[AutoML] AutoML SDK API: validate schema types of input IDataView#3597

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daholste merged 2 commits into from
Apr 26, 2019
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[AutoML] AutoML SDK API: validate schema types of input IDataView #3597

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AutoML API: validate schema types of input IDataView
daholste Apr 25, 2019
fda914e
rev error message
daholste Apr 26, 2019
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6 changes: 3 additions & 3 deletions src/Microsoft.ML.Auto/API/ExperimentBase.cs
View file
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Original file line numberDiff line numberDiff line change
Expand Up@@ -239,7 +239,7 @@ private ExperimentResult<TMetrics> ExecuteTrainValidate(IDataView trainData,
IProgress<RunDetail<TMetrics>> progressHandler)
{
columnInfo = columnInfo ?? new ColumnInformation();
UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData);
UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData, _task);

// Apply pre-featurizer
ITransformer preprocessorTransform = null;
Expand All@@ -263,7 +263,7 @@ private CrossValidationExperimentResult<TMetrics> ExecuteCrossVal(IDataView[] tr
IProgress<CrossValidationRunDetail<TMetrics>> progressHandler)
{
columnInfo = columnInfo ?? new ColumnInformation();
UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

// Apply pre-featurizer
ITransformer[] preprocessorTransforms = null;
Expand All@@ -290,7 +290,7 @@ private ExperimentResult<TMetrics> ExecuteCrossValSummary(IDataView[] trainDatas
IProgress<RunDetail<TMetrics>> progressHandler)
{
columnInfo = columnInfo ?? new ColumnInformation();
UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

// Apply pre-featurizer
ITransformer[] preprocessorTransforms = null;
Expand Down
48 changes: 39 additions & 9 deletions src/Microsoft.ML.Auto/Utils/UserInputValidationUtil.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,10 +22,10 @@ internal static class UserInputValidationUtil
private const string SamplingKeyColumnPurposeName = "sampling key";

public static void ValidateExperimentExecuteArgs(IDataView trainData, ColumnInformation columnInformation,
IDataView validationData)
IDataView validationData, TaskKind task)
{
ValidateTrainData(trainData);
ValidateColumnInformation(trainData, columnInformation);
ValidateTrainData(trainData, columnInformation);
ValidateColumnInformation(trainData, columnInformation, task);
ValidateValidationData(trainData, validationData);
}

Expand DownExpand Up@@ -54,24 +54,37 @@ public static void ValidateNumberOfCVFoldsArg(uint numberOfCVFolds)
}
}

private static void ValidateTrainData(IDataView trainData)
private static void ValidateTrainData(IDataView trainData, ColumnInformation columnInformation)
{
if (trainData == null)
{
throw new ArgumentNullException(nameof(trainData), "Training data cannot be null");
}

var type = trainData.Schema.GetColumnOrNull(DefaultColumnNames.Features)?.Type.GetItemType();
if (type != null && type != NumberDataViewType.Single)
foreach (var column in trainData.Schema)
{
throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type Single", nameof(trainData));
if (column.Name == DefaultColumnNames.Features && column.Type.GetItemType() != NumberDataViewType.Single)
{
throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type {NumberDataViewType.Single}", nameof(trainData));
}

if (column.Name != columnInformation.LabelColumnName &&
column.Type.GetItemType() != BooleanDataViewType.Instance &&
column.Type.GetItemType() != NumberDataViewType.Single &&
column.Type.GetItemType() != TextDataViewType.Instance)
{
throw new ArgumentException($"Only supported feature column types are " +
$"{BooleanDataViewType.Instance}, {NumberDataViewType.Single}, and {TextDataViewType.Instance}. " +
$"Please change the feature column {column.Name} of type {column.Type} to one of " +
$"the supported types.", nameof(trainData));
}
}
}

private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation)
private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation, TaskKind task)
{
ValidateColumnInformation(columnInformation);
ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName);
ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName, GetAllowedLabelTypes(task));
ValidateTrainDataColumn(trainData, columnInformation.ExampleWeightColumnName, WeightColumnPurposeName);
ValidateTrainDataColumn(trainData, columnInformation.SamplingKeyColumnName, SamplingKeyColumnPurposeName);
ValidateTrainDataColumns(trainData, columnInformation.CategoricalColumnNames, CategoricalColumnPurposeName,
Expand DownExpand Up@@ -228,5 +241,22 @@ private static string FindFirstDuplicate(IEnumerable<string> values)
var groups = values.GroupBy(v => v);
return groups.FirstOrDefault(g => g.Count() > 1)?.Key;
}

private static IEnumerable<DataViewType> GetAllowedLabelTypes(TaskKind task)
{
switch (task)
{
case TaskKind.BinaryClassification:
return new DataViewType[] { BooleanDataViewType.Instance };
// Multiclass label types are flexible, as we convert the label to a key type
// (if input label is not already a key) before invoking the trainer.
case TaskKind.MulticlassClassification:
return null;
case TaskKind.Regression:
return new DataViewType[] { NumberDataViewType.Single };
default:
throw new NotSupportedException($"Unsupported task type: {task}");
}
}
}
}
93 changes: 82 additions & 11 deletions test/Microsoft.ML.AutoML.Tests/UserInputValidationTests.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,23 +18,23 @@ public class UserInputValidationTests
[ExpectedException(typeof(ArgumentNullException))]
public void ValidateExperimentExecuteNullTrainData()
{
UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null);
UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null, TaskKind.Regression);
}

[TestMethod]
[ExpectedException(typeof(ArgumentException))]
public void ValidateExperimentExecuteNullLabel()
{
UserInputValidationUtil.ValidateExperimentExecuteArgs(Data,
new ColumnInformation() { LabelColumnName = null }, null);
new ColumnInformation() { LabelColumnName = null }, null, TaskKind.Regression);
}

[TestMethod]
[ExpectedException(typeof(ArgumentException))]
public void ValidateExperimentExecuteLabelNotInTrain()
{
UserInputValidationUtil.ValidateExperimentExecuteArgs(Data,
new ColumnInformation() { LabelColumnName = "L" }, null);
new ColumnInformation() { LabelColumnName = "L" }, null, TaskKind.Regression);
}

[TestMethod]
Expand All@@ -44,7 +44,7 @@ public void ValidateExperimentExecuteNumericColNotInTrain()
var columnInfo = new ColumnInformation();
columnInfo.NumericColumnNames.Add("N");

UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
}

[TestMethod]
Expand All@@ -53,7 +53,7 @@ public void ValidateExperimentExecuteNullNumericCol()
{
var columnInfo = new ColumnInformation();
columnInfo.NumericColumnNames.Add(null);
UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
}

[TestMethod]
Expand All@@ -63,7 +63,7 @@ public void ValidateExperimentExecuteDuplicateCol()
var columnInfo = new ColumnInformation();
columnInfo.NumericColumnNames.Add(DefaultColumnNames.Label);

UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
}

[TestMethod]
Expand All@@ -82,7 +82,7 @@ public void ValidateExperimentExecuteArgsTrainValidColCountMismatch()
var validData = validDataBuilder.GetDataView();

UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
new ColumnInformation() { LabelColumnName = "0" }, validData);
new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
}

[TestMethod]
Expand All@@ -102,7 +102,7 @@ public void ValidateExperimentExecuteArgsTrainValidColNamesMismatch()
var validData = validDataBuilder.GetDataView();

UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
new ColumnInformation() { LabelColumnName = "0" }, validData);
new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
}

[TestMethod]
Expand All@@ -122,7 +122,7 @@ public void ValidateExperimentExecuteArgsTrainValidColTypeMismatch()
var validData = validDataBuilder.GetDataView();

UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
new ColumnInformation() { LabelColumnName = "0" }, validData);
new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
}

