FastTreeRankingTrainer expose non-advanced args(#1246)

.vsts-dotnet-ci.yml

@@ -18,7 +18,15 @@ phases:
 
 - template: /build/ci/phase-template.yml
   parameters:
-    name: Windows_NT
+    name: Windows_x64
+    buildScript: build.cmd
+    queue:
+      name: Hosted VS2017
+
+- template: /build/ci/phase-template.yml
+  parameters:
+    name: Windows_x86
+    architecture: x86
     buildScript: build.cmd
     queue:
       name: Hosted VS2017

README.md

@@ -8,7 +8,7 @@ ML.NET allows .NET developers to develop their own models and infuse custom mach
 
 ML.NET was originally developed in Microsoft Research, and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, PowerPoint, Excel and more.
 
-With this first preview release, ML.NET enables machine learning tasks like classification (for example: support text classification, sentiment analysis) and regression (for example, price-prediction).
+ML.NET enables machine learning tasks like classification (for example: support text classification, sentiment analysis) and regression (for example, price-prediction).
 
 Along with these ML capabilities, this first release of ML.NET also brings the first draft of .NET APIs for training models, using models for predictions, as well as the core components of this framework such as learning algorithms, transforms, and ML data structures. 
 

build/ci/phase-template.yml

@@ -1,5 +1,6 @@
 parameters:
   name: ''
+  architecture: x64
   buildScript: ''
   queue: {}
 
@@ -8,6 +9,7 @@ phases:
     variables:
       _buildScript: ${{ parameters.buildScript }}
       _phaseName: ${{ parameters.name }}
+      _arch: ${{ parameters.architecture }}
     queue:
       parallel: 99
       matrix:
@@ -17,7 +19,7 @@ phases:
           _configuration: Release
       ${{ insert }}: ${{ parameters.queue }}
     steps:
-    - script: $(_buildScript) -$(_configuration)
+    - script: $(_buildScript) -$(_configuration) -buildArch=$(_arch)
       displayName: Build
     - ${{ if eq(parameters.name, 'MacOS') }}:
       - script: brew install libomp

docs/building/unix-instructions.md

@@ -3,7 +3,7 @@ Building ML.NET on Linux and macOS
 ## Building
 
 1. Install the prerequisites ([Linux](#user-content-linux), [macOS](#user-content-macos))
-2. Clone the machine learning repo `git clone https://github.com/dotnet/machinelearning.git`
+2. Clone the machine learning repo `git clone --recursive https://github.com/dotnet/machinelearning.git`
 3. Navigate to the `machinelearning` directory
 4. Run the build script `./build.sh`
 

init-tools.cmd

@@ -12,6 +12,7 @@ set BUILD_TOOLS_PATH=%PACKAGES_DIR%\Microsoft.DotNet.BuildTools\%BUILDTOOLS_VERS
 set INIT_TOOLS_RESTORE_PROJECT=%~dp0init-tools.msbuild
 set BUILD_TOOLS_SEMAPHORE_DIR=%TOOLRUNTIME_DIR%\%BUILDTOOLS_VERSION%
 set BUILD_TOOLS_SEMAPHORE=%BUILD_TOOLS_SEMAPHORE_DIR%\init-tools.completed
+set ARCH=x64
 
 :: if force option is specified then clean the tool runtime and build tools package directory to force it to get recreated
 if [%1]==[force] (
@@ -47,9 +48,17 @@ echo Running %0 > "%INIT_TOOLS_LOG%"
 set /p DOTNET_VERSION=< "%~dp0DotnetCLIVersion.txt"
 if exist "%DOTNET_CMD%" goto :afterdotnetrestore
 
+:Arg_Loop
+if [%1] == [] goto :ArchSet
+if /i [%1] == [x86]         ( set ARCH=x86&&goto ArchSet)
+shift
+goto :Arg_Loop
+
+:ArchSet
+
 echo Installing dotnet cli...
 if NOT exist "%DOTNET_PATH%" mkdir "%DOTNET_PATH%"
-set DOTNET_ZIP_NAME=dotnet-sdk-%DOTNET_VERSION%-win-x64.zip
+set DOTNET_ZIP_NAME=dotnet-sdk-%DOTNET_VERSION%-win-%ARCH%.zip
 set DOTNET_REMOTE_PATH=https://dotnetcli.azureedge.net/dotnet/Sdk/%DOTNET_VERSION%/%DOTNET_ZIP_NAME%
 set DOTNET_LOCAL_PATH=%DOTNET_PATH%%DOTNET_ZIP_NAME%
 echo Installing '%DOTNET_REMOTE_PATH%' to '%DOTNET_LOCAL_PATH%' >> "%INIT_TOOLS_LOG%"

