Skip to content

Commit 05482eb

Browse files
george-microsoftgeorge-microsoft
committed
Adding support for training metrics in PipelineSweeperMacro and needed support files. Also includes new output information in PipelineSweeperMacro output graph to make consumption of returned pipelines easier.
1 parent 3102180 commit 05482eb

File tree

8 files changed

+49190
-259
lines changed

8 files changed

+49190
-259
lines changed

‎src/Microsoft.ML.PipelineInference/AutoInference.cs

+10-7
Original file line numberDiff line numberDiff line change
@@ -172,12 +172,14 @@ private bool GetDataVariableName(IExceptionContext ectx, string nameOfData, JTok
172172
public sealed class RunSummary
173173
{
174174
public double MetricValue { get; }
175+
public double TrainingMetricValue { get; }
175176
public int NumRowsInTraining { get; }
176177
public long RunTimeMilliseconds { get; }
177178

178-
public RunSummary(double metricValue, int numRows, long runTimeMilliseconds)
179+
public RunSummary(double metricValue, int numRows, long runTimeMilliseconds, double trainingMetricValue)
179180
{
180181
MetricValue = metricValue;
182+
TrainingMetricValue = trainingMetricValue;
181183
NumRowsInTraining = numRows;
182184
RunTimeMilliseconds = runTimeMilliseconds;
183185
}
@@ -303,7 +305,7 @@ private void MainLearningLoop(int batchSize, int numOfTrainingRows)
303305
var stopwatch = new Stopwatch();
304306
var probabilityUtils = new Sweeper.Algorithms.SweeperProbabilityUtils(_host);
305307

306-
while (!_terminator.ShouldTerminate(_history))
308+
while (!_terminator.ShouldTerminate(_history))
307309
{
308310
// Get next set of candidates
309311
var currentBatchSize = batchSize;
@@ -341,16 +343,17 @@ private void ProcessPipeline(Sweeper.Algorithms.SweeperProbabilityUtils utils, S
341343

342344
// Run pipeline, and time how long it takes
343345
stopwatch.Restart();
344-
double d = candidate.RunTrainTestExperiment(_trainData.Take(randomizedNumberOfRows),
345-
_testData, Metric, TrainerKind);
346+
candidate.RunTrainTestExperiment(_trainData.Take(randomizedNumberOfRows),
347+
_testData, Metric, TrainerKind, out var testMetricVal, out var trainMetricVal);
346348
stopwatch.Stop();
347349

348350
// Handle key collisions on sorted list
349-
while (_sortedSampledElements.ContainsKey(d))
350-
d += 1e-10;
351+
while (_sortedSampledElements.ContainsKey(testMetricVal))
352+
testMetricVal += 1e-10;
351353

352354
// Save performance score
353-
candidate.PerformanceSummary = new RunSummary(d, randomizedNumberOfRows, stopwatch.ElapsedMilliseconds);
355+
candidate.PerformanceSummary =
356+
new RunSummary(testMetricVal, randomizedNumberOfRows, stopwatch.ElapsedMilliseconds, trainMetricVal);
354357
_sortedSampledElements.Add(candidate.PerformanceSummary.MetricValue, candidate);
355358
_history.Add(candidate);
356359
}

‎src/Microsoft.ML.PipelineInference/AutoMlUtils.cs

+20-4
Original file line numberDiff line numberDiff line change
@@ -15,21 +15,35 @@ namespace Microsoft.ML.Runtime.PipelineInference
1515
{
1616
public static class AutoMlUtils
1717
{
18-
public static AutoInference.RunSummary ExtractRunSummary(IHostEnvironment env, IDataView data, string metricColumnName)
18+
public static AutoInference.RunSummary ExtractRunSummary(IHostEnvironment env, IDataView result, string metricColumnName, IDataView trainResult = null)
1919
{
2020
double metricValue = 0;
21+
double trainingMetricValue = -1d;
2122
int numRows = 0;
22-
var schema = data.Schema;
23+
var schema = result.Schema;
2324
schema.TryGetColumnIndex(metricColumnName, out var metricCol);
2425