[TestMethod]
Expand DownExpand Up@@ -163,7 +163,7 @@ public void ValidateFeaturesColInvalidType()
schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
var schema = schemaBuilder.ToSchema();
var dataView = new EmptyDataView(new MLContext(), schema);
UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null);
UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, TaskKind.Regression);
}

[TestMethod]
Expand All@@ -181,7 +181,78 @@ public void ValidateTextColumnNotText()
var columnInfo = new ColumnInformation();
columnInfo.NumericColumnNames.Add(TextPurposeColName);

UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null);
UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null, TaskKind.Regression);
}

[TestMethod]
public void ValidateRegressionLabelTypes()
{
ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Single, true);
ValidateLabelTypeTestCore(TaskKind.Regression, BooleanDataViewType.Instance, false);
ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Double, false);
ValidateLabelTypeTestCore(TaskKind.Regression, TextDataViewType.Instance, false);
}

[TestMethod]
public void ValidateBinaryClassificationLabelTypes()
{
ValidateLabelTypeTestCore(TaskKind.BinaryClassification, NumberDataViewType.Single, false);
ValidateLabelTypeTestCore(TaskKind.BinaryClassification, BooleanDataViewType.Instance, true);
}

[TestMethod]
public void ValidateMulticlassLabelTypes()
{
ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Single, true);
ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, BooleanDataViewType.Instance, true);
ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Double, true);
ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, TextDataViewType.Instance, true);
}

[TestMethod]
public void ValidateAllowedFeatureColumnTypes()
{
var schemaBuilder = new DataViewSchema.Builder();
schemaBuilder.AddColumn("Boolean", BooleanDataViewType.Instance);
schemaBuilder.AddColumn("Number", NumberDataViewType.Single);
schemaBuilder.AddColumn("Text", TextDataViewType.Instance);
schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
var schema = schemaBuilder.ToSchema();
var dataView = new EmptyDataView(new MLContext(), schema);
UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
null, TaskKind.Regression);
}

[TestMethod]
[ExpectedException(typeof(ArgumentException))]
public void ValidateProhibitedFeatureColumnType()
{
var schemaBuilder = new DataViewSchema.Builder();
schemaBuilder.AddColumn("UInt64", NumberDataViewType.UInt64);
schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
var schema = schemaBuilder.ToSchema();
var dataView = new EmptyDataView(new MLContext(), schema);
UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
null, TaskKind.Regression);
}

private static void ValidateLabelTypeTestCore(TaskKind task, DataViewType labelType, bool labelTypeShouldBeValid)
{
var schemaBuilder = new DataViewSchema.Builder();
schemaBuilder.AddColumn(DefaultColumnNames.Features, NumberDataViewType.Single);
schemaBuilder.AddColumn(DefaultColumnNames.Label, labelType);
var schema = schemaBuilder.ToSchema();
var dataView = new EmptyDataView(new MLContext(), schema);
var validationExceptionThrown = false;
try
{
UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, task);
}
catch
{
validationExceptionThrown = true;
}
Assert.AreEqual(labelTypeShouldBeValid, !validationExceptionThrown);
}
}
}
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 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
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[AutoML] AutoML SDK API: validate schema types of input IDataView#3597

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to your account

 Merged

daholste
merged 2 commits into

from

Apr 26, 2019
 Merged


[AutoML] AutoML SDK API: validate schema types of input IDataView
#3597
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52333e1

AutoML API: validate schema types of input IDataView


daholste Apr 25, 2019
fda914e

rev error message


daholste Apr 26, 2019

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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.Auto/API/ExperimentBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -239,7 +239,7 @@ private ExperimentResult<TMetrics> ExecuteTrainValidate(IDataView trainData,
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData, _task);

 // Apply pre-featurizer
 ITransformer preprocessorTransform = null;
Expand All@@ -263,7 +263,7 @@ private CrossValidationExperimentResult<TMetrics> ExecuteCrossVal(IDataView[] tr
 IProgress<CrossValidationRunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand All@@ -290,7 +290,7 @@ private ExperimentResult<TMetrics> ExecuteCrossValSummary(IDataView[] trainDatas
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand Down

48 changes: 39 additions & 9 deletions
src/Microsoft.ML.Auto/Utils/UserInputValidationUtil.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,10 +22,10 @@ internal static class UserInputValidationUtil
 private const string SamplingKeyColumnPurposeName = "sampling key";

 public static void ValidateExperimentExecuteArgs(IDataView trainData, ColumnInformation columnInformation,
 IDataView validationData)
 IDataView validationData, TaskKind task)
 {
 ValidateTrainData(trainData);
 ValidateColumnInformation(trainData, columnInformation);
 ValidateTrainData(trainData, columnInformation);
 ValidateColumnInformation(trainData, columnInformation, task);
 ValidateValidationData(trainData, validationData);
 }

Expand DownExpand Up@@ -54,24 +54,37 @@ public static void ValidateNumberOfCVFoldsArg(uint numberOfCVFolds)
 }
 }

 private static void ValidateTrainData(IDataView trainData)
 private static void ValidateTrainData(IDataView trainData, ColumnInformation columnInformation)
 {
 if (trainData == null)
 {
 throw new ArgumentNullException(nameof(trainData), "Training data cannot be null");
 }

 var type = trainData.Schema.GetColumnOrNull(DefaultColumnNames.Features)?.Type.GetItemType();
 if (type != null && type != NumberDataViewType.Single)
 foreach (var column in trainData.Schema)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type Single", nameof(trainData));
 if (column.Name == DefaultColumnNames.Features && column.Type.GetItemType() != NumberDataViewType.Single)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type {NumberDataViewType.Single}", nameof(trainData));
 }

 if (column.Name != columnInformation.LabelColumnName &&
 column.Type.GetItemType() != BooleanDataViewType.Instance &&
 column.Type.GetItemType() != NumberDataViewType.Single &&
 column.Type.GetItemType() != TextDataViewType.Instance)
 {
 throw new ArgumentException($"Only supported feature column types are " +
 $"{BooleanDataViewType.Instance}, {NumberDataViewType.Single}, and {TextDataViewType.Instance}. " +
 $"Please change the feature column {column.Name} of type {column.Type} to one of " +
 $"the supported types.", nameof(trainData));
 }
 }
 }

 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation)
 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation, TaskKind task)
 {
 ValidateColumnInformation(columnInformation);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName, GetAllowedLabelTypes(task));
 ValidateTrainDataColumn(trainData, columnInformation.ExampleWeightColumnName, WeightColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.SamplingKeyColumnName, SamplingKeyColumnPurposeName);
 ValidateTrainDataColumns(trainData, columnInformation.CategoricalColumnNames, CategoricalColumnPurposeName,
Expand DownExpand Up@@ -228,5 +241,22 @@ private static string FindFirstDuplicate(IEnumerable<string> values)
 var groups = values.GroupBy(v => v);
 return groups.FirstOrDefault(g => g.Count() > 1)?.Key;
 }

 private static IEnumerable<DataViewType> GetAllowedLabelTypes(TaskKind task)
 {
 switch (task)
 {
 case TaskKind.BinaryClassification:
 return new DataViewType[] { BooleanDataViewType.Instance };
 // Multiclass label types are flexible, as we convert the label to a key type
 // (if input label is not already a key) before invoking the trainer.
 case TaskKind.MulticlassClassification:
 return null;
 case TaskKind.Regression:
 return new DataViewType[] { NumberDataViewType.Single };
 default:
 throw new NotSupportedException($"Unsupported task type: {task}");
 }
 }
 }
}

