public async Task AutoMLExperiment_return_current_best_trial_when_ct_is_canceled_with_trial_completed_Async()
{
var context = new MLContext(1);
var pipeline = context.Transforms.Concatenate("Features", "Features")
.Append(context.Auto().Regression());
var dummyTrainer = new DummyTrialRunner(context, 1);
var experiment = context.Auto().CreateExperiment();
experiment.SetPipeline(pipeline)
.SetDataset(GetDummyData(), 10)
.SetEvaluateMetric(RegressionMetric.RootMeanSquaredError, "Label")
.SetTrainingTimeInSeconds(100)
.SetTrialRunner(dummyTrainer);
var cts = new CancellationTokenSource();
context.Log += (o, e) =>
{
if (e.RawMessage.Contains("Update Completed Trial"))
{
cts.CancelAfter(100);
}
};
var res = await experiment.RunAsync(cts.Token);
res.Metric.Should().BeGreaterThan(0);
}
public async Task AutoMLExperiment_throw_timeout_exception_when_ct_is_canceled_and_no_trial_completed_Async()
{
var context = new MLContext(1);
var pipeline = context.Transforms.Concatenate("Features", "Features")
.Append(context.Auto().Regression());
var dummyTrainer = new DummyTrialRunner(context, 5);
var experiment = context.Auto().CreateExperiment();
experiment.SetPipeline(pipeline)
.SetDataset(GetDummyData(), 10)
.SetEvaluateMetric(RegressionMetric.RootMeanSquaredError, "Label")
.SetTrainingTimeInSeconds(1)
.SetTrialRunner(dummyTrainer);
var cts = new CancellationTokenSource();
context.Log += (o, e) =>
{
if (e.RawMessage.Contains("Update Running Trial"))
{
cts.Cancel();
}
};
var runExperimentAction = async() => await experiment.RunAsync(cts.Token);
await runExperimentAction.Should().ThrowExactlyAsync <TimeoutException>();
}
public async Task AutoMLExperiment_finish_training_when_time_is_up_Async()
{
var context = new MLContext(1);
var pipeline = context.Transforms.Concatenate("Features", "Features")
.Append(context.Auto().Regression());
var dummyTrainer = new DummyTrialRunner(context, 1);
var experiment = context.Auto().CreateExperiment();
experiment.SetPipeline(pipeline)
.SetDataset(GetDummyData(), 10)
.SetEvaluateMetric(RegressionMetric.RootMeanSquaredError, "Label")
.SetTrainingTimeInSeconds(5)
.SetTrialRunner(dummyTrainer);
var cts = new CancellationTokenSource();
cts.CancelAfter(10 * 1000);
var res = await experiment.RunAsync(cts.Token);
res.Metric.Should().BeGreaterThan(0);
cts.IsCancellationRequested.Should().BeFalse();
}
