public void TrainerGeneratorBasicAdvancedParameterTest()
{
var context = new MLContext();
var elementProperties = new Dictionary <string, object>()
{
{ "LearningRate", 0.1f },
{ "NumLeaves", 1 },
{ "UseSoftmax", true }
};
PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
var actual = codeGenerator.GenerateTrainerAndUsings();
string expectedTrainer = "LightGbm(new LightGbmBinaryTrainer.Options(){LearningRate=0.1f,NumLeaves=1,UseSoftmax=true,LabelColumnName=\"Label\",FeatureColumnName=\"Features\"})";
string expectedUsing = "using Microsoft.ML.Trainers.LightGbm;\r\n";
Assert.Equal(expectedTrainer, actual.Item1);
Assert.Equal(expectedUsing, actual.Item2[0]);
}
public async Task Pipeline_With_ContinueOnError_Returns_Exceptions_On_All_Failures()
{
var pipelineNode = new PipelineNode <TestObjectA>
{
LocalOptions = new ExecutionOptions {
ContinueOnFailure = true
}
};
pipelineNode.AddChild(new FaultingTestNodeA());
pipelineNode.AddChild(new FaultingTestNodeA());
var testObject = new TestObjectA();
NodeResult result = await pipelineNode.ExecuteAsync(testObject);
IEnumerable <Exception> exceptions = result.GetFailExceptions();
exceptions.Should().NotBeNull();
exceptions.Count().Should().Be(2);
}
public async Task When_Cancelling_Pipeline_At_First_Node_Then_Status_Is_NotRun()
{
var pipelineNode = new PipelineNode <TestObjectA>();
var testNode1 = new SimpleTestNodeA1(true, false, true);
var testNode2 = new SimpleTestNodeA2();
pipelineNode.AddChild(testNode1);
pipelineNode.AddChild(testNode2);
var testObject = new TestObjectA();
NodeResult result = await pipelineNode.ExecuteAsync(testObject);
result.Status.Should().Be(NodeResultStatus.NotRun);
pipelineNode.Status.Should().Be(NodeRunStatus.Completed);
testNode1.Status.Should().Be(NodeRunStatus.NotRun);
testNode2.Status.Should().Be(NodeRunStatus.NotRun);
}
public void TrainerComplexParameterTest()
{
var context = new MLContext();
var elementProperties = new Dictionary <string, object>()
{
{ "Booster", new CustomProperty()
{
Properties = new Dictionary <string, object>(), Name = "TreeBooster"
} },
};
PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.Trainer, new string[] { "Label" }, default(string), elementProperties);
Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
var actual = codeGenerator.GenerateTrainerAndUsings();
string expectedTrainer = "LightGbm(new LightGbmBinaryTrainer.Options(){Booster=new TreeBooster(){},LabelColumnName=\"Label\",FeatureColumnName=\"Features\"})";
var expectedUsings = "using Microsoft.ML.Trainers.LightGbm;\r\n";
Assert.Equal(expectedTrainer, actual.Item1);
Assert.Equal(expectedUsings, actual.Item2[0]);
}
public async Task Can_Add_Base_Type_Pipeline_Node_To_Inherited_Type_Pipeline()
{
var testNode = new SimpleTestNodeA1();
var pipeline = new PipelineNode <TestObjectA>();
pipeline.AddChild(testNode);
var testNode2 = new SimpleTestNodeASub1();
var pipelineSub = new PipelineNode <TestObjectASub>();
pipelineSub.AddChild(testNode2);
pipelineSub.AddChild(pipeline);
var testObject = new TestObjectASub();
var result = await pipeline.ExecuteAsync(testObject);
testNode.Status.Should().Be(NodeRunStatus.Completed);
result.Status.Should().Be(NodeResultStatus.Succeeded);
}
public async Task Pipeline_Overall_Result_Subject_Equals_Changed_Subject()
{
var pipelineNode = new PipelineNode <TestObjectA>();
var node1 = new SimpleTestNodeA1();
var node2 = new SubjectChangingNode1();
var node3 = new SimpleTestNodeA2();
pipelineNode.AddChild(node1);
pipelineNode.AddChild(node2);
pipelineNode.AddChild(node3);
var testObject = new TestObjectA();
NodeResult result = await pipelineNode.ExecuteAsync(testObject);
pipelineNode.Status.Should().Be(NodeRunStatus.Completed);