93 changes: 82 additions & 11 deletions
test/Microsoft.ML.AutoML.Tests/UserInputValidationTests.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,23 +18,23 @@ public class UserInputValidationTests
 [ExpectedException(typeof(ArgumentNullException))]
 public void ValidateExperimentExecuteNullTrainData()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteNullLabel()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, 
 new ColumnInformation() { LabelColumnName = null }, null);
 new ColumnInformation() { LabelColumnName = null }, null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteLabelNotInTrain()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data,
 new ColumnInformation() { LabelColumnName = "L" }, null);
 new ColumnInformation() { LabelColumnName = "L" }, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -44,7 +44,7 @@ public void ValidateExperimentExecuteNumericColNotInTrain()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add("N");

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -53,7 +53,7 @@ public void ValidateExperimentExecuteNullNumericCol()
 {
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -63,7 +63,7 @@ public void ValidateExperimentExecuteDuplicateCol()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(DefaultColumnNames.Label);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -82,7 +82,7 @@ public void ValidateExperimentExecuteArgsTrainValidColCountMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, 
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -102,7 +102,7 @@ public void ValidateExperimentExecuteArgsTrainValidColNamesMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -122,7 +122,7 @@ public void ValidateExperimentExecuteArgsTrainValidColTypeMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand DownExpand Up@@ -163,7 +163,7 @@ public void ValidateFeaturesColInvalidType()
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -181,7 +181,78 @@ public void ValidateTextColumnNotText()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(TextPurposeColName);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
 public void ValidateRegressionLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.Regression, BooleanDataViewType.Instance, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Double, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, TextDataViewType.Instance, false);
 }

 [TestMethod]
 public void ValidateBinaryClassificationLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, NumberDataViewType.Single, false);
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, BooleanDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateMulticlassLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, BooleanDataViewType.Instance, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Double, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, TextDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateAllowedFeatureColumnTypes()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("Boolean", BooleanDataViewType.Instance);
 schemaBuilder.AddColumn("Number", NumberDataViewType.Single);
 schemaBuilder.AddColumn("Text", TextDataViewType.Instance);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateProhibitedFeatureColumnType()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("UInt64", NumberDataViewType.UInt64);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 private static void ValidateLabelTypeTestCore(TaskKind task, DataViewType labelType, bool labelTypeShouldBeValid)
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn(DefaultColumnNames.Features, NumberDataViewType.Single);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, labelType);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 var validationExceptionThrown = false;
 try
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, task);
 }
 catch
 {
 validationExceptionThrown = true;
 }
 Assert.AreEqual(labelTypeShouldBeValid, !validationExceptionThrown);
 }
 }
}

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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[AutoML] AutoML SDK API: validate schema types of input IDataView#3597

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daholste
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Apr 26, 2019
 Merged


[AutoML] AutoML SDK API: validate schema types of input IDataView
#3597
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52333e1

AutoML API: validate schema types of input IDataView


daholste Apr 25, 2019
fda914e

rev error message


daholste Apr 26, 2019

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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.Auto/API/ExperimentBase.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -239,7 +239,7 @@ private ExperimentResult<TMetrics> ExecuteTrainValidate(IDataView trainData,
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData, _task);

 // Apply pre-featurizer
 ITransformer preprocessorTransform = null;
Expand All@@ -263,7 +263,7 @@ private CrossValidationExperimentResult<TMetrics> ExecuteCrossVal(IDataView[] tr
 IProgress<CrossValidationRunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand All@@ -290,7 +290,7 @@ private ExperimentResult<TMetrics> ExecuteCrossValSummary(IDataView[] trainDatas
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand Down

48 changes: 39 additions & 9 deletions
src/Microsoft.ML.Auto/Utils/UserInputValidationUtil.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,10 +22,10 @@ internal static class UserInputValidationUtil
 private const string SamplingKeyColumnPurposeName = "sampling key";

 public static void ValidateExperimentExecuteArgs(IDataView trainData, ColumnInformation columnInformation,
 IDataView validationData)
 IDataView validationData, TaskKind task)
 {
 ValidateTrainData(trainData);
 ValidateColumnInformation(trainData, columnInformation);
 ValidateTrainData(trainData, columnInformation);
 ValidateColumnInformation(trainData, columnInformation, task);
 ValidateValidationData(trainData, validationData);
 }

Expand DownExpand Up@@ -54,24 +54,37 @@ public static void ValidateNumberOfCVFoldsArg(uint numberOfCVFolds)
 }
 }

 private static void ValidateTrainData(IDataView trainData)
 private static void ValidateTrainData(IDataView trainData, ColumnInformation columnInformation)
 {
 if (trainData == null)
 {
 throw new ArgumentNullException(nameof(trainData), "Training data cannot be null");
 }

 var type = trainData.Schema.GetColumnOrNull(DefaultColumnNames.Features)?.Type.GetItemType();
 if (type != null && type != NumberDataViewType.Single)
 foreach (var column in trainData.Schema)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type Single", nameof(trainData));
 if (column.Name == DefaultColumnNames.Features && column.Type.GetItemType() != NumberDataViewType.Single)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type {NumberDataViewType.Single}", nameof(trainData));
 }

 if (column.Name != columnInformation.LabelColumnName &&
 column.Type.GetItemType() != BooleanDataViewType.Instance &&
 column.Type.GetItemType() != NumberDataViewType.Single &&
 column.Type.GetItemType() != TextDataViewType.Instance)
 {
 throw new ArgumentException($"Only supported feature column types are " +
 $"{BooleanDataViewType.Instance}, {NumberDataViewType.Single}, and {TextDataViewType.Instance}. " +
 $"Please change the feature column {column.Name} of type {column.Type} to one of " +
 $"the supported types.", nameof(trainData));
 }
 }
 }

 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation)
 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation, TaskKind task)
 {
 ValidateColumnInformation(columnInformation);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName, GetAllowedLabelTypes(task));
 ValidateTrainDataColumn(trainData, columnInformation.ExampleWeightColumnName, WeightColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.SamplingKeyColumnName, SamplingKeyColumnPurposeName);
 ValidateTrainDataColumns(trainData, columnInformation.CategoricalColumnNames, CategoricalColumnPurposeName,
Expand DownExpand Up@@ -228,5 +241,22 @@ private static string FindFirstDuplicate(IEnumerable<string> values)
 var groups = values.GroupBy(v => v);
 return groups.FirstOrDefault(g => g.Count() > 1)?.Key;
 }

 private static IEnumerable<DataViewType> GetAllowedLabelTypes(TaskKind task)
 {
 switch (task)
 {
 case TaskKind.BinaryClassification:
 return new DataViewType[] { BooleanDataViewType.Instance };
 // Multiclass label types are flexible, as we convert the label to a key type
 // (if input label is not already a key) before invoking the trainer.
 case TaskKind.MulticlassClassification:
 return null;
 case TaskKind.Regression:
 return new DataViewType[] { NumberDataViewType.Single };
 default:
 throw new NotSupportedException($"Unsupported task type: {task}");
 }
 }
 }
}

93 changes: 82 additions & 11 deletions
test/Microsoft.ML.AutoML.Tests/UserInputValidationTests.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -18,23 +18,23 @@ public class UserInputValidationTests
 [ExpectedException(typeof(ArgumentNullException))]
 public void ValidateExperimentExecuteNullTrainData()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteNullLabel()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, 
 new ColumnInformation() { LabelColumnName = null }, null);
 new ColumnInformation() { LabelColumnName = null }, null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteLabelNotInTrain()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data,
 new ColumnInformation() { LabelColumnName = "L" }, null);
 new ColumnInformation() { LabelColumnName = "L" }, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -44,7 +44,7 @@ public void ValidateExperimentExecuteNumericColNotInTrain()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add("N");

