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no need to add combiner if you don't have transforms. #172

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merged 2 commits into from
May 16, 2018
Merged

no need to add combiner if you don't have transforms. #172

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37896b6
no need to add combiner if you don't have transforms.
May 16, 2018
49fca4e
fix NextSigned
May 16, 2018
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2 changes: 1 addition & 1 deletion src/Microsoft.ML.Core/Utilities/Random.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -151,7 +151,7 @@ public int NextSigned()
{
// Note that, according to the documentation for System.Random,
// this won't ever achieve int.MaxValue, but oh well.
return _rnd.Next(int.MinValue, int.MinValue);
return _rnd.Next(int.MinValue, int.MaxValue);
}
}

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22 changes: 14 additions & 8 deletions src/Microsoft.ML/LearningPipeline.cs
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Expand Up @@ -154,23 +154,29 @@ public PredictionModel<TInput, TOutput> Train<TInput, TOutput>()
step = currentItem.ApplyStep(step, experiment);
if (step is ILearningPipelineDataStep dataStep && dataStep.Model != null)
transformModels.Add(dataStep.Model);

else if (step is ILearningPipelinePredictorStep predictorDataStep)
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Nit: I think this change here was unintentional. :D

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@Ivanidzo4ka Ivanidzo4ka May 16, 2018 •
edited
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I just ctrl+k+d this file, and this is what VS produce to me. It just replace line full of spaces to empty line. #ByDesign

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@TomFinley TomFinley May 17, 2018 •
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I'd rather you hadn't inserted two completely empty lines here at all. :D

In reply to: 188751411 [](ancestors = 188751411)

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FALSE ALLEGATIONS! It's actually specific of codeflow. If you look on github PR or merge code, you will see it has only one line, and first line actually suppose to be removed, but for some reason codeflow mark it as yellow instead of red (addition instead of deletion.

In reply to: 188834888 [](ancestors = 188834888,188751411)

{
if (lastTransformModel != null)
transformModels.Insert(0, lastTransformModel);

var localModelInput = new Transforms.ManyHeterogeneousModelCombiner
Var<IPredictorModel> predictorModel;
if (transformModels.Count != 0)
{
PredictorModel = predictorDataStep.Model,
TransformModels = new ArrayVar<ITransformModel>(transformModels.ToArray())
};

var localModelOutput = experiment.Add(localModelInput);
var localModelInput = new Transforms.ManyHeterogeneousModelCombiner
{
PredictorModel = predictorDataStep.Model,
TransformModels = new ArrayVar<ITransformModel>(transformModels.ToArray())
};
var localModelOutput = experiment.Add(localModelInput);
predictorModel = localModelOutput.PredictorModel;
}
else
predictorModel = predictorDataStep.Model;

var scorer = new Transforms.Scorer
{
PredictorModel = localModelOutput.PredictorModel
PredictorModel = predictorModel
};

var scorerOutput = experiment.Add(scorer);
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31 changes: 31 additions & 0 deletions test/Microsoft.ML.Tests/LearningPipelineTests.cs
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Expand Up @@ -3,8 +3,10 @@
// See the LICENSE file in the project root for more information.

using Microsoft.ML;
using Microsoft.ML.Data;
using Microsoft.ML.Runtime.Api;
using Microsoft.ML.TestFramework;
using Microsoft.ML.Trainers;
using Microsoft.ML.Transforms;
using System.Linq;
using Xunit;
Expand Down Expand Up @@ -79,5 +81,34 @@ public void TransformOnlyPipeline()
else
Assert.Equal(0, predictionModel.TransformedF1[index]);
}

public class Data
{
[ColumnName("Features")]
[VectorType(2)]
public float[] Features;

[ColumnName("Label")]
public float Label;
}

public class Prediction
{
[ColumnName("PredictedLabel")]
public bool PredictedLabel;
}

[Fact]
public void NoTransformPipeline()
{
var data = new Data[1];
data[0] = new Data();
data[0].Features = new float[] { 0.0f, 1.0f };
data[0].Label = 0f;
var pipeline = new LearningPipeline();
pipeline.Add(CollectionDataSource.Create(data));
pipeline.Add(new FastForestBinaryClassifier());
var model = pipeline.Train<Data, Prediction>();
}
}
}