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Added Onnx Export to PlattCalibratorTransformer #4699

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merged 10 commits into from
Jan 27, 2020
Merged

Added Onnx Export to PlattCalibratorTransformer #4699

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a3436ac
Added OnnxConversionTests for PlattEstimator
antoniovs1029 Jan 24, 2020
1234f76
Fixed bug in how PlattCalibrator is saved to Onnx
antoniovs1029 Jan 24, 2020
bacaea8
Add saving to Onnx capabilities to CalibratorTransformer.Mapper
antoniovs1029 Jan 24, 2020
18c9559
Updated names in CT.Mapper.SaveAsOnnx for readability
antoniovs1029 Jan 24, 2020
e6c5463
Removed Platt2 Sample
antoniovs1029 Jan 24, 2020
9592641
Updated names in CT.Mapper.SaveAsOnnx for readability
antoniovs1029 Jan 24, 2020
4d3b962
Update
antoniovs1029 Jan 24, 2020
25a66bd
Update after merge conflict
antoniovs1029 Jan 24, 2020
96de055
Updated Offset variable in Baselines
antoniovs1029 Jan 24, 2020
1c23a3c
Removed spaces and comment
antoniovs1029 Jan 25, 2020
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40 changes: 37 additions & 3 deletions test/Microsoft.ML.Tests/OnnxConversionTest.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -309,6 +309,40 @@ public void BinaryClassificationTrainersOnnxConversionTest()
Done();
}

[Fact]
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This shouldn't be part of your changes. Maybe you did your merge steps wrong?

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Yeah, I think I messed up, but it's fixed now

public void TestVectorWhiteningOnnxConversionTest()
{
var mlContext = new MLContext(seed: 1);
string dataPath = GetDataPath(TestDatasets.generatedRegressionDataset.trainFilename);
var dataView = mlContext.Data.LoadFromTextFile(dataPath, new[] {
new TextLoader.Column("label", DataKind.Single, 11),
new TextLoader.Column("features", DataKind.Single, 0, 10)
}, hasHeader: true, separatorChar: ';');

var pipeline = new VectorWhiteningEstimator(mlContext, "whitened1", "features")
.Append(new VectorWhiteningEstimator(mlContext, "whitened2", "features", kind: WhiteningKind.PrincipalComponentAnalysis, rank: 5));
var model = pipeline.Fit(dataView);
var transformedData = model.Transform(dataView);
var onnxModel = mlContext.Model.ConvertToOnnxProtobuf(model, dataView);

// Compare model scores produced by ML.NET and ONNX's runtime.
if (IsOnnxRuntimeSupported())
{
var onnxFileName = $"VectorWhitening.onnx";
var onnxModelPath = GetOutputPath(onnxFileName);
SaveOnnxModel(onnxModel, onnxModelPath, null);
// Evaluate the saved ONNX model using the data used to train the ML.NET pipeline.
string[] inputNames = onnxModel.Graph.Input.Select(valueInfoProto => valueInfoProto.Name).ToArray();
string[] outputNames = onnxModel.Graph.Output.Select(valueInfoProto => valueInfoProto.Name).ToArray();
var onnxEstimator = mlContext.Transforms.ApplyOnnxModel(outputNames, inputNames, onnxModelPath);
var onnxTransformer = onnxEstimator.Fit(dataView);
var onnxResult = onnxTransformer.Transform(dataView);
CompareSelectedR4VectorColumns(transformedData.Schema[2].Name, outputNames[2], transformedData, onnxResult); // whitened1
CompareSelectedR4VectorColumns(transformedData.Schema[3].Name, outputNames[3], transformedData, onnxResult); // whitened2
}
Done();
}

[Fact]
public void PlattCalibratorOnnxConversionTest()
{
Expand Down Expand Up @@ -345,7 +379,7 @@ public void PlattCalibratorOnnxConversionTest()
var outputSchema = model.GetOutputSchema(dataView.Schema);
var transformedData = model.Transform(dataView);
var onnxModel = mlContext.Model.ConvertToOnnxProtobuf(model, dataView);

// Compare model scores produced by ML.NET and ONNX's runtime.
if (IsOnnxRuntimeSupported())
{
Expand Down Expand Up @@ -374,7 +408,7 @@ class PlattModelInput

static IEnumerable<PlattModelInput> PlattGetData()
{
for(int i = 0; i < 100; i++)
for (int i = 0; i < 100; i++)
{
yield return new PlattModelInput { Score = i, Label = i % 2 == 0 };
}
Expand All @@ -394,7 +428,7 @@ public void PlattCalibratorOnnxConversionTest2()
var calibratorTransformer = calibratorEstimator.Fit(data);
var transformedData = calibratorTransformer.Transform(data);
var onnxModel = mlContext.Model.ConvertToOnnxProtobuf(calibratorTransformer, data);

// Compare model scores produced by ML.NET and ONNX's runtime.
if (IsOnnxRuntimeSupported())
{
Expand Down