25-
using (var cursor = data.GetRowCursor(col => col == metricCol))
26+
using (var cursor = result.GetRowCursor(col => col == metricCol))
2627
{
2728
var getter = cursor.GetGetter<double>(metricCol);
2829
cursor.MoveNext();
2930
getter(ref metricValue);
3031
}
3132

32-
return new AutoInference.RunSummary(metricValue, numRows, 0);
33+
if (trainResult != null)
34+
{
35+
var trainSchema = trainResult.Schema;
36+
trainSchema.TryGetColumnIndex(metricColumnName, out var trainingMetricCol);
37+
38+
using (var cursor = trainResult.GetRowCursor(col => col == trainingMetricCol))
39+
{
40+
var getter = cursor.GetGetter<double>(trainingMetricCol);
41+
cursor.MoveNext();
42+
getter(ref trainingMetricValue);
43+
}
44+
}
45+
46+
return new AutoInference.RunSummary(metricValue, numRows, 0, trainingMetricValue);
3347
}
3448

3549
public static CommonInputs.IEvaluatorInput CloneEvaluatorInstance(CommonInputs.IEvaluatorInput evalInput) =>
@@ -618,5 +632,7 @@ public static Tuple<string, string[]>[] ConvertToSweepArgumentStrings(TlcModule.
618632
}
619633
return results;
620634
}
635+
636+
public static string GenerateOverallTrainingMetricVarName(Guid id) => $"Var_Training_OM_{id:N}";
621637
}
622638
}

‎src/Microsoft.ML.PipelineInference/Macros/PipelineSweeperMacro.cs

+14-5
Original file line numberDiff line numberDiff line change
@@ -65,18 +65,24 @@ public static Output ExtractSweepResult(IHostEnvironment env, ResultInput input)
6565
var col1 = new KeyValuePair<string, ColumnType>("Graph", TextType.Instance);
6666
var col2 = new KeyValuePair<string, ColumnType>("MetricValue", PrimitiveType.FromKind(DataKind.R8));
6767
var col3 = new KeyValuePair<string, ColumnType>("PipelineId", TextType.Instance);
68+
var col4 = new KeyValuePair<string, ColumnType>("TrainingMetricValue", PrimitiveType.FromKind(DataKind.R8));
69+
var col5 = new KeyValuePair<string, ColumnType>("FirstInput", TextType.Instance);
70+
var col6 = new KeyValuePair<string, ColumnType>("PredictorModel", TextType.Instance);
6871

6972
if (rows.Count == 0)
7073
{
7174
var host = env.Register("ExtractSweepResult");
72-
outputView = new EmptyDataView(host, new SimpleSchema(host, col1, col2, col3));
75+
outputView = new EmptyDataView(host, new SimpleSchema(host, col1, col2, col3, col4, col5, col6));
7376
}
7477
else
7578
{
7679
var builder = new ArrayDataViewBuilder(env);
7780
builder.AddColumn(col1.Key, (PrimitiveType)col1.Value, rows.Select(r => new DvText(r.GraphJson)).ToArray());
7881
builder.AddColumn(col2.Key, (PrimitiveType)col2.Value, rows.Select(r => r.MetricValue).ToArray());
7982
builder.AddColumn(col3.Key, (PrimitiveType)col3.Value, rows.Select(r => new DvText(r.PipelineId)).ToArray());
83+
builder.AddColumn(col4.Key, (PrimitiveType)col4.Value, rows.Select(r => r.TrainingMetricValue).ToArray());
84+
builder.AddColumn(col5.Key, (PrimitiveType)col5.Value, rows.Select(r => new DvText(r.FirstInput)).ToArray());
85+
builder.AddColumn(col6.Key, (PrimitiveType)col6.Value, rows.Select(r => new DvText(r.PredictorModel)).ToArray());
8086
outputView = builder.GetDataView();
8187
}
8288
return new Output { Results = outputView, State = autoMlState };
@@ -132,11 +138,11 @@ public static CommonOutputs.MacroOutput<Output> PipelineSweep(
132138
// Extract performance summaries and assign to previous candidate pipelines.
133139
foreach (var pipeline in autoMlState.BatchCandidates)
134140
{
135-
if (node.Context.TryGetVariable(ExperimentUtils.GenerateOverallMetricVarName(pipeline.UniqueId),
136-
out var v))
141+
if (node.Context.TryGetVariable(ExperimentUtils.GenerateOverallMetricVarName(pipeline.UniqueId), out var v) &&
142+
node.Context.TryGetVariable(AutoMlUtils.GenerateOverallTrainingMetricVarName(pipeline.UniqueId), out var v2))
137143
{
138144
pipeline.PerformanceSummary =
139-
AutoMlUtils.ExtractRunSummary(env, (IDataView)v.Value, autoMlState.Metric.Name);
145+
AutoMlUtils.ExtractRunSummary(env, (IDataView)v.Value, autoMlState.Metric.Name, (IDataView)v2.Value);
140146
autoMlState.AddEvaluated(pipeline);
141147
}
142148
}
@@ -168,14 +174,17 @@ public static CommonOutputs.MacroOutput<Output> PipelineSweep(
168174
{
169175
// Add train test experiments to current graph for candidate pipeline
170176
var subgraph = new Experiment(env);
171-
var trainTestOutput = p.AddAsTrainTest(training, testing, autoMlState.TrainerKind, subgraph);
177+
var trainTestOutput = p.AddAsTrainTest(training, testing, autoMlState.TrainerKind, subgraph, true);
172178

