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LightGBM Crash issue #4918

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Merged
frank-dong-ms-zz merged 5 commits into from
Mar 5, 2020
Merged

LightGBM Crash issue #4918

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477e2be
try lightgbm tests with threads number to number of processor
frank-dong-ms-zz Mar 4, 2020
cb18de3
enable test run parallelization for ML.Test assembly
frank-dong-ms-zz Mar 4, 2020
23b0d7b
try test on private agent pool see if issue can be repro
frank-dong-ms-zz Mar 4, 2020
cf16c7d
revert unnecessary changes
frank-dong-ms-zz Mar 5, 2020
8199244
add comments to explain the issue
frank-dong-ms-zz Mar 5, 2020
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4 changes: 4 additions & 0 deletions test/Microsoft.ML.Tests/Microsoft.ML.Tests.csproj
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Original file line number Diff line number Diff line change
Expand Up @@ -64,4 +64,8 @@
<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
</None>
</ItemGroup>

<ItemGroup>
<Folder Include="Properties\" />
</ItemGroup>
</Project>
9 changes: 0 additions & 9 deletions test/Microsoft.ML.Tests/Properties/AssemblyInfo.cs
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3 changes: 2 additions & 1 deletion test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs
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Expand Up @@ -811,12 +811,13 @@ private void ExecuteTFTransformMNISTConvTrainingTest(bool shuffle, int? shuffleS
batchSize: 20))
.Append(mlContext.Transforms.Concatenate("Features", "Prediction"))
.AppendCacheCheckpoint(mlContext)
// Attention: Do not set NumberOfThreads here, left this to use default value to avoid test crash.
// Details can be found here: https://github.com/dotnet/machinelearning/pull/4918
.Append(mlContext.MulticlassClassification.Trainers.LightGbm(new Trainers.LightGbm.LightGbmMulticlassTrainer.Options()
{
LabelColumnName = "Label",
FeatureColumnName = "Features",
Seed = 1,
NumberOfThreads = 1,
NumberOfIterations = 1
}));

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32 changes: 26 additions & 6 deletions test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs
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Expand Up @@ -52,10 +52,11 @@ public void LightGBMBinaryEstimator()
{
var (pipe, dataView) = GetBinaryClassificationPipeline();

// Attention: Do not set NumberOfThreads here, left this to use default value to avoid test crash.
// Details can be found here: https://github.com/dotnet/machinelearning/pull/4918
var trainer = ML.BinaryClassification.Trainers.LightGbm(new LightGbmBinaryTrainer.Options
{
NumberOfLeaves = 10,
NumberOfThreads = 1,
MinimumExampleCountPerLeaf = 2,
UnbalancedSets = false, // default value
});
Expand All @@ -73,10 +74,11 @@ public void LightGBMBinaryEstimatorUnbalanced()
{
var (pipe, dataView) = GetBinaryClassificationPipeline();

// Attention: Do not set NumberOfThreads here, left this to use default value to avoid test crash.
// Details can be found here: https://github.com/dotnet/machinelearning/pull/4918
var trainer = ML.BinaryClassification.Trainers.LightGbm(new LightGbmBinaryTrainer.Options
{
NumberOfLeaves = 10,
NumberOfThreads = 1,
MinimumExampleCountPerLeaf = 2,

@harishsk harishsk Mar 5, 2020

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Can we add a detailed note somewhere in code visibly about why this is done?
Can we also add a cross reference to that comment wherever we have removed the NumberOfThreads = 1

@frank-dong-ms-zz frank-dong-ms-zz Mar 5, 2020

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Yes, I can add some comments with // Attention tags and put explain on comments

In reply to: 388442580 [](ancestors = 388442580)

UnbalancedSets = true,
});
Expand All @@ -98,10 +100,11 @@ public void LightGBMBinaryEstimatorCorrectSigmoid()
var (pipe, dataView) = GetBinaryClassificationPipeline();
var sigmoid = .789;

// Attention: Do not set NumberOfThreads here, left this to use default value to avoid test crash.
// Details can be found here: https://github.com/dotnet/machinelearning/pull/4918
var trainer = ML.BinaryClassification.Trainers.LightGbm(new LightGbmBinaryTrainer.Options
{
NumberOfLeaves = 10,
NumberOfThreads = 1,
MinimumExampleCountPerLeaf = 2,
Sigmoid = sigmoid
});
Expand Down Expand Up @@ -218,9 +221,11 @@ public void FastTreeRegressorEstimator()
public void LightGBMRegressorEstimator()
{
var dataView = GetRegressionPipeline();

// Attention: Do not set NumberOfThreads here, left this to use default value to avoid test crash.
// Details can be found here: https://github.com/dotnet/machinelearning/pull/4918
var trainer = ML.Regression.Trainers.LightGbm(new LightGbmRegressionTrainer.Options
{
NumberOfThreads = 1,
NormalizeFeatures = NormalizeOption.Warn,
L2CategoricalRegularization = 5,
});
Expand Down Expand Up @@ -930,8 +935,15 @@ public void FastTreeTweedieRegressorTestSummary()
public void LightGbmRegressorTestSummary()
{
var dataView = GetRegressionPipeline();

// Attention: Do not set NumberOfThreads here, left this to use default value to avoid test crash.
// Details can be found here: https://github.com/dotnet/machinelearning/pull/4918
var trainer = ML.Regression.Trainers.LightGbm(
new LightGbmRegressionTrainer.Options { NumberOfIterations = 10, NumberOfThreads = 1, NumberOfLeaves = 5});
new LightGbmRegressionTrainer.Options
{
NumberOfIterations = 10,
NumberOfLeaves = 5
});

var transformer = trainer.Fit(dataView);

Expand Down Expand Up @@ -984,8 +996,16 @@ public void FastForestBinaryClassificationTestSummary()
public void LightGbmBinaryClassificationTestSummary()
{
var (pipeline, dataView) = GetOneHotBinaryClassificationPipeline();

// Attention: Do not set NumberOfThreads here, left this to use default value to avoid test crash.
// Details can be found here: https://github.com/dotnet/machinelearning/pull/4918
var trainer = pipeline.Append(ML.BinaryClassification.Trainers.LightGbm(
new LightGbmBinaryTrainer.Options { NumberOfIterations = 10, NumberOfThreads = 1, NumberOfLeaves = 5, UseCategoricalSplit = true }));
new LightGbmBinaryTrainer.Options
{
NumberOfIterations = 10,
NumberOfLeaves = 5,
UseCategoricalSplit = true
}));

var transformer = trainer.Fit(dataView);

Expand Down