Replace SubComponent with IComponentFactory in ML.Ensemble#681

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Merged
eerhardt merged 8 commits into from
Aug 17, 2018
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Replace SubComponent with IComponentFactory in ML.Ensemble #681

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77fff03
Convert Ensemble stacking SubComponent to IComponentFactory.
eerhardt Aug 15, 2018
84119d3
Replace SubComponent with IComponentFactory in ML.Ensemble
eerhardt Aug 15, 2018
7c06f93
Convert SimpleComponentFactory classes to ComponentFactoryUtils stati…
eerhardt Aug 16, 2018
d41dbe6
Move Stacking arguments abstract properties to internal get methods.
eerhardt Aug 16, 2018
6f852cb
Merge remote-tracking branch 'upstream/master' into EnsembleSubComponent
eerhardt Aug 17, 2018
2beb2ce
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eerhardt Aug 17, 2018
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125 changes: 81 additions & 44 deletions src/Microsoft.ML.Core/EntryPoints/ComponentFactory.cs
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Expand Up@@ -37,41 +37,6 @@ public interface IComponentFactory<in TArg1, out TComponent> : IComponentFactory
TComponent CreateComponent(IHostEnvironment env, TArg1 argument1);
}

/// <summary>
/// A class for creating a component when we take one extra parameter
/// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
/// creates the component.
/// </summary>
public class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
{
private Func<IHostEnvironment, TArg1, TComponent> _factory;

public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
{
_factory = factory;
}

public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
{
return _factory(env, argument1);
}
}

public class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
{
private Func<IHostEnvironment, TComponent> _factory;

public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
{
_factory = factory;
}

public TComponent CreateComponent(IHostEnvironment env)
{
return _factory(env);
}
}

/// <summary>
/// An interface for creating a component when we take two extra parameters (and an <see cref="IHostEnvironment"/>).
/// </summary>
Expand All@@ -89,22 +54,94 @@ public interface IComponentFactory<in TArg1, in TArg2, in TArg3, out TComponent>
}

/// <summary>
/// A class for creating a component when we take three extra parameters
/// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
/// creates the component.
/// A utility class for creating <see cref="IComponentFactory"/> instances.
/// </summary>
public class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
public static class ComponentFactoryUtils
{
private Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;
/// <summary>
/// Creates a component factory with no extra parameters (other than an <see cref="IHostEnvironment"/>)
/// that simply wraps a delegate which creates the component.
/// </summary>
public static IComponentFactory<TComponent> CreateFromFunction<TComponent>(Func<IHostEnvironment, TComponent> factory)
{
return new SimpleComponentFactory<TComponent>(factory);
}

/// <summary>
/// Creates a component factory when we take one extra parameter (and an
/// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
/// </summary>
public static IComponentFactory<TArg1, TComponent> CreateFromFunction<TArg1, TComponent>(Func<IHostEnvironment, TArg1, TComponent> factory)
{
return new SimpleComponentFactory<TArg1, TComponent>(factory);
}

/// <summary>
/// Creates a component factory when we take three extra parameters (and an
/// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
/// </summary>
public static IComponentFactory<TArg1, TArg2, TArg3, TComponent> CreateFromFunction<TArg1, TArg2, TArg3, TComponent>(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
{
return new SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent>(factory);
}

public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
/// <summary>
/// A class for creating a component with no extra parameters (other than an <see cref="IHostEnvironment"/>)
/// that simply wraps a delegate which creates the component.
/// </summary>
private sealed class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
{
_factory = factory;
private readonly Func<IHostEnvironment, TComponent> _factory;

public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
{
_factory = factory;
}

public TComponent CreateComponent(IHostEnvironment env)
{
return _factory(env);
}
}

public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
/// <summary>
/// A class for creating a component when we take one extra parameter
/// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
/// creates the component.
/// </summary>
private sealed class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
{
return _factory(env, argument1, argument2, argument3);
private readonly Func<IHostEnvironment, TArg1, TComponent> _factory;

public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
{
_factory = factory;
}

public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
{
return _factory(env, argument1);
}
}

/// <summary>
/// A class for creating a component when we take three extra parameters
/// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
/// creates the component.
/// </summary>
private sealed class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
{
private readonly Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;

public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
{
_factory = factory;
}

public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
{
return _factory(env, argument1, argument2, argument3);
}
}
}
}
2 changes: 1 addition & 1 deletion src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs
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Expand Up@@ -164,7 +164,7 @@ private void RunCore(IChannel ch, string cmd)
new[]
{
new KeyValuePair<string, IComponentFactory<IDataView, IDataTransform>>(
"", new SimpleComponentFactory<IDataView, IDataTransform>(
"", ComponentFactoryUtils.CreateFromFunction<IDataView, IDataTransform>(
(env, input) =>
{
var args = new GenerateNumberTransform.Arguments();
Expand Down
2 changes: 1 addition & 1 deletion src/Microsoft.ML.Data/Commands/ScoreCommand.cs
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Expand Up@@ -330,7 +330,7 @@ public static TScorerFactory GetScorerComponent(
};
}

return new SimpleComponentFactory<IDataView, ISchemaBoundMapper, RoleMappedSchema, IDataScorerTransform>(factoryFunc);
return ComponentFactoryUtils.CreateFromFunction(factoryFunc);
}

/// <summary>
Expand Down
1 change: 1 addition & 0 deletions src/Microsoft.ML.Ensemble/Microsoft.ML.Ensemble.csproj
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Expand Up@@ -10,6 +10,7 @@
<ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
<ProjectReference Include="..\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
<ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />
<ProjectReference Include="..\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />

@TomFinleyTomFinleyAug 15, 2018•
edited by eerhardt
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[](start = 4, length = 84)

We need this due to the usage of FastTree as the default traniner for some ensemble classes. This could be fine, but I wonder if using something from StandardLearners might make a bit more sense, if we envision that someday FastTree will be factored into a separate nuget package. (Maybe we don't want that though, in which case this dependency is probably fine.) #Resolved

@eerhardteerhardtAug 15, 2018•
edited
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One advantage to this change is that it brings to light these dependencies. Before we had a weakly-typed dependency using strings and DI. So if we ever did refactor FastTree to be separate, we could have easily broken this dependency.

I've logged #682 for this issue. #Resolved

@TomFinleyTomFinleyAug 16, 2018•
edited by eerhardt
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Thanks @eerhardt ... yes I expect we'll see some more of this "hidden dependency" becoming exposed as we move away from direct usage of subcomponents and dependency injection. I recall a similar issue in #446 with the normalizers being defined in Microsoft.ML.Transforms and used in Microsoft.ML.Data, despite the former project depending on the latter. 😄 #Resolved

</ItemGroup>

</Project>
2 changes: 1 addition & 1 deletion src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs
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Expand Up@@ -9,7 +9,7 @@

namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
public abstract class BaseScalarStacking<TSigBase> : BaseStacking<Single, TSigBase>
public abstract class BaseScalarStacking : BaseStacking<Single>
{
internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)
: base(env, name, args)
Expand Down
16 changes: 7 additions & 9 deletions src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs
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Expand Up@@ -7,6 +7,7 @@
using System.Threading.Tasks;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
Expand All@@ -15,7 +16,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
using ColumnRole = RoleMappedSchema.ColumnRole;
public abstract class BaseStacking<TOutput, TSigBase> : IStackingTrainer<TOutput>
public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
{
public abstract class ArgumentsBase
{
Expand All@@ -24,13 +25,10 @@ public abstract class ArgumentsBase
[TGUI(Label = "Validation Dataset Proportion")]
public Single ValidationDatasetProportion = 0.3f;

[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
[TGUI(Label = "Base predictor")]
public SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
internal abstract IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> GetPredictorFactory();
}

protected readonly SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
protected readonly IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> BasePredictorType;
protected readonly IHost Host;
protected IPredictorProducing<TOutput> Meta;

Expand All@@ -45,10 +43,10 @@ internal BaseStacking(IHostEnvironment env, string name, ArgumentsBase args)
Host.CheckUserArg(0 <= args.ValidationDatasetProportion && args.ValidationDatasetProportion < 1,
nameof(args.ValidationDatasetProportion),
"The validation proportion for stacking should be greater than or equal to 0 and less than 1");
Host.CheckUserArg(args.BasePredictorType.IsGood(), nameof(args.BasePredictorType));

ValidationDatasetProportion = args.ValidationDatasetProportion;
BasePredictorType = args.BasePredictorType;
BasePredictorType = args.GetPredictorFactory();
Host.CheckValue(BasePredictorType, nameof(BasePredictorType));
}

internal BaseStacking(IHostEnvironment env, string name, ModelLoadContext ctx)
Expand DownExpand Up@@ -187,7 +185,7 @@ public void Train(List<FeatureSubsetModel<IPredictorProducing<TOutput>>> models,
var view = bldr.GetDataView();
var rmd = new RoleMappedData(view, DefaultColumnNames.Label, DefaultColumnNames.Features);

var trainer = BasePredictorType.CreateInstance(host);
var trainer = BasePredictorType.CreateComponent(host);
if (trainer.Info.NeedNormalization)
ch.Warning("The trainer specified for stacking wants normalization, but we do not currently allow this.");
Meta = trainer.Train(rmd);
Expand Down
20 changes: 17 additions & 3 deletions src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs
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Expand Up@@ -8,7 +8,10 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Learners;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -20,7 +23,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
using TVectorPredictor = IPredictorProducing<VBuffer<Single>>;
public sealed class MultiStacking : BaseStacking<VBuffer<Single>, SignatureMultiClassClassifierTrainer>, ICanSaveModel, IMultiClassOutputCombiner
public sealed class MultiStacking : BaseStacking<VBuffer<Single>>, ICanSaveModel, IMultiClassOutputCombiner
{
public const string LoadName = "MultiStacking";
public const string LoaderSignature = "MultiStackingCombiner";
Expand All@@ -38,13 +41,24 @@ private static VersionInfo GetVersionInfo()
[TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory
{
[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
[TGUI(Label = "Base predictor")]
public IComponentFactory<ITrainer<TVectorPredictor>> BasePredictorType;

internal override IComponentFactory<ITrainer<TVectorPredictor>> GetPredictorFactory() => BasePredictorType;

public IMultiClassOutputCombiner CreateComponent(IHostEnvironment env) => new MultiStacking(env, this);

public Arguments()
{
// REVIEW: Perhaps we can have a better non-parametetric learner.
BasePredictorType = new SubComponent<ITrainer<TVectorPredictor>, SignatureMultiClassClassifierTrainer>(
"OVA", "p=FastTreeBinaryClassification");
BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
env => new Ova(env, new Ova.Arguments()
{
PredictorType = ComponentFactoryUtils.CreateFromFunction(
e => new FastTreeBinaryClassificationTrainer(e, new FastTreeBinaryClassificationTrainer.Arguments()))
}));
}
}

Expand Down
14 changes: 12 additions & 2 deletions src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs
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Expand Up@@ -7,6 +7,8 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -19,7 +21,7 @@ namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
using TScalarPredictor = IPredictorProducing<Single>;

public sealed class RegressionStacking : BaseScalarStacking<SignatureRegressorTrainer>, IRegressionOutputCombiner, ICanSaveModel

@TomFinleyTomFinleyAug 15, 2018•
edited by eerhardt
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SignatureRegressorTrainer [](start = 64, length = 25)

What are we going to do about this sort of restriction? I had suggested previously using something like ITrainer<IRegressionPredictor> or something like this, but I'm not sure what you thought of that idea. #Resolved

@eerhardteerhardtAug 16, 2018•
edited
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Which restriction are you referring to? The Signature Type restriction, where we can't use typeof(TSig) in an attribute?

My hope is that some day we remove signature types all together. I haven't thought of/discovered a good replacement for them yet. Maybe an approach similar to ComponentKind which is just a string "Kind".

