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4 changes: 3 additions & 1 deletion src/Microsoft.ML.Transforms/CustomMappingTransformer.cs
Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@ public sealed class CustomMappingTransformer<TSrc, TDst> : ITransformer
private readonly IHost _host;
private readonly Action<TSrc, TDst> _mapAction;
private readonly string _contractName;
private readonly string _contractAssembly;

internal InternalSchemaDefinition AddedSchema { get; }
internal SchemaDefinition InputSchemaDefinition { get; }
Expand Down Expand Up @@ -58,6 +59,7 @@ internal CustomMappingTransformer(IHostEnvironment env, Action<TSrc, TDst> mapAc
: InternalSchemaDefinition.Create(typeof(TDst), outputSchemaDefinition);

_contractName = contractName;
_contractAssembly = _mapAction.Method.DeclaringType.Assembly.FullName;

@antoniovs1029 antoniovs1029 Apr 1, 2020

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Is there any case where the loaded model would actually require having a different name registered from the "FullName" retrieved from here? #Resolved

@antoniovs1029 antoniovs1029 Apr 1, 2020

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Or any case where trying to access that member of _mapAction would throw? #Resolved

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The call to Method can throw a MemberAccessException. But that would be up to the caller to fix in their code and the exception would help with that.


In reply to: 401790783 [](ancestors = 401790783)

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I think we should enforce the idea that the same transform that is used in training should be used in prediction as well. If they were to be different, then they are not the same pipelines and not the same models.


In reply to: 401431899 [](ancestors = 401431899)

AddedSchema = outSchema;
}

Expand All @@ -67,7 +69,7 @@ internal void SaveModel(ModelSaveContext ctx)
{
if (_contractName == null)
throw _host.Except("Empty contract name for a transform: the transform cannot be saved");
LambdaTransform.SaveCustomTransformer(_host, ctx, _contractName);
LambdaTransform.SaveCustomTransformer(_host, ctx, _contractName, _contractAssembly);
}

/// <summary>
Expand Down
17 changes: 14 additions & 3 deletions src/Microsoft.ML.Transforms/LambdaTransform.cs
Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@

using System;
using System.IO;
using System.Reflection;
using System.Text;
using Microsoft.ML;
using Microsoft.ML.Data;
Expand Down Expand Up @@ -40,14 +41,17 @@ private static VersionInfo GetVersionInfo()
{
return new VersionInfo(
modelSignature: "CUSTOMXF",
verWrittenCur: 0x00010001,
verReadableCur: 0x00010001,
//verWrittenCur: 0x00010001, // Initial
verWrittenCur: 0x00010002, // Added name of assembly in which the contractName is present
verReadableCur: 0x00010002,
verWeCanReadBack: 0x00010001,
loaderSignature: LoaderSignature,
loaderAssemblyName: typeof(LambdaTransform).Assembly.FullName);
}

internal static void SaveCustomTransformer(IExceptionContext ectx, ModelSaveContext ctx, string contractName)
private const uint VerAssemblyNameSaved = 0x00010002;

internal static void SaveCustomTransformer(IExceptionContext ectx, ModelSaveContext ctx, string contractName, string contractAssembly)
{
ectx.CheckValue(ctx, nameof(ctx));
ectx.CheckValue(contractName, nameof(contractName));
Expand All @@ -56,6 +60,7 @@ internal static void SaveCustomTransformer(IExceptionContext ectx, ModelSaveCont
ctx.SetVersionInfo(GetVersionInfo());

ctx.SaveString(contractName);
ctx.SaveString(contractAssembly);
}

// Factory for SignatureLoadModel.
Expand All @@ -66,6 +71,12 @@ private static ITransformer Create(IHostEnvironment env, ModelLoadContext ctx)
ctx.CheckAtModel(GetVersionInfo());

var contractName = ctx.LoadString();
if (ctx.Header.ModelVerWritten >= VerAssemblyNameSaved)
{
var contractAssembly = ctx.LoadString();
Assembly assembly = Assembly.Load(contractAssembly);
env.ComponentCatalog.RegisterAssembly(assembly);
}

object factoryObject = env.ComponentCatalog.GetExtensionValue(env, typeof(CustomMappingFactoryAttributeAttribute), contractName);
if (!(factoryObject is ICustomMappingFactory mappingFactory))
Expand Down
43 changes: 39 additions & 4 deletions test/Microsoft.ML.Core.Tests/UnitTests/TestCustomTypeRegister.cs
Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@

using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using Microsoft.ML.Data;
using Microsoft.ML.Transforms;
Expand Down Expand Up @@ -151,7 +152,7 @@ public SuperAlienHero()

