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Legacy API namespace rename
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‎src/Microsoft.ML.PipelineInference/Macros/PipelineSweeperMacro.cs

+4-4
Original file line numberDiff line numberDiff line change
@@ -258,8 +258,8 @@ public static CommonOutputs.MacroOutput<Output> PipelineSweep(
258258
{
259259
// Add a node to extract the sweep result.
260260
var resultSubgraph = new Experiment(env);
261-
var resultNode = new Microsoft.ML.Models.SweepResultExtractor() { State = amlsVarObj };
262-
var resultOutput = new Models.SweepResultExtractor.Output() { State = outStateVar, Results = outDvVar };
261+
var resultNode = new Microsoft.ML.Legacy.Models.SweepResultExtractor() { State = amlsVarObj };
262+
var resultOutput = new Legacy.Models.SweepResultExtractor.Output() { State = outStateVar, Results = outDvVar };
263263
resultSubgraph.Add(resultNode, resultOutput);
264264
var resultSubgraphNodes = EntryPointNode.ValidateNodes(env, node.Context, resultSubgraph.GetNodes(), node.Catalog);
265265
expNodes.AddRange(resultSubgraphNodes);
@@ -290,15 +290,15 @@ public static CommonOutputs.MacroOutput<Output> PipelineSweep(
290290

291291
// Add recursive macro node
292292
var macroSubgraph = new Experiment(env);
293-
var macroNode = new Models.PipelineSweeper()
293+
var macroNode = new Legacy.Models.PipelineSweeper()
294294
{
295295
BatchSize = input.BatchSize,
296296
CandidateOutputs = new ArrayVar<IDataView>(pipelineIndicators.ToArray()),
297297
TrainingData = training,
298298
TestingData = testing,
299299
State = amlsVarObj
300300
};
301-
var output = new Models.PipelineSweeper.Output() { Results = outDvVar, State = outStateVar };
301+
var output = new Legacy.Models.PipelineSweeper.Output() { Results = outDvVar, State = outStateVar };
302302
macroSubgraph.Add(macroNode, output);
303303

304304
var subgraphNodes = EntryPointNode.ValidateNodes(env, node.Context, macroSubgraph.GetNodes(), node.Catalog);

‎src/Microsoft.ML.PipelineInference/PipelinePattern.cs

+8-8
Original file line numberDiff line numberDiff line change
@@ -5,7 +5,7 @@
55
using System;
66
using System.Collections.Generic;
77
using System.Linq;
8-
using Microsoft.ML;
8+
using Microsoft.ML.Legacy;
99
using Microsoft.ML.Runtime.EntryPoints;
1010
using Microsoft.ML.Runtime.Data;
1111

@@ -106,7 +106,7 @@ public AutoInference.EntryPointGraphDef ToEntryPointGraph(Experiment experiment
106106
// if transforms present.
107107
if (Transforms.Length > 0)
108108
{
109-
var modelCombine = new ML.Transforms.ManyHeterogeneousModelCombiner
109+
var modelCombine = new Legacy.Transforms.ManyHeterogeneousModelCombiner
110110
{
111111
TransformModels = new ArrayVar<ITransformModel>(transformsModels.ToArray()),
112112
PredictorModel = returnedDataAndModel2?.Model
@@ -130,7 +130,7 @@ public AutoInference.EntryPointGraphDef ToEntryPointGraph(Experiment experiment
130130

131131
// REVIEW: We may want to allow for sweeping with CV in the future, so we will need to add new methods like this, or refactor these in that case.
132132
public Experiment CreateTrainTestExperiment(IDataView trainData, IDataView testData, MacroUtils.TrainerKinds trainerKind,
133-
bool includeTrainingMetrics, out Models.TrainTestEvaluator.Output resultsOutput)
133+
bool includeTrainingMetrics, out Legacy.Models.TrainTestEvaluator.Output resultsOutput)
134134
{
135135
var graphDef = ToEntryPointGraph();
136136
var subGraph = graphDef.Graph;
@@ -142,7 +142,7 @@ public Experiment CreateTrainTestExperiment(IDataView trainData, IDataView testD
142142
var finalOutput = graphDef.ModelOutput;
143143

144144
// TrainTestMacro
145-
var trainTestInput = new Models.TrainTestEvaluator
145+
var trainTestInput = new Legacy.Models.TrainTestEvaluator
146146
{
147147
TransformModel = null,
148148
Nodes = subGraph,
@@ -155,7 +155,7 @@ public Experiment CreateTrainTestExperiment(IDataView trainData, IDataView testD
155155
PredictorModel = finalOutput
156156
},
157157
PipelineId = UniqueId.ToString("N"),
158-
Kind = MacroUtils.TrainerKindApiValue<Models.MacroUtilsTrainerKinds>(trainerKind),
158+
Kind = MacroUtils.TrainerKindApiValue<Legacy.Models.MacroUtilsTrainerKinds>(trainerKind),
159159
IncludeTrainingMetrics = includeTrainingMetrics
160160
};
161161