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -53,7 +53,7 @@ public void ValidateExperimentExecuteNullNumericCol()
 {
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -63,7 +63,7 @@ public void ValidateExperimentExecuteDuplicateCol()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(DefaultColumnNames.Label);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -82,7 +82,7 @@ public void ValidateExperimentExecuteArgsTrainValidColCountMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, 
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -102,7 +102,7 @@ public void ValidateExperimentExecuteArgsTrainValidColNamesMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -122,7 +122,7 @@ public void ValidateExperimentExecuteArgsTrainValidColTypeMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand DownExpand Up@@ -163,7 +163,7 @@ public void ValidateFeaturesColInvalidType()
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -181,7 +181,78 @@ public void ValidateTextColumnNotText()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(TextPurposeColName);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
 public void ValidateRegressionLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.Regression, BooleanDataViewType.Instance, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Double, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, TextDataViewType.Instance, false);
 }

 [TestMethod]
 public void ValidateBinaryClassificationLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, NumberDataViewType.Single, false);
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, BooleanDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateMulticlassLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, BooleanDataViewType.Instance, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Double, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, TextDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateAllowedFeatureColumnTypes()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("Boolean", BooleanDataViewType.Instance);
 schemaBuilder.AddColumn("Number", NumberDataViewType.Single);
 schemaBuilder.AddColumn("Text", TextDataViewType.Instance);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateProhibitedFeatureColumnType()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("UInt64", NumberDataViewType.UInt64);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 private static void ValidateLabelTypeTestCore(TaskKind task, DataViewType labelType, bool labelTypeShouldBeValid)
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn(DefaultColumnNames.Features, NumberDataViewType.Single);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, labelType);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 var validationExceptionThrown = false;
 try
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, task);
 }
 catch
 {
 validationExceptionThrown = true;
 }
 Assert.AreEqual(labelTypeShouldBeValid, !validationExceptionThrown);
 }
 }
}

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
[AutoML] AutoML SDK API: validate schema types of input IDataView#3597

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 Merged

daholste
merged 2 commits into

from

Apr 26, 2019
 Merged


[AutoML] AutoML SDK API: validate schema types of input IDataView
#3597
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52333e1

AutoML API: validate schema types of input IDataView


daholste Apr 25, 2019
fda914e

rev error message


daholste Apr 26, 2019

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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.Auto/API/ExperimentBase.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -239,7 +239,7 @@ private ExperimentResult<TMetrics> ExecuteTrainValidate(IDataView trainData,
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData, _task);

 // Apply pre-featurizer
 ITransformer preprocessorTransform = null;
Expand All@@ -263,7 +263,7 @@ private CrossValidationExperimentResult<TMetrics> ExecuteCrossVal(IDataView[] tr
 IProgress<CrossValidationRunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand All@@ -290,7 +290,7 @@ private ExperimentResult<TMetrics> ExecuteCrossValSummary(IDataView[] trainDatas
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand Down

48 changes: 39 additions & 9 deletions
src/Microsoft.ML.Auto/Utils/UserInputValidationUtil.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,10 +22,10 @@ internal static class UserInputValidationUtil
 private const string SamplingKeyColumnPurposeName = "sampling key";

 public static void ValidateExperimentExecuteArgs(IDataView trainData, ColumnInformation columnInformation,
 IDataView validationData)
 IDataView validationData, TaskKind task)
 {
 ValidateTrainData(trainData);
 ValidateColumnInformation(trainData, columnInformation);
 ValidateTrainData(trainData, columnInformation);
 ValidateColumnInformation(trainData, columnInformation, task);
 ValidateValidationData(trainData, validationData);
 }

Expand DownExpand Up@@ -54,24 +54,37 @@ public static void ValidateNumberOfCVFoldsArg(uint numberOfCVFolds)
 }
 }

 private static void ValidateTrainData(IDataView trainData)
 private static void ValidateTrainData(IDataView trainData, ColumnInformation columnInformation)
 {
 if (trainData == null)
 {
 throw new ArgumentNullException(nameof(trainData), "Training data cannot be null");
 }

 var type = trainData.Schema.GetColumnOrNull(DefaultColumnNames.Features)?.Type.GetItemType();
 if (type != null && type != NumberDataViewType.Single)
 foreach (var column in trainData.Schema)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type Single", nameof(trainData));
 if (column.Name == DefaultColumnNames.Features && column.Type.GetItemType() != NumberDataViewType.Single)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type {NumberDataViewType.Single}", nameof(trainData));
 }

 if (column.Name != columnInformation.LabelColumnName &&
 column.Type.GetItemType() != BooleanDataViewType.Instance &&
 column.Type.GetItemType() != NumberDataViewType.Single &&
 column.Type.GetItemType() != TextDataViewType.Instance)
 {
 throw new ArgumentException($"Only supported feature column types are " +
 $"{BooleanDataViewType.Instance}, {NumberDataViewType.Single}, and {TextDataViewType.Instance}. " +
 $"Please change the feature column {column.Name} of type {column.Type} to one of " +
 $"the supported types.", nameof(trainData));
 }
 }
 }

 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation)
 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation, TaskKind task)
 {
 ValidateColumnInformation(columnInformation);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName, GetAllowedLabelTypes(task));
 ValidateTrainDataColumn(trainData, columnInformation.ExampleWeightColumnName, WeightColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.SamplingKeyColumnName, SamplingKeyColumnPurposeName);
 ValidateTrainDataColumns(trainData, columnInformation.CategoricalColumnNames, CategoricalColumnPurposeName,
Expand DownExpand Up@@ -228,5 +241,22 @@ private static string FindFirstDuplicate(IEnumerable<string> values)
 var groups = values.GroupBy(v => v);
 return groups.FirstOrDefault(g => g.Count() > 1)?.Key;
 }

 private static IEnumerable<DataViewType> GetAllowedLabelTypes(TaskKind task)
 {
 switch (task)
 {
 case TaskKind.BinaryClassification:
 return new DataViewType[] { BooleanDataViewType.Instance };
 // Multiclass label types are flexible, as we convert the label to a key type
 // (if input label is not already a key) before invoking the trainer.
 case TaskKind.MulticlassClassification:
 return null;
 case TaskKind.Regression:
 return new DataViewType[] { NumberDataViewType.Single };
 default:
 throw new NotSupportedException($"Unsupported task type: {task}");
 }
 }
 }
}

93 changes: 82 additions & 11 deletions
test/Microsoft.ML.AutoML.Tests/UserInputValidationTests.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -18,23 +18,23 @@ public class UserInputValidationTests
 [ExpectedException(typeof(ArgumentNullException))]
 public void ValidateExperimentExecuteNullTrainData()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteNullLabel()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, 
 new ColumnInformation() { LabelColumnName = null }, null);
 new ColumnInformation() { LabelColumnName = null }, null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteLabelNotInTrain()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data,
 new ColumnInformation() { LabelColumnName = "L" }, null);
 new ColumnInformation() { LabelColumnName = "L" }, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -44,7 +44,7 @@ public void ValidateExperimentExecuteNumericColNotInTrain()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add("N");

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -53,7 +53,7 @@ public void ValidateExperimentExecuteNullNumericCol()
 {
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -63,7 +63,7 @@ public void ValidateExperimentExecuteDuplicateCol()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(DefaultColumnNames.Label);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -82,7 +82,7 @@ public void ValidateExperimentExecuteArgsTrainValidColCountMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, 
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -102,7 +102,7 @@ public void ValidateExperimentExecuteArgsTrainValidColNamesMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -122,7 +122,7 @@ public void ValidateExperimentExecuteArgsTrainValidColTypeMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand DownExpand Up@@ -163,7 +163,7 @@ public void ValidateFeaturesColInvalidType()
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -181,7 +181,78 @@ public void ValidateTextColumnNotText()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(TextPurposeColName);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
 public void ValidateRegressionLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.Regression, BooleanDataViewType.Instance, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Double, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, TextDataViewType.Instance, false);
 }