/// <summary>
/// A mapping from <see cref="AlienHero"/> to <see cref="SuperAlienHero"/>. It is used to create a
/// <see cref="CustomMappingEstimator{TSrc, TDst}"/> in <see cref="RegisterTypeWithAttribute()"/>.
/// <see cref="CustomMappingEstimator{TSrc, TDst}"/> in <see cref="RegisterTypeWithAttribute(bool)"/>.
/// </summary>
[CustomMappingFactoryAttribute("LambdaAlienHero")]
private class AlienFusionProcess : CustomMappingFactory<AlienHero, SuperAlienHero>
Expand All @@ -171,8 +172,10 @@ public override Action<AlienHero, SuperAlienHero> GetMapping()
}
}

[Fact]
public void RegisterTypeWithAttribute()
[Theory]
[InlineData(true)]
[InlineData(false)]
public void RegisterTypeWithAttribute(bool saveModel)
{
// Build in-memory data.
var tribe = new List<AlienHero>() { new AlienHero("ML.NET", 2, 1000, 2000, 3000, 4000, 5000, 6000, 7000) };
Expand All @@ -184,6 +187,13 @@ public void RegisterTypeWithAttribute()
var tribeTransformed = model.Transform(tribeDataView);
var tribeEnumerable = ML.Data.CreateEnumerable<SuperAlienHero>(tribeTransformed, false).ToList();

ITransformer modelForPrediction = model;
if (saveModel)
{
ML.Model.Save(model, tribeDataView.Schema, "customTransform.zip");
modelForPrediction = ML.Model.Load("customTransform.zip", out var tribeDataViewSchema);
}

// Make sure the pipeline output is correct.
Assert.Equal(tribeEnumerable[0].Name, "Super " + tribe[0].Name);
Assert.Equal(tribeEnumerable[0].Merged.Age, tribe[0].One.Age + tribe[0].Two.Age);
Expand All @@ -192,7 +202,7 @@ public void RegisterTypeWithAttribute()
Assert.Equal(tribeEnumerable[0].Merged.HandCount, tribe[0].One.HandCount + tribe[0].Two.HandCount);

// Build prediction engine from the trained pipeline.
var engine = ML.Model.CreatePredictionEngine<AlienHero, SuperAlienHero>(model);
var engine = ML.Model.CreatePredictionEngine<AlienHero, SuperAlienHero>(modelForPrediction);
var alien = new AlienHero("TEN.LM", 1, 2, 3, 4, 5, 6, 7, 8);
var superAlien = engine.Predict(alien);

Expand All @@ -202,6 +212,31 @@ public void RegisterTypeWithAttribute()
Assert.Equal(superAlien.Merged.Height, alien.One.Height + alien.Two.Height);
Assert.Equal(superAlien.Merged.Weight, alien.One.Weight + alien.Two.Weight);
Assert.Equal(superAlien.Merged.HandCount, alien.One.HandCount + alien.Two.HandCount);

Done();
}

[Fact]
void TestCustomTransformBackcompat()
{
// With older versions, it is necessary to register the assembly
ML.ComponentCatalog.RegisterAssembly(typeof(AlienFusionProcess).Assembly);

var modelPath = Path.Combine(DataDir, "backcompat", "customTransform.zip");
var trainedModel = ML.Model.Load(modelPath, out var dataViewSchema);

var engine = ML.Model.CreatePredictionEngine<AlienHero, SuperAlienHero>(trainedModel);
var alien = new AlienHero("TEN.LM", 1, 2, 3, 4, 5, 6, 7, 8);
var superAlien = engine.Predict(alien);