However, that still wouldn't help in this case, because we need a different signature/kind/etc for each concrete class, but we want to define the argument on the base class. #Resolved

@TomFinleyTomFinleyAug 16, 2018

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I meant just restricting the DI and API usage to only consider actual, in this case, regression trainers, which is one of the functions of the signatures. Currently this is done in a fairly half-hearted fashion using this IPredictorProducing<float> and IPredictorProducing<VBuffer<float>>, but if we got rid of this and replaced it with, say, IRegressionPredictor and IBinaryClassificationPredictor and IMulticlassPredictor (or something like that), then we could just have this be c omponent factory producing ITrainer<IRegressionPredictor> in this case. I think MEF should work well with that restriction as well, from a DI perspective.

In reply to: 210463209 [](ancestors = 210463209)

public sealed class RegressionStacking : BaseScalarStacking, IRegressionOutputCombiner, ICanSaveModel
{
public const string LoadName = "RegressionStacking";
public const string LoaderSignature = "RegressionStacking";
Expand All@@ -37,9 +39,17 @@ private static VersionInfo GetVersionInfo()
[TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory
{
[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
[TGUI(Label = "Base predictor")]
public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

public Arguments()
{
BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureRegressorTrainer>("FastTreeRegression");
BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
env => new FastTreeRegressionTrainer(env, new FastTreeRegressionTrainer.Arguments()));
}

public IRegressionOutputCombiner CreateComponent(IHostEnvironment env) => new RegressionStacking(env, this);
Expand Down
15 changes: 12 additions & 3 deletions src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs
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Expand Up@@ -5,9 +5,10 @@
using System;
using Microsoft.ML.Runtime;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)]
Expand All@@ -16,7 +17,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
using TScalarPredictor = IPredictorProducing<Single>;
public sealed class Stacking : BaseScalarStacking<SignatureBinaryClassifierTrainer>, IBinaryOutputCombiner, ICanSaveModel
public sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner, ICanSaveModel
{
public const string UserName = "Stacking";
public const string LoadName = "Stacking";
Expand All@@ -35,9 +36,17 @@ private static VersionInfo GetVersionInfo()
[TlcModule.Component(Name = LoadName, FriendlyName = UserName)]
public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory
{
[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
[TGUI(Label = "Base predictor")]
public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

public Arguments()
{
BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureBinaryClassifierTrainer>("FastTreeBinaryClassification");
BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
env => new FastTreeBinaryClassificationTrainer(env, new FastTreeBinaryClassificationTrainer.Arguments()));
}

public IBinaryOutputCombiner CreateComponent(IHostEnvironment env) => new Stacking(env, this);
Expand Down
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 Merged

eerhardt
merged 8 commits into

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Aug 17, 2018
 Merged


Replace SubComponent with IComponentFactory in ML.Ensemble
#681
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77fff03

Convert Ensemble stacking SubComponent to IComponentFactory.


eerhardt Aug 15, 2018
84119d3

Replace SubComponent with IComponentFactory in ML.Ensemble


eerhardt Aug 15, 2018
7c06f93

Convert SimpleComponentFactory classes to ComponentFactoryUtils stati…


eerhardt Aug 16, 2018
d41dbe6

Move Stacking arguments abstract properties to internal get methods.


eerhardt Aug 16, 2018
6f852cb

Merge remote-tracking branch 'upstream/master' into EnsembleSubComponent


eerhardt Aug 17, 2018
2beb2ce

PR feedback


eerhardt Aug 17, 2018
4923971

PR Feedback


eerhardt Aug 17, 2018
78a4178

Trigger


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125 changes: 81 additions & 44 deletions
src/Microsoft.ML.Core/EntryPoints/ComponentFactory.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,41 +37,6 @@ public interface IComponentFactory<in TArg1, out TComponent> : IComponentFactory
 TComponent CreateComponent(IHostEnvironment env, TArg1 argument1);
 }

 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 private Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 public class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 private Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 /// <summary>
 /// An interface for creating a component when we take two extra parameters (and an <see cref="IHostEnvironment"/>).
 /// </summary>
Expand All@@ -89,22 +54,94 @@ public interface IComponentFactory<in TArg1, in TArg2, in TArg3, out TComponent>
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// A utility class for creating <see cref="IComponentFactory"/> instances.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 public static class ComponentFactoryUtils
 {
 private Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;
 /// <summary>
 /// Creates a component factory with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TComponent> CreateFromFunction<TComponent>(Func<IHostEnvironment, TComponent> factory)
 {
 return new SimpleComponentFactory<TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take one extra parameter (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TComponent> CreateFromFunction<TArg1, TComponent>(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take three extra parameters (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TArg2, TArg3, TComponent> CreateFromFunction<TArg1, TArg2, TArg3, TComponent>(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent>(factory);
 }

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 /// <summary>
 /// A class for creating a component with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 _factory = factory;
 private readonly Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 return _factory(env, argument1, argument2, argument3);
 private readonly Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 {
 private readonly Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 {
 return _factory(env, argument1, argument2, argument3);
 }
 }
 }
}

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,7 +164,7 @@ private void RunCore(IChannel ch, string cmd)
 new[]
 {
 new KeyValuePair<string, IComponentFactory<IDataView, IDataTransform>>(
 "", new SimpleComponentFactory<IDataView, IDataTransform>(
 "", ComponentFactoryUtils.CreateFromFunction<IDataView, IDataTransform>(
 (env, input) =>
 {
 var args = new GenerateNumberTransform.Arguments();
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/ScoreCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -330,7 +330,7 @@ public static TScorerFactory GetScorerComponent(
 };
 }

 return new SimpleComponentFactory<IDataView, ISchemaBoundMapper, RoleMappedSchema, IDataScorerTransform>(factoryFunc);
 return ComponentFactoryUtils.CreateFromFunction(factoryFunc);
 }

 /// <summary>
Expand Down

1 change: 1 addition & 0 deletions
src/Microsoft.ML.Ensemble/Microsoft.ML.Ensemble.csproj

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Original file line numberDiff line numberDiff line change
Expand Up@@ -10,6 +10,7 @@
 <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
 <ProjectReference Include="..\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
 <ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />
 <ProjectReference Include="..\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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 [](start = 4, length = 84)
We need this due to the usage of FastTree as the default traniner for some ensemble classes. This could be fine, but I wonder if using something from StandardLearners might make a bit more sense, if we envision that someday FastTree will be factored into a separate nuget package. (Maybe we don't want that though, in which case this dependency is probably fine.) #Resolved
@eerhardteerhardtAug 15, 2018•

edited

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One advantage to this change is that it brings to light these dependencies. Before we had a weakly-typed dependency using strings and DI. So if we ever did refactor FastTree to be separate, we could have easily broken this dependency.
I've logged #682 for this issue. #Resolved
@TomFinleyTomFinleyAug 16, 2018•

edited by eerhardt

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Thanks @eerhardt ... yes I expect we'll see some more of this "hidden dependency" becoming exposed as we move away from direct usage of subcomponents and dependency injection. I recall a similar issue in #446 with the normalizers being defined in Microsoft.ML.Transforms and used in Microsoft.ML.Data, despite the former project depending on the latter. 😄 #Resolved
 </ItemGroup>

</Project>

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,7 +9,7 @@

namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 public abstract class BaseScalarStacking<TSigBase> : BaseStacking<Single, TSigBase>
 public abstract class BaseScalarStacking : BaseStacking<Single>
 {
 internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)
 : base(env, name, args)
Expand Down

16 changes: 7 additions & 9 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
using System.Threading.Tasks;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
Expand All@@ -15,7 +16,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using ColumnRole = RoleMappedSchema.ColumnRole;
 public abstract class BaseStacking<TOutput, TSigBase> : IStackingTrainer<TOutput>
 public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
 {
 public abstract class ArgumentsBase
 {
Expand All@@ -24,13 +25,10 @@ public abstract class ArgumentsBase
 [TGUI(Label = "Validation Dataset Proportion")]
 public Single ValidationDatasetProportion = 0.3f;

 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
 [TGUI(Label = "Base predictor")]
 public SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 internal abstract IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> GetPredictorFactory();
 }

 protected readonly SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 protected readonly IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> BasePredictorType;
 protected readonly IHost Host;
 protected IPredictorProducing<TOutput> Meta;

Expand All@@ -45,10 +43,10 @@ internal BaseStacking(IHostEnvironment env, string name, ArgumentsBase args)
 Host.CheckUserArg(0 <= args.ValidationDatasetProportion && args.ValidationDatasetProportion < 1,
 nameof(args.ValidationDatasetProportion),
 "The validation proportion for stacking should be greater than or equal to 0 and less than 1");
 Host.CheckUserArg(args.BasePredictorType.IsGood(), nameof(args.BasePredictorType));

 ValidationDatasetProportion = args.ValidationDatasetProportion;
 BasePredictorType = args.BasePredictorType;
 BasePredictorType = args.GetPredictorFactory();
 Host.CheckValue(BasePredictorType, nameof(BasePredictorType));
 }

 internal BaseStacking(IHostEnvironment env, string name, ModelLoadContext ctx)
Expand DownExpand Up@@ -187,7 +185,7 @@ public void Train(List<FeatureSubsetModel<IPredictorProducing<TOutput>>> models,
 var view = bldr.GetDataView();
 var rmd = new RoleMappedData(view, DefaultColumnNames.Label, DefaultColumnNames.Features);

 var trainer = BasePredictorType.CreateInstance(host);
 var trainer = BasePredictorType.CreateComponent(host);
 if (trainer.Info.NeedNormalization)
 ch.Warning("The trainer specified for stacking wants normalization, but we do not currently allow this.");
 Meta = trainer.Train(rmd);
Expand Down

20 changes: 17 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,7 +8,10 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Learners;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -20,7 +23,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TVectorPredictor = IPredictorProducing<VBuffer<Single>>;
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>, SignatureMultiClassClassifierTrainer>, ICanSaveModel, IMultiClassOutputCombiner
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>>, ICanSaveModel, IMultiClassOutputCombiner
 {
 public const string LoadName = "MultiStacking";
 public const string LoaderSignature = "MultiStackingCombiner";
Expand All@@ -38,13 +41,24 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TVectorPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TVectorPredictor>> GetPredictorFactory() => BasePredictorType;

 public IMultiClassOutputCombiner CreateComponent(IHostEnvironment env) => new MultiStacking(env, this);

 public Arguments()
 {
 // REVIEW: Perhaps we can have a better non-parametetric learner.
 BasePredictorType = new SubComponent<ITrainer<TVectorPredictor>, SignatureMultiClassClassifierTrainer>(
 "OVA", "p=FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new Ova(env, new Ova.Arguments()
 {
 PredictorType = ComponentFactoryUtils.CreateFromFunction(
 e => new FastTreeBinaryClassificationTrainer(e, new FastTreeBinaryClassificationTrainer.Arguments()))
 }));
 }
 }

Expand Down

14 changes: 12 additions & 2 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,8 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -19,7 +21,7 @@ namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;

 public sealed class RegressionStacking : BaseScalarStacking<SignatureRegressorTrainer>, IRegressionOutputCombiner, ICanSaveModel
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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SignatureRegressorTrainer [](start = 64, length = 25)
What are we going to do about this sort of restriction? I had suggested previously using something like ITrainer<IRegressionPredictor> or something like this, but I'm not sure what you thought of that idea. #Resolved
@eerhardteerhardtAug 16, 2018•

edited

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Which restriction are you referring to? The Signature Type restriction, where we can't use typeof(TSig) in an attribute?
My hope is that some day we remove signature types all together. I haven't thought of/discovered a good replacement for them yet. Maybe an approach similar to ComponentKind which is just a string "Kind".
However, that still wouldn't help in this case, because we need a different signature/kind/etc for each concrete class, but we want to define the argument on the base class. #Resolved
@TomFinleyTomFinleyAug 16, 2018

