PR feedback.

Microsoft.ML.sln

@@ -107,7 +107,7 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Microsoft.ML.Parquet", "Mic
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Microsoft.ML.Benchmarks", "test\Microsoft.ML.Benchmarks\Microsoft.ML.Benchmarks.csproj", "{7A9DB75F-2CA5-4184-9EF5-1F17EB39483F}"
 EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Microsoft.ML.Commands", "src\Microsoft.ML.Commands\Microsoft.ML.Commands.csproj", "{C5EB2982-739C-4D42-8DA5-0FB5F4223B6D}"
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Microsoft.ML.Maml", "src\Microsoft.ML.Commands\Microsoft.ML.Maml.csproj", "{C5EB2982-739C-4D42-8DA5-0FB5F4223B6D}"
 EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution

src/Microsoft.ML.Core/Data/ITransformModel.cs

@@ -32,16 +32,6 @@ public interface ITransformModel
         /// </summary>
         ISchema OutputSchema { get; }
 
-        /// <summary>
-        /// This contains the transforms to save instantiated on an IDataView with
-        /// appropriate initial schema. Note that the "root" of this is typically either
-        /// an empty IDataView or a BinaryLoader with no rows. However, other root
-        /// types are possible, since we don't insist on this when loading a model
-        /// from a zip file. However, whenever we save, we force a BinaryLoader to
-        /// be serialized for the root.
-        /// </summary>
-        IDataView View { get; }
-
         /// <summary>
         /// Apply the transform(s) in the model to the given input data.
         /// </summary>

src/Microsoft.ML.Data/EntryPoints/PredictorModel.cs

@@ -36,18 +36,6 @@ public PredictorModel(IHostEnvironment env, RoleMappedData trainingData, IDataVi
             _predictor = predictor;
         }
 
-        //REVIEW: I'm not sure this is the right thing to do because we are setting predictor to null
-        //when this class is supposed to contain a predictor. TransformModel may or may not
-        //contain a predictor. Here we are just using this class as a wrapper for TransformModel 
-        //so that we can use a single class to accept TransformModel and PredictorModel has inputs.
-        public PredictorModel(IHostEnvironment env, ITransformModel transformModel)
-        {
-            Contracts.CheckValue(env, nameof(env));
-            env.CheckValue(transformModel, nameof(transformModel));
-
-            _transformModel = transformModel;
-        }
-
         public PredictorModel(IHostEnvironment env, Stream stream)
         {
             Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Data/EntryPoints/TransformModel.cs

@@ -48,16 +48,6 @@ public sealed class TransformModel : ITransformModel
         /// </summary>
         public ISchema OutputSchema => _chain.Schema;
 
-        /// <summary>
-        /// This contains the transforms to save instantiated on an IDataView with
-        /// appropriate initial schema. Note that the "root" of this is typically either
-        /// an empty IDataView or a BinaryLoader with no rows. However, other root
-        /// types are possible, since we don't insist on this when loading a model
-        /// from a zip file. However, whenever we save, we force a BinaryLoader to
-        /// be serialized for the root.
-        /// </summary>
-        public IDataView View => _chain;
-
         /// <summary>
         /// Create a TransformModel containing the transforms from "result" back to "input".
         /// </summary>

src/Microsoft.ML.Data/Model/Onnx/SaveOnnxCommand.cs

@@ -18,7 +18,7 @@
 [assembly: LoadableClass(SaveOnnxCommand.Summary, typeof(SaveOnnxCommand), typeof(SaveOnnxCommand.Arguments), typeof(SignatureCommand),
     "Save ONNX", "SaveOnnx", DocName = "command/SaveOnnx.md")]
 
