Skip to content

Fix MatrixFactorization trainer's warning #5071

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 6 commits into from
May 6, 2020
Merged

Fix MatrixFactorization trainer's warning #5071

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
c073e6b
upgrade to 3.1
LittleLittleCloud Apr 28, 2020
8f0fc1a
write inline data using invariantCulture
LittleLittleCloud Apr 28, 2020
e96d716
Merge branch 'master' of https://github.com/dotnet/machinelearning
LittleLittleCloud Apr 29, 2020
e0c0807
use 2*thread + 1 to initialize n_bin
LittleLittleCloud Apr 29, 2020
00f8af9
fix test
LittleLittleCloud Apr 30, 2020
b3a580c
fix linux test
LittleLittleCloud May 4, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion src/Microsoft.ML.Recommender/MatrixFactorizationTrainer.cs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -513,7 +513,7 @@ private MatrixFactorizationModelParameters TrainCore(IChannel ch, RoleMappedData

private SafeTrainingAndModelBuffer PrepareBuffer()
{
return new SafeTrainingAndModelBuffer(_host, _fun, _k, _threads, _threads == 1 ? 1 : Math.Max(20, 2 * _threads),
return new SafeTrainingAndModelBuffer(_host, _fun, _k, _threads, 2 * _threads + 1,
_iter, _lambda, _eta, _alpha, _c, _doNmf, _quiet, copyData: false);
}

Expand Down
12 changes: 6 additions & 6 deletions test/Microsoft.ML.Tests/TrainerEstimators/MatrixFactorizationTests.cs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -96,10 +96,10 @@ public void MatrixFactorizationSimpleTrainAndPredict()
// MF produce different matrices on different platforms, so check their content on Windows.
if (RuntimeInformation.IsOSPlatform(OSPlatform.Windows))
{
Assert.Equal(0.301269173622131, leftMatrix[0], 5);
Assert.Equal(0.558746933937073, leftMatrix[leftMatrix.Count - 1], 5);
Assert.Equal(0.27028301358223, rightMatrix[0], 5);
Assert.Equal(0.390790820121765, rightMatrix[rightMatrix.Count - 1], 5);
Assert.Equal(0.290507137775421, leftMatrix[0], 5);
Assert.Equal(0.558072924613953, leftMatrix[leftMatrix.Count - 1], 5);
Assert.Equal(0.270811557769775, rightMatrix[0], 5);
Assert.Equal(0.376706808805466, rightMatrix[rightMatrix.Count - 1], 5);
}
// Read the test data set as an IDataView
var testData = reader.Load(new MultiFileSource(GetDataPath(TestDatasets.trivialMatrixFactorization.testFilename)));
Expand Down Expand Up @@ -129,7 +129,7 @@ public void MatrixFactorizationSimpleTrainAndPredict()
if (RuntimeInformation.IsOSPlatform(OSPlatform.Linux))
{
// Linux case
var expectedUnixL2Error = 0.612974867782832; // Linux baseline
var expectedUnixL2Error = 0.610332110253861; // Linux baseline
Assert.InRange(metrices.MeanSquaredError, expectedUnixL2Error - linuxTolerance, expectedUnixL2Error + linuxTolerance);
}
else if (RuntimeInformation.IsOSPlatform(OSPlatform.OSX))
Expand All @@ -142,7 +142,7 @@ public void MatrixFactorizationSimpleTrainAndPredict()
else if (RuntimeInformation.IsOSPlatform(OSPlatform.Windows))
{
// Windows case
var expectedWindowsL2Error = 0.622283290742721; // Windows baseline
var expectedWindowsL2Error = 0.60226203382884; // Windows baseline
Assert.InRange(metrices.MeanSquaredError, expectedWindowsL2Error - windowsTolerance, expectedWindowsL2Error + windowsTolerance);
}

Expand Down