 [TestMethod]
 public void ValidateBinaryClassificationLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, NumberDataViewType.Single, false);
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, BooleanDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateMulticlassLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, BooleanDataViewType.Instance, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Double, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, TextDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateAllowedFeatureColumnTypes()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("Boolean", BooleanDataViewType.Instance);
 schemaBuilder.AddColumn("Number", NumberDataViewType.Single);
 schemaBuilder.AddColumn("Text", TextDataViewType.Instance);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateProhibitedFeatureColumnType()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("UInt64", NumberDataViewType.UInt64);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 private static void ValidateLabelTypeTestCore(TaskKind task, DataViewType labelType, bool labelTypeShouldBeValid)
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn(DefaultColumnNames.Features, NumberDataViewType.Single);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, labelType);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 var validationExceptionThrown = false;
 try
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, task);
 }
 catch
 {
 validationExceptionThrown = true;
 }
 Assert.AreEqual(labelTypeShouldBeValid, !validationExceptionThrown);
 }
 }
}

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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[AutoML] AutoML SDK API: validate schema types of input IDataView#3597

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Apr 26, 2019
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[AutoML] AutoML SDK API: validate schema types of input IDataView
#3597
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52333e1

AutoML API: validate schema types of input IDataView


daholste Apr 25, 2019
fda914e

rev error message


daholste Apr 26, 2019

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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.Auto/API/ExperimentBase.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -239,7 +239,7 @@ private ExperimentResult<TMetrics> ExecuteTrainValidate(IDataView trainData,
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData, _task);

 // Apply pre-featurizer
 ITransformer preprocessorTransform = null;
Expand All@@ -263,7 +263,7 @@ private CrossValidationExperimentResult<TMetrics> ExecuteCrossVal(IDataView[] tr
 IProgress<CrossValidationRunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand All@@ -290,7 +290,7 @@ private ExperimentResult<TMetrics> ExecuteCrossValSummary(IDataView[] trainDatas
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand Down

48 changes: 39 additions & 9 deletions
src/Microsoft.ML.Auto/Utils/UserInputValidationUtil.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,10 +22,10 @@ internal static class UserInputValidationUtil
 private const string SamplingKeyColumnPurposeName = "sampling key";

 public static void ValidateExperimentExecuteArgs(IDataView trainData, ColumnInformation columnInformation,
 IDataView validationData)
 IDataView validationData, TaskKind task)
 {
 ValidateTrainData(trainData);
 ValidateColumnInformation(trainData, columnInformation);
 ValidateTrainData(trainData, columnInformation);
 ValidateColumnInformation(trainData, columnInformation, task);
 ValidateValidationData(trainData, validationData);
 }

Expand DownExpand Up@@ -54,24 +54,37 @@ public static void ValidateNumberOfCVFoldsArg(uint numberOfCVFolds)
 }
 }

 private static void ValidateTrainData(IDataView trainData)
 private static void ValidateTrainData(IDataView trainData, ColumnInformation columnInformation)
 {
 if (trainData == null)
 {
 throw new ArgumentNullException(nameof(trainData), "Training data cannot be null");
 }

 var type = trainData.Schema.GetColumnOrNull(DefaultColumnNames.Features)?.Type.GetItemType();
 if (type != null && type != NumberDataViewType.Single)
 foreach (var column in trainData.Schema)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type Single", nameof(trainData));
 if (column.Name == DefaultColumnNames.Features && column.Type.GetItemType() != NumberDataViewType.Single)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type {NumberDataViewType.Single}", nameof(trainData));
 }

 if (column.Name != columnInformation.LabelColumnName &&
 column.Type.GetItemType() != BooleanDataViewType.Instance &&
 column.Type.GetItemType() != NumberDataViewType.Single &&
 column.Type.GetItemType() != TextDataViewType.Instance)
 {
 throw new ArgumentException($"Only supported feature column types are " +
 $"{BooleanDataViewType.Instance}, {NumberDataViewType.Single}, and {TextDataViewType.Instance}. " +
 $"Please change the feature column {column.Name} of type {column.Type} to one of " +
 $"the supported types.", nameof(trainData));
 }
 }
 }

 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation)
 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation, TaskKind task)
 {
 ValidateColumnInformation(columnInformation);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName, GetAllowedLabelTypes(task));
 ValidateTrainDataColumn(trainData, columnInformation.ExampleWeightColumnName, WeightColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.SamplingKeyColumnName, SamplingKeyColumnPurposeName);
 ValidateTrainDataColumns(trainData, columnInformation.CategoricalColumnNames, CategoricalColumnPurposeName,
Expand DownExpand Up@@ -228,5 +241,22 @@ private static string FindFirstDuplicate(IEnumerable<string> values)
 var groups = values.GroupBy(v => v);
 return groups.FirstOrDefault(g => g.Count() > 1)?.Key;
 }

 private static IEnumerable<DataViewType> GetAllowedLabelTypes(TaskKind task)
 {
 switch (task)
 {
 case TaskKind.BinaryClassification:
 return new DataViewType[] { BooleanDataViewType.Instance };
 // Multiclass label types are flexible, as we convert the label to a key type
 // (if input label is not already a key) before invoking the trainer.
 case TaskKind.MulticlassClassification:
 return null;
 case TaskKind.Regression:
 return new DataViewType[] { NumberDataViewType.Single };
 default:
 throw new NotSupportedException($"Unsupported task type: {task}");
 }
 }
 }
}

93 changes: 82 additions & 11 deletions
test/Microsoft.ML.AutoML.Tests/UserInputValidationTests.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -18,23 +18,23 @@ public class UserInputValidationTests
 [ExpectedException(typeof(ArgumentNullException))]
 public void ValidateExperimentExecuteNullTrainData()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteNullLabel()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, 
 new ColumnInformation() { LabelColumnName = null }, null);
 new ColumnInformation() { LabelColumnName = null }, null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteLabelNotInTrain()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data,
 new ColumnInformation() { LabelColumnName = "L" }, null);
 new ColumnInformation() { LabelColumnName = "L" }, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -44,7 +44,7 @@ public void ValidateExperimentExecuteNumericColNotInTrain()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add("N");

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -53,7 +53,7 @@ public void ValidateExperimentExecuteNullNumericCol()
 {
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -63,7 +63,7 @@ public void ValidateExperimentExecuteDuplicateCol()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(DefaultColumnNames.Label);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -82,7 +82,7 @@ public void ValidateExperimentExecuteArgsTrainValidColCountMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, 
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -102,7 +102,7 @@ public void ValidateExperimentExecuteArgsTrainValidColNamesMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -122,7 +122,7 @@ public void ValidateExperimentExecuteArgsTrainValidColTypeMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand DownExpand Up@@ -163,7 +163,7 @@ public void ValidateFeaturesColInvalidType()
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -181,7 +181,78 @@ public void ValidateTextColumnNotText()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(TextPurposeColName);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
 public void ValidateRegressionLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.Regression, BooleanDataViewType.Instance, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Double, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, TextDataViewType.Instance, false);
 }

 [TestMethod]
 public void ValidateBinaryClassificationLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, NumberDataViewType.Single, false);
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, BooleanDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateMulticlassLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, BooleanDataViewType.Instance, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Double, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, TextDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateAllowedFeatureColumnTypes()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("Boolean", BooleanDataViewType.Instance);
 schemaBuilder.AddColumn("Number", NumberDataViewType.Single);
 schemaBuilder.AddColumn("Text", TextDataViewType.Instance);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateProhibitedFeatureColumnType()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("UInt64", NumberDataViewType.UInt64);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 private static void ValidateLabelTypeTestCore(TaskKind task, DataViewType labelType, bool labelTypeShouldBeValid)
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn(DefaultColumnNames.Features, NumberDataViewType.Single);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, labelType);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 var validationExceptionThrown = false;
 try
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, task);
 }
 catch
 {
 validationExceptionThrown = true;
 }
 Assert.AreEqual(labelTypeShouldBeValid, !validationExceptionThrown);
 }
 }
}

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
[AutoML] AutoML SDK API: validate schema types of input IDataView#3597

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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privacy statement. We’ll occasionally send you account related emails.

