Revert "Set Nullable Auto params to null values" (dotnet#53)

srsaggam · Dmitry-A · commit 20e337f8bb83 · 2019-08-22T14:35:41.000-07:00
* Revert "First public api propsal (dotnet#52)" This reverts commit e4a64cf. * Revert "Set Nullable Auto params to null values (dotnet#50)" This reverts commit 41c663c.
diff --git a/src/AutoML/TrainerExtensions/SweepableParams.cs b/src/AutoML/TrainerExtensions/SweepableParams.cs
@@ -31,14 +31,14 @@ private static IEnumerable<SweepableParam> BuildOnlineLinearArgsParams()
 
         private static IEnumerable<SweepableParam> BuildTreeArgsParams()
         {
-            return new SweepableParam[]
-            {
+           return new SweepableParam[]
+           {
                 new SweepableLongParam("NumLeaves", 2, 128, isLogScale: true, stepSize: 4),
                 new SweepableDiscreteParam("MinDocumentsInLeafs", new object[] { 1, 10, 50 }),
                 new SweepableDiscreteParam("NumTrees", new object[] { 20, 100, 500 }),
                 new SweepableFloatParam("LearningRates", 0.025f, 0.4f, isLogScale: true),
                 new SweepableFloatParam("Shrinkage", 0.025f, 4f, isLogScale: true),
-            };
+           };
         }
 
         private static IEnumerable<SweepableParam> BuildLbfgsArgsParams()
@@ -123,24 +123,22 @@ public static IEnumerable<SweepableParam> BuildPoissonRegressionParams()
         public static IEnumerable<SweepableParam> BuildSdcaParams()
         {
             return new SweepableParam[] {
-                new SweepableDiscreteParam("L2Const", new object[] { null, 1e-7f, 1e-6f, 1e-5f, 1e-4f, 1e-3f, 1e-2f }),
-                new SweepableDiscreteParam("L1Threshold", new object[] { null, 0f, 0.25f, 0.5f, 0.75f, 1f }),
+                new SweepableDiscreteParam("L2Const", new object[] { "<Auto>", 1e-7f, 1e-6f, 1e-5f, 1e-4f, 1e-3f, 1e-2f }),
+                new SweepableDiscreteParam("L1Threshold", new object[] { "<Auto>", 0f, 0.25f, 0.5f, 0.75f, 1f }),
                 new SweepableDiscreteParam("ConvergenceTolerance", new object[] { 0.001f, 0.01f, 0.1f, 0.2f }),
-                new SweepableDiscreteParam("MaxIterations", new object[] { null, 10, 20, 100 }),
+                new SweepableDiscreteParam("MaxIterations", new object[] { "<Auto>", 10, 20, 100 }),
                 new SweepableDiscreteParam("Shuffle", null, isBool: true),
                 new SweepableDiscreteParam("BiasLearningRate", new object[] { 0.0f, 0.01f, 0.1f, 1f })
             };
         }
 
-        public static IEnumerable<SweepableParam> BuildOrdinaryLeastSquaresParams()
-        {
+        public static IEnumerable<SweepableParam> BuildOrdinaryLeastSquaresParams() {
             return new SweepableParam[] {
                 new SweepableDiscreteParam("L2Weight", new object[] { 1e-6f, 0.1f, 1f })
             };
         }
 
-        public static IEnumerable<SweepableParam> BuildSgdParams()
-        {
+        public static IEnumerable<SweepableParam> BuildSgdParams() {
             return new SweepableParam[] {
                 new SweepableDiscreteParam("L2Weight", new object[] { 1e-7f, 5e-7f, 1e-6f, 5e-6f, 1e-5f }),
                 new SweepableDiscreteParam("ConvergenceTolerance", new object[] { 1e-2f, 1e-3f, 1e-4f, 1e-5f }),
@@ -149,13 +147,12 @@ public static IEnumerable<SweepableParam> BuildSgdParams()
             };
         }
 
-        public static IEnumerable<SweepableParam> BuildSymSgdParams()
-        {
+        public static IEnumerable<SweepableParam> BuildSymSgdParams() {
             return new SweepableParam[] {
                 new SweepableDiscreteParam("NumberOfIterations", new object[] { 1, 5, 10, 20, 30, 40, 50 }),
-                new SweepableDiscreteParam("LearningRate", new object[] { null, 1e1f, 1e0f, 1e-1f, 1e-2f, 1e-3f }),
+                new SweepableDiscreteParam("LearningRate", new object[] { "<Auto>", 1e1f, 1e0f, 1e-1f, 1e-2f, 1e-3f }),
                 new SweepableDiscreteParam("L2Regularization", new object[] { 0.0f, 1e-5f, 1e-5f, 1e-6f, 1e-7f }),
-                new SweepableDiscreteParam("UpdateFrequency", new object[] { null, 5, 20 })
+                new SweepableDiscreteParam("UpdateFrequency", new object[] { "<Auto>", 5, 20 })
             };
         }
     }
diff --git a/src/AutoML/TrainerExtensions/TrainerExtensionUtil.cs b/src/AutoML/TrainerExtensions/TrainerExtensionUtil.cs
@@ -77,7 +77,7 @@ public static Action<LightGbmArguments> CreateLightGbmArgsFunc(IEnumerable<Sweep
 
         public static IDictionary<string, object> BuildPipelineNodeProps(TrainerName trainerName, IEnumerable<SweepableParam> sweepParams)
         {
-            if (trainerName == TrainerName.LightGbmBinary || trainerName == TrainerName.LightGbmMulti ||
+            if(trainerName == TrainerName.LightGbmBinary || trainerName == TrainerName.LightGbmMulti ||
                 trainerName == TrainerName.LightGbmRegression)
             {
                 return BuildLightGbmPipelineNodeProps(sweepParams);
@@ -96,7 +96,7 @@ private static IDictionary<string, object> BuildLightGbmPipelineNodeProps(IEnume
 
             var props = parentArgParams.ToDictionary(p => p.Name, p => (object)p.ProcessedValue());
             props[LightGbmTreeBoosterPropName] = treeBoosterCustomProp;
-
+            
             return props;
         }
 