173179
// Change variable name to reference pipeline ID in output map, context and entrypoint output.
174180
var uniqueName = ExperimentUtils.GenerateOverallMetricVarName(p.UniqueId);
181+
var uniqueNameTraining = AutoMlUtils.GenerateOverallTrainingMetricVarName(p.UniqueId);
175182
var sgNode = EntryPointNode.ValidateNodes(env, node.Context,
176183
new JArray(subgraph.GetNodes().Last()), node.Catalog).Last();
177184
sgNode.RenameOutputVariable(trainTestOutput.OverallMetrics.VarName, uniqueName, cascadeChanges: true);
185+
sgNode.RenameOutputVariable(trainTestOutput.TrainingOverallMetrics.VarName, uniqueNameTraining, cascadeChanges: true);
178186
trainTestOutput.OverallMetrics.VarName = uniqueName;
187+
trainTestOutput.TrainingOverallMetrics.VarName = uniqueNameTraining;
179188
expNodes.Add(sgNode);
180189

181190
// Store indicators, to pass to next iteration of macro.

‎src/Microsoft.ML.PipelineInference/Microsoft.ML.PipelineInference.csproj

+1
Original file line numberDiff line numberDiff line change
@@ -17,6 +17,7 @@
1717
<ProjectReference Include="..\Microsoft.ML.Core\Microsoft.ML.Core.csproj" />
1818
<ProjectReference Include="..\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
1919
<ProjectReference Include="..\Microsoft.ML.Sweeper\Microsoft.ML.Sweeper.csproj" />
20+
<ProjectReference Include="..\Microsoft.ML\Microsoft.ML.csproj" />
2021
</ItemGroup>
2122

2223
</Project>

‎src/Microsoft.ML.PipelineInference/PipelinePattern.cs

+67-14
Original file line numberDiff line numberDiff line change
@@ -21,16 +21,24 @@ public sealed class PipelineResultRow
2121
{
2222
public string GraphJson { get; }
2323
public double MetricValue { get; }
24+
public double TrainingMetricValue { get; }
2425
public string PipelineId { get; }
26+
public string FirstInput { get; }
27+
public string PredictorModel { get; }
2528

2629
public PipelineResultRow()
2730
{ }
2831

29-
public PipelineResultRow(string graphJson, double metricValue, string pipelineId)
32+
public PipelineResultRow(string graphJson, double metricValue,
33+
string pipelineId, double trainingMetricValue, string firstInput,
34+
string predictorModel)
3035
{
3136
GraphJson = graphJson;
3237
MetricValue = metricValue;
3338
PipelineId = pipelineId;
39+
TrainingMetricValue = trainingMetricValue;
40+
FirstInput = firstInput;
41+
PredictorModel = predictorModel;
3442
}
3543
}
3644

@@ -111,7 +119,8 @@ public AutoInference.EntryPointGraphDef ToEntryPointGraph(Experiment experiment
111119
public bool Equals(PipelinePattern obj) => obj != null && UniqueId == obj.UniqueId;
112120