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I meant just restricting the DI and API usage to only consider actual, in this case, regression trainers, which is one of the functions of the signatures. Currently this is done in a fairly half-hearted fashion using this IPredictorProducing<float> and IPredictorProducing<VBuffer<float>>, but if we got rid of this and replaced it with, say, IRegressionPredictor and IBinaryClassificationPredictor and IMulticlassPredictor (or something like that), then we could just have this be c omponent factory producing ITrainer<IRegressionPredictor> in this case. I think MEF should work well with that restriction as well, from a DI perspective.
In reply to: 210463209 [](ancestors = 210463209)
 public sealed class RegressionStacking : BaseScalarStacking, IRegressionOutputCombiner, ICanSaveModel
 {
 public const string LoadName = "RegressionStacking";
 public const string LoaderSignature = "RegressionStacking";
Expand All@@ -37,9 +39,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureRegressorTrainer>("FastTreeRegression");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeRegressionTrainer(env, new FastTreeRegressionTrainer.Arguments()));
 }

 public IRegressionOutputCombiner CreateComponent(IHostEnvironment env) => new RegressionStacking(env, this);
Expand Down

15 changes: 12 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -5,9 +5,10 @@
using System;
using Microsoft.ML.Runtime;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)]
Expand All@@ -16,7 +17,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;
 public sealed class Stacking : BaseScalarStacking<SignatureBinaryClassifierTrainer>, IBinaryOutputCombiner, ICanSaveModel
 public sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner, ICanSaveModel
 {
 public const string UserName = "Stacking";
 public const string LoadName = "Stacking";
Expand All@@ -35,9 +36,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureBinaryClassifierTrainer>("FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeBinaryClassificationTrainer(env, new FastTreeBinaryClassificationTrainer.Arguments()));
 }

 public IBinaryOutputCombiner CreateComponent(IHostEnvironment env) => new Stacking(env, this);
Expand Down
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 Merged

eerhardt
merged 8 commits into

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Aug 17, 2018
 Merged


Replace SubComponent with IComponentFactory in ML.Ensemble
#681
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77fff03

Convert Ensemble stacking SubComponent to IComponentFactory.


eerhardt Aug 15, 2018
84119d3

Replace SubComponent with IComponentFactory in ML.Ensemble


eerhardt Aug 15, 2018
7c06f93

Convert SimpleComponentFactory classes to ComponentFactoryUtils stati…


eerhardt Aug 16, 2018
d41dbe6

Move Stacking arguments abstract properties to internal get methods.


eerhardt Aug 16, 2018
6f852cb

Merge remote-tracking branch 'upstream/master' into EnsembleSubComponent


eerhardt Aug 17, 2018
2beb2ce

PR feedback


eerhardt Aug 17, 2018
4923971

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eerhardt Aug 17, 2018
78a4178

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125 changes: 81 additions & 44 deletions
src/Microsoft.ML.Core/EntryPoints/ComponentFactory.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,41 +37,6 @@ public interface IComponentFactory<in TArg1, out TComponent> : IComponentFactory
 TComponent CreateComponent(IHostEnvironment env, TArg1 argument1);
 }

 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 private Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 public class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 private Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 /// <summary>
 /// An interface for creating a component when we take two extra parameters (and an <see cref="IHostEnvironment"/>).
 /// </summary>
Expand All@@ -89,22 +54,94 @@ public interface IComponentFactory<in TArg1, in TArg2, in TArg3, out TComponent>
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// A utility class for creating <see cref="IComponentFactory"/> instances.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 public static class ComponentFactoryUtils
 {
 private Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;
 /// <summary>
 /// Creates a component factory with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TComponent> CreateFromFunction<TComponent>(Func<IHostEnvironment, TComponent> factory)
 {
 return new SimpleComponentFactory<TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take one extra parameter (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TComponent> CreateFromFunction<TArg1, TComponent>(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take three extra parameters (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TArg2, TArg3, TComponent> CreateFromFunction<TArg1, TArg2, TArg3, TComponent>(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent>(factory);
 }

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 /// <summary>
 /// A class for creating a component with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 _factory = factory;
 private readonly Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 return _factory(env, argument1, argument2, argument3);
 private readonly Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 {
 private readonly Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 {
 return _factory(env, argument1, argument2, argument3);
 }
 }
 }
}

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,7 +164,7 @@ private void RunCore(IChannel ch, string cmd)
 new[]
 {
 new KeyValuePair<string, IComponentFactory<IDataView, IDataTransform>>(
 "", new SimpleComponentFactory<IDataView, IDataTransform>(
 "", ComponentFactoryUtils.CreateFromFunction<IDataView, IDataTransform>(
 (env, input) =>
 {
 var args = new GenerateNumberTransform.Arguments();
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/ScoreCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -330,7 +330,7 @@ public static TScorerFactory GetScorerComponent(
 };
 }

 return new SimpleComponentFactory<IDataView, ISchemaBoundMapper, RoleMappedSchema, IDataScorerTransform>(factoryFunc);
 return ComponentFactoryUtils.CreateFromFunction(factoryFunc);
 }

 /// <summary>
Expand Down

1 change: 1 addition & 0 deletions
src/Microsoft.ML.Ensemble/Microsoft.ML.Ensemble.csproj

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Expand Up@@ -10,6 +10,7 @@
 <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
 <ProjectReference Include="..\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
 <ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />
 <ProjectReference Include="..\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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 [](start = 4, length = 84)
We need this due to the usage of FastTree as the default traniner for some ensemble classes. This could be fine, but I wonder if using something from StandardLearners might make a bit more sense, if we envision that someday FastTree will be factored into a separate nuget package. (Maybe we don't want that though, in which case this dependency is probably fine.) #Resolved
@eerhardteerhardtAug 15, 2018•

edited

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One advantage to this change is that it brings to light these dependencies. Before we had a weakly-typed dependency using strings and DI. So if we ever did refactor FastTree to be separate, we could have easily broken this dependency.
I've logged #682 for this issue. #Resolved
@TomFinleyTomFinleyAug 16, 2018•

edited by eerhardt

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Thanks @eerhardt ... yes I expect we'll see some more of this "hidden dependency" becoming exposed as we move away from direct usage of subcomponents and dependency injection. I recall a similar issue in #446 with the normalizers being defined in Microsoft.ML.Transforms and used in Microsoft.ML.Data, despite the former project depending on the latter. 😄 #Resolved
 </ItemGroup>

</Project>

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,7 +9,7 @@

namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 public abstract class BaseScalarStacking<TSigBase> : BaseStacking<Single, TSigBase>
 public abstract class BaseScalarStacking : BaseStacking<Single>
 {
 internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)
 : base(env, name, args)
Expand Down

16 changes: 7 additions & 9 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
using System.Threading.Tasks;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
Expand All@@ -15,7 +16,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using ColumnRole = RoleMappedSchema.ColumnRole;
 public abstract class BaseStacking<TOutput, TSigBase> : IStackingTrainer<TOutput>
 public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
 {
 public abstract class ArgumentsBase
 {
Expand All@@ -24,13 +25,10 @@ public abstract class ArgumentsBase
 [TGUI(Label = "Validation Dataset Proportion")]
 public Single ValidationDatasetProportion = 0.3f;

 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
 [TGUI(Label = "Base predictor")]
 public SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 internal abstract IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> GetPredictorFactory();
 }

 protected readonly SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 protected readonly IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> BasePredictorType;
 protected readonly IHost Host;
 protected IPredictorProducing<TOutput> Meta;

Expand All@@ -45,10 +43,10 @@ internal BaseStacking(IHostEnvironment env, string name, ArgumentsBase args)
 Host.CheckUserArg(0 <= args.ValidationDatasetProportion && args.ValidationDatasetProportion < 1,
 nameof(args.ValidationDatasetProportion),
 "The validation proportion for stacking should be greater than or equal to 0 and less than 1");
 Host.CheckUserArg(args.BasePredictorType.IsGood(), nameof(args.BasePredictorType));

 ValidationDatasetProportion = args.ValidationDatasetProportion;
 BasePredictorType = args.BasePredictorType;
 BasePredictorType = args.GetPredictorFactory();
 Host.CheckValue(BasePredictorType, nameof(BasePredictorType));
 }

 internal BaseStacking(IHostEnvironment env, string name, ModelLoadContext ctx)
Expand DownExpand Up@@ -187,7 +185,7 @@ public void Train(List<FeatureSubsetModel<IPredictorProducing<TOutput>>> models,
 var view = bldr.GetDataView();
 var rmd = new RoleMappedData(view, DefaultColumnNames.Label, DefaultColumnNames.Features);

 var trainer = BasePredictorType.CreateInstance(host);
 var trainer = BasePredictorType.CreateComponent(host);
 if (trainer.Info.NeedNormalization)
 ch.Warning("The trainer specified for stacking wants normalization, but we do not currently allow this.");
 Meta = trainer.Train(rmd);
Expand Down

20 changes: 17 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,7 +8,10 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Learners;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -20,7 +23,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TVectorPredictor = IPredictorProducing<VBuffer<Single>>;
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>, SignatureMultiClassClassifierTrainer>, ICanSaveModel, IMultiClassOutputCombiner
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>>, ICanSaveModel, IMultiClassOutputCombiner
 {
 public const string LoadName = "MultiStacking";
 public const string LoaderSignature = "MultiStackingCombiner";
Expand All@@ -38,13 +41,24 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TVectorPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TVectorPredictor>> GetPredictorFactory() => BasePredictorType;

 public IMultiClassOutputCombiner CreateComponent(IHostEnvironment env) => new MultiStacking(env, this);

 public Arguments()
 {
 // REVIEW: Perhaps we can have a better non-parametetric learner.
 BasePredictorType = new SubComponent<ITrainer<TVectorPredictor>, SignatureMultiClassClassifierTrainer>(
 "OVA", "p=FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new Ova(env, new Ova.Arguments()
 {
 PredictorType = ComponentFactoryUtils.CreateFromFunction(
 e => new FastTreeBinaryClassificationTrainer(e, new FastTreeBinaryClassificationTrainer.Arguments()))
 }));
 }
 }

Expand Down

14 changes: 12 additions & 2 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,8 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -19,7 +21,7 @@ namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;

 public sealed class RegressionStacking : BaseScalarStacking<SignatureRegressorTrainer>, IRegressionOutputCombiner, ICanSaveModel
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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SignatureRegressorTrainer [](start = 64, length = 25)
What are we going to do about this sort of restriction? I had suggested previously using something like ITrainer<IRegressionPredictor> or something like this, but I'm not sure what you thought of that idea. #Resolved
@eerhardteerhardtAug 16, 2018•

edited

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Which restriction are you referring to? The Signature Type restriction, where we can't use typeof(TSig) in an attribute?
My hope is that some day we remove signature types all together. I haven't thought of/discovered a good replacement for them yet. Maybe an approach similar to ComponentKind which is just a string "Kind".
However, that still wouldn't help in this case, because we need a different signature/kind/etc for each concrete class, but we want to define the argument on the base class. #Resolved
@TomFinleyTomFinleyAug 16, 2018

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I meant just restricting the DI and API usage to only consider actual, in this case, regression trainers, which is one of the functions of the signatures. Currently this is done in a fairly half-hearted fashion using this IPredictorProducing<float> and IPredictorProducing<VBuffer<float>>, but if we got rid of this and replaced it with, say, IRegressionPredictor and IBinaryClassificationPredictor and IMulticlassPredictor (or something like that), then we could just have this be c omponent factory producing ITrainer<IRegressionPredictor> in this case. I think MEF should work well with that restriction as well, from a DI perspective.
In reply to: 210463209 [](ancestors = 210463209)
 public sealed class RegressionStacking : BaseScalarStacking, IRegressionOutputCombiner, ICanSaveModel
 {
 public const string LoadName = "RegressionStacking";
 public const string LoaderSignature = "RegressionStacking";
Expand All@@ -37,9 +39,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureRegressorTrainer>("FastTreeRegression");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeRegressionTrainer(env, new FastTreeRegressionTrainer.Arguments()));
 }

 public IRegressionOutputCombiner CreateComponent(IHostEnvironment env) => new RegressionStacking(env, this);
Expand Down

