on pl-PL culture set 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 <[email protected]> * 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 <[email protected]> Co-authored-by: Antonio Velazquez <[email protected]>
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‎src/Microsoft.ML.AutoML/Sweepers/Parameters.cs‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -83,7 +83,7 @@ public LongParameterValue(string name, long value)
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{
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_name = name;
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_value = value;
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_valueText = _value.ToString("D");
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_valueText = _value.ToString("D", CultureInfo.InvariantCulture);
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}
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public bool Equals(IParameterValue other)

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

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

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

Lines changed: 51 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,10 @@
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// The .NET Foundation licenses this file to you under the MIT license.
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// See the LICENSE file in the project root for more information.
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using System;
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using System.Globalization;
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using System.Linq;
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using System.Threading;
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using Microsoft.ML.Data;
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using Microsoft.ML.TestFramework;
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using Microsoft.ML.TestFramework.Attributes;
@@ -102,22 +105,55 @@ private void Context_Log(object sender, LoggingEventArgs e)
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//throw new NotImplementedException();
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}
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[Fact]
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public void AutoFitRegressionTest()
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[Theory]
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[InlineData("en-US")]
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[InlineData("ar-SA")]
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[InlineData("pl-PL")]
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public void AutoFitRegressionTest(string culture)
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{
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var context = new MLContext(1);
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var dataPath = DatasetUtil.GetMlNetGeneratedRegressionDataset();
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var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.MlNetGeneratedRegressionLabel);
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var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions);
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var trainData = textLoader.Load(dataPath);
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var validationData = context.Data.TakeRows(trainData, 20);
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trainData = context.Data.SkipRows(trainData, 20);
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var result = context.Auto()
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.CreateRegressionExperiment(0)
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.Execute(trainData, validationData,
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new ColumnInformation() { LabelColumnName = DatasetUtil.MlNetGeneratedRegressionLabel });
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var originalCulture = Thread.CurrentThread.CurrentCulture;
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try
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{
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Thread.CurrentThread.CurrentCulture = new CultureInfo(culture);
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// If users run AutoML with a different locale, sometimes
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// the sweeper encounters problems when parsing some strings.
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// So testing in another culture is necessary.
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// Furthermore, these issues might only occur after ~70
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// iterations, so more experiment time is needed for this to
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// occur.
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uint experimentTime = (uint) (culture == "en-US" ? 0 : 180);
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var experimentSettings = new RegressionExperimentSettings { MaxExperimentTimeInSeconds = experimentTime};
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if (!Environment.Is64BitProcess)
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{
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// LightGBM isn't available on x86 machines
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experimentSettings.Trainers.Remove(RegressionTrainer.LightGbm);
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}
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var context = new MLContext(1);
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var dataPath = DatasetUtil.GetMlNetGeneratedRegressionDataset();
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var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.MlNetGeneratedRegressionLabel);
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var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions);
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var trainData = textLoader.Load(dataPath);
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var validationData = context.Data.TakeRows(trainData, 20);
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trainData = context.Data.SkipRows(trainData, 20);
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var result = context.Auto()
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.CreateRegressionExperiment(experimentSettings)
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.Execute(trainData, validationData,
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new ColumnInformation() { LabelColumnName = DatasetUtil.MlNetGeneratedRegressionLabel });
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Assert.True(result.RunDetails.Max(i => i.ValidationMetrics.RSquared > 0.9));
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// Ensure experimentTime allows enough iterations to fully test the internationalization code
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// If the below assertion fails, increase the experiment time so the number of iterations is met
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Assert.True(culture == "en-US" || result.RunDetails.Count() >= 75, $"RunDetails.Count() = {result.RunDetails.Count()}, below 75");
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120-
Assert.True(result.RunDetails.Max(i => i.ValidationMetrics.RSquared > 0.9));
152+
}
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finally
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{
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Thread.CurrentThread.CurrentCulture = originalCulture;
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}
121157
}
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[LightGBMFact]
@@ -351,4 +387,4 @@ private TextLoader.Options GetLoaderArgsRank(string labelColumnName, string grou
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};
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}
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}
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}
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}

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