pkg/Microsoft.ML.TensorFlow.Redist/Microsoft.ML.TensorFlow.Redist.nupkgproj

@@ -16,6 +16,6 @@
   <ItemGroup>
     <Content Include="..\common\CommonPackage.props" Pack="true" PackagePath="build\netstandard2.0\$(MSBuildProjectName).props" />
     <Content Include="$(PackageAssetsPath)$(PackageIdFolderName)\LICENSE.txt" Pack="true" PackagePath=".\" />
-    <Content Include="$(PackageAssetsPath)$(PackageIdFolderName)\THIRD_PARTY_NOTICES.txt" Pack="true" PackagePath=".\" />
+    <Content Condition="Exists('$(PackageAssetsPath)$(PackageIdFolderName)\THIRD_PARTY_NOTICES.txt')" Include="$(PackageAssetsPath)$(PackageIdFolderName)\THIRD_PARTY_NOTICES.txt" Pack="true" PackagePath=".\" />
   </ItemGroup>
 </Project>

run.cmd

@@ -11,7 +11,7 @@ set DOTNET_SKIP_FIRST_TIME_EXPERIENCE=1
 set DOTNET_MULTILEVEL_LOOKUP=0
 
 :: Restore the Tools directory
-call "%~dp0init-tools.cmd"
+call "%~dp0init-tools.cmd" %*
 if NOT [%ERRORLEVEL%]==[0] exit /b 1
 
 set _toolRuntime=%~dp0Tools

src/Microsoft.ML.Data/Training/TrainerEstimatorBase.cs

@@ -50,7 +50,10 @@ public abstract class TrainerEstimatorBase<TTransformer, TModel> : ITrainerEstim
 
         public abstract PredictionKind PredictionKind { get; }
 
-        public TrainerEstimatorBase(IHost host, SchemaShape.Column feature, SchemaShape.Column label, SchemaShape.Column weight = null)
+        public TrainerEstimatorBase(IHost host,
+            SchemaShape.Column feature,
+            SchemaShape.Column label,
+            SchemaShape.Column weight = null)
         {
             Contracts.CheckValue(host, nameof(host));
             Host = host;
@@ -149,9 +152,39 @@ protected TTransformer TrainTransformer(IDataView trainSet,
 
         protected abstract TTransformer MakeTransformer(TModel model, Schema trainSchema);
 
-        private RoleMappedData MakeRoles(IDataView data) =>
+        protected virtual RoleMappedData MakeRoles(IDataView data) =>
             new RoleMappedData(data, label: LabelColumn?.Name, feature: FeatureColumn.Name, weight: WeightColumn?.Name);
 
         IPredictor ITrainer.Train(TrainContext context) => Train(context);
     }
+
+    /// <summary>
+    /// This represents a basic class for 'simple trainer'.
+    /// A 'simple trainer' accepts one feature column and one label column, also optionally a weight column.
+    /// It produces a 'prediction transformer'.
+    /// </summary>
+    public abstract class TrainerEstimatorBaseWithGroupId<TTransformer, TModel> : TrainerEstimatorBase<TTransformer, TModel>
+        where TTransformer : ISingleFeaturePredictionTransformer<TModel>
+        where TModel : IPredictor
+    {
+        /// <summary>
+        /// The optional groupID column that the ranking trainers expects.
+        /// </summary>
+        public readonly SchemaShape.Column GroupIdColumn;
+
+        public TrainerEstimatorBaseWithGroupId(IHost host,
+                SchemaShape.Column feature,
+                SchemaShape.Column label,
+                SchemaShape.Column weight = null,
+                SchemaShape.Column groupId = null)
+            :base(host, feature, label, weight)
+        {
+            Host.CheckValueOrNull(groupId);
+            GroupIdColumn = groupId;
+        }
+
+        protected override RoleMappedData MakeRoles(IDataView data) =>
+            new RoleMappedData(data, label: LabelColumn?.Name, feature: FeatureColumn.Name, group: GroupIdColumn?.Name, weight: WeightColumn?.Name);
+
+    }
 }