15 changes: 12 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -5,9 +5,10 @@
using System;
using Microsoft.ML.Runtime;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)]
Expand All@@ -16,7 +17,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;
 public sealed class Stacking : BaseScalarStacking<SignatureBinaryClassifierTrainer>, IBinaryOutputCombiner, ICanSaveModel
 public sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner, ICanSaveModel
 {
 public const string UserName = "Stacking";
 public const string LoadName = "Stacking";
Expand All@@ -35,9 +36,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureBinaryClassifierTrainer>("FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeBinaryClassificationTrainer(env, new FastTreeBinaryClassificationTrainer.Arguments()));
 }

 public IBinaryOutputCombiner CreateComponent(IHostEnvironment env) => new Stacking(env, this);
Expand Down
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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");
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} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
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var __m = "*";
var __re = new RegExp('^' + ".*" + '

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 Merged

eerhardt
merged 8 commits into

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Aug 17, 2018
 Merged


Replace SubComponent with IComponentFactory in ML.Ensemble
#681
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77fff03

Convert Ensemble stacking SubComponent to IComponentFactory.


eerhardt Aug 15, 2018
84119d3

Replace SubComponent with IComponentFactory in ML.Ensemble


eerhardt Aug 15, 2018
7c06f93

Convert SimpleComponentFactory classes to ComponentFactoryUtils stati…


eerhardt Aug 16, 2018
d41dbe6

Move Stacking arguments abstract properties to internal get methods.


eerhardt Aug 16, 2018
6f852cb

Merge remote-tracking branch 'upstream/master' into EnsembleSubComponent


eerhardt Aug 17, 2018
2beb2ce

PR feedback


eerhardt Aug 17, 2018
4923971

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125 changes: 81 additions & 44 deletions
src/Microsoft.ML.Core/EntryPoints/ComponentFactory.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,41 +37,6 @@ public interface IComponentFactory<in TArg1, out TComponent> : IComponentFactory
 TComponent CreateComponent(IHostEnvironment env, TArg1 argument1);
 }

 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 private Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 public class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 private Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 /// <summary>
 /// An interface for creating a component when we take two extra parameters (and an <see cref="IHostEnvironment"/>).
 /// </summary>
Expand All@@ -89,22 +54,94 @@ public interface IComponentFactory<in TArg1, in TArg2, in TArg3, out TComponent>
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// A utility class for creating <see cref="IComponentFactory"/> instances.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 public static class ComponentFactoryUtils
 {
 private Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;
 /// <summary>
 /// Creates a component factory with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TComponent> CreateFromFunction<TComponent>(Func<IHostEnvironment, TComponent> factory)
 {
 return new SimpleComponentFactory<TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take one extra parameter (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TComponent> CreateFromFunction<TArg1, TComponent>(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take three extra parameters (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TArg2, TArg3, TComponent> CreateFromFunction<TArg1, TArg2, TArg3, TComponent>(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent>(factory);
 }

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 /// <summary>
 /// A class for creating a component with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 _factory = factory;
 private readonly Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 return _factory(env, argument1, argument2, argument3);
 private readonly Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 {
 private readonly Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 {
 return _factory(env, argument1, argument2, argument3);
 }
 }
 }
}

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,7 +164,7 @@ private void RunCore(IChannel ch, string cmd)
 new[]
 {
 new KeyValuePair<string, IComponentFactory<IDataView, IDataTransform>>(
 "", new SimpleComponentFactory<IDataView, IDataTransform>(
 "", ComponentFactoryUtils.CreateFromFunction<IDataView, IDataTransform>(
 (env, input) =>
 {
 var args = new GenerateNumberTransform.Arguments();
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/ScoreCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -330,7 +330,7 @@ public static TScorerFactory GetScorerComponent(
 };
 }

 return new SimpleComponentFactory<IDataView, ISchemaBoundMapper, RoleMappedSchema, IDataScorerTransform>(factoryFunc);
 return ComponentFactoryUtils.CreateFromFunction(factoryFunc);
 }

 /// <summary>
Expand Down

1 change: 1 addition & 0 deletions
src/Microsoft.ML.Ensemble/Microsoft.ML.Ensemble.csproj

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Original file line numberDiff line numberDiff line change
Expand Up@@ -10,6 +10,7 @@
 <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
 <ProjectReference Include="..\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
 <ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />
 <ProjectReference Include="..\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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 [](start = 4, length = 84)
We need this due to the usage of FastTree as the default traniner for some ensemble classes. This could be fine, but I wonder if using something from StandardLearners might make a bit more sense, if we envision that someday FastTree will be factored into a separate nuget package. (Maybe we don't want that though, in which case this dependency is probably fine.) #Resolved
@eerhardteerhardtAug 15, 2018•

edited

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One advantage to this change is that it brings to light these dependencies. Before we had a weakly-typed dependency using strings and DI. So if we ever did refactor FastTree to be separate, we could have easily broken this dependency.
I've logged #682 for this issue. #Resolved
@TomFinleyTomFinleyAug 16, 2018•

edited by eerhardt

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Thanks @eerhardt ... yes I expect we'll see some more of this "hidden dependency" becoming exposed as we move away from direct usage of subcomponents and dependency injection. I recall a similar issue in #446 with the normalizers being defined in Microsoft.ML.Transforms and used in Microsoft.ML.Data, despite the former project depending on the latter. 😄 #Resolved
 </ItemGroup>

</Project>

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,7 +9,7 @@

namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 public abstract class BaseScalarStacking<TSigBase> : BaseStacking<Single, TSigBase>
 public abstract class BaseScalarStacking : BaseStacking<Single>
 {
 internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)
 : base(env, name, args)
Expand Down

16 changes: 7 additions & 9 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
using System.Threading.Tasks;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
Expand All@@ -15,7 +16,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using ColumnRole = RoleMappedSchema.ColumnRole;
 public abstract class BaseStacking<TOutput, TSigBase> : IStackingTrainer<TOutput>
 public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
 {
 public abstract class ArgumentsBase
 {
Expand All@@ -24,13 +25,10 @@ public abstract class ArgumentsBase
 [TGUI(Label = "Validation Dataset Proportion")]
 public Single ValidationDatasetProportion = 0.3f;

 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
 [TGUI(Label = "Base predictor")]
 public SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 internal abstract IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> GetPredictorFactory();
 }

 protected readonly SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 protected readonly IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> BasePredictorType;
 protected readonly IHost Host;
 protected IPredictorProducing<TOutput> Meta;

Expand All@@ -45,10 +43,10 @@ internal BaseStacking(IHostEnvironment env, string name, ArgumentsBase args)
 Host.CheckUserArg(0 <= args.ValidationDatasetProportion && args.ValidationDatasetProportion < 1,
 nameof(args.ValidationDatasetProportion),
 "The validation proportion for stacking should be greater than or equal to 0 and less than 1");
 Host.CheckUserArg(args.BasePredictorType.IsGood(), nameof(args.BasePredictorType));

 ValidationDatasetProportion = args.ValidationDatasetProportion;
 BasePredictorType = args.BasePredictorType;
 BasePredictorType = args.GetPredictorFactory();
 Host.CheckValue(BasePredictorType, nameof(BasePredictorType));
 }

 internal BaseStacking(IHostEnvironment env, string name, ModelLoadContext ctx)
Expand DownExpand Up@@ -187,7 +185,7 @@ public void Train(List<FeatureSubsetModel<IPredictorProducing<TOutput>>> models,
 var view = bldr.GetDataView();
 var rmd = new RoleMappedData(view, DefaultColumnNames.Label, DefaultColumnNames.Features);

 var trainer = BasePredictorType.CreateInstance(host);
 var trainer = BasePredictorType.CreateComponent(host);
 if (trainer.Info.NeedNormalization)
 ch.Warning("The trainer specified for stacking wants normalization, but we do not currently allow this.");
 Meta = trainer.Train(rmd);
Expand Down

20 changes: 17 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,7 +8,10 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Learners;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -20,7 +23,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TVectorPredictor = IPredictorProducing<VBuffer<Single>>;
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>, SignatureMultiClassClassifierTrainer>, ICanSaveModel, IMultiClassOutputCombiner
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>>, ICanSaveModel, IMultiClassOutputCombiner
 {
 public const string LoadName = "MultiStacking";
 public const string LoaderSignature = "MultiStackingCombiner";
Expand All@@ -38,13 +41,24 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TVectorPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TVectorPredictor>> GetPredictorFactory() => BasePredictorType;

 public IMultiClassOutputCombiner CreateComponent(IHostEnvironment env) => new MultiStacking(env, this);

 public Arguments()
 {
 // REVIEW: Perhaps we can have a better non-parametetric learner.
 BasePredictorType = new SubComponent<ITrainer<TVectorPredictor>, SignatureMultiClassClassifierTrainer>(
 "OVA", "p=FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new Ova(env, new Ova.Arguments()
 {
 PredictorType = ComponentFactoryUtils.CreateFromFunction(
 e => new FastTreeBinaryClassificationTrainer(e, new FastTreeBinaryClassificationTrainer.Arguments()))
 }));
 }
 }

Expand Down

14 changes: 12 additions & 2 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,8 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -19,7 +21,7 @@ namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;

 public sealed class RegressionStacking : BaseScalarStacking<SignatureRegressorTrainer>, IRegressionOutputCombiner, ICanSaveModel
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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SignatureRegressorTrainer [](start = 64, length = 25)
What are we going to do about this sort of restriction? I had suggested previously using something like ITrainer<IRegressionPredictor> or something like this, but I'm not sure what you thought of that idea. #Resolved
@eerhardteerhardtAug 16, 2018•

edited

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Which restriction are you referring to? The Signature Type restriction, where we can't use typeof(TSig) in an attribute?
My hope is that some day we remove signature types all together. I haven't thought of/discovered a good replacement for them yet. Maybe an approach similar to ComponentKind which is just a string "Kind".
However, that still wouldn't help in this case, because we need a different signature/kind/etc for each concrete class, but we want to define the argument on the base class. #Resolved
@TomFinleyTomFinleyAug 16, 2018

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I meant just restricting the DI and API usage to only consider actual, in this case, regression trainers, which is one of the functions of the signatures. Currently this is done in a fairly half-hearted fashion using this IPredictorProducing<float> and IPredictorProducing<VBuffer<float>>, but if we got rid of this and replaced it with, say, IRegressionPredictor and IBinaryClassificationPredictor and IMulticlassPredictor (or something like that), then we could just have this be c omponent factory producing ITrainer<IRegressionPredictor> in this case. I think MEF should work well with that restriction as well, from a DI perspective.
In reply to: 210463209 [](ancestors = 210463209)
 public sealed class RegressionStacking : BaseScalarStacking, IRegressionOutputCombiner, ICanSaveModel
 {
 public const string LoadName = "RegressionStacking";
 public const string LoaderSignature = "RegressionStacking";
Expand All@@ -37,9 +39,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureRegressorTrainer>("FastTreeRegression");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeRegressionTrainer(env, new FastTreeRegressionTrainer.Arguments()));
 }

 public IRegressionOutputCombiner CreateComponent(IHostEnvironment env) => new RegressionStacking(env, this);
Expand Down