var childResults = result.ChildResults.ToList();
result.Subject.Should().NotBeSameAs(testObject);
result.Subject.Should().BeSameAs(childResults[1].Subject);
}
public async Task Adding_State_To_A_Node_Is_Available_In_Global_Context()
{
var pipelineNode = new PipelineNode <TestObjectA>();
pipelineNode.AddChild(new SimpleTestNodeA1());
pipelineNode.AddChild(new FuncNode <TestObjectA>
{
ExecutedFunc = ctxt =>
{
ctxt.State.Foo = "Bar";
return(Task.FromResult(NodeResultStatus.Succeeded));
}
});
var testObject = new TestObjectA();
var context = new ExecutionContext <TestObjectA>(testObject);
var result = await pipelineNode.ExecuteAsync(context);
result.Status.Should().Be(NodeResultStatus.Succeeded);
Assert.Equal("Bar", context.State.Foo);
}
private void SetRequiredNugetPackages(IEnumerable <PipelineNode> trainerNodes, ref bool includeLightGbmPackage,
ref bool includeMklComponentsPackage, ref bool includeFastTreePackage,
ref bool includeImageTransformerPackage, ref bool includeImageClassificationPackage, ref bool includeRecommenderPackage)
{
foreach (var node in trainerNodes)
{
PipelineNode currentNode = node;
if (currentNode.Name == TrainerName.Ova.ToString())
{
currentNode = (PipelineNode)currentNode.Properties["BinaryTrainer"];
}
if (_lightGbmTrainers.Contains(currentNode.Name))
{
includeLightGbmPackage = true;
}
else if (_mklComponentsTrainers.Contains(currentNode.Name))
{
includeMklComponentsPackage = true;
}
else if (_fastTreeTrainers.Contains(currentNode.Name))
{
includeFastTreePackage = true;
}
else if (_imageTransformers.Contains(currentNode.Name))
{
includeImageTransformerPackage = true;
}
else if (_imageClassificationTrainers.Contains(currentNode.Name))
{
includeImageClassificationPackage = true;
}
else if (_recommendationTrainers.Contains(currentNode.Name))
{
includeRecommenderPackage = true;
}
}
}
public async void When_Cancelling_Pipeline_At_Later_Node_Then_Status_Is_Success()
{
var pipelineNode = new PipelineNode <TestObjectA>();
var testNode1 = new SimpleTestNodeA1();
var testNode2 = new SimpleTestNodeA1(true, false, true);
var testNode3 = new SimpleTestNodeA2();
pipelineNode.AddChild(testNode1);
pipelineNode.AddChild(testNode2);
pipelineNode.AddChild(testNode3);
var testObject = new TestObjectA();
NodeResult result = await pipelineNode.ExecuteAsync(testObject);
result.Status.ShouldEqual(NodeResultStatus.Succeeded);
pipelineNode.Status.ShouldEqual(NodeRunStatus.Completed);
testNode1.Status.ShouldEqual(NodeRunStatus.Completed);
testNode2.Status.ShouldEqual(NodeRunStatus.NotRun);
testNode3.Status.ShouldEqual(NodeRunStatus.NotRun);
}
public async void Pipeline_Node_Results_Following_Subject_Change_Node_Return_Changed_Subject()
{
var pipelineNode = new PipelineNode <TestObjectA>();
var node1 = new SimpleTestNodeA1();
var node2 = new SubjectChangingNode1();
var node3 = new SimpleTestNodeA2();
pipelineNode.AddChild(node1);
pipelineNode.AddChild(node2);
pipelineNode.AddChild(node3);
var testObject = new TestObjectA();
NodeResult result = await pipelineNode.ExecuteAsync(testObject);
pipelineNode.Status.ShouldEqual(NodeRunStatus.Completed);
var childResults = result.ChildResults.ToList();
childResults[0].Subject.ShouldBeSameAs(testObject);
childResults[1].Subject.ShouldNotBeSameAs(testObject);
childResults[2].Subject.ShouldNotBeSameAs(testObject);
childResults[1].Subject.ShouldEqual(childResults[2].Subject);
}
public LinearSvm(PipelineNode node) : base(node)
{
}
public FastTreeTweedie(PipelineNode node) : base(node)
{
}
public FastTreeRegression(PipelineNode node) : base(node)
{
}
public FastTreeClassification(PipelineNode node) : base(node)
{
}
public FastForestRegression(PipelineNode node) : base(node)
{
}
