move ReportTrialResourceUsage to IPerformanceMonitor and rename it to OnPerformanceMetricsUpdatedHandler

src/Microsoft.ML.AutoML.Interactive/NotebookMonitor.cs

@@ -24,8 +24,6 @@ public class NotebookMonitor : IMonitor
         public List<TrialResult> CompletedTrials { get; set; }
         public DataFrame TrialData { get; set; }
 
-        public int ResourceUsageCheckInterval => 5000;
-
         public NotebookMonitor(SweepablePipeline pipeline)
         {
             CompletedTrials = new List<TrialResult>();
@@ -86,9 +84,5 @@ public void SetUpdate(DisplayedValue valueToUpdate)
             _valueToUpdate = valueToUpdate;
             ThrottledUpdate();
         }
-
-        public void ReportTrialResourceUsage(TrialSettings setting)
-        {
-        }
     }
 }

src/Microsoft.ML.AutoML/API/AutoMLExperimentExtension.cs

@@ -149,18 +149,53 @@ public static AutoMLExperiment SetPipeline(this AutoMLExperiment experiment, Swe
             return experiment;
         }
 
+        /// <summary>
+        /// Set <see cref="DefaultPerformanceMonitor"/> as <see cref="IPerformanceMonitor"/> for <see cref="AutoMLExperiment"/>.
+        /// </summary>
+        /// <param name="experiment"><see cref="AutoMLExperiment"/></param>
+        /// <param name="checkIntervalInMilliseconds">the interval in milliseconds for <see cref="DefaultPerformanceMonitor"/> to sample <see cref="TrialPerformanceMetrics"/></param>
+        /// <returns></returns>
         public static AutoMLExperiment SetPerformanceMonitor(this AutoMLExperiment experiment, int checkIntervalInMilliseconds = 1000)
         {
             experiment.SetPerformanceMonitor((service) =>
             {
                 var channel = service.GetService<IChannel>();
-
-                return new DefaultPerformanceMonitor(channel, checkIntervalInMilliseconds);
+                var settings = service.GetRequiredService<AutoMLExperiment.AutoMLExperimentSettings>();
+                return new DefaultPerformanceMonitor(settings, channel, checkIntervalInMilliseconds);
             });
 
             return experiment;
         }
 
+        /// <summary>
+        /// Set a custom performance monitor as <see cref="IPerformanceMonitor"/> for <see cref="AutoMLExperiment"/>.
+        /// </summary>
+        /// <typeparam name="TPerformanceMonitor"></typeparam>
+        /// <param name="experiment"><see cref="AutoMLExperiment"/></param>
+        /// <param name="factory"></param>
+        /// <returns></returns>
+        public static AutoMLExperiment SetPerformanceMonitor<TPerformanceMonitor>(this AutoMLExperiment experiment, Func<IServiceProvider, TPerformanceMonitor> factory)
+            where TPerformanceMonitor : class, IPerformanceMonitor
+        {
+            experiment.ServiceCollection.AddTransient<IPerformanceMonitor>(factory);
+
+            return experiment;
+        }
+
+        /// <summary>
+        /// Set a custom performance monitor as <see cref="IPerformanceMonitor"/> for <see cref="AutoMLExperiment"/>.
+        /// </summary>
+        /// <typeparam name="TPerformanceMonitor"></typeparam>
+        /// <param name="experiment"><see cref="AutoMLExperiment"/></param>
+        /// <returns></returns>
+        public static AutoMLExperiment SetPerformanceMonitor<TPerformanceMonitor>(this AutoMLExperiment experiment)
+            where TPerformanceMonitor : class, IPerformanceMonitor
+        {
+            experiment.ServiceCollection.AddTransient<IPerformanceMonitor, TPerformanceMonitor>();
+
+            return experiment;
+        }
+
         /// <summary>
         /// Set <see cref="SmacTuner"/> as tuner for hyper-parameter optimization. The performance of smac is in a large extend determined 
         /// by <paramref name="numberOfTrees"/>, <paramref name="nMinForSpit"/> and <paramref name="splitRatio"/>, which are used to fit smac's inner 

src/Microsoft.ML.AutoML/AutoMLExperiment/AutoMLExperiment.cs

@@ -194,22 +194,6 @@ public AutoMLExperiment SetTuner<TTuner>()
             return this;
         }
 