15 changes: 12 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -5,9 +5,10 @@
using System;
using Microsoft.ML.Runtime;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)]
Expand All@@ -16,7 +17,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;
 public sealed class Stacking : BaseScalarStacking<SignatureBinaryClassifierTrainer>, IBinaryOutputCombiner, ICanSaveModel
 public sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner, ICanSaveModel
 {
 public const string UserName = "Stacking";
 public const string LoadName = "Stacking";
Expand All@@ -35,9 +36,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureBinaryClassifierTrainer>("FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeBinaryClassificationTrainer(env, new FastTreeBinaryClassificationTrainer.Arguments()));
 }

 public IBinaryOutputCombiner CreateComponent(IHostEnvironment env) => new Stacking(env, this);
Expand Down
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, '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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 Merged

eerhardt
merged 8 commits into

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Aug 17, 2018
 Merged


Replace SubComponent with IComponentFactory in ML.Ensemble
#681
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77fff03

Convert Ensemble stacking SubComponent to IComponentFactory.


eerhardt Aug 15, 2018
84119d3

Replace SubComponent with IComponentFactory in ML.Ensemble


eerhardt Aug 15, 2018
7c06f93

Convert SimpleComponentFactory classes to ComponentFactoryUtils stati…


eerhardt Aug 16, 2018
d41dbe6

Move Stacking arguments abstract properties to internal get methods.


eerhardt Aug 16, 2018
6f852cb

Merge remote-tracking branch 'upstream/master' into EnsembleSubComponent


eerhardt Aug 17, 2018
2beb2ce

PR feedback


eerhardt Aug 17, 2018
4923971

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125 changes: 81 additions & 44 deletions
src/Microsoft.ML.Core/EntryPoints/ComponentFactory.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,41 +37,6 @@ public interface IComponentFactory<in TArg1, out TComponent> : IComponentFactory
 TComponent CreateComponent(IHostEnvironment env, TArg1 argument1);
 }

 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 private Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 public class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 private Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 /// <summary>
 /// An interface for creating a component when we take two extra parameters (and an <see cref="IHostEnvironment"/>).
 /// </summary>
Expand All@@ -89,22 +54,94 @@ public interface IComponentFactory<in TArg1, in TArg2, in TArg3, out TComponent>
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// A utility class for creating <see cref="IComponentFactory"/> instances.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 public static class ComponentFactoryUtils
 {
 private Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;
 /// <summary>
 /// Creates a component factory with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TComponent> CreateFromFunction<TComponent>(Func<IHostEnvironment, TComponent> factory)
 {
 return new SimpleComponentFactory<TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take one extra parameter (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TComponent> CreateFromFunction<TArg1, TComponent>(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take three extra parameters (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TArg2, TArg3, TComponent> CreateFromFunction<TArg1, TArg2, TArg3, TComponent>(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent>(factory);
 }

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 /// <summary>
 /// A class for creating a component with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 _factory = factory;
 private readonly Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 return _factory(env, argument1, argument2, argument3);
 private readonly Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 {
 private readonly Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 {
 return _factory(env, argument1, argument2, argument3);
 }
 }
 }
}

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,7 +164,7 @@ private void RunCore(IChannel ch, string cmd)
 new[]
 {
 new KeyValuePair<string, IComponentFactory<IDataView, IDataTransform>>(
 "", new SimpleComponentFactory<IDataView, IDataTransform>(
 "", ComponentFactoryUtils.CreateFromFunction<IDataView, IDataTransform>(
 (env, input) =>
 {
 var args = new GenerateNumberTransform.Arguments();
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/ScoreCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -330,7 +330,7 @@ public static TScorerFactory GetScorerComponent(
 };
 }

 return new SimpleComponentFactory<IDataView, ISchemaBoundMapper, RoleMappedSchema, IDataScorerTransform>(factoryFunc);
 return ComponentFactoryUtils.CreateFromFunction(factoryFunc);
 }

 /// <summary>
Expand Down

1 change: 1 addition & 0 deletions
src/Microsoft.ML.Ensemble/Microsoft.ML.Ensemble.csproj

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Original file line numberDiff line numberDiff line change
Expand Up@@ -10,6 +10,7 @@
 <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
 <ProjectReference Include="..\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
 <ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />
 <ProjectReference Include="..\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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 [](start = 4, length = 84)
We need this due to the usage of FastTree as the default traniner for some ensemble classes. This could be fine, but I wonder if using something from StandardLearners might make a bit more sense, if we envision that someday FastTree will be factored into a separate nuget package. (Maybe we don't want that though, in which case this dependency is probably fine.) #Resolved
@eerhardteerhardtAug 15, 2018•

edited

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One advantage to this change is that it brings to light these dependencies. Before we had a weakly-typed dependency using strings and DI. So if we ever did refactor FastTree to be separate, we could have easily broken this dependency.
I've logged #682 for this issue. #Resolved
@TomFinleyTomFinleyAug 16, 2018•

edited by eerhardt

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Thanks @eerhardt ... yes I expect we'll see some more of this "hidden dependency" becoming exposed as we move away from direct usage of subcomponents and dependency injection. I recall a similar issue in #446 with the normalizers being defined in Microsoft.ML.Transforms and used in Microsoft.ML.Data, despite the former project depending on the latter. 😄 #Resolved
 </ItemGroup>

</Project>

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,7 +9,7 @@

namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 public abstract class BaseScalarStacking<TSigBase> : BaseStacking<Single, TSigBase>
 public abstract class BaseScalarStacking : BaseStacking<Single>
 {
 internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)
 : base(env, name, args)
Expand Down

16 changes: 7 additions & 9 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
using System.Threading.Tasks;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
Expand All@@ -15,7 +16,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using ColumnRole = RoleMappedSchema.ColumnRole;
 public abstract class BaseStacking<TOutput, TSigBase> : IStackingTrainer<TOutput>
 public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
 {
 public abstract class ArgumentsBase
 {
Expand All@@ -24,13 +25,10 @@ public abstract class ArgumentsBase
 [TGUI(Label = "Validation Dataset Proportion")]
 public Single ValidationDatasetProportion = 0.3f;

 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
 [TGUI(Label = "Base predictor")]
 public SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 internal abstract IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> GetPredictorFactory();
 }

 protected readonly SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 protected readonly IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> BasePredictorType;
 protected readonly IHost Host;
 protected IPredictorProducing<TOutput> Meta;

Expand All@@ -45,10 +43,10 @@ internal BaseStacking(IHostEnvironment env, string name, ArgumentsBase args)
 Host.CheckUserArg(0 <= args.ValidationDatasetProportion && args.ValidationDatasetProportion < 1,
 nameof(args.ValidationDatasetProportion),
 "The validation proportion for stacking should be greater than or equal to 0 and less than 1");
 Host.CheckUserArg(args.BasePredictorType.IsGood(), nameof(args.BasePredictorType));

 ValidationDatasetProportion = args.ValidationDatasetProportion;
 BasePredictorType = args.BasePredictorType;
 BasePredictorType = args.GetPredictorFactory();
 Host.CheckValue(BasePredictorType, nameof(BasePredictorType));
 }

 internal BaseStacking(IHostEnvironment env, string name, ModelLoadContext ctx)
Expand DownExpand Up@@ -187,7 +185,7 @@ public void Train(List<FeatureSubsetModel<IPredictorProducing<TOutput>>> models,
 var view = bldr.GetDataView();
 var rmd = new RoleMappedData(view, DefaultColumnNames.Label, DefaultColumnNames.Features);

 var trainer = BasePredictorType.CreateInstance(host);
 var trainer = BasePredictorType.CreateComponent(host);
 if (trainer.Info.NeedNormalization)
 ch.Warning("The trainer specified for stacking wants normalization, but we do not currently allow this.");
 Meta = trainer.Train(rmd);
Expand Down

20 changes: 17 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,7 +8,10 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Learners;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -20,7 +23,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TVectorPredictor = IPredictorProducing<VBuffer<Single>>;
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>, SignatureMultiClassClassifierTrainer>, ICanSaveModel, IMultiClassOutputCombiner
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>>, ICanSaveModel, IMultiClassOutputCombiner
 {
 public const string LoadName = "MultiStacking";
 public const string LoaderSignature = "MultiStackingCombiner";
Expand All@@ -38,13 +41,24 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TVectorPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TVectorPredictor>> GetPredictorFactory() => BasePredictorType;

 public IMultiClassOutputCombiner CreateComponent(IHostEnvironment env) => new MultiStacking(env, this);

 public Arguments()
 {
 // REVIEW: Perhaps we can have a better non-parametetric learner.
 BasePredictorType = new SubComponent<ITrainer<TVectorPredictor>, SignatureMultiClassClassifierTrainer>(
 "OVA", "p=FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new Ova(env, new Ova.Arguments()
 {
 PredictorType = ComponentFactoryUtils.CreateFromFunction(
 e => new FastTreeBinaryClassificationTrainer(e, new FastTreeBinaryClassificationTrainer.Arguments()))
 }));
 }
 }

Expand Down

14 changes: 12 additions & 2 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,8 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -19,7 +21,7 @@ namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;

 public sealed class RegressionStacking : BaseScalarStacking<SignatureRegressorTrainer>, IRegressionOutputCombiner, ICanSaveModel
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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SignatureRegressorTrainer [](start = 64, length = 25)
What are we going to do about this sort of restriction? I had suggested previously using something like ITrainer<IRegressionPredictor> or something like this, but I'm not sure what you thought of that idea. #Resolved
@eerhardteerhardtAug 16, 2018•

edited

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Which restriction are you referring to? The Signature Type restriction, where we can't use typeof(TSig) in an attribute?
My hope is that some day we remove signature types all together. I haven't thought of/discovered a good replacement for them yet. Maybe an approach similar to ComponentKind which is just a string "Kind".
However, that still wouldn't help in this case, because we need a different signature/kind/etc for each concrete class, but we want to define the argument on the base class. #Resolved
@TomFinleyTomFinleyAug 16, 2018

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I meant just restricting the DI and API usage to only consider actual, in this case, regression trainers, which is one of the functions of the signatures. Currently this is done in a fairly half-hearted fashion using this IPredictorProducing<float> and IPredictorProducing<VBuffer<float>>, but if we got rid of this and replaced it with, say, IRegressionPredictor and IBinaryClassificationPredictor and IMulticlassPredictor (or something like that), then we could just have this be c omponent factory producing ITrainer<IRegressionPredictor> in this case. I think MEF should work well with that restriction as well, from a DI perspective.
In reply to: 210463209 [](ancestors = 210463209)
 public sealed class RegressionStacking : BaseScalarStacking, IRegressionOutputCombiner, ICanSaveModel
 {
 public const string LoadName = "RegressionStacking";
 public const string LoaderSignature = "RegressionStacking";
Expand All@@ -37,9 +39,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureRegressorTrainer>("FastTreeRegression");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeRegressionTrainer(env, new FastTreeRegressionTrainer.Arguments()));
 }

 public IRegressionOutputCombiner CreateComponent(IHostEnvironment env) => new RegressionStacking(env, this);
Expand Down

15 changes: 12 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -5,9 +5,10 @@
using System;
using Microsoft.ML.Runtime;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)]
Expand All@@ -16,7 +17,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;
 public sealed class Stacking : BaseScalarStacking<SignatureBinaryClassifierTrainer>, IBinaryOutputCombiner, ICanSaveModel
 public sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner, ICanSaveModel
 {
 public const string UserName = "Stacking";
 public const string LoadName = "Stacking";
Expand All@@ -35,9 +36,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureBinaryClassifierTrainer>("FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeBinaryClassificationTrainer(env, new FastTreeBinaryClassificationTrainer.Arguments()));
 }

 public IBinaryOutputCombiner CreateComponent(IHostEnvironment env) => new Stacking(env, this);
Expand Down
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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");
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var __m = "*";
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 Merged

eerhardt
merged 8 commits into

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Aug 17, 2018
 Merged


Replace SubComponent with IComponentFactory in ML.Ensemble
#681
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77fff03

Convert Ensemble stacking SubComponent to IComponentFactory.