src/Microsoft.ML.Data/Training/TrainerUtils.cs

@@ -362,9 +362,14 @@ public static SchemaShape.Column MakeR4ScalarLabel(string labelColumn)
         /// <summary>
         /// The <see cref="SchemaShape.Column"/> for the label column for regression tasks.
         /// </summary>
-        /// <param name="labelColumn">name of the weight column</param>
-        public static SchemaShape.Column MakeU4ScalarLabel(string labelColumn)
-            => new SchemaShape.Column(labelColumn, SchemaShape.Column.VectorKind.Scalar, NumberType.U4, true);
+        /// <param name="columnName">name of the weight column</param>
+        public static SchemaShape.Column MakeU4ScalarColumn(string columnName)
+        {
+            if (columnName == null)
+                return null;
+
+            return new SchemaShape.Column(columnName, SchemaShape.Column.VectorKind.Scalar, NumberType.U4, true);
+        }
 
         /// <summary>
         /// The <see cref="SchemaShape.Column"/> for the feature column.
@@ -377,69 +382,13 @@ public static SchemaShape.Column MakeR4VecFeature(string featureColumn)
         /// The <see cref="SchemaShape.Column"/> for the weight column.
         /// </summary>
         /// <param name="weightColumn">name of the weight column</param>
-        public static SchemaShape.Column MakeR4ScalarWeightColumn(string weightColumn)
+        /// <param name="isExplicit">whether the column is implicitly, or explicitly defined</param>
+        public static SchemaShape.Column MakeR4ScalarWeightColumn(string weightColumn, bool isExplicit = true)
         {
-            if (weightColumn == null)
+            if (weightColumn == null || !isExplicit)
                 return null;
             return new SchemaShape.Column(weightColumn, SchemaShape.Column.VectorKind.Scalar, NumberType.R4, false);
         }
-
-        private static void CheckArgColName(IHostEnvironment host, string defaultColName, string argValue)
-        {
-            if (argValue != defaultColName)
-                throw host.Except($"Don't supply a value for the {defaultColName} column in the arguments, as it will be ignored. Specify them in the loader, or constructor instead instead.");
-        }
-
-        /// <summary>
-        /// Check that the label, feature, weights, groupId column names are not supplied in the args of the constructor, through the advancedSettings parameter,
-        /// for cases when the public constructor is called.
-        /// The recommendation is to set the column names directly.
-        /// </summary>
-        public static void CheckArgsHaveDefaultColNames(IHostEnvironment host, LearnerInputBaseWithGroupId args)
-        {
-            // check that the users didn't specify different label, group, feature, weights in the args, from what they supplied directly
-            CheckArgColName(host, DefaultColumnNames.Label, args.LabelColumn);
-            CheckArgColName(host, DefaultColumnNames.Features, args.FeatureColumn);
-            CheckArgColName(host, DefaultColumnNames.Weight, args.WeightColumn);
-
-            if (args.GroupIdColumn != null)
-                CheckArgColName(host, DefaultColumnNames.GroupId, args.GroupIdColumn);
-        }
-
-        /// <summary>
-        /// Check that the label, feature, and weights column names are not supplied in the args of the constructor, through the advancedSettings parameter,
-        /// for cases when the public constructor is called.
-        /// The recommendation is to set the column names directly.
-        /// </summary>
-        public static void CheckArgsHaveDefaultColNames(IHostEnvironment host, LearnerInputBaseWithWeight args)
-        {
-            // check that the users didn't specify different label, group, feature, weights in the args, from what they supplied directly
-            CheckArgColName(host, DefaultColumnNames.Label, args.LabelColumn);
-            CheckArgColName(host, DefaultColumnNames.Features, args.FeatureColumn);
-            CheckArgColName(host, DefaultColumnNames.Weight, args.WeightColumn);
-        }
-
-        /// <summary>
-        /// Check that the label and feature column names are not supplied in the args of the constructor, through the advancedSettings parameter,
-        /// for cases when the public constructor is called.
-        /// The recommendation is to set the column names directly.
-        /// </summary>
-        public static void CheckArgsHaveDefaultColNames(IHostEnvironment host, LearnerInputBaseWithLabel args)
-        {
-            // check that the users didn't specify different label, group, feature, weights in the args, from what they supplied directly
-            CheckArgColName(host, DefaultColumnNames.Label, args.LabelColumn);
-            CheckArgColName(host, DefaultColumnNames.Features, args.FeatureColumn);
-        }
-
-        /// <summary>
-        /// If, after applying the advancedArgs delegate, the args are different that the default value
-        /// and are also different than the value supplied directly to the xtension method, warn the user.
-        /// </summary>
-        public static void CheckArgsAndAdvancedSettingMismatch<T>(IChannel channel, T methodParam, T defaultVal, T setting, string argName)
-        {
-            if (!setting.Equals(defaultVal) && !setting.Equals(methodParam))
-                channel.Warning($"The value supplied to advanced settings , is different than the value supplied directly. Using value {setting} for {argName}");
-        }
     }
 