-        internal AutoMLExperiment SetPerformanceMonitor<TPerformanceMonitor>()
-            where TPerformanceMonitor : class, IPerformanceMonitor
-        {
-            _serviceCollection.AddTransient<IPerformanceMonitor, TPerformanceMonitor>();
-
-            return this;
-        }
-
-        internal AutoMLExperiment SetPerformanceMonitor<TPerformanceMonitor>(Func<IServiceProvider, TPerformanceMonitor> factory)
-            where TPerformanceMonitor : class, IPerformanceMonitor
-        {
-            _serviceCollection.AddTransient<IPerformanceMonitor>(factory);
-
-            return this;
-        }
-
         /// <summary>
         /// Run experiment and return the best trial result synchronizely.
         /// </summary>
@@ -257,29 +241,14 @@ public async Task<TrialResult> RunAsync(CancellationToken ct = default)
                 {
                     TrialId = trialNum++,
                     Parameter = Parameter.CreateNestedParameter(),
-                    CancellationTokenSource = null,
-                    PerformanceMetrics = new TrialPerformanceMetrics(),
                 };
                 var parameter = tuner.Propose(trialSettings);
                 trialSettings.Parameter = parameter;
 
                 using (var trialCancellationTokenSource = new CancellationTokenSource())
                 {
-                    trialSettings.CancellationTokenSource = trialCancellationTokenSource;
                     monitor?.ReportRunningTrial(trialSettings);
 
-                    System.Timers.Timer resourceUsageTimer = null;
-                    if ((monitor != null) && (monitor?.ResourceUsageCheckInterval > 0))
-                    {
-                        resourceUsageTimer = new System.Timers.Timer(monitor.ResourceUsageCheckInterval);
-                        resourceUsageTimer.Elapsed += (o, e) =>
-                        {
-                            monitor?.ReportTrialResourceUsage(trialSettings);
-                        };
-                        resourceUsageTimer.AutoReset = true;
-                        resourceUsageTimer.Enabled = false;
-                    }
-
                     void handler(object o, EventArgs e)
                     {
                         // only force-canceling running trials when there's completed trials.
@@ -296,21 +265,11 @@ void handler(object o, EventArgs e)
 
                             performanceMonitor.PerformanceMetricsUpdated += (o, metrics) =>
                             {
-                                trialSettings.PerformanceMetrics = metrics;
-
-                                if (_settings.MaximumMemoryUsageInMegaByte is double d && metrics.PeakMemoryUsage > d && !trialCancellationTokenSource.IsCancellationRequested)
-                                {
-                                    logger.Trace($"cancel current trial {trialSettings.TrialId} because it uses {metrics.PeakMemoryUsage} mb memory and the maximum memory usage is {d}");
-                                    trialCancellationTokenSource.Cancel();
-
-                                    GC.AddMemoryPressure(Convert.ToInt64(metrics.PeakMemoryUsage) * 1024 * 1024);
-                                    GC.Collect();
-                                }
+                                performanceMonitor.OnPerformanceMetricsUpdatedHandler(trialSettings, metrics, trialCancellationTokenSource);
                             };
 
                             var trialTask = runner.RunAsync(trialSettings, trialCancellationTokenSource.Token);
                             performanceMonitor.Start();
-                            resourceUsageTimer?.Start();
                             logger.Trace($"trial setting - {JsonSerializer.Serialize(trialSettings)}");
                             var trialResult = await trialTask;
 
@@ -365,7 +324,6 @@ void handler(object o, EventArgs e)
                     finally
                     {
                         aggregateTrainingStopManager.OnStopTraining -= handler;
-                        resourceUsageTimer?.Stop();
                     }
                 }
             }

src/Microsoft.ML.AutoML/AutoMLExperiment/IMonitor.cs

@@ -13,15 +13,13 @@ namespace Microsoft.ML.AutoML
     /// </summary>
     public interface IMonitor
     {
-        /// <summary>
-        /// Interval in milliseconds to report resource usage.
-        /// </summary>
-        int ResourceUsageCheckInterval { get; }
         void ReportCompletedTrial(TrialResult result);
+
         void ReportBestTrial(TrialResult result);
+
         void ReportFailTrial(TrialSettings settings, Exception exception = null);
+
         void ReportRunningTrial(TrialSettings settings);
-        void ReportTrialResourceUsage(TrialSettings settings);
     }
 
     /// <summary>
@@ -32,14 +30,12 @@ internal class MLContextMonitor : IMonitor
         private readonly IChannel _logger;
         private readonly List<TrialResult> _completedTrials;
         private readonly SweepablePipeline _pipeline;
-        public int ResourceUsageCheckInterval { get; private set; }
 
-        public MLContextMonitor(IChannel logger, SweepablePipeline pipeline, int resourceUsageCheckInterval = 5000)
+        public MLContextMonitor(IChannel logger, SweepablePipeline pipeline)
         {
             _logger = logger;
             _completedTrials = new List<TrialResult>();
             _pipeline = pipeline;
-            ResourceUsageCheckInterval = resourceUsageCheckInterval;
         }
 
         public virtual void ReportBestTrial(TrialResult result)
@@ -62,10 +58,6 @@ public virtual void ReportRunningTrial(TrialSettings setting)
         {
             _logger.Info($"Update Running Trial - Id: {setting.TrialId}");
         }
-
-        public void ReportTrialResourceUsage(TrialSettings setting)
-        {
-        }
     }
 
     internal class TrialResultMonitor<TMetrics> : MLContextMonitor

src/Microsoft.ML.AutoML/AutoMLExperiment/IPerformanceMonitor.cs

@@ -8,13 +8,15 @@
 using System.IO;
 using System.Linq;
 using System.Text;
+using System.Threading;
 using System.Threading.Tasks;
 using System.Timers;
 using Microsoft.ML.Runtime;
+using Timer = System.Timers.Timer;
 
 namespace Microsoft.ML.AutoML
 {
-    internal interface IPerformanceMonitor : IDisposable
+    public interface IPerformanceMonitor : IDisposable
     {
         void Start();
 
