Unable to use CostFrugalTuner in AutoML

[hieu-n]

System Information (please complete the following information):

• OS & Version: Ubuntu 22.04.2 LTS
• ML.NET Version: 2.0.1
• .NET Version: 7.0.101

Describe the bug
Trying to SetCostFrugalTuner for an AutoML experiment and got the exception:

Unhandled exception. System.AggregateException: One or more errors occurred. (Object reference not set to an instance of an object.)
 ---> System.NullReferenceException: Object reference not set to an instance of an object.
 at Microsoft.ML.AutoML.CostFrugalTuner..ctor(AutoMLExperimentSettings settings, ITrialResultManager trialResultManager)
 at Microsoft.ML.AutoML.AutoMLExperimentExtension.<>c.<SetCostFrugalTuner>b__9_0(IServiceProvider service)
 at Microsoft.Extensions.DependencyInjection.ServiceLookup.CallSiteRuntimeResolver.VisitFactory(FactoryCallSite factoryCallSite, RuntimeResolverContext context)
 at Microsoft.Extensions.DependencyInjection.ServiceLookup.CallSiteVisitor`2.VisitCallSiteMain(ServiceCallSite callSite, TArgument argument)
 at Microsoft.Extensions.DependencyInjection.ServiceLookup.CallSiteRuntimeResolver.VisitRootCache(ServiceCallSite callSite, RuntimeResolverContext context)
 at Microsoft.Extensions.DependencyInjection.ServiceLookup.CallSiteVisitor`2.VisitCallSite(ServiceCallSite callSite, TArgument argument)
 at Microsoft.Extensions.DependencyInjection.ServiceLookup.CallSiteRuntimeResolver.Resolve(ServiceCallSite callSite, ServiceProviderEngineScope scope)
 at Microsoft.Extensions.DependencyInjection.ServiceProvider.CreateServiceAccessor(Type serviceType)
 at System.Collections.Concurrent.ConcurrentDictionary`2.GetOrAdd(TKey key, Func`2 valueFactory)
 at Microsoft.Extensions.DependencyInjection.ServiceProvider.GetService(Type serviceType, ServiceProviderEngineScope serviceProviderEngineScope)
 at Microsoft.Extensions.DependencyInjection.ServiceProvider.GetService(Type serviceType)
 at Microsoft.Extensions.DependencyInjection.ServiceProviderServiceExtensions.GetService[T](IServiceProvider provider)
 at Microsoft.ML.AutoML.AutoMLExperiment.RunAsync(CancellationToken ct)
 --- End of inner exception stack trace ---
 at System.Threading.Tasks.Task.ThrowIfExceptional(Boolean includeTaskCanceledExceptions)
 at System.Threading.Tasks.Task`1.GetResultCore(Boolean waitCompletionNotification)
 at Microsoft.ML.AutoML.AutoMLExperiment.Run()
 at SampleProject.Program.Main(String[] args) in /home/myhome/SampleProject/Program.cs:line 54 

To Reproduce
Steps to reproduce the behavior:

1. Create a new console application with the command dotnet new console -o SampleProject.
2. Adding ML.Net packages.
3. Create a simple code to use AutoML to train a binary classification model and SetCostFrugalTuner().
4. Run and encounter the exception.

Expected behavior
The program should run without exceptions and the model is successfully trained.

Screenshots, Code, Sample Projects
SampleProject.csproj:

<Project Sdk="Microsoft.NET.Sdk">

 <PropertyGroup>
 <OutputType>Exe</OutputType>
 <TargetFramework>net7.0</TargetFramework>
 <Nullable>enable</Nullable>
 </PropertyGroup>
 
 <ItemGroup>
 <PackageReference Include="Microsoft.ML" Version="2.0.1" />
 <PackageReference Include="Microsoft.ML.AutoML" Version="0.20.1" />
 <PackageReference Include="Microsoft.ML.LightGbm" Version="2.0.1" />
 <PackageReference Include="Microsoft.ML.Probabilistic.Compiler" Version="0.4.2301.301" />
 <PackageReference Include="MKL.NET.linux-x64" Version="2022.0.1.117" />
 </ItemGroup>

</Project>

Program.cs

using Microsoft.ML;
using Microsoft.ML.AutoML;
using Microsoft.ML.Data;

namespace SampleProject;

public class HousingData
{
 public float Size { get; set; }

 [VectorType(3)]
 public float[] HistoricalPrices { get; set; }

 public float CurrentPrice { get; set; }
 public bool Label { get; set; }
}

public class Program
{
 public static void Main(string[] args)
 {
 HousingData[] inMemoryCollection = new HousingData[]
 {
 new HousingData
 {
 Size = 700f,
 HistoricalPrices = new float[]
 {
 100000f, 3000000f, 250000f
 },
 CurrentPrice = 500000f,
 Label = true
 },
 new HousingData
 {
 Size = 1000f,
 HistoricalPrices = new float[]
 {
 600000f, 400000f, 650000f
 },
 CurrentPrice = 700000f,
 Label = false
 }
 };
 // Create MLContext
 MLContext mlContext = new MLContext();

 //Load Data
 IDataView data = mlContext.Data.LoadFromEnumerable(inMemoryCollection);
 var pipeline = mlContext.Auto().Featurizer(data, excludeColumns: new[]{"Label"}).Append(
 mlContext.Auto().BinaryClassification());
 var experiment = new MLContext().Auto().CreateExperiment();
 experiment.SetPipeline(pipeline).SetTrainingTimeInSeconds(60).SetDataset(data).SetCostFrugalTuner();
 experiment.Run();
 }
}

Additional context
Add any other context about the problem here.