Polish early stop rules in fast tree

src/Microsoft.ML.FastTree/BoostingFastTree.cs

@@ -49,7 +49,8 @@ private protected override void CheckOptions(IChannel ch)
             if (FastTreeTrainerOptions.EnablePruning && !HasValidSet)
                 throw ch.Except("Cannot perform pruning (pruning) without a validation set (valid).");
 
-            if (FastTreeTrainerOptions.EarlyStoppingRule != null && !HasValidSet)
+            bool doEarlyStop = FastTreeTrainerOptions.EarlyStoppingRuleFactory != null;
+            if (doEarlyStop && !HasValidSet)
                 throw ch.Except("Cannot perform early stopping without a validation set (valid).");
 
             if (FastTreeTrainerOptions.UseTolerantPruning && (!FastTreeTrainerOptions.EnablePruning || !HasValidSet))
@@ -113,9 +114,9 @@ private protected override IGradientAdjuster MakeGradientWrapper(IChannel ch)
                 return new BestStepRegressionGradientWrapper();
         }
 
-        private protected override bool ShouldStop(IChannel ch, ref IEarlyStoppingCriterion earlyStoppingRule, ref int bestIteration)
+        private protected override bool ShouldStop(IChannel ch, ref EarlyStoppingRuleBase earlyStoppingRule, ref int bestIteration)
         {
-            if (FastTreeTrainerOptions.EarlyStoppingRule == null)
+            if (FastTreeTrainerOptions.EarlyStoppingRuleFactory == null)
                 return false;
 
             ch.AssertValue(ValidTest);
@@ -128,13 +129,16 @@ private protected override bool ShouldStop(IChannel ch, ref IEarlyStoppingCriter
             var trainingResult = TrainTest.ComputeTests().First();
             ch.Assert(trainingResult.FinalValue >= 0);
 
-            // Create early stopping rule.
+            // Create early stopping rule if it's null.
             if (earlyStoppingRule == null)
             {
-                earlyStoppingRule = FastTreeTrainerOptions.EarlyStoppingRule.CreateComponent(Host, lowerIsBetter);
-                ch.Assert(earlyStoppingRule != null);
+                if (FastTreeTrainerOptions.EarlyStoppingRuleFactory != null)
+                    earlyStoppingRule = FastTreeTrainerOptions.EarlyStoppingRuleFactory.CreateComponent(Host, lowerIsBetter);
             }
 
+            // Early stopping rule cannot be null!
+            ch.Assert(earlyStoppingRule != null);
+
             bool isBestCandidate;
             bool shouldStop = earlyStoppingRule.CheckScore((float)validationResult.FinalValue,
                 (float)trainingResult.FinalValue, out isBestCandidate);

src/Microsoft.ML.FastTree/FastTree.cs

@@ -245,7 +245,7 @@ private protected void TrainCore(IChannel ch)
             }
         }
 
-        private protected virtual bool ShouldStop(IChannel ch, ref IEarlyStoppingCriterion earlyStopping, ref int bestIteration)
+        private protected virtual bool ShouldStop(IChannel ch, ref EarlyStoppingRuleBase earlyStopping, ref int bestIteration)
         {
             bestIteration = Ensemble.NumTrees;
             return false;
@@ -650,7 +650,7 @@ private protected virtual void Train(IChannel ch)
 #endif
 #endif
 
-            IEarlyStoppingCriterion earlyStoppingRule = null;
+            EarlyStoppingRuleBase earlyStoppingRule = null;
             int bestIteration = 0;
             int emptyTrees = 0;
             using (var pch = Host.StartProgressChannel("FastTree training"))

src/Microsoft.ML.FastTree/FastTreeArguments.cs

@@ -621,9 +621,29 @@ public enum OptimizationAlgorithmType { GradientDescent, AcceleratedGradientDesc
         /// <summary>
         /// Early stopping rule. (Validation set (/valid) is required).
         /// </summary>
-        [Argument(ArgumentType.Multiple, HelpText = "Early stopping rule. (Validation set (/valid) is required.)", ShortName = "esr", NullName = "<Disable>")]
+        [BestFriend]
+        [Argument(ArgumentType.Multiple, HelpText = "Early stopping rule. (Validation set (/valid) is required.)", Name = "EarlyStoppingRule", ShortName = "esr", NullName = "<Disable>")]
         [TGUI(Label = "Early Stopping Rule", Description = "Early stopping rule. (Validation set (/valid) is required.)")]
-        public IEarlyStoppingCriterionFactory EarlyStoppingRule;
+        internal IEarlyStoppingCriterionFactory EarlyStoppingRuleFactory;
+
+        /// <summary>
+        /// The underlying state of <see cref="EarlyStoppingRuleFactory"/> and <see cref="EarlyStoppingRule"/>.
+        /// </summary>
+        private EarlyStoppingRuleBase _earlyStoppingRuleBase;
+
+        /// <summary>
+        /// Early stopping rule used to terminate training process once meeting a specified criterion. Possible choices are
+        /// <see cref="EarlyStoppingRuleBase"/>'s implementations such as <see cref="TolerantEarlyStoppingRule"/> and <see cref="GeneralityLossRule"/>.
+        /// </summary>
+        public EarlyStoppingRuleBase EarlyStoppingRule
+        {
+            get { return _earlyStoppingRuleBase;  }
+            set
+            {
+                _earlyStoppingRuleBase = value;
+                EarlyStoppingRuleFactory = _earlyStoppingRuleBase.BuildFactory();
+            }
+        }
 