-[assembly: LoadableClass(typeof(void), typeof(SaveOnnxCommand), null, typeof(SignatureEntryPointModule), "SaveOnnxCommand")]
+[assembly: LoadableClass(typeof(void), typeof(SaveOnnxCommand), null, typeof(SignatureEntryPointModule), "SaveOnnx")]
 
 namespace Microsoft.ML.Runtime.Model.Onnx
 {
@@ -41,24 +41,24 @@ public sealed class Arguments : DataCommand.ArgumentsBase
             [Argument(ArgumentType.AtMostOnce, HelpText = "The 'domain' property in the output ONNX.", NullName = "<Auto>", SortOrder = 4)]
             public string Domain;
 
-            [Argument(ArgumentType.AtMostOnce, HelpText = "Comma delimited list of input column names to drop", ShortName = "idrop", SortOrder = 5)]
+            [Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Comma delimited list of input column names to drop", ShortName = "idrop", SortOrder = 5)]
             public string InputsToDrop;
 
-            [Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Array of input column names to drop", SortOrder = 6)]
+            [Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Array of input column names to drop", Name = nameof(InputsToDrop), SortOrder = 6)]
             public string[] InputsToDropArray;
 
-            [Argument(ArgumentType.AtMostOnce, HelpText = "Comma delimited list of output column names to drop", ShortName = "odrop", SortOrder = 7)]
+            [Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Comma delimited list of output column names to drop", ShortName = "odrop", SortOrder = 7)]
             public string OutputsToDrop;
 
-            [Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Array of output column names to drop", SortOrder = 8)]
+            [Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Array of output column names to drop", Name = nameof(OutputsToDrop), SortOrder = 8)]
             public string[] OutputsToDropArray;
 
-            [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to load the predictor and attach the scorer to the pipeline if one is present.", ShortName = "pred", SortOrder = 9)]
+            [Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Whether we should attempt to load the predictor and attach the scorer to the pipeline if one is present.", ShortName = "pred", SortOrder = 9)]
             public bool? LoadPredictor;
 
-            [Argument(ArgumentType.Required, HelpText = "Model that needs to be converted to ONNX format.", SortOrder = 10)]
+            [Argument(ArgumentType.Required, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Model that needs to be converted to ONNX format.", SortOrder = 10)]
 
-            public IPredictorModel Model;
+            public ITransformModel Model;
         }
 
         private readonly string _outputModelPath;
@@ -68,7 +68,7 @@ public sealed class Arguments : DataCommand.ArgumentsBase
         private readonly bool? _loadPredictor;
         private readonly HashSet<string> _inputsToDrop;
         private readonly HashSet<string> _outputsToDrop;
-        private readonly IPredictorModel _model;
+        private readonly ITransformModel _model;
 
         public SaveOnnxCommand(IHostEnvironment env, Arguments args)
                 : base(env, args, LoadName)
@@ -83,20 +83,12 @@ public SaveOnnxCommand(IHostEnvironment env, Arguments args)
                 _name = args.Name;
 
             _loadPredictor = args.LoadPredictor;
-            _inputsToDrop = args.InputsToDropArray != null ? CreateDropMap(args.InputsToDropArray) : CreateDropMap(args.InputsToDrop);
-            _outputsToDrop = args.OutputsToDropArray != null ? CreateDropMap(args.OutputsToDropArray) : CreateDropMap(args.OutputsToDrop);
+            _inputsToDrop = CreateDropMap(args.InputsToDropArray ?? args.InputsToDrop?.Split(','));
+            _outputsToDrop = CreateDropMap(args.OutputsToDropArray ?? args.OutputsToDrop?.Split(','));
             _domain = args.Domain;
             _model = args.Model;
         }
 
-        private static HashSet<string> CreateDropMap(string toDrop)
-        {
-            if (string.IsNullOrWhiteSpace(toDrop))
-                return new HashSet<string>();
-
-            return new HashSet<string>(toDrop.Split(','));
-        }
-
         private static HashSet<string> CreateDropMap(string[] toDrop)
         {
             if (toDrop == null)
@@ -140,8 +132,8 @@ private void GetPipe(IChannel ch, IDataView end, out IDataView source, out IData
 
         private void Run(IChannel ch)
         {
-            IDataLoader loader = null; ;
-            IPredictor rawPred;
+            IDataLoader loader = null;
+            IPredictor rawPred = null;
             IDataView view;
             RoleMappedSchema trainSchema = null;
 