113121
// 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.
114-
public Experiment CreateTrainTestExperiment(IDataView trainData, IDataView testData, MacroUtils.TrainerKinds trainerKind, out Models.TrainTestEvaluator.Output resultsOutput)
122+
public Experiment CreateTrainTestExperiment(IDataView trainData, IDataView testData, MacroUtils.TrainerKinds trainerKind,
123+
bool includeTrainingMetrics, out Models.TrainTestEvaluator.Output resultsOutput)
115124
{
116125
var graphDef = ToEntryPointGraph();
117126
var subGraph = graphDef.Graph;
@@ -136,7 +145,8 @@ public Experiment CreateTrainTestExperiment(IDataView trainData, IDataView testD
136145
Model = finalOutput
137146
},
138147
PipelineId = UniqueId.ToString("N"),
139-
Kind = MacroUtils.TrainerKindApiValue<Models.MacroUtilsTrainerKinds>(trainerKind)
148+
Kind = MacroUtils.TrainerKindApiValue<Models.MacroUtilsTrainerKinds>(trainerKind),
149+
IncludeTrainingMetrics = includeTrainingMetrics
140150
};
141151

142152
var experiment = _env.CreateExperiment();
@@ -150,7 +160,7 @@ public Experiment CreateTrainTestExperiment(IDataView trainData, IDataView testD
150160
}
151161

152162
public Models.TrainTestEvaluator.Output AddAsTrainTest(Var<IDataView> trainData, Var<IDataView> testData,
153-
MacroUtils.TrainerKinds trainerKind, Experiment experiment = null)
163+
MacroUtils.TrainerKinds trainerKind, Experiment experiment = null, bool includeTrainingMetrics = false)
154164
{
155165
experiment = experiment ?? _env.CreateExperiment();
156166
var graphDef = ToEntryPointGraph(experiment);
@@ -174,7 +184,8 @@ public Models.TrainTestEvaluator.Output AddAsTrainTest(Var<IDataView> trainData,
174184
TrainingData = trainData,
175185
TestingData = testData,
176186
Kind = MacroUtils.TrainerKindApiValue<Models.MacroUtilsTrainerKinds>(trainerKind),
177-
PipelineId = UniqueId.ToString("N")
187+
PipelineId = UniqueId.ToString("N"),
188+
IncludeTrainingMetrics = includeTrainingMetrics
178189
};
179190
var trainTestOutput = experiment.Add(trainTestInput);
180191
return trainTestOutput;
@@ -183,34 +194,58 @@ public Models.TrainTestEvaluator.Output AddAsTrainTest(Var<IDataView> trainData,
183194
/// <summary>
184195
/// Runs a train-test experiment on the current pipeline, through entrypoints.
185196
/// </summary>
186-
public double RunTrainTestExperiment(IDataView trainData, IDataView testData, AutoInference.SupportedMetric metric, MacroUtils.TrainerKinds trainerKind)
197+
public void RunTrainTestExperiment(IDataView trainData, IDataView testData,
198+
AutoInference.SupportedMetric metric, MacroUtils.TrainerKinds trainerKind, out double testMetricValue,
199+
out double trainMetricValue)
187200
{
188-
var experiment = CreateTrainTestExperiment(trainData, testData, trainerKind, out var trainTestOutput);
201+
var experiment = CreateTrainTestExperiment(trainData, testData, trainerKind, true, out var trainTestOutput);
189202
experiment.Run();
203+
190204
var dataOut = experiment.GetOutput(trainTestOutput.OverallMetrics);
191205
var schema = dataOut.Schema;
192206
schema.TryGetColumnIndex(metric.Name, out var metricCol);
207+
double metricValue = 0;
208+
double trainingMetricValue = 0;
193209