         /// <summary>
         /// Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3).

src/Microsoft.ML.FastTree/FastTreeRanking.cs

@@ -156,8 +156,12 @@ private protected override void CheckOptions(IChannel ch)
                 Dataset.DatasetSkeleton.LabelGainMap = gains;
             }
 
-            ch.CheckUserArg((FastTreeTrainerOptions.EarlyStoppingRule == null && !FastTreeTrainerOptions.EnablePruning) || (FastTreeTrainerOptions.EarlyStoppingMetrics == 1 || FastTreeTrainerOptions.EarlyStoppingMetrics == 3), nameof(FastTreeTrainerOptions.EarlyStoppingMetrics),
-                "earlyStoppingMetrics should be 1 or 3.");
+            bool doEarlyStop = FastTreeTrainerOptions.EarlyStoppingRuleFactory != null ||
+                FastTreeTrainerOptions.EnablePruning;
+
+            if (doEarlyStop)
+                ch.CheckUserArg(FastTreeTrainerOptions.EarlyStoppingMetrics == 1 || FastTreeTrainerOptions.EarlyStoppingMetrics == 3,
+                    nameof(FastTreeTrainerOptions.EarlyStoppingMetrics), "should be 1 or 3.");
 
             base.CheckOptions(ch);
         }

src/Microsoft.ML.FastTree/FastTreeRegression.cs

@@ -105,8 +105,12 @@ private protected override void CheckOptions(IChannel ch)
 
             base.CheckOptions(ch);
 
-            ch.CheckUserArg((FastTreeTrainerOptions.EarlyStoppingRule == null && !FastTreeTrainerOptions.EnablePruning) || (FastTreeTrainerOptions.EarlyStoppingMetrics >= 1 && FastTreeTrainerOptions.EarlyStoppingMetrics <= 2), nameof(FastTreeTrainerOptions.EarlyStoppingMetrics),
-                    "earlyStoppingMetrics should be 1 or 2. (1: L1, 2: L2)");
+            bool doEarlyStop = FastTreeTrainerOptions.EarlyStoppingRuleFactory != null ||
+                FastTreeTrainerOptions.EnablePruning;
+
+            if (doEarlyStop)
+                ch.CheckUserArg(FastTreeTrainerOptions.EarlyStoppingMetrics >= 1 && FastTreeTrainerOptions.EarlyStoppingMetrics <= 2,
+                    nameof(FastTreeTrainerOptions.EarlyStoppingMetrics), "earlyStoppingMetrics should be 1 or 2. (1: L1, 2: L2)");
         }
 
         private static SchemaShape.Column MakeLabelColumn(string labelColumn)

src/Microsoft.ML.FastTree/FastTreeTweedie.cs

@@ -112,12 +112,16 @@ private protected override void CheckOptions(IChannel ch)
             // REVIEW: In order to properly support early stopping, the early stopping metric should be a subcomponent, not just
             // a simple integer, because the metric that we might want is parameterized by this floating point "index" parameter. For now
             // we just leave the existing regression checks, though with a warning.
-
             if (FastTreeTrainerOptions.EarlyStoppingMetrics > 0)
                 ch.Warning("For Tweedie regression, early stopping does not yet use the Tweedie distribution.");
 
-            ch.CheckUserArg((FastTreeTrainerOptions.EarlyStoppingRule == null && !FastTreeTrainerOptions.EnablePruning) || (FastTreeTrainerOptions.EarlyStoppingMetrics >= 1 && FastTreeTrainerOptions.EarlyStoppingMetrics <= 2), nameof(FastTreeTrainerOptions.EarlyStoppingMetrics),
-                    "earlyStoppingMetrics should be 1 or 2. (1: L1, 2: L2)");
+            bool doEarlyStop = FastTreeTrainerOptions.EarlyStoppingRuleFactory != null ||
+                FastTreeTrainerOptions.EnablePruning;
+
+            // Please do not remove it! See comment above.
+            if (doEarlyStop)
+                ch.CheckUserArg(FastTreeTrainerOptions.EarlyStoppingMetrics == 1 || FastTreeTrainerOptions.EarlyStoppingMetrics == 2,
+                nameof(FastTreeTrainerOptions.EarlyStoppingMetrics), "should be 1 (L1-norm) or 2 (L2-norm).");
         }
 
         private protected override ObjectiveFunctionBase ConstructObjFunc(IChannel ch)