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Sign in
to your account

 Merged

daholste
merged 2 commits into

from

Apr 26, 2019
 Merged


[AutoML] AutoML SDK API: validate schema types of input IDataView
#3597
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52333e1

AutoML API: validate schema types of input IDataView


daholste Apr 25, 2019
fda914e

rev error message


daholste Apr 26, 2019

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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.Auto/API/ExperimentBase.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -239,7 +239,7 @@ private ExperimentResult<TMetrics> ExecuteTrainValidate(IDataView trainData,
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData, _task);

 // Apply pre-featurizer
 ITransformer preprocessorTransform = null;
Expand All@@ -263,7 +263,7 @@ private CrossValidationExperimentResult<TMetrics> ExecuteCrossVal(IDataView[] tr
 IProgress<CrossValidationRunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand All@@ -290,7 +290,7 @@ private ExperimentResult<TMetrics> ExecuteCrossValSummary(IDataView[] trainDatas
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand Down

48 changes: 39 additions & 9 deletions
src/Microsoft.ML.Auto/Utils/UserInputValidationUtil.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,10 +22,10 @@ internal static class UserInputValidationUtil
 private const string SamplingKeyColumnPurposeName = "sampling key";

 public static void ValidateExperimentExecuteArgs(IDataView trainData, ColumnInformation columnInformation,
 IDataView validationData)
 IDataView validationData, TaskKind task)
 {
 ValidateTrainData(trainData);
 ValidateColumnInformation(trainData, columnInformation);
 ValidateTrainData(trainData, columnInformation);
 ValidateColumnInformation(trainData, columnInformation, task);
 ValidateValidationData(trainData, validationData);
 }

Expand DownExpand Up@@ -54,24 +54,37 @@ public static void ValidateNumberOfCVFoldsArg(uint numberOfCVFolds)
 }
 }

 private static void ValidateTrainData(IDataView trainData)
 private static void ValidateTrainData(IDataView trainData, ColumnInformation columnInformation)
 {
 if (trainData == null)
 {
 throw new ArgumentNullException(nameof(trainData), "Training data cannot be null");
 }

 var type = trainData.Schema.GetColumnOrNull(DefaultColumnNames.Features)?.Type.GetItemType();
 if (type != null && type != NumberDataViewType.Single)
 foreach (var column in trainData.Schema)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type Single", nameof(trainData));
 if (column.Name == DefaultColumnNames.Features && column.Type.GetItemType() != NumberDataViewType.Single)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type {NumberDataViewType.Single}", nameof(trainData));
 }

 if (column.Name != columnInformation.LabelColumnName &&
 column.Type.GetItemType() != BooleanDataViewType.Instance &&
 column.Type.GetItemType() != NumberDataViewType.Single &&
 column.Type.GetItemType() != TextDataViewType.Instance)
 {
 throw new ArgumentException($"Only supported feature column types are " +
 $"{BooleanDataViewType.Instance}, {NumberDataViewType.Single}, and {TextDataViewType.Instance}. " +
 $"Please change the feature column {column.Name} of type {column.Type} to one of " +
 $"the supported types.", nameof(trainData));
 }
 }
 }

 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation)
 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation, TaskKind task)
 {
 ValidateColumnInformation(columnInformation);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName, GetAllowedLabelTypes(task));
 ValidateTrainDataColumn(trainData, columnInformation.ExampleWeightColumnName, WeightColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.SamplingKeyColumnName, SamplingKeyColumnPurposeName);
 ValidateTrainDataColumns(trainData, columnInformation.CategoricalColumnNames, CategoricalColumnPurposeName,
Expand DownExpand Up@@ -228,5 +241,22 @@ private static string FindFirstDuplicate(IEnumerable<string> values)
 var groups = values.GroupBy(v => v);
 return groups.FirstOrDefault(g => g.Count() > 1)?.Key;
 }

 private static IEnumerable<DataViewType> GetAllowedLabelTypes(TaskKind task)
 {
 switch (task)
 {
 case TaskKind.BinaryClassification:
 return new DataViewType[] { BooleanDataViewType.Instance };
 // Multiclass label types are flexible, as we convert the label to a key type
 // (if input label is not already a key) before invoking the trainer.
 case TaskKind.MulticlassClassification:
 return null;
 case TaskKind.Regression:
 return new DataViewType[] { NumberDataViewType.Single };
 default:
 throw new NotSupportedException($"Unsupported task type: {task}");
 }
 }
 }
}

93 changes: 82 additions & 11 deletions
test/Microsoft.ML.AutoML.Tests/UserInputValidationTests.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -18,23 +18,23 @@ public class UserInputValidationTests
 [ExpectedException(typeof(ArgumentNullException))]
 public void ValidateExperimentExecuteNullTrainData()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteNullLabel()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, 
 new ColumnInformation() { LabelColumnName = null }, null);
 new ColumnInformation() { LabelColumnName = null }, null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteLabelNotInTrain()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data,
 new ColumnInformation() { LabelColumnName = "L" }, null);
 new ColumnInformation() { LabelColumnName = "L" }, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -44,7 +44,7 @@ public void ValidateExperimentExecuteNumericColNotInTrain()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add("N");

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -53,7 +53,7 @@ public void ValidateExperimentExecuteNullNumericCol()
 {
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -63,7 +63,7 @@ public void ValidateExperimentExecuteDuplicateCol()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(DefaultColumnNames.Label);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -82,7 +82,7 @@ public void ValidateExperimentExecuteArgsTrainValidColCountMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, 
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -102,7 +102,7 @@ public void ValidateExperimentExecuteArgsTrainValidColNamesMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -122,7 +122,7 @@ public void ValidateExperimentExecuteArgsTrainValidColTypeMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand DownExpand Up@@ -163,7 +163,7 @@ public void ValidateFeaturesColInvalidType()
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -181,7 +181,78 @@ public void ValidateTextColumnNotText()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(TextPurposeColName);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
 public void ValidateRegressionLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.Regression, BooleanDataViewType.Instance, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Double, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, TextDataViewType.Instance, false);
 }

 [TestMethod]
 public void ValidateBinaryClassificationLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, NumberDataViewType.Single, false);
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, BooleanDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateMulticlassLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, BooleanDataViewType.Instance, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Double, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, TextDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateAllowedFeatureColumnTypes()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("Boolean", BooleanDataViewType.Instance);
 schemaBuilder.AddColumn("Number", NumberDataViewType.Single);
 schemaBuilder.AddColumn("Text", TextDataViewType.Instance);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateProhibitedFeatureColumnType()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("UInt64", NumberDataViewType.UInt64);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 private static void ValidateLabelTypeTestCore(TaskKind task, DataViewType labelType, bool labelTypeShouldBeValid)
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn(DefaultColumnNames.Features, NumberDataViewType.Single);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, labelType);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 var validationExceptionThrown = false;
 try
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, task);
 }
 catch
 {
 validationExceptionThrown = true;
 }
 Assert.AreEqual(labelTypeShouldBeValid, !validationExceptionThrown);
 }
 }
}

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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[AutoML] AutoML SDK API: validate schema types of input IDataView#3597

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daholste
merged 2 commits into

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Apr 26, 2019
 Merged


[AutoML] AutoML SDK API: validate schema types of input IDataView
#3597
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52333e1

AutoML API: validate schema types of input IDataView


daholste Apr 25, 2019
fda914e

rev error message


daholste Apr 26, 2019

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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.Auto/API/ExperimentBase.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -239,7 +239,7 @@ private ExperimentResult<TMetrics> ExecuteTrainValidate(IDataView trainData,
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData, _task);