@@ -161,12 +153,7 @@ private void Run(IChannel ch)
                 view = loader;
             }
             else
-            {
-                view = _model.TransformModel.View;
-                rawPred = _model?.Predictor;
-                if (rawPred != null)
-                    trainSchema = _model.GetTrainingSchema(Host);
-            }
+                view = _model.Apply(Host, new EmptyDataView(Host, _model.InputSchema));
 
             // Get the transform chain.
             IDataView source;
@@ -276,7 +263,6 @@ private void Run(IChannel ch)
 
         public sealed class Output
         {
-            //REVIEW: Would be nice to include ONNX protobuf model here but code generator needs an upgrade.
         }
 
         //REVIEW: Ideally there is no need to define this input class and just reuse the Argument class from SaveONNX command
@@ -302,12 +288,8 @@ public sealed class Input
             [Argument(ArgumentType.AtMostOnce, HelpText = "Array of output column names to drop", SortOrder = 6)]
             public string[] OutputsToDrop;
 
-            [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to load the predictor and attach the scorer to the pipeline if one is present.", ShortName = "pred", SortOrder = 7)]
-            public bool? LoadPredictor;
-
-            [Argument(ArgumentType.Required, HelpText = "Model that needs to be converted to ONNX format.", SortOrder = 8)]
-
-            public IPredictorModel Model;
+            [Argument(ArgumentType.Required, HelpText = "Model that needs to be converted to ONNX format.", SortOrder = 7)]
+            public ITransformModel Model;
         }
 
 
@@ -321,7 +303,6 @@ public static Output Apply(IHostEnvironment env, Input input)
             args.Domain = input.Domain;
             args.InputsToDropArray = input.InputsToDrop;
             args.OutputsToDropArray = input.OutputsToDrop;
-            args.LoadPredictor = input.LoadPredictor;
             args.Model = input.Model;
 
             var cmd = new SaveOnnxCommand(env, args);

src/Microsoft.ML.Maml/Console.cs

@@ -0,0 +1,21 @@
+// Licensed to the .NET Foundation under one or more agreements.
+// The .NET Foundation licenses this file to you under the MIT license.
+// See the LICENSE file in the project root for more information.
+
+namespace Microsoft.ML.Runtime.Tools.Console
+{
+    public static class Console
+    {
+        public static int Main(string[] args)
+        {
+            string all = string.Join(" ", args);
+            return Maml.MainAll(all);
+        }
+
+        public static unsafe int MainRaw(char* psz)
+        {
+            string args = new string(psz);
+            return Maml.MainAll(args);
+        }
+    }
+}

src/Microsoft.ML.Maml/Microsoft.ML.Console.csproj

@@ -6,11 +6,11 @@
 	<IncludeInPackage>Microsoft.ML</IncludeInPackage>
 	<TargetFramework>netcoreapp2.0</TargetFramework>
 	<OutputType>Exe</OutputType>
-	<StartupObject>Microsoft.ML.Runtime.Tools.Maml</StartupObject>
+	<StartupObject>Microsoft.ML.Runtime.Tools.Console.Console</StartupObject>
   </PropertyGroup>
 
   <ItemGroup>
-    <ProjectReference Include="..\Microsoft.ML.Commands\Microsoft.ML.Commands.csproj" />
+    <ProjectReference Include="..\Microsoft.ML.Commands\Microsoft.ML.Maml.csproj" />
     <ProjectReference Include="..\Microsoft.ML.Core\Microsoft.ML.Core.csproj" />
   </ItemGroup>
 

