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Copy file name to clipboardExpand all lines: test/Microsoft.ML.Tests/OnnxConversionTest.cs
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@@ -43,7 +43,7 @@ public OnnxConversionTest(ITestOutputHelper output) : base(output)
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/// call <see cref="OnnxScoringEstimator"/> to evaluate that file. The outputs of <see cref="OnnxScoringEstimator"/> are checked against the original
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/// ML.NET model's outputs.
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/// </summary>
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[ConditionalFact(typeof(BaseTestBaseline),nameof(BaseTestBaseline.NotFullFramework))]// Tracked by https://github.com/dotnet/machinelearning/issues/2106
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[Fact]
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publicvoidSimpleEndToEndOnnxConversionTest()
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{
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// Step 1: Create and train a ML.NET pipeline.
@@ -118,7 +118,7 @@ private class BreastCancerMulticlassExample
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publicfloat[]Features;
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}
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[ConditionalFact(typeof(BaseTestBaseline),nameof(BaseTestBaseline.LessThanNetCore30AndNotFullFramework))]// Tracked by https://github.com/dotnet/machinelearning/issues/2087
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[ConditionalFact(typeof(BaseTestBaseline),nameof(BaseTestBaseline.LessThanNetCore30OrNotNetCore))]// Tracked by https://github.com/dotnet/machinelearning/issues/2087
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publicvoidKmeansOnnxConversionTest()
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{
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// Create a new context for ML.NET operations. It can be used for exception tracking and logging,
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