 // Apply pre-featurizer
 ITransformer preprocessorTransform = null;
Expand All@@ -263,7 +263,7 @@ private CrossValidationExperimentResult<TMetrics> ExecuteCrossVal(IDataView[] tr
 IProgress<CrossValidationRunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand All@@ -290,7 +290,7 @@ private ExperimentResult<TMetrics> ExecuteCrossValSummary(IDataView[] trainDatas
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand Down

48 changes: 39 additions & 9 deletions
src/Microsoft.ML.Auto/Utils/UserInputValidationUtil.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,10 +22,10 @@ internal static class UserInputValidationUtil
 private const string SamplingKeyColumnPurposeName = "sampling key";

 public static void ValidateExperimentExecuteArgs(IDataView trainData, ColumnInformation columnInformation,
 IDataView validationData)
 IDataView validationData, TaskKind task)
 {
 ValidateTrainData(trainData);
 ValidateColumnInformation(trainData, columnInformation);
 ValidateTrainData(trainData, columnInformation);
 ValidateColumnInformation(trainData, columnInformation, task);
 ValidateValidationData(trainData, validationData);
 }

Expand DownExpand Up@@ -54,24 +54,37 @@ public static void ValidateNumberOfCVFoldsArg(uint numberOfCVFolds)
 }
 }

 private static void ValidateTrainData(IDataView trainData)
 private static void ValidateTrainData(IDataView trainData, ColumnInformation columnInformation)
 {
 if (trainData == null)
 {
 throw new ArgumentNullException(nameof(trainData), "Training data cannot be null");
 }

 var type = trainData.Schema.GetColumnOrNull(DefaultColumnNames.Features)?.Type.GetItemType();
 if (type != null && type != NumberDataViewType.Single)
 foreach (var column in trainData.Schema)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type Single", nameof(trainData));
 if (column.Name == DefaultColumnNames.Features && column.Type.GetItemType() != NumberDataViewType.Single)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type {NumberDataViewType.Single}", nameof(trainData));
 }

 if (column.Name != columnInformation.LabelColumnName &&
 column.Type.GetItemType() != BooleanDataViewType.Instance &&
 column.Type.GetItemType() != NumberDataViewType.Single &&
 column.Type.GetItemType() != TextDataViewType.Instance)
 {
 throw new ArgumentException($"Only supported feature column types are " +
 $"{BooleanDataViewType.Instance}, {NumberDataViewType.Single}, and {TextDataViewType.Instance}. " +
 $"Please change the feature column {column.Name} of type {column.Type} to one of " +
 $"the supported types.", nameof(trainData));
 }
 }
 }

 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation)
 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation, TaskKind task)
 {
 ValidateColumnInformation(columnInformation);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName, GetAllowedLabelTypes(task));
 ValidateTrainDataColumn(trainData, columnInformation.ExampleWeightColumnName, WeightColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.SamplingKeyColumnName, SamplingKeyColumnPurposeName);
 ValidateTrainDataColumns(trainData, columnInformation.CategoricalColumnNames, CategoricalColumnPurposeName,
Expand DownExpand Up@@ -228,5 +241,22 @@ private static string FindFirstDuplicate(IEnumerable<string> values)
 var groups = values.GroupBy(v => v);
 return groups.FirstOrDefault(g => g.Count() > 1)?.Key;
 }

 private static IEnumerable<DataViewType> GetAllowedLabelTypes(TaskKind task)
 {
 switch (task)
 {
 case TaskKind.BinaryClassification:
 return new DataViewType[] { BooleanDataViewType.Instance };
 // Multiclass label types are flexible, as we convert the label to a key type
 // (if input label is not already a key) before invoking the trainer.
 case TaskKind.MulticlassClassification:
 return null;
 case TaskKind.Regression:
 return new DataViewType[] { NumberDataViewType.Single };
 default:
 throw new NotSupportedException($"Unsupported task type: {task}");
 }
 }
 }
}

93 changes: 82 additions & 11 deletions
test/Microsoft.ML.AutoML.Tests/UserInputValidationTests.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -18,23 +18,23 @@ public class UserInputValidationTests
 [ExpectedException(typeof(ArgumentNullException))]
 public void ValidateExperimentExecuteNullTrainData()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteNullLabel()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, 
 new ColumnInformation() { LabelColumnName = null }, null);
 new ColumnInformation() { LabelColumnName = null }, null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteLabelNotInTrain()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data,
 new ColumnInformation() { LabelColumnName = "L" }, null);
 new ColumnInformation() { LabelColumnName = "L" }, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -44,7 +44,7 @@ public void ValidateExperimentExecuteNumericColNotInTrain()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add("N");

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -53,7 +53,7 @@ public void ValidateExperimentExecuteNullNumericCol()
 {
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -63,7 +63,7 @@ public void ValidateExperimentExecuteDuplicateCol()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(DefaultColumnNames.Label);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -82,7 +82,7 @@ public void ValidateExperimentExecuteArgsTrainValidColCountMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, 
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -102,7 +102,7 @@ public void ValidateExperimentExecuteArgsTrainValidColNamesMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -122,7 +122,7 @@ public void ValidateExperimentExecuteArgsTrainValidColTypeMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand DownExpand Up@@ -163,7 +163,7 @@ public void ValidateFeaturesColInvalidType()
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -181,7 +181,78 @@ public void ValidateTextColumnNotText()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(TextPurposeColName);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
 public void ValidateRegressionLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.Regression, BooleanDataViewType.Instance, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Double, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, TextDataViewType.Instance, false);
 }

 [TestMethod]
 public void ValidateBinaryClassificationLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, NumberDataViewType.Single, false);
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, BooleanDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateMulticlassLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, BooleanDataViewType.Instance, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Double, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, TextDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateAllowedFeatureColumnTypes()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("Boolean", BooleanDataViewType.Instance);
 schemaBuilder.AddColumn("Number", NumberDataViewType.Single);
 schemaBuilder.AddColumn("Text", TextDataViewType.Instance);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateProhibitedFeatureColumnType()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("UInt64", NumberDataViewType.UInt64);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 private static void ValidateLabelTypeTestCore(TaskKind task, DataViewType labelType, bool labelTypeShouldBeValid)
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn(DefaultColumnNames.Features, NumberDataViewType.Single);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, labelType);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 var validationExceptionThrown = false;
 try
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, task);
 }
 catch
 {
 validationExceptionThrown = true;
 }
 Assert.AreEqual(labelTypeShouldBeValid, !validationExceptionThrown);
 }
 }
}

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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[AutoML] AutoML SDK API: validate schema types of input IDataView#3597

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 Merged

daholste
merged 2 commits into

from

Apr 26, 2019
 Merged


[AutoML] AutoML SDK API: validate schema types of input IDataView
#3597
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52333e1

AutoML API: validate schema types of input IDataView


daholste Apr 25, 2019
fda914e

rev error message


daholste Apr 26, 2019

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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.Auto/API/ExperimentBase.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -239,7 +239,7 @@ private ExperimentResult<TMetrics> ExecuteTrainValidate(IDataView trainData,
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, columnInfo, validationData, _task);

 // Apply pre-featurizer
 ITransformer preprocessorTransform = null;
Expand All@@ -263,7 +263,7 @@ private CrossValidationExperimentResult<TMetrics> ExecuteCrossVal(IDataView[] tr
 IProgress<CrossValidationRunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand All@@ -290,7 +290,7 @@ private ExperimentResult<TMetrics> ExecuteCrossValSummary(IDataView[] trainDatas
 IProgress<RunDetail<TMetrics>> progressHandler)
 {
 columnInfo = columnInfo ?? new ColumnInformation();
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0]);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainDatasets[0], columnInfo, validationDatasets[0], _task);

 // Apply pre-featurizer
 ITransformer[] preprocessorTransforms = null;
Expand Down