src/Microsoft.ML.ResultProcessor/Microsoft.ML.ResultProcessor.csproj

@@ -8,7 +8,7 @@
   </PropertyGroup>
 
   <ItemGroup>
-    <ProjectReference Include="..\Microsoft.ML.Commands\Microsoft.ML.Commands.csproj" />
+    <ProjectReference Include="..\Microsoft.ML.Commands\Microsoft.ML.Maml.csproj" />
     <ProjectReference Include="..\Microsoft.ML.Core\Microsoft.ML.Core.csproj" />
     <ProjectReference Include="..\Microsoft.ML.CpuMath\Microsoft.ML.CpuMath.csproj" />
     <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />

src/Microsoft.ML/CSharpApi.cs

@@ -2789,15 +2789,10 @@ public sealed partial class OnnxConverter
             /// </summary>
             public string[] OutputsToDrop { get; set; }
 
-            /// <summary>
-            /// Whether we should attempt to load the predictor and attach the scorer to the pipeline if one is present.
-            /// </summary>
-            public bool? LoadPredictor { get; set; }
-
             /// <summary>
             /// Model that needs to be converted to ONNX format.
             /// </summary>
-            public Var<Microsoft.ML.Runtime.EntryPoints.IPredictorModel> Model { get; set; } = new Var<Microsoft.ML.Runtime.EntryPoints.IPredictorModel>();
+            public Var<Microsoft.ML.Runtime.EntryPoints.ITransformModel> Model { get; set; } = new Var<Microsoft.ML.Runtime.EntryPoints.ITransformModel>();
 
 
             public sealed class Output

src/Microsoft.ML/Microsoft.ML.csproj

@@ -14,7 +14,7 @@
 
   <ItemGroup>
     <ProjectReference Include="..\Microsoft.ML.Api\Microsoft.ML.Api.csproj" />
-    <ProjectReference Include="..\Microsoft.ML.Commands\Microsoft.ML.Commands.csproj" />
+    <ProjectReference Include="..\Microsoft.ML.Commands\Microsoft.ML.Maml.csproj" />
     <ProjectReference Include="..\Microsoft.ML.Core\Microsoft.ML.Core.csproj" />
     <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
     <ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />

src/Microsoft.ML/Models/OnnxConverter.cs

@@ -1,6 +1,9 @@
-using Microsoft.ML.Runtime;
+// Licensed to the .NET Foundation under one or more agreements.
+// The .NET Foundation licenses this file to you under the MIT license.
+// See the LICENSE file in the project root for more information.
+
+using Microsoft.ML.Runtime;
 using Microsoft.ML.Runtime.Data;
-using Microsoft.ML.Runtime.EntryPoints;
 
 namespace Microsoft.ML.Models
 {
@@ -19,7 +22,7 @@ public void Convert(PredictionModel model)
                 Experiment experiment = environment.CreateExperiment();
                 experiment.Add(this);
                 experiment.Compile();
-                experiment.SetInput(Model, new PredictorModel(environment, model.PredictorModel));
+                experiment.SetInput(Model, model.PredictorModel);
                 experiment.Run();
             }
         }

test/Microsoft.ML.TestFramework/Microsoft.ML.TestFramework.csproj

@@ -6,10 +6,10 @@
 
   <ItemGroup>
     <ProjectReference Include="..\..\src\Microsoft.ML.Api\Microsoft.ML.Api.csproj" />
+    <ProjectReference Include="..\..\src\Microsoft.ML.Commands\Microsoft.ML.Maml.csproj" />
     <ProjectReference Include="..\..\src\Microsoft.ML.Core\Microsoft.ML.Core.csproj" />
     <ProjectReference Include="..\..\src\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
     <ProjectReference Include="..\..\src\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />
-    <ProjectReference Include="..\..\src\Microsoft.ML.Maml\Microsoft.ML.Console.csproj" />
     <ProjectReference Include="..\..\src\Microsoft.ML.ResultProcessor\Microsoft.ML.ResultProcessor.csproj" />
     <ProjectReference Include="..\..\src\Microsoft.ML\Microsoft.ML.csproj" />
   </ItemGroup>