[ConditionalFact(typeof(BaseTestBaseline), nameof(BaseTestBaseline.LessThanNetCore30OrNotNetCore))] // netcore3.0 output differs from Baseline
public void GcnWorkout()
{
string dataSource = GetDataPath(TestDatasets.generatedRegressionDataset.trainFilename);
var data = TextLoader.CreateReader(ML,
c => (label: c.LoadFloat(11), features: c.LoadFloat(0, 10)),
separator: ';', hasHeader: true)
.Read(dataSource);
var invalidData = TextLoader.CreateReader(ML,
c => (label: c.LoadFloat(11), features: c.LoadText(0, 10)),
separator: ';', hasHeader: true)
.Read(dataSource);
var est = new GlobalContrastNormalizingEstimator(ML, "features", "gcnNorm1")
.Append(new GlobalContrastNormalizingEstimator(ML, "features", "gcnNorm2", substractMean: false, useStdDev: true, scale: 3));
TestEstimatorCore(est, data.AsDynamic, invalidInput: invalidData.AsDynamic);
var outputPath = GetOutputPath("NormalizerEstimator", "gcnNorm.tsv");
using (var ch = Env.Start("save"))
{
var saver = new TextSaver(ML, new TextSaver.Arguments {
Silent = true, OutputHeader = false
});
IDataView savedData = TakeFilter.Create(ML, est.Fit(data.AsDynamic).Transform(data.AsDynamic), 4);
savedData = ColumnSelectingTransformer.CreateKeep(ML, savedData, new[] { "gcnNorm1", "gcnNorm2" });
using (var fs = File.Create(outputPath))
DataSaverUtils.SaveDataView(ch, saver, savedData, fs, keepHidden: true);
}
CheckEquality("NormalizerEstimator", "gcnNorm.tsv", digitsOfPrecision: 4);
Done();
}
public void TestGcnNormOldSavingAndLoading()
{
string dataSource = GetDataPath(TestDatasets.generatedRegressionDataset.trainFilename);
var dataView = TextLoader.CreateReader(ML,
c => (label: c.LoadFloat(11), features: c.LoadFloat(0, 10)),
separator: ';', hasHeader: true)
.Read(dataSource).AsDynamic;
var pipe = new GlobalContrastNormalizingEstimator(ML, "features", "whitened");
var result = pipe.Fit(dataView).Transform(dataView);
var resultRoles = new RoleMappedData(result);
using (var ms = new MemoryStream())
{
TrainUtils.SaveModel(ML, Env.Start("saving"), ms, null, resultRoles);
ms.Position = 0;
var loadedView = ModelFileUtils.LoadTransforms(ML, dataView, ms);
}
}