// Make sure the prediction engine produces expected result.
Assert.Equal(superAlien.Name, "Super " + alien.Name);
Assert.Equal(superAlien.Merged.Age, alien.One.Age + alien.Two.Age);
Assert.Equal(superAlien.Merged.Height, alien.One.Height + alien.Two.Height);
Assert.Equal(superAlien.Merged.Weight, alien.One.Weight + alien.Two.Weight);
Assert.Equal(superAlien.Merged.HandCount, alien.One.HandCount + alien.Two.HandCount);

Done();
}

[Fact]
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -1250,14 +1250,10 @@ public void TensorFlowStringTest()
}

[TensorFlowFact]
// This test hangs occasionally
[Trait("Category", "SkipInCI")]
public void TensorFlowImageClassificationDefault()
{
if (RuntimeInformation.IsOSPlatform(OSPlatform.Linux))
{
Output.WriteLine("TODO TEST_STABILITY: TensorFlowImageClassificationDefault hangs on Linux.");
return;
}

string imagesDownloadFolderPath = Path.Combine(TensorFlowScenariosTestsFixture.assetsPath, "inputs",
"images");

Expand Down Expand Up @@ -1628,13 +1624,10 @@ internal void TensorFlowImageClassificationWithLRScheduling(LearningRateSchedule
[TensorFlowTheory]
[InlineData(ImageClassificationTrainer.EarlyStoppingMetric.Accuracy)]
[InlineData(ImageClassificationTrainer.EarlyStoppingMetric.Loss)]
// This test hangs ocassionally
[Trait("Category", "SkipInCI")]
public void TensorFlowImageClassificationEarlyStopping(ImageClassificationTrainer.EarlyStoppingMetric earlyStoppingMetric)
{
if (RuntimeInformation.IsOSPlatform(OSPlatform.Linux))
{
Output.WriteLine("TODO TEST_STABILITY: TensorFlowImageClassificationEarlyStopping hangs on Linux.");
return;
}
string imagesDownloadFolderPath = Path.Combine(TensorFlowScenariosTestsFixture.assetsPath, "inputs",
"images");

Expand Down
24 changes: 11 additions & 13 deletions test/Microsoft.ML.Tests/Transformers/CustomMappingTests.cs
Original file line number Diff line number Diff line change
Expand Up @@ -44,8 +44,10 @@ public override Action<MyInput, MyOutput> GetMapping()
}
}

[Fact]
public void TestCustomTransformer()
[Theory]
[InlineData(true)]
[InlineData(false)]
public void TestCustomTransformer(bool registerAssembly)
{
string dataPath = GetDataPath("adult.tiny.with-schema.txt");
var source = new MultiFileSource(dataPath);
Expand All @@ -62,17 +64,13 @@ public void TestCustomTransformer()
var tempoEnv = new MLContext(1);
var customEst = new CustomMappingEstimator<MyInput, MyOutput>(tempoEnv, MyLambda.MyAction, "MyLambda");

try
{
TestEstimatorCore(customEst, data);
Assert.True(false, "Cannot work without RegisterAssembly");
}
catch (InvalidOperationException ex)
{
if (!ex.IsMarked())
throw;
}
ML.ComponentCatalog.RegisterAssembly(typeof(MyLambda).Assembly);

@antoniovs1029 antoniovs1029 Apr 1, 2020

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I wonder, what happens (and what should happen) if the user actually registers the assembly as done here and then tries to load the model? Will it throw an exception, or will it work anyway with the fix on this PR? #Resolved

@harishsk harishsk Apr 1, 2020

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It will work. The assembly can be registered multiple times. #Resolved

@antoniovs1029 antoniovs1029 Apr 1, 2020

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Great.

If anything, I would recommend using the InlineData trick I mentioned in another comment to test both cases: when the user registers the assembly manually (even if it's not necessary) and when they don't register it. #Resolved

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Done in the next iteration.


In reply to: 401794399 [](ancestors = 401794399)

// Before 1.5-preview3 it was required to register the assembly.
// Now, the assembly information is automatically saved in the model and the assembly is registered
// when loading.
// This tests the case that the CustomTransformer still works even if you explicitly register the assembly
if (registerAssembly)
ML.ComponentCatalog.RegisterAssembly(typeof(MyLambda).Assembly);

TestEstimatorCore(customEst, data);
transformedData = customEst.Fit(data).Transform(data);

Expand Down
Binary file added test/data/backcompat/customTransform.zip
Binary file not shown.