     /// <summary>

src/Microsoft.ML.Ensemble/Microsoft.ML.Ensemble.csproj

@@ -2,7 +2,7 @@
 
   <PropertyGroup>
     <TargetFramework>netstandard2.0</TargetFramework>
-    <IncludeInPackage>Microsoft.ML.Ensemble</IncludeInPackage>
+    <IncludeInPackage>Microsoft.ML</IncludeInPackage>
     <DefineConstants>CORECLR</DefineConstants>
   </PropertyGroup>
 

src/Microsoft.ML.FastTree/BoostingFastTree.cs

@@ -21,10 +21,24 @@ protected BoostingFastTreeTrainerBase(IHostEnvironment env, TArgs args, SchemaSh
         {
         }
 
-        protected BoostingFastTreeTrainerBase(IHostEnvironment env, SchemaShape.Column label, string featureColumn,
-            string weightColumn = null, string groupIdColumn = null, Action<TArgs> advancedSettings = null)
-            : base(env, label, featureColumn, weightColumn, groupIdColumn, advancedSettings)
+        protected BoostingFastTreeTrainerBase(IHostEnvironment env,
+            SchemaShape.Column label,
+            string featureColumn,
+            string weightColumn,
+            string groupIdColumn,
+            int numLeaves,
+            int numTrees,
+            int minDocumentsInLeafs,
+            double learningRate,
+            Action<TArgs> advancedSettings)
+            : base(env, label, featureColumn, weightColumn, groupIdColumn, numLeaves, numTrees, minDocumentsInLeafs, advancedSettings)
         {
+
+            if (Args.LearningRates != learningRate)
+            {
+                using (var ch = Host.Start($"Setting learning rate to: {learningRate} as supplied in the direct arguments."))
+                    Args.LearningRates = learningRate;
+            }
         }
 
         protected override void CheckArgs(IChannel ch)

src/Microsoft.ML.FastTree/FastTree.cs

@@ -7,6 +7,7 @@
 using Microsoft.ML.Runtime.CommandLine;
 using Microsoft.ML.Runtime.Data;
 using Microsoft.ML.Runtime.Data.Conversion;
+using Microsoft.ML.Runtime.EntryPoints;
 using Microsoft.ML.Runtime.Internal.Calibration;
 using Microsoft.ML.Runtime.Internal.Internallearn;
 using Microsoft.ML.Runtime.Internal.Utilities;
@@ -45,7 +46,7 @@ internal static class FastTreeShared
     }
 
     public abstract class FastTreeTrainerBase<TArgs, TTransformer, TModel> :
-        TrainerEstimatorBase<TTransformer, TModel>
+        TrainerEstimatorBaseWithGroupId<TTransformer, TModel>
         where TTransformer: ISingleFeaturePredictionTransformer<TModel>
         where TArgs : TreeArgs, new()
         where TModel : IPredictorProducing<Float>
@@ -92,26 +93,36 @@ public abstract class FastTreeTrainerBase<TArgs, TTransformer, TModel> :
         /// <summary>
         /// Constructor to use when instantiating the classes deriving from here through the API.
         /// </summary>
-        private protected FastTreeTrainerBase(IHostEnvironment env, SchemaShape.Column label, string featureColumn,
-            string weightColumn = null, string groupIdColumn = null, Action<TArgs> advancedSettings = null)
-            : base(Contracts.CheckRef(env, nameof(env)).Register(RegisterName), TrainerUtils.MakeR4VecFeature(featureColumn), label, TrainerUtils.MakeR4ScalarWeightColumn(weightColumn))
+        private protected FastTreeTrainerBase(IHostEnvironment env,
+            SchemaShape.Column label,
+            string featureColumn,
+            string weightColumn,
+            string groupIdColumn,
+            int numLeaves,
+            int numTrees,
+            int minDocumentsInLeafs,
+            Action<TArgs> advancedSettings)
+            : base(Contracts.CheckRef(env, nameof(env)).Register(RegisterName), TrainerUtils.MakeR4VecFeature(featureColumn), label, TrainerUtils.MakeR4ScalarWeightColumn(weightColumn), TrainerUtils.MakeU4ScalarColumn(groupIdColumn))
         {
             Args = new TArgs();
 