@@ -155,9 +155,24 @@ public static void UpdateFields(object obj, IEnumerable<SweepableParam> sweepPar
                     {
                         var optIndex = (int)dp.RawValue;
                         //Contracts.Assert(0 <= optIndex && optIndex < dp.Options.Length, $"Options index out of range: {optIndex}");
-                        var option = dp.Options[optIndex];
-
-                        if (option != null)
+                        var option = dp.Options[optIndex].ToString().ToLower();
+
+                        // Handle <Auto> string values in sweep params
+                        if (option == "auto" || option == "<auto>" || option == "< auto >")
+                        {
+                            //Check if nullable type, in which case 'null' is the auto value.
+                            if (Nullable.GetUnderlyingType(fi.FieldType) != null)
+                                fi.SetValue(obj, null);
+                            else if (fi.FieldType.IsEnum)
+                            {
+                                // Check if there is an enum option named Auto
+                                var enumDict = fi.FieldType.GetEnumValues().Cast<int>()
+                                    .ToDictionary(v => Enum.GetName(fi.FieldType, v), v => v);
+                                if (enumDict.ContainsKey("Auto"))
+                                    fi.SetValue(obj, enumDict["Auto"]);
+                            }
+                        }
+                        else
                             SetValue(fi, (IComparable)dp.Options[optIndex], obj, propType);
                     }
                     else
diff --git a/src/Test/TrainerExtensionsTests.cs b/src/Test/TrainerExtensionsTests.cs
@@ -17,7 +17,7 @@ public void TrainerExtensionInstanceTests()
         {
             var context = new MLContext();
             var trainerNames = Enum.GetValues(typeof(TrainerName)).Cast<TrainerName>();
-            foreach (var trainerName in trainerNames)
+            foreach(var trainerName in trainerNames)
             {
                 var extension = TrainerExtensionCatalog.GetTrainerExtension(trainerName);
                 var instance = extension.CreateInstance(context, null);
@@ -33,7 +33,7 @@ public void GetTrainersByMaxIterations()
             var tasks = new TaskKind[] { TaskKind.BinaryClassification,
                 TaskKind.MulticlassClassification, TaskKind.Regression  };
 
-            foreach (var task in tasks)
+            foreach(var task in tasks)
             {
                 var trainerSet10 = TrainerExtensionCatalog.GetTrainers(task, 10);
                 var trainerSet50 = TrainerExtensionCatalog.GetTrainers(task, 50);
@@ -52,7 +52,7 @@ public void GetTrainersByMaxIterations()
         public void BuildPipelineNodePropsLightGbm()
         {
             var sweepParams = SweepableParams.BuildLightGbmParams();
-            foreach (var sweepParam in sweepParams)
+            foreach(var sweepParam in sweepParams)
             {
                 sweepParam.RawValue = 1;
             }
@@ -91,7 +91,7 @@ public void BuildPipelineNodePropsLightGbm()
         public void BuildPipelineNodePropsSdca()
         {
             var sweepParams = SweepableParams.BuildSdcaParams();
-            foreach (var sweepParam in sweepParams)
+            foreach(var sweepParam in sweepParams)
             {
                 sweepParam.RawValue = 1;
             }
@@ -108,29 +108,7 @@ public void BuildPipelineNodePropsSdca()
 }";
             Util.AssertObjectMatchesJson(expectedJson, sdcaBinaryProps);
         }
-
-        [TestMethod]
-        public void BuildPipelineNodePropsSdcaWithNullValues()
-        {
-            var sweepParams = SweepableParams.BuildSdcaParams();
-            foreach (var sweepParam in sweepParams)
-            {
-                sweepParam.RawValue = 0;
-            }
-
-            var sdcaBinaryProps = TrainerExtensionUtil.BuildPipelineNodeProps(TrainerName.SdcaBinary, sweepParams);
-            var expectedJson = @"
-{
-  ""L2Const"": null,
-  ""L1Threshold"": null,
-  ""ConvergenceTolerance"": 0.001,
-  ""MaxIterations"": null,
-  ""Shuffle"": false,
-  ""BiasLearningRate"": 0.0
-}";
-            Util.AssertObjectMatchesJson(expectedJson, sdcaBinaryProps);
-        }
-
+        
         [TestMethod]
         public void BuildParameterSetLightGbm()
         {
@@ -151,7 +129,7 @@ public void BuildParameterSetLightGbm()
             var multiParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmMulti, props);
             var regressionParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmRegression, props);
 
-            foreach (var paramSet in new ParameterSet[] { binaryParams, multiParams, regressionParams })
+            foreach(var paramSet in new ParameterSet[] { binaryParams, multiParams, regressionParams })
             {
                 Assert.AreEqual(4, paramSet.Count);
                 Assert.AreEqual("1", paramSet["NumBoostRound"].ValueText);
@@ -170,7 +148,7 @@ public void BuildParameterSetSdca()
             };
 
             var sdcaParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.SdcaBinary, props);
-
+            
             Assert.AreEqual(1, sdcaParams.Count);
             Assert.AreEqual("1", sdcaParams["LearningRate"].ValueText);
         }