194210
using (var cursor = dataOut.GetRowCursor(col => col == metricCol))
195211
{
196212
var getter = cursor.GetGetter<double>(metricCol);
197-
double metricValue = 0;
198213
cursor.MoveNext();
199214
getter(ref metricValue);
200-
return metricValue;
215+
}
216+
217+
dataOut = experiment.GetOutput(trainTestOutput.TrainingOverallMetrics);
218+
schema = dataOut.Schema;
219+
schema.TryGetColumnIndex(metric.Name, out metricCol);
220+
221+
using (var cursor = dataOut.GetRowCursor(col => col == metricCol))
222+
{
223+
var getter = cursor.GetGetter<double>(metricCol);
224+
cursor.MoveNext();
225+
getter(ref trainingMetricValue);
226+
testMetricValue = metricValue;
227+
trainMetricValue = trainingMetricValue;
201228
}
202229
}
203230

204-
public static PipelineResultRow[] ExtractResults(IHostEnvironment env, IDataView data, string graphColName, string metricColName, string idColName)
231+
public static PipelineResultRow[] ExtractResults(IHostEnvironment env, IDataView data,
232+
string graphColName, string metricColName, string idColName, string trainingMetricColName,
233+
string firstInputColName, string predictorModelColName)
205234
{
206235
var results = new List<PipelineResultRow>();
207236
var schema = data.Schema;
208237
if (!schema.TryGetColumnIndex(graphColName, out var graphCol))
209238
throw env.ExceptNotSupp($"Column name {graphColName} not found");
210239
if (!schema.TryGetColumnIndex(metricColName, out var metricCol))
211240
throw env.ExceptNotSupp($"Column name {metricColName} not found");
241+
if (!schema.TryGetColumnIndex(trainingMetricColName, out var trainingMetricCol))
242+
throw env.ExceptNotSupp($"Column name {trainingMetricColName} not found");
212243
if (!schema.TryGetColumnIndex(idColName, out var pipelineIdCol))
213244
throw env.ExceptNotSupp($"Column name {idColName} not found");
245+
if (!schema.TryGetColumnIndex(firstInputColName, out var firstInputCol))
246+
throw env.ExceptNotSupp($"Column name {firstInputColName} not found");
247+
if (!schema.TryGetColumnIndex(predictorModelColName, out var predictorModelCol))
248+
throw env.ExceptNotSupp($"Column name {predictorModelColName} not found");
214249

215250
using (var cursor = data.GetRowCursor(col => true))
216251
{
@@ -225,15 +260,33 @@ public static PipelineResultRow[] ExtractResults(IHostEnvironment env, IDataView
225260
var getter3 = cursor.GetGetter<DvText>(pipelineIdCol);
226261
DvText pipelineId = new DvText();
227262
getter3(ref pipelineId);
228-
results.Add(new PipelineResultRow(graphJson.ToString(), metricValue, pipelineId.ToString()));
263+
var getter4 = cursor.GetGetter<double>(trainingMetricCol);
264+
double trainingMetricValue = 0;
265+
getter4(ref trainingMetricValue);
266+
var getter5 = cursor.GetGetter<DvText>(firstInputCol);
267+
DvText firstInput = new DvText();
268+
getter5(ref firstInput);
269+
var getter6 = cursor.GetGetter<DvText>(predictorModelCol);
270+
DvText predictorModel = new DvText();
271+
getter6(ref predictorModel);
272+
273+
results.Add(new PipelineResultRow(graphJson.ToString(),
274+
metricValue, pipelineId.ToString(), trainingMetricValue,
275+
firstInput.ToString(), predictorModel.ToString()));
229276
}
230277
}
231278

232279
return results.ToArray();
233280
}
234281

235-
public PipelineResultRow ToResultRow() =>
236-
new PipelineResultRow(ToEntryPointGraph().Graph.ToJsonString(),
237-
PerformanceSummary?.MetricValue ?? -1d, UniqueId.ToString("N"));
282+
public PipelineResultRow ToResultRow() {
283+
var graphDef = ToEntryPointGraph();
284+
285+
return new PipelineResultRow($"{{'Nodes' : [{graphDef.Graph.ToJsonString()}]}}",
286+
PerformanceSummary?.MetricValue ?? -1d, UniqueId.ToString("N"),
287+
PerformanceSummary?.TrainingMetricValue ?? -1d,
288+
graphDef.GetSubgraphFirstNodeDataVarName(_env),
289+
graphDef.ModelOutput.VarName);
290+
}
238291
}
239292
}

0 commit comments

Comments
 (0)