@@ -24,20 +26,28 @@ internal interface IPerformanceMonitor : IDisposable
 
         double? GetPeakCpuUsage();
 
+        /// <summary>
+        /// The handler function every time <see cref="PerformanceMetricsUpdated"/> get fired.
+        /// </summary>
+        void OnPerformanceMetricsUpdatedHandler(TrialSettings trialSettings, TrialPerformanceMetrics metrics, CancellationTokenSource trialCancellationTokenSource);
+
+
         public event EventHandler<TrialPerformanceMetrics> PerformanceMetricsUpdated;
     }
 
-    internal class DefaultPerformanceMonitor : IPerformanceMonitor
+    public class DefaultPerformanceMonitor : IPerformanceMonitor
     {
         private readonly IChannel _logger;
+        private readonly AutoMLExperiment.AutoMLExperimentSettings _settings;
         private Timer _timer;
         private double? _peakCpuUsage;
         private double? _peakMemoryUsage;
         private readonly int _checkIntervalInMilliseconds;
         private TimeSpan _totalCpuProcessorTime;
 
-        public DefaultPerformanceMonitor(IChannel logger, int checkIntervalInMilliseconds)
+        public DefaultPerformanceMonitor(AutoMLExperiment.AutoMLExperimentSettings settings, IChannel logger, int checkIntervalInMilliseconds)
         {
+            _settings = settings;
             _logger = logger;
             _checkIntervalInMilliseconds = checkIntervalInMilliseconds;
         }
@@ -122,5 +132,17 @@ private void SampleCpuAndMemoryUsage()
                 PerformanceMetricsUpdated?.Invoke(this, metrics);
             }
         }
+
+        public virtual void OnPerformanceMetricsUpdatedHandler(TrialSettings trialSettings, TrialPerformanceMetrics metrics, CancellationTokenSource trialCancellationTokenSource)
+        {
+            if (_settings.MaximumMemoryUsageInMegaByte is double d && metrics.PeakMemoryUsage > d && !trialCancellationTokenSource.IsCancellationRequested)
+            {
+                _logger.Trace($"cancel current trial {trialSettings.TrialId} because it uses {metrics.PeakMemoryUsage} mb memory and the maximum memory usage is {d}");
+                trialCancellationTokenSource.Cancel();
+
+                GC.AddMemoryPressure(Convert.ToInt64(metrics.PeakMemoryUsage) * 1024 * 1024);
+                GC.Collect();
+            }
+        }
     }
 }

src/Microsoft.ML.AutoML/AutoMLExperiment/TrialSettings.cs

@@ -23,14 +23,5 @@ public class TrialSettings
         /// Parameters for the pipeline used in this trial
         /// </summary>
         public Parameter Parameter { get; set; }
-        /// <summary>
-        /// Cancellation token source to have the ability to cancel the trial
-        /// </summary>
-        [JsonIgnore]
-        public CancellationTokenSource CancellationTokenSource { get; set; }
-        /// <summary>
-        /// Performance metrics of the trial
-        /// </summary>
-        public TrialPerformanceMetrics PerformanceMetrics { get; internal set; }
     }
 }

test/Microsoft.ML.AutoML.Tests/AutoMLExperimentTests.cs

@@ -81,8 +81,7 @@ public async Task AutoMLExperiment_cancel_trial_when_exceeds_memory_limit_Async(
                           return new DummyTrialRunner(settings, 5, channel);
                       })
                       .SetTuner<RandomSearchTuner>()
-                      .SetMaximumMemoryUsageInMegaByte(0.01)
-                      .SetPerformanceMonitor<DummyPeformanceMonitor>();
+                      .SetMaximumMemoryUsageInMegaByte(0.01);
 
             var runExperimentAction = async () => await experiment.RunAsync();
             await runExperimentAction.Should().ThrowExactlyAsync<TimeoutException>();
@@ -423,6 +422,10 @@ public void Dispose()
             return 1000;
         }
 
+        public void OnPerformanceMetricsUpdatedHandler(TrialSettings trialSettings, TrialPerformanceMetrics metrics, CancellationTokenSource trialCancellationTokenSource)
+        {
+        }
+
         public void Start()
         {
             if (_timer == null)