eerhardt Aug 15, 2018
84119d3

Replace SubComponent with IComponentFactory in ML.Ensemble


eerhardt Aug 15, 2018
7c06f93

Convert SimpleComponentFactory classes to ComponentFactoryUtils stati…


eerhardt Aug 16, 2018
d41dbe6

Move Stacking arguments abstract properties to internal get methods.


eerhardt Aug 16, 2018
6f852cb

Merge remote-tracking branch 'upstream/master' into EnsembleSubComponent


eerhardt Aug 17, 2018
2beb2ce

PR feedback


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125 changes: 81 additions & 44 deletions
src/Microsoft.ML.Core/EntryPoints/ComponentFactory.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,41 +37,6 @@ public interface IComponentFactory<in TArg1, out TComponent> : IComponentFactory
 TComponent CreateComponent(IHostEnvironment env, TArg1 argument1);
 }

 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 private Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 public class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 private Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 /// <summary>
 /// An interface for creating a component when we take two extra parameters (and an <see cref="IHostEnvironment"/>).
 /// </summary>
Expand All@@ -89,22 +54,94 @@ public interface IComponentFactory<in TArg1, in TArg2, in TArg3, out TComponent>
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// A utility class for creating <see cref="IComponentFactory"/> instances.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 public static class ComponentFactoryUtils
 {
 private Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;
 /// <summary>
 /// Creates a component factory with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TComponent> CreateFromFunction<TComponent>(Func<IHostEnvironment, TComponent> factory)
 {
 return new SimpleComponentFactory<TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take one extra parameter (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TComponent> CreateFromFunction<TArg1, TComponent>(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take three extra parameters (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TArg2, TArg3, TComponent> CreateFromFunction<TArg1, TArg2, TArg3, TComponent>(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent>(factory);
 }

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 /// <summary>
 /// A class for creating a component with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 _factory = factory;
 private readonly Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 return _factory(env, argument1, argument2, argument3);
 private readonly Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 {
 private readonly Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 {
 return _factory(env, argument1, argument2, argument3);
 }
 }
 }
}

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,7 +164,7 @@ private void RunCore(IChannel ch, string cmd)
 new[]
 {
 new KeyValuePair<string, IComponentFactory<IDataView, IDataTransform>>(
 "", new SimpleComponentFactory<IDataView, IDataTransform>(
 "", ComponentFactoryUtils.CreateFromFunction<IDataView, IDataTransform>(
 (env, input) =>
 {
 var args = new GenerateNumberTransform.Arguments();
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/ScoreCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -330,7 +330,7 @@ public static TScorerFactory GetScorerComponent(
 };
 }

 return new SimpleComponentFactory<IDataView, ISchemaBoundMapper, RoleMappedSchema, IDataScorerTransform>(factoryFunc);
 return ComponentFactoryUtils.CreateFromFunction(factoryFunc);
 }

 /// <summary>
Expand Down

1 change: 1 addition & 0 deletions
src/Microsoft.ML.Ensemble/Microsoft.ML.Ensemble.csproj

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Original file line numberDiff line numberDiff line change
Expand Up@@ -10,6 +10,7 @@
 <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
 <ProjectReference Include="..\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
 <ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />
 <ProjectReference Include="..\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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 [](start = 4, length = 84)
We need this due to the usage of FastTree as the default traniner for some ensemble classes. This could be fine, but I wonder if using something from StandardLearners might make a bit more sense, if we envision that someday FastTree will be factored into a separate nuget package. (Maybe we don't want that though, in which case this dependency is probably fine.) #Resolved
@eerhardteerhardtAug 15, 2018•

edited

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One advantage to this change is that it brings to light these dependencies. Before we had a weakly-typed dependency using strings and DI. So if we ever did refactor FastTree to be separate, we could have easily broken this dependency.
I've logged #682 for this issue. #Resolved
@TomFinleyTomFinleyAug 16, 2018•

edited by eerhardt

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Thanks @eerhardt ... yes I expect we'll see some more of this "hidden dependency" becoming exposed as we move away from direct usage of subcomponents and dependency injection. I recall a similar issue in #446 with the normalizers being defined in Microsoft.ML.Transforms and used in Microsoft.ML.Data, despite the former project depending on the latter. 😄 #Resolved
 </ItemGroup>

</Project>

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,7 +9,7 @@

namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 public abstract class BaseScalarStacking<TSigBase> : BaseStacking<Single, TSigBase>
 public abstract class BaseScalarStacking : BaseStacking<Single>
 {
 internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)
 : base(env, name, args)
Expand Down

16 changes: 7 additions & 9 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
using System.Threading.Tasks;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
Expand All@@ -15,7 +16,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using ColumnRole = RoleMappedSchema.ColumnRole;
 public abstract class BaseStacking<TOutput, TSigBase> : IStackingTrainer<TOutput>
 public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
 {
 public abstract class ArgumentsBase
 {
Expand All@@ -24,13 +25,10 @@ public abstract class ArgumentsBase
 [TGUI(Label = "Validation Dataset Proportion")]
 public Single ValidationDatasetProportion = 0.3f;

 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
 [TGUI(Label = "Base predictor")]
 public SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 internal abstract IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> GetPredictorFactory();
 }

 protected readonly SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 protected readonly IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> BasePredictorType;
 protected readonly IHost Host;
 protected IPredictorProducing<TOutput> Meta;

Expand All@@ -45,10 +43,10 @@ internal BaseStacking(IHostEnvironment env, string name, ArgumentsBase args)
 Host.CheckUserArg(0 <= args.ValidationDatasetProportion && args.ValidationDatasetProportion < 1,
 nameof(args.ValidationDatasetProportion),
 "The validation proportion for stacking should be greater than or equal to 0 and less than 1");
 Host.CheckUserArg(args.BasePredictorType.IsGood(), nameof(args.BasePredictorType));

 ValidationDatasetProportion = args.ValidationDatasetProportion;
 BasePredictorType = args.BasePredictorType;
 BasePredictorType = args.GetPredictorFactory();
 Host.CheckValue(BasePredictorType, nameof(BasePredictorType));
 }

 internal BaseStacking(IHostEnvironment env, string name, ModelLoadContext ctx)
Expand DownExpand Up@@ -187,7 +185,7 @@ public void Train(List<FeatureSubsetModel<IPredictorProducing<TOutput>>> models,
 var view = bldr.GetDataView();
 var rmd = new RoleMappedData(view, DefaultColumnNames.Label, DefaultColumnNames.Features);

 var trainer = BasePredictorType.CreateInstance(host);
 var trainer = BasePredictorType.CreateComponent(host);
 if (trainer.Info.NeedNormalization)
 ch.Warning("The trainer specified for stacking wants normalization, but we do not currently allow this.");
 Meta = trainer.Train(rmd);
Expand Down

20 changes: 17 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,7 +8,10 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Learners;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -20,7 +23,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TVectorPredictor = IPredictorProducing<VBuffer<Single>>;
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>, SignatureMultiClassClassifierTrainer>, ICanSaveModel, IMultiClassOutputCombiner
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>>, ICanSaveModel, IMultiClassOutputCombiner
 {
 public const string LoadName = "MultiStacking";
 public const string LoaderSignature = "MultiStackingCombiner";
Expand All@@ -38,13 +41,24 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TVectorPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TVectorPredictor>> GetPredictorFactory() => BasePredictorType;

 public IMultiClassOutputCombiner CreateComponent(IHostEnvironment env) => new MultiStacking(env, this);

 public Arguments()
 {
 // REVIEW: Perhaps we can have a better non-parametetric learner.
 BasePredictorType = new SubComponent<ITrainer<TVectorPredictor>, SignatureMultiClassClassifierTrainer>(
 "OVA", "p=FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new Ova(env, new Ova.Arguments()
 {
 PredictorType = ComponentFactoryUtils.CreateFromFunction(
 e => new FastTreeBinaryClassificationTrainer(e, new FastTreeBinaryClassificationTrainer.Arguments()))
 }));
 }
 }

Expand Down

14 changes: 12 additions & 2 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,8 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -19,7 +21,7 @@ namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;

 public sealed class RegressionStacking : BaseScalarStacking<SignatureRegressorTrainer>, IRegressionOutputCombiner, ICanSaveModel
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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SignatureRegressorTrainer [](start = 64, length = 25)
What are we going to do about this sort of restriction? I had suggested previously using something like ITrainer<IRegressionPredictor> or something like this, but I'm not sure what you thought of that idea. #Resolved
@eerhardteerhardtAug 16, 2018•

edited

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Which restriction are you referring to? The Signature Type restriction, where we can't use typeof(TSig) in an attribute?
My hope is that some day we remove signature types all together. I haven't thought of/discovered a good replacement for them yet. Maybe an approach similar to ComponentKind which is just a string "Kind".
However, that still wouldn't help in this case, because we need a different signature/kind/etc for each concrete class, but we want to define the argument on the base class. #Resolved
@TomFinleyTomFinleyAug 16, 2018

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I meant just restricting the DI and API usage to only consider actual, in this case, regression trainers, which is one of the functions of the signatures. Currently this is done in a fairly half-hearted fashion using this IPredictorProducing<float> and IPredictorProducing<VBuffer<float>>, but if we got rid of this and replaced it with, say, IRegressionPredictor and IBinaryClassificationPredictor and IMulticlassPredictor (or something like that), then we could just have this be c omponent factory producing ITrainer<IRegressionPredictor> in this case. I think MEF should work well with that restriction as well, from a DI perspective.
In reply to: 210463209 [](ancestors = 210463209)
 public sealed class RegressionStacking : BaseScalarStacking, IRegressionOutputCombiner, ICanSaveModel
 {
 public const string LoadName = "RegressionStacking";
 public const string LoaderSignature = "RegressionStacking";
Expand All@@ -37,9 +39,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureRegressorTrainer>("FastTreeRegression");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeRegressionTrainer(env, new FastTreeRegressionTrainer.Arguments()));
 }

 public IRegressionOutputCombiner CreateComponent(IHostEnvironment env) => new RegressionStacking(env, this);
Expand Down

15 changes: 12 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -5,9 +5,10 @@
using System;
using Microsoft.ML.Runtime;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)]
Expand All@@ -16,7 +17,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;
 public sealed class Stacking : BaseScalarStacking<SignatureBinaryClassifierTrainer>, IBinaryOutputCombiner, ICanSaveModel
 public sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner, ICanSaveModel
 {
 public const string UserName = "Stacking";
 public const string LoadName = "Stacking";
Expand All@@ -35,9 +36,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureBinaryClassifierTrainer>("FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeBinaryClassificationTrainer(env, new FastTreeBinaryClassificationTrainer.Arguments()));
 }

 public IBinaryOutputCombiner CreateComponent(IHostEnvironment env) => new Stacking(env, this);
Expand Down
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 Merged

eerhardt
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Aug 17, 2018
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Replace SubComponent with IComponentFactory in ML.Ensemble
#681
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77fff03

Convert Ensemble stacking SubComponent to IComponentFactory.


eerhardt Aug 15, 2018
84119d3

Replace SubComponent with IComponentFactory in ML.Ensemble


eerhardt Aug 15, 2018
7c06f93

Convert SimpleComponentFactory classes to ComponentFactoryUtils stati…


eerhardt Aug 16, 2018
d41dbe6

Move Stacking arguments abstract properties to internal get methods.


eerhardt Aug 16, 2018
6f852cb

Merge remote-tracking branch 'upstream/master' into EnsembleSubComponent


eerhardt Aug 17, 2018
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125 changes: 81 additions & 44 deletions
src/Microsoft.ML.Core/EntryPoints/ComponentFactory.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,41 +37,6 @@ public interface IComponentFactory<in TArg1, out TComponent> : IComponentFactory
 TComponent CreateComponent(IHostEnvironment env, TArg1 argument1);
 }