@@ -169,7 +169,7 @@ public Experiment CreateTrainTestExperiment(IDataView trainData, IDataView testD
169169
return experiment;
170170
}
171171

172-
public Models.TrainTestEvaluator.Output AddAsTrainTest(Var<IDataView> trainData, Var<IDataView> testData,
172+
public Legacy.Models.TrainTestEvaluator.Output AddAsTrainTest(Var<IDataView> trainData, Var<IDataView> testData,
173173
MacroUtils.TrainerKinds trainerKind, Experiment experiment = null, bool includeTrainingMetrics = false)
174174
{
175175
experiment = experiment ?? _env.CreateExperiment();
@@ -179,7 +179,7 @@ public Models.TrainTestEvaluator.Output AddAsTrainTest(Var<IDataView> trainData,
179179
var finalOutput = graphDef.ModelOutput;
180180

181181
// TrainTestMacro
182-
var trainTestInput = new Models.TrainTestEvaluator
182+
var trainTestInput = new Legacy.Models.TrainTestEvaluator
183183
{
184184
Nodes = subGraph,
185185
TransformModel = null,
@@ -193,7 +193,7 @@ public Models.TrainTestEvaluator.Output AddAsTrainTest(Var<IDataView> trainData,
193193
},
194194
TrainingData = trainData,
195195
TestingData = testData,
196-
Kind = MacroUtils.TrainerKindApiValue<Models.MacroUtilsTrainerKinds>(trainerKind),
196+
Kind = MacroUtils.TrainerKindApiValue<Legacy.Models.MacroUtilsTrainerKinds>(trainerKind),
197197
PipelineId = UniqueId.ToString("N"),
198198
IncludeTrainingMetrics = includeTrainingMetrics
199199
};

‎src/Microsoft.ML.PipelineInference/RecipeInference.cs

+5-5
Original file line numberDiff line numberDiff line change
@@ -99,7 +99,7 @@ public AutoInference.EntryPointGraphDef ToEntryPointGraph(IHostEnvironment env)
9999
// if transforms present.
100100
if (Transforms.Length > 0)
101101
{
102-
var modelCombine = new ML.Transforms.ManyHeterogeneousModelCombiner
102+
var modelCombine = new ML.Legacy.Transforms.ManyHeterogeneousModelCombiner
103103
{
104104
TransformModels = new ArrayVar<ITransformModel>(transformsModels.ToArray()),
105105
PredictorModel = learnerAddResult.Model
@@ -243,7 +243,7 @@ protected override IEnumerable<SuggestedRecipe> ApplyCore(Type predictorType,
243243
{
244244
learner.LoadableClassInfo = ComponentCatalog.GetLoadableClassInfo<SignatureTrainer>(Learners.AveragedPerceptronTrainer.LoadNameValue);
245245
learner.Settings = "iter=10";
246-
var epInput = new Trainers.AveragedPerceptronBinaryClassifier
246+
var epInput = new Legacy.Trainers.AveragedPerceptronBinaryClassifier
247247
{
248248
NumIterations = 10
249249
};
@@ -276,7 +276,7 @@ protected override IEnumerable<SuggestedRecipe> ApplyCore(Type predictorType,
276276
learner.LoadableClassInfo =
277277
ComponentCatalog.GetLoadableClassInfo<SignatureTrainer>(FastTreeBinaryClassificationTrainer.LoadNameValue);
278278
learner.Settings = "";
279-
var epInput = new Trainers.FastTreeBinaryClassifier();
279+
var epInput = new Legacy.Trainers.FastTreeBinaryClassifier();
280280
learner.PipelineNode = new TrainerPipelineNode(epInput);
281281
}
282282

@@ -304,7 +304,7 @@ protected override IEnumerable<SuggestedRecipe> ApplyCore(Type predictorType,
304304
{
305305
learner.LoadableClassInfo =
306306
ComponentCatalog.GetLoadableClassInfo<SignatureTrainer>(Learners.LinearClassificationTrainer.LoadNameValue);
307-
var epInput = new Trainers.StochasticDualCoordinateAscentBinaryClassifier();
307+
var epInput = new Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier();
308308
learner.PipelineNode = new TrainerPipelineNode(epInput);
309309
}
310310

@@ -327,7 +327,7 @@ protected override IEnumerable<SuggestedRecipe> ApplyCore(Type predictorType,
327327
learner.LoadableClassInfo =
328328
ComponentCatalog.GetLoadableClassInfo<SignatureTrainer>(Learners.MultiClassNaiveBayesTrainer.LoadName);
329329
learner.Settings = "";
330-
var epInput = new Trainers.NaiveBayesClassifier();
330+
var epInput = new Legacy.Trainers.NaiveBayesClassifier();
331331
learner.PipelineNode = new TrainerPipelineNode(epInput);
332332
yield return new SuggestedRecipe(ToString(), transforms, new[] { learner });
333333
}

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