Improve exception msg by adding column name

src/Microsoft.ML.Data/Transforms/KeyToVector.cs

@@ -246,14 +246,28 @@ public Mapper(KeyToVectorMappingTransformer parent, DataViewSchema inputSchema)
                 _parent = parent;
                 _infos = CreateInfos(inputSchema);
                 _types = new VectorDataViewType[_parent.ColumnPairs.Length];
-                for (int i = 0; i < _parent.ColumnPairs.Length; i++)
+
+                // The following try catch block is designed to provide user a better exception message
+                // by providing related column name when some exceptions occur in VectorDataViewType()(e.g overflow)
+                // This change is related with https://github.com/dotnet/machinelearning/issues/5211
+                try
                 {
-                    int valueCount = _infos[i].TypeSrc.GetValueCount();
-                    int keyCount = _infos[i].TypeSrc.GetItemType().GetKeyCountAsInt32(Host);
-                    if (_parent._columns[i].OutputCountVector || valueCount == 1)
-                        _types[i] = new VectorDataViewType(NumberDataViewType.Single, keyCount);
-                    else
-                        _types[i] = new VectorDataViewType(NumberDataViewType.Single, valueCount, keyCount);
+                    for (int i = 0; i < _parent.ColumnPairs.Length; i++)
+                    {
+                        int valueCount = _infos[i].TypeSrc.GetValueCount();
+                        int keyCount = _infos[i].TypeSrc.GetItemType().GetKeyCountAsInt32(Host);
+                        if (_parent._columns[i].OutputCountVector || valueCount == 1)
+                            _types[i] = new VectorDataViewType(NumberDataViewType.Single, keyCount);
+                        else
+                            _types[i] = new VectorDataViewType(NumberDataViewType.Single, valueCount, keyCount);
+                    }
+                }
+                catch (Exception e)
+                {
+                    var errorMsg = e.Message + " Related column: ";
+                    foreach (var info in _infos)
+                        errorMsg += info.Name + " ";
+                    throw Host.Except(errorMsg);
                 }
             }
 

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

@@ -0,0 +1,72 @@
+// Licensed to the .NET Foundation under one or more agreements.
+// 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.IO;
+using Microsoft.ML.Data;
+using Microsoft.ML.TestFramework;
+using Xunit;
+using Xunit.Abstractions;
+
+namespace Microsoft.ML.AutoML.Test
+{
+
+    public class AutoMLFailureTests : BaseTestClass
+    {
+        public AutoMLFailureTests(ITestOutputHelper output) : base(output)
+        {
+        }
+
+        public class ModelInput
+        {
+            [ColumnName("Label"), LoadColumn(0)]
+            public int Label { get; set; }
+
+
+            [ColumnName("ProblematicColumn"), LoadColumn(1)]
+            public string ProblematicColumn { get; set; }
+
+        }
+
+        [Fact]
+        public void CrossValidationOverflowTest()
+        {
+            // This test is introduced for https://github.com/dotnet/machinelearning/issues/5211
+            // that provides users an informational exception message
+            MLContext mlContext = new MLContext(1);
+
+            IDataView trainingDataView = mlContext.Data.LoadFromTextFile<ModelInput>(
+                                            path: GetDataPath("cross_validation_overflow_dataset.txt"),
+                                            hasHeader: true,
+                                            separatorChar: '\t',
+                                            allowQuoting: true,
+                                            allowSparse: false);
+
+            IDataView testDataView = mlContext.Data.BootstrapSample(trainingDataView);
+
+            ExperimentResult<MulticlassClassificationMetrics> experimentResult = mlContext.Auto()
+                .CreateMulticlassClassificationExperiment(60)
+                .Execute(trainingDataView, labelColumnName: "Label");
+            RunDetail<MulticlassClassificationMetrics> bestRun = experimentResult.BestRun;
+            IDataView testDataViewWithBestScore = bestRun.Model.Transform(testDataView);
+
+            try
+            {
+                var testMetrics = mlContext.MulticlassClassification.CrossValidate(
+                                      testDataViewWithBestScore,
+                                      bestRun.Estimator,
+                                      numberOfFolds: 5,
+                                      labelColumnName: "Label");
+                Assert.True(false);
+            }
+            catch (System.Exception ex)
+            {
+                Assert.Contains("Arithmetic operation resulted in an overflow. Related column: ProblematicColumn", ex.Message);
+                return;
+            }
+
+        }
+    }
+}
+
+