 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 private Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 public class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 private Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 /// <summary>
 /// An interface for creating a component when we take two extra parameters (and an <see cref="IHostEnvironment"/>).
 /// </summary>
Expand All@@ -89,22 +54,94 @@ public interface IComponentFactory<in TArg1, in TArg2, in TArg3, out TComponent>
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// A utility class for creating <see cref="IComponentFactory"/> instances.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 public static class ComponentFactoryUtils
 {
 private Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;
 /// <summary>
 /// Creates a component factory with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TComponent> CreateFromFunction<TComponent>(Func<IHostEnvironment, TComponent> factory)
 {
 return new SimpleComponentFactory<TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take one extra parameter (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TComponent> CreateFromFunction<TArg1, TComponent>(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take three extra parameters (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TArg2, TArg3, TComponent> CreateFromFunction<TArg1, TArg2, TArg3, TComponent>(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent>(factory);
 }

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 /// <summary>
 /// A class for creating a component with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 _factory = factory;
 private readonly Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 return _factory(env, argument1, argument2, argument3);
 private readonly Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 {
 private readonly Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 {
 return _factory(env, argument1, argument2, argument3);
 }
 }
 }
}

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,7 +164,7 @@ private void RunCore(IChannel ch, string cmd)
 new[]
 {
 new KeyValuePair<string, IComponentFactory<IDataView, IDataTransform>>(
 "", new SimpleComponentFactory<IDataView, IDataTransform>(
 "", ComponentFactoryUtils.CreateFromFunction<IDataView, IDataTransform>(
 (env, input) =>
 {
 var args = new GenerateNumberTransform.Arguments();
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/ScoreCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -330,7 +330,7 @@ public static TScorerFactory GetScorerComponent(
 };
 }

 return new SimpleComponentFactory<IDataView, ISchemaBoundMapper, RoleMappedSchema, IDataScorerTransform>(factoryFunc);
 return ComponentFactoryUtils.CreateFromFunction(factoryFunc);
 }

 /// <summary>
Expand Down

1 change: 1 addition & 0 deletions
src/Microsoft.ML.Ensemble/Microsoft.ML.Ensemble.csproj

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Original file line numberDiff line numberDiff line change
Expand Up@@ -10,6 +10,7 @@
 <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
 <ProjectReference Include="..\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
 <ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />
 <ProjectReference Include="..\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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 [](start = 4, length = 84)
We need this due to the usage of FastTree as the default traniner for some ensemble classes. This could be fine, but I wonder if using something from StandardLearners might make a bit more sense, if we envision that someday FastTree will be factored into a separate nuget package. (Maybe we don't want that though, in which case this dependency is probably fine.) #Resolved
@eerhardteerhardtAug 15, 2018•

edited

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One advantage to this change is that it brings to light these dependencies. Before we had a weakly-typed dependency using strings and DI. So if we ever did refactor FastTree to be separate, we could have easily broken this dependency.
I've logged #682 for this issue. #Resolved
@TomFinleyTomFinleyAug 16, 2018•

edited by eerhardt

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Thanks @eerhardt ... yes I expect we'll see some more of this "hidden dependency" becoming exposed as we move away from direct usage of subcomponents and dependency injection. I recall a similar issue in #446 with the normalizers being defined in Microsoft.ML.Transforms and used in Microsoft.ML.Data, despite the former project depending on the latter. 😄 #Resolved
 </ItemGroup>

</Project>

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,7 +9,7 @@

namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 public abstract class BaseScalarStacking<TSigBase> : BaseStacking<Single, TSigBase>
 public abstract class BaseScalarStacking : BaseStacking<Single>
 {
 internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)
 : base(env, name, args)
Expand Down

16 changes: 7 additions & 9 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
using System.Threading.Tasks;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
Expand All@@ -15,7 +16,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using ColumnRole = RoleMappedSchema.ColumnRole;
 public abstract class BaseStacking<TOutput, TSigBase> : IStackingTrainer<TOutput>
 public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
 {
 public abstract class ArgumentsBase
 {
Expand All@@ -24,13 +25,10 @@ public abstract class ArgumentsBase
 [TGUI(Label = "Validation Dataset Proportion")]
 public Single ValidationDatasetProportion = 0.3f;

 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
 [TGUI(Label = "Base predictor")]
 public SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 internal abstract IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> GetPredictorFactory();
 }

 protected readonly SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 protected readonly IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> BasePredictorType;
 protected readonly IHost Host;
 protected IPredictorProducing<TOutput> Meta;

Expand All@@ -45,10 +43,10 @@ internal BaseStacking(IHostEnvironment env, string name, ArgumentsBase args)
 Host.CheckUserArg(0 <= args.ValidationDatasetProportion && args.ValidationDatasetProportion < 1,
 nameof(args.ValidationDatasetProportion),
 "The validation proportion for stacking should be greater than or equal to 0 and less than 1");
 Host.CheckUserArg(args.BasePredictorType.IsGood(), nameof(args.BasePredictorType));

 ValidationDatasetProportion = args.ValidationDatasetProportion;
 BasePredictorType = args.BasePredictorType;
 BasePredictorType = args.GetPredictorFactory();
 Host.CheckValue(BasePredictorType, nameof(BasePredictorType));
 }

 internal BaseStacking(IHostEnvironment env, string name, ModelLoadContext ctx)
Expand DownExpand Up@@ -187,7 +185,7 @@ public void Train(List<FeatureSubsetModel<IPredictorProducing<TOutput>>> models,
 var view = bldr.GetDataView();
 var rmd = new RoleMappedData(view, DefaultColumnNames.Label, DefaultColumnNames.Features);

 var trainer = BasePredictorType.CreateInstance(host);
 var trainer = BasePredictorType.CreateComponent(host);
 if (trainer.Info.NeedNormalization)
 ch.Warning("The trainer specified for stacking wants normalization, but we do not currently allow this.");
 Meta = trainer.Train(rmd);
Expand Down

20 changes: 17 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,7 +8,10 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Learners;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -20,7 +23,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TVectorPredictor = IPredictorProducing<VBuffer<Single>>;
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>, SignatureMultiClassClassifierTrainer>, ICanSaveModel, IMultiClassOutputCombiner
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>>, ICanSaveModel, IMultiClassOutputCombiner
 {
 public const string LoadName = "MultiStacking";
 public const string LoaderSignature = "MultiStackingCombiner";
Expand All@@ -38,13 +41,24 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TVectorPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TVectorPredictor>> GetPredictorFactory() => BasePredictorType;

 public IMultiClassOutputCombiner CreateComponent(IHostEnvironment env) => new MultiStacking(env, this);

 public Arguments()
 {
 // REVIEW: Perhaps we can have a better non-parametetric learner.
 BasePredictorType = new SubComponent<ITrainer<TVectorPredictor>, SignatureMultiClassClassifierTrainer>(
 "OVA", "p=FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new Ova(env, new Ova.Arguments()
 {
 PredictorType = ComponentFactoryUtils.CreateFromFunction(
 e => new FastTreeBinaryClassificationTrainer(e, new FastTreeBinaryClassificationTrainer.Arguments()))
 }));
 }
 }

Expand Down

14 changes: 12 additions & 2 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,8 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -19,7 +21,7 @@ namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;

 public sealed class RegressionStacking : BaseScalarStacking<SignatureRegressorTrainer>, IRegressionOutputCombiner, ICanSaveModel
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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SignatureRegressorTrainer [](start = 64, length = 25)
What are we going to do about this sort of restriction? I had suggested previously using something like ITrainer<IRegressionPredictor> or something like this, but I'm not sure what you thought of that idea. #Resolved
@eerhardteerhardtAug 16, 2018•

edited

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Which restriction are you referring to? The Signature Type restriction, where we can't use typeof(TSig) in an attribute?
My hope is that some day we remove signature types all together. I haven't thought of/discovered a good replacement for them yet. Maybe an approach similar to ComponentKind which is just a string "Kind".
However, that still wouldn't help in this case, because we need a different signature/kind/etc for each concrete class, but we want to define the argument on the base class. #Resolved
@TomFinleyTomFinleyAug 16, 2018

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I meant just restricting the DI and API usage to only consider actual, in this case, regression trainers, which is one of the functions of the signatures. Currently this is done in a fairly half-hearted fashion using this IPredictorProducing<float> and IPredictorProducing<VBuffer<float>>, but if we got rid of this and replaced it with, say, IRegressionPredictor and IBinaryClassificationPredictor and IMulticlassPredictor (or something like that), then we could just have this be c omponent factory producing ITrainer<IRegressionPredictor> in this case. I think MEF should work well with that restriction as well, from a DI perspective.
In reply to: 210463209 [](ancestors = 210463209)
 public sealed class RegressionStacking : BaseScalarStacking, IRegressionOutputCombiner, ICanSaveModel
 {
 public const string LoadName = "RegressionStacking";
 public const string LoaderSignature = "RegressionStacking";
Expand All@@ -37,9 +39,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureRegressorTrainer>("FastTreeRegression");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeRegressionTrainer(env, new FastTreeRegressionTrainer.Arguments()));
 }

 public IRegressionOutputCombiner CreateComponent(IHostEnvironment env) => new RegressionStacking(env, this);
Expand Down

15 changes: 12 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -5,9 +5,10 @@
using System;
using Microsoft.ML.Runtime;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)]
Expand All@@ -16,7 +17,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;
 public sealed class Stacking : BaseScalarStacking<SignatureBinaryClassifierTrainer>, IBinaryOutputCombiner, ICanSaveModel
 public sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner, ICanSaveModel
 {
 public const string UserName = "Stacking";
 public const string LoadName = "Stacking";
Expand All@@ -35,9 +36,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureBinaryClassifierTrainer>("FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeBinaryClassificationTrainer(env, new FastTreeBinaryClassificationTrainer.Arguments()));
 }

 public IBinaryOutputCombiner CreateComponent(IHostEnvironment env) => new Stacking(env, this);
Expand Down
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, '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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 Merged

eerhardt
merged 8 commits into

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Aug 17, 2018
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Replace SubComponent with IComponentFactory in ML.Ensemble
#681
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77fff03

Convert Ensemble stacking SubComponent to IComponentFactory.


eerhardt Aug 15, 2018
84119d3

Replace SubComponent with IComponentFactory in ML.Ensemble


eerhardt Aug 15, 2018
7c06f93

Convert SimpleComponentFactory classes to ComponentFactoryUtils stati…


eerhardt Aug 16, 2018
d41dbe6

Move Stacking arguments abstract properties to internal get methods.


eerhardt Aug 16, 2018
6f852cb

Merge remote-tracking branch 'upstream/master' into EnsembleSubComponent


eerhardt Aug 17, 2018
2beb2ce

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eerhardt Aug 17, 2018
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125 changes: 81 additions & 44 deletions
src/Microsoft.ML.Core/EntryPoints/ComponentFactory.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,41 +37,6 @@ public interface IComponentFactory<in TArg1, out TComponent> : IComponentFactory
 TComponent CreateComponent(IHostEnvironment env, TArg1 argument1);
 }

 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 private Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 public class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 private Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 /// <summary>
 /// An interface for creating a component when we take two extra parameters (and an <see cref="IHostEnvironment"/>).
 /// </summary>
Expand All@@ -89,22 +54,94 @@ public interface IComponentFactory<in TArg1, in TArg2, in TArg3, out TComponent>
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// A utility class for creating <see cref="IComponentFactory"/> instances.
 /// </summary>
 public class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 public static class ComponentFactoryUtils
 {
 private Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;
 /// <summary>
 /// Creates a component factory with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TComponent> CreateFromFunction<TComponent>(Func<IHostEnvironment, TComponent> factory)
 {
 return new SimpleComponentFactory<TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take one extra parameter (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TComponent> CreateFromFunction<TArg1, TComponent>(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TComponent>(factory);
 }