48 changes: 39 additions & 9 deletions
src/Microsoft.ML.Auto/Utils/UserInputValidationUtil.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,10 +22,10 @@ internal static class UserInputValidationUtil
 private const string SamplingKeyColumnPurposeName = "sampling key";

 public static void ValidateExperimentExecuteArgs(IDataView trainData, ColumnInformation columnInformation,
 IDataView validationData)
 IDataView validationData, TaskKind task)
 {
 ValidateTrainData(trainData);
 ValidateColumnInformation(trainData, columnInformation);
 ValidateTrainData(trainData, columnInformation);
 ValidateColumnInformation(trainData, columnInformation, task);
 ValidateValidationData(trainData, validationData);
 }

Expand DownExpand Up@@ -54,24 +54,37 @@ public static void ValidateNumberOfCVFoldsArg(uint numberOfCVFolds)
 }
 }

 private static void ValidateTrainData(IDataView trainData)
 private static void ValidateTrainData(IDataView trainData, ColumnInformation columnInformation)
 {
 if (trainData == null)
 {
 throw new ArgumentNullException(nameof(trainData), "Training data cannot be null");
 }

 var type = trainData.Schema.GetColumnOrNull(DefaultColumnNames.Features)?.Type.GetItemType();
 if (type != null && type != NumberDataViewType.Single)
 foreach (var column in trainData.Schema)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type Single", nameof(trainData));
 if (column.Name == DefaultColumnNames.Features && column.Type.GetItemType() != NumberDataViewType.Single)
 {
 throw new ArgumentException($"{DefaultColumnNames.Features} column must be of data type {NumberDataViewType.Single}", nameof(trainData));
 }

 if (column.Name != columnInformation.LabelColumnName &&
 column.Type.GetItemType() != BooleanDataViewType.Instance &&
 column.Type.GetItemType() != NumberDataViewType.Single &&
 column.Type.GetItemType() != TextDataViewType.Instance)
 {
 throw new ArgumentException($"Only supported feature column types are " +
 $"{BooleanDataViewType.Instance}, {NumberDataViewType.Single}, and {TextDataViewType.Instance}. " +
 $"Please change the feature column {column.Name} of type {column.Type} to one of " +
 $"the supported types.", nameof(trainData));
 }
 }
 }

 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation)
 private static void ValidateColumnInformation(IDataView trainData, ColumnInformation columnInformation, TaskKind task)
 {
 ValidateColumnInformation(columnInformation);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.LabelColumnName, LabelColumnPurposeName, GetAllowedLabelTypes(task));
 ValidateTrainDataColumn(trainData, columnInformation.ExampleWeightColumnName, WeightColumnPurposeName);
 ValidateTrainDataColumn(trainData, columnInformation.SamplingKeyColumnName, SamplingKeyColumnPurposeName);
 ValidateTrainDataColumns(trainData, columnInformation.CategoricalColumnNames, CategoricalColumnPurposeName,
Expand DownExpand Up@@ -228,5 +241,22 @@ private static string FindFirstDuplicate(IEnumerable<string> values)
 var groups = values.GroupBy(v => v);
 return groups.FirstOrDefault(g => g.Count() > 1)?.Key;
 }

 private static IEnumerable<DataViewType> GetAllowedLabelTypes(TaskKind task)
 {
 switch (task)
 {
 case TaskKind.BinaryClassification:
 return new DataViewType[] { BooleanDataViewType.Instance };
 // Multiclass label types are flexible, as we convert the label to a key type
 // (if input label is not already a key) before invoking the trainer.
 case TaskKind.MulticlassClassification:
 return null;
 case TaskKind.Regression:
 return new DataViewType[] { NumberDataViewType.Single };
 default:
 throw new NotSupportedException($"Unsupported task type: {task}");
 }
 }
 }
}

93 changes: 82 additions & 11 deletions
test/Microsoft.ML.AutoML.Tests/UserInputValidationTests.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -18,23 +18,23 @@ public class UserInputValidationTests
 [ExpectedException(typeof(ArgumentNullException))]
 public void ValidateExperimentExecuteNullTrainData()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(null, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteNullLabel()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, 
 new ColumnInformation() { LabelColumnName = null }, null);
 new ColumnInformation() { LabelColumnName = null }, null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateExperimentExecuteLabelNotInTrain()
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data,
 new ColumnInformation() { LabelColumnName = "L" }, null);
 new ColumnInformation() { LabelColumnName = "L" }, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -44,7 +44,7 @@ public void ValidateExperimentExecuteNumericColNotInTrain()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add("N");

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -53,7 +53,7 @@ public void ValidateExperimentExecuteNullNumericCol()
 {
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -63,7 +63,7 @@ public void ValidateExperimentExecuteDuplicateCol()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(DefaultColumnNames.Label);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(Data, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -82,7 +82,7 @@ public void ValidateExperimentExecuteArgsTrainValidColCountMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData, 
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -102,7 +102,7 @@ public void ValidateExperimentExecuteArgsTrainValidColNamesMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -122,7 +122,7 @@ public void ValidateExperimentExecuteArgsTrainValidColTypeMismatch()
 var validData = validDataBuilder.GetDataView();

 UserInputValidationUtil.ValidateExperimentExecuteArgs(trainData,
 new ColumnInformation() { LabelColumnName = "0" }, validData);
 new ColumnInformation() { LabelColumnName = "0" }, validData, TaskKind.Regression);
 }

 [TestMethod]
Expand DownExpand Up@@ -163,7 +163,7 @@ public void ValidateFeaturesColInvalidType()
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, TaskKind.Regression);
 }

 [TestMethod]
Expand All@@ -181,7 +181,78 @@ public void ValidateTextColumnNotText()
 var columnInfo = new ColumnInformation();
 columnInfo.NumericColumnNames.Add(TextPurposeColName);

 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, columnInfo, null, TaskKind.Regression);
 }

 [TestMethod]
 public void ValidateRegressionLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.Regression, BooleanDataViewType.Instance, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, NumberDataViewType.Double, false);
 ValidateLabelTypeTestCore(TaskKind.Regression, TextDataViewType.Instance, false);
 }

 [TestMethod]
 public void ValidateBinaryClassificationLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, NumberDataViewType.Single, false);
 ValidateLabelTypeTestCore(TaskKind.BinaryClassification, BooleanDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateMulticlassLabelTypes()
 {
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Single, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, BooleanDataViewType.Instance, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, NumberDataViewType.Double, true);
 ValidateLabelTypeTestCore(TaskKind.MulticlassClassification, TextDataViewType.Instance, true);
 }

 [TestMethod]
 public void ValidateAllowedFeatureColumnTypes()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("Boolean", BooleanDataViewType.Instance);
 schemaBuilder.AddColumn("Number", NumberDataViewType.Single);
 schemaBuilder.AddColumn("Text", TextDataViewType.Instance);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 [TestMethod]
 [ExpectedException(typeof(ArgumentException))]
 public void ValidateProhibitedFeatureColumnType()
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn("UInt64", NumberDataViewType.UInt64);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(),
 null, TaskKind.Regression);
 }

 private static void ValidateLabelTypeTestCore(TaskKind task, DataViewType labelType, bool labelTypeShouldBeValid)
 {
 var schemaBuilder = new DataViewSchema.Builder();
 schemaBuilder.AddColumn(DefaultColumnNames.Features, NumberDataViewType.Single);
 schemaBuilder.AddColumn(DefaultColumnNames.Label, labelType);
 var schema = schemaBuilder.ToSchema();
 var dataView = new EmptyDataView(new MLContext(), schema);
 var validationExceptionThrown = false;
 try
 {
 UserInputValidationUtil.ValidateExperimentExecuteArgs(dataView, new ColumnInformation(), null, task);
 }
 catch
 {
 validationExceptionThrown = true;
 }
 Assert.AreEqual(labelTypeShouldBeValid, !validationExceptionThrown);
 }
 }
}