+            // set up the directly provided values
+            // override with the directly provided values.
+            Args.NumLeaves = numLeaves;
+            Args.NumTrees = numTrees;
+            Args.MinDocumentsInLeafs = minDocumentsInLeafs;
+
             //apply the advanced args, if the user supplied any
             advancedSettings?.Invoke(Args);
 
-            // check that the users didn't specify different label, group, feature, weights in the args, from what they supplied directly
-            TrainerUtils.CheckArgsHaveDefaultColNames(Host, Args);
-
             Args.LabelColumn = label.Name;
             Args.FeatureColumn = featureColumn;
 
             if (weightColumn != null)
-                Args.WeightColumn = weightColumn;
+                Args.WeightColumn = Optional<string>.Explicit(weightColumn); ;
 
             if (groupIdColumn != null)
-                Args.GroupIdColumn = groupIdColumn;
+                Args.GroupIdColumn = Optional<string>.Explicit(groupIdColumn); ;
 
             // The discretization step renders this trainer non-parametric, and therefore it does not need normalization.
             // Also since it builds its own internal discretized columnar structures, it cannot benefit from caching.
@@ -128,7 +139,7 @@ private protected FastTreeTrainerBase(IHostEnvironment env, SchemaShape.Column l
         /// Legacy constructor that is used when invoking the classes deriving from this, through maml.
         /// </summary>
         private protected FastTreeTrainerBase(IHostEnvironment env, TArgs args, SchemaShape.Column label)
-            : base(Contracts.CheckRef(env, nameof(env)).Register(RegisterName), TrainerUtils.MakeR4VecFeature(args.FeatureColumn), label, TrainerUtils.MakeR4ScalarWeightColumn(args.WeightColumn))
+            : base(Contracts.CheckRef(env, nameof(env)).Register(RegisterName), TrainerUtils.MakeR4VecFeature(args.FeatureColumn), label, TrainerUtils.MakeR4ScalarWeightColumn(args.WeightColumn, args.WeightColumn.IsExplicit))
         {
             Host.CheckValue(args, nameof(args));
             Args = args;
@@ -159,32 +170,6 @@ protected virtual Float GetMaxLabel()
             return Float.PositiveInfinity;
         }
 
-        /// <summary>
-        /// If, after applying the advancedSettings delegate, the args are different that the default value
-        /// and are also different than the value supplied directly to the xtension method, warn the user
-        /// about which value is being used.
-        /// The parameters that appear here, numTrees, minDocumentsInLeafs, numLeaves, learningRate are the ones the users are most likely to tune.
-        /// This list should follow the one in the constructor, and the extension methods on the <see cref="TrainContextBase"/>.
-        /// REVIEW: we should somehow mark the arguments that are set apart in those two places. Currently they stand out by their sort order annotation.
-        /// </summary>
-        protected void CheckArgsAndAdvancedSettingMismatch(int numLeaves,
-            int numTrees,
-            int minDocumentsInLeafs,
-            double learningRate,
-            BoostedTreeArgs snapshot,
-            BoostedTreeArgs currentArgs)
-        {
-            using (var ch = Host.Start("Comparing advanced settings with the directly provided values."))
-            {
-
-                // Check that the user didn't supply different parameters in the args, from what it specified directly.
-                TrainerUtils.CheckArgsAndAdvancedSettingMismatch(ch, numLeaves, snapshot.NumLeaves, currentArgs.NumLeaves, nameof(numLeaves));
-                TrainerUtils.CheckArgsAndAdvancedSettingMismatch(ch, numTrees, snapshot.NumTrees, currentArgs.NumTrees, nameof(numTrees));
-                TrainerUtils.CheckArgsAndAdvancedSettingMismatch(ch, minDocumentsInLeafs, snapshot.MinDocumentsInLeafs, currentArgs.MinDocumentsInLeafs, nameof(minDocumentsInLeafs));
-                TrainerUtils.CheckArgsAndAdvancedSettingMismatch(ch, learningRate, snapshot.LearningRates, currentArgs.LearningRates, nameof(learningRate));
-            }
-        }
-
         private void Initialize(IHostEnvironment env)
         {
             int numThreads = Args.NumThreads ?? Environment.ProcessorCount;