 /// <summary>
 /// Creates a component factory when we take three extra parameters (and an
 /// <see cref="IHostEnvironment"/>) that simply wraps a delegate which creates the component.
 /// </summary>
 public static IComponentFactory<TArg1, TArg2, TArg3, TComponent> CreateFromFunction<TArg1, TArg2, TArg3, TComponent>(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 return new SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent>(factory);
 }

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 /// <summary>
 /// A class for creating a component with no extra parameters (other than an <see cref="IHostEnvironment"/>)
 /// that simply wraps a delegate which creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TComponent> : IComponentFactory<TComponent>
 {
 _factory = factory;
 private readonly Func<IHostEnvironment, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env)
 {
 return _factory(env);
 }
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 /// <summary>
 /// A class for creating a component when we take one extra parameter
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TComponent> : IComponentFactory<TArg1, TComponent>
 {
 return _factory(env, argument1, argument2, argument3);
 private readonly Func<IHostEnvironment, TArg1, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1)
 {
 return _factory(env, argument1);
 }
 }

 /// <summary>
 /// A class for creating a component when we take three extra parameters
 /// (and an <see cref="IHostEnvironment"/>) that simply wraps a delegate which
 /// creates the component.
 /// </summary>
 private sealed class SimpleComponentFactory<TArg1, TArg2, TArg3, TComponent> : IComponentFactory<TArg1, TArg2, TArg3, TComponent>
 {
 private readonly Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> _factory;

 public SimpleComponentFactory(Func<IHostEnvironment, TArg1, TArg2, TArg3, TComponent> factory)
 {
 _factory = factory;
 }

 public TComponent CreateComponent(IHostEnvironment env, TArg1 argument1, TArg2 argument2, TArg3 argument3)
 {
 return _factory(env, argument1, argument2, argument3);
 }
 }
 }
}

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,7 +164,7 @@ private void RunCore(IChannel ch, string cmd)
 new[]
 {
 new KeyValuePair<string, IComponentFactory<IDataView, IDataTransform>>(
 "", new SimpleComponentFactory<IDataView, IDataTransform>(
 "", ComponentFactoryUtils.CreateFromFunction<IDataView, IDataTransform>(
 (env, input) =>
 {
 var args = new GenerateNumberTransform.Arguments();
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Data/Commands/ScoreCommand.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -330,7 +330,7 @@ public static TScorerFactory GetScorerComponent(
 };
 }

 return new SimpleComponentFactory<IDataView, ISchemaBoundMapper, RoleMappedSchema, IDataScorerTransform>(factoryFunc);
 return ComponentFactoryUtils.CreateFromFunction(factoryFunc);
 }

 /// <summary>
Expand Down

1 change: 1 addition & 0 deletions
src/Microsoft.ML.Ensemble/Microsoft.ML.Ensemble.csproj

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Original file line numberDiff line numberDiff line change
Expand Up@@ -10,6 +10,7 @@
 <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
 <ProjectReference Include="..\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
 <ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />
 <ProjectReference Include="..\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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 [](start = 4, length = 84)
We need this due to the usage of FastTree as the default traniner for some ensemble classes. This could be fine, but I wonder if using something from StandardLearners might make a bit more sense, if we envision that someday FastTree will be factored into a separate nuget package. (Maybe we don't want that though, in which case this dependency is probably fine.) #Resolved
@eerhardteerhardtAug 15, 2018•

edited

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One advantage to this change is that it brings to light these dependencies. Before we had a weakly-typed dependency using strings and DI. So if we ever did refactor FastTree to be separate, we could have easily broken this dependency.
I've logged #682 for this issue. #Resolved
@TomFinleyTomFinleyAug 16, 2018•

edited by eerhardt

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Thanks @eerhardt ... yes I expect we'll see some more of this "hidden dependency" becoming exposed as we move away from direct usage of subcomponents and dependency injection. I recall a similar issue in #446 with the normalizers being defined in Microsoft.ML.Transforms and used in Microsoft.ML.Data, despite the former project depending on the latter. 😄 #Resolved
 </ItemGroup>

</Project>

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,7 +9,7 @@

namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 public abstract class BaseScalarStacking<TSigBase> : BaseStacking<Single, TSigBase>
 public abstract class BaseScalarStacking : BaseStacking<Single>
 {
 internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)
 : base(env, name, args)
Expand Down

16 changes: 7 additions & 9 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
using System.Threading.Tasks;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
Expand All@@ -15,7 +16,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using ColumnRole = RoleMappedSchema.ColumnRole;
 public abstract class BaseStacking<TOutput, TSigBase> : IStackingTrainer<TOutput>
 public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
 {
 public abstract class ArgumentsBase
 {
Expand All@@ -24,13 +25,10 @@ public abstract class ArgumentsBase
 [TGUI(Label = "Validation Dataset Proportion")]
 public Single ValidationDatasetProportion = 0.3f;

 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
 [TGUI(Label = "Base predictor")]
 public SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 internal abstract IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> GetPredictorFactory();
 }

 protected readonly SubComponent<ITrainer<IPredictorProducing<TOutput>>, TSigBase> BasePredictorType;
 protected readonly IComponentFactory<ITrainer<IPredictorProducing<TOutput>>> BasePredictorType;
 protected readonly IHost Host;
 protected IPredictorProducing<TOutput> Meta;

Expand All@@ -45,10 +43,10 @@ internal BaseStacking(IHostEnvironment env, string name, ArgumentsBase args)
 Host.CheckUserArg(0 <= args.ValidationDatasetProportion && args.ValidationDatasetProportion < 1,
 nameof(args.ValidationDatasetProportion),
 "The validation proportion for stacking should be greater than or equal to 0 and less than 1");
 Host.CheckUserArg(args.BasePredictorType.IsGood(), nameof(args.BasePredictorType));

 ValidationDatasetProportion = args.ValidationDatasetProportion;
 BasePredictorType = args.BasePredictorType;
 BasePredictorType = args.GetPredictorFactory();
 Host.CheckValue(BasePredictorType, nameof(BasePredictorType));
 }

 internal BaseStacking(IHostEnvironment env, string name, ModelLoadContext ctx)
Expand DownExpand Up@@ -187,7 +185,7 @@ public void Train(List<FeatureSubsetModel<IPredictorProducing<TOutput>>> models,
 var view = bldr.GetDataView();
 var rmd = new RoleMappedData(view, DefaultColumnNames.Label, DefaultColumnNames.Features);

 var trainer = BasePredictorType.CreateInstance(host);
 var trainer = BasePredictorType.CreateComponent(host);
 if (trainer.Info.NeedNormalization)
 ch.Warning("The trainer specified for stacking wants normalization, but we do not currently allow this.");
 Meta = trainer.Train(rmd);
Expand Down

20 changes: 17 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,7 +8,10 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Learners;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -20,7 +23,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TVectorPredictor = IPredictorProducing<VBuffer<Single>>;
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>, SignatureMultiClassClassifierTrainer>, ICanSaveModel, IMultiClassOutputCombiner
 public sealed class MultiStacking : BaseStacking<VBuffer<Single>>, ICanSaveModel, IMultiClassOutputCombiner
 {
 public const string LoadName = "MultiStacking";
 public const string LoaderSignature = "MultiStackingCombiner";
Expand All@@ -38,13 +41,24 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TVectorPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TVectorPredictor>> GetPredictorFactory() => BasePredictorType;

 public IMultiClassOutputCombiner CreateComponent(IHostEnvironment env) => new MultiStacking(env, this);

 public Arguments()
 {
 // REVIEW: Perhaps we can have a better non-parametetric learner.
 BasePredictorType = new SubComponent<ITrainer<TVectorPredictor>, SignatureMultiClassClassifierTrainer>(
 "OVA", "p=FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new Ova(env, new Ova.Arguments()
 {
 PredictorType = ComponentFactoryUtils.CreateFromFunction(
 e => new FastTreeBinaryClassificationTrainer(e, new FastTreeBinaryClassificationTrainer.Arguments()))
 }));
 }
 }

Expand Down

14 changes: 12 additions & 2 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,8 @@
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner),
Expand All@@ -19,7 +21,7 @@ namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;

 public sealed class RegressionStacking : BaseScalarStacking<SignatureRegressorTrainer>, IRegressionOutputCombiner, ICanSaveModel
@TomFinleyTomFinleyAug 15, 2018•

edited by eerhardt

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SignatureRegressorTrainer [](start = 64, length = 25)
What are we going to do about this sort of restriction? I had suggested previously using something like ITrainer<IRegressionPredictor> or something like this, but I'm not sure what you thought of that idea. #Resolved
@eerhardteerhardtAug 16, 2018•

edited

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Which restriction are you referring to? The Signature Type restriction, where we can't use typeof(TSig) in an attribute?
My hope is that some day we remove signature types all together. I haven't thought of/discovered a good replacement for them yet. Maybe an approach similar to ComponentKind which is just a string "Kind".
However, that still wouldn't help in this case, because we need a different signature/kind/etc for each concrete class, but we want to define the argument on the base class. #Resolved
@TomFinleyTomFinleyAug 16, 2018

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I meant just restricting the DI and API usage to only consider actual, in this case, regression trainers, which is one of the functions of the signatures. Currently this is done in a fairly half-hearted fashion using this IPredictorProducing<float> and IPredictorProducing<VBuffer<float>>, but if we got rid of this and replaced it with, say, IRegressionPredictor and IBinaryClassificationPredictor and IMulticlassPredictor (or something like that), then we could just have this be c omponent factory producing ITrainer<IRegressionPredictor> in this case. I think MEF should work well with that restriction as well, from a DI perspective.
In reply to: 210463209 [](ancestors = 210463209)
 public sealed class RegressionStacking : BaseScalarStacking, IRegressionOutputCombiner, ICanSaveModel
 {
 public const string LoadName = "RegressionStacking";
 public const string LoaderSignature = "RegressionStacking";
Expand All@@ -37,9 +39,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureRegressorTrainer>("FastTreeRegression");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeRegressionTrainer(env, new FastTreeRegressionTrainer.Arguments()));
 }

 public IRegressionOutputCombiner CreateComponent(IHostEnvironment env) => new RegressionStacking(env, this);
Expand Down

15 changes: 12 additions & 3 deletions
src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -5,9 +5,10 @@
using System;
using Microsoft.ML.Runtime;
using Microsoft.ML.Runtime.CommandLine;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FastTree;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Model;

[assembly: LoadableClass(typeof(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)]
Expand All@@ -16,7 +17,7 @@
namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
{
 using TScalarPredictor = IPredictorProducing<Single>;
 public sealed class Stacking : BaseScalarStacking<SignatureBinaryClassifierTrainer>, IBinaryOutputCombiner, ICanSaveModel
 public sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner, ICanSaveModel
 {
 public const string UserName = "Stacking";
 public const string LoadName = "Stacking";
Expand All@@ -35,9 +36,17 @@ private static VersionInfo GetVersionInfo()
 [TlcModule.Component(Name = LoadName, FriendlyName = UserName)]
 public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory
 {
 [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
 [TGUI(Label = "Base predictor")]
 public IComponentFactory<ITrainer<TScalarPredictor>> BasePredictorType;

 internal override IComponentFactory<ITrainer<TScalarPredictor>> GetPredictorFactory() => BasePredictorType;

 public Arguments()
 {
 BasePredictorType = new SubComponent<ITrainer<TScalarPredictor>, SignatureBinaryClassifierTrainer>("FastTreeBinaryClassification");
 BasePredictorType = ComponentFactoryUtils.CreateFromFunction(
 env => new FastTreeBinaryClassificationTrainer(env, new FastTreeBinaryClassificationTrainer.Arguments()));
 }

 public IBinaryOutputCombiner CreateComponent(IHostEnvironment env) => new Stacking(env, this);
Expand Down
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