1 implementation of SetProgress
Microsoft.ML.Core (1)
Data\ProgressReporter.cs (1)
534public void SetProgress(int index, Double value, Double lim)
29 references to SetProgress
Microsoft.ML.Data (3)
DataLoadSave\Text\TextSaver.cs (1)
446pch.SetHeader(new ProgressHeader(new[] { "rows" }), e => e.SetProgress(0, stateCount, rowCount));
Transforms\ValueToKeyMappingTransformer.cs (2)
493e.SetProgress(0, rowCur, rowCount); 608e.SetProgress(0, rowCur, rowCount);
Microsoft.ML.FastTree (7)
FastTree.cs (5)
648pch.SetHeader(new ProgressHeader("trees"), e => e.SetProgress(0, Ensemble.NumTrees, numTotalTrees)); 1405pch.SetHeader(new ProgressHeader("features"), e => e.SetProgress(0, iFeature, features.Length)); 1817e => e.SetProgress(0, pos, rowCountDbl)); 1913pch.SetHeader(new ProgressHeader("features"), e => e.SetProgress(0, iFeature, NumFeatures)); 2069pch.SetHeader(new ProgressHeader("features"), e => e.SetProgress(0, iFeature, NumFeatures));
GamTrainer.cs (1)
307pch.SetHeader(new ProgressHeader("iterations"), e => e.SetProgress(0, iteration, iterations));
SumupPerformanceCommand.cs (1)
156pch.SetHeader(new ProgressHeader("arrays"), e => e.SetProgress(0, created, arrays.Length));
Microsoft.ML.KMeansClustering (3)
KMeansPlusPlusTrainer.cs (3)
351pCh.SetHeader(new ProgressHeader("centroids"), (e) => e.SetProgress(0, i, k)); 827pCh.SetHeader(new ProgressHeader("rounds"), (e) => e.SetProgress(0, logicalExternalRounds, numRounds + 2)); 1371(e) => e.SetProgress(0, state.Iteration, maxIterations));
Microsoft.ML.LightGbm (1)
WrappedLightGbmTraining.cs (1)
60e.SetProgress(0, iter, numIteration);
Microsoft.ML.Mkl.Components (2)
SymSgdClassificationTrainer.cs (2)
756entry => entry.SetProgress(0, state.PassIteration, _options.NumberOfIterations)); 766entry => entry.SetProgress(0, iter, _options.NumberOfIterations));
Microsoft.ML.StandardTrainers (7)
FactorizationMachine\FactorizationMachineTrainer.cs (1)
474entry.SetProgress(0, iter, _numIterations);
Standard\LogisticRegression\LbfgsPredictorBase.cs (2)
608e => e.SetProgress(0, exCount, totalCount)); 848pch.SetHeader(new ProgressHeader(null, new[] { "examples" }), e => e.SetProgress(0, iv - ivMin, ivLim - ivMin));
Standard\MulticlassClassification\MulticlassNaiveBayesTrainer.cs (1)
157e.SetProgress(0, examplesProcessed, int.MaxValue);
Standard\SdcaBinary.cs (3)
575pch.SetHeader(new ProgressHeader("examples"), e => e.SetProgress(0, row, count)); 603pch.SetHeader(new ProgressHeader(metricNames, new[] { "iterations" }), e => e.SetProgress(0, iter, maxIterations)); 2173entry => entry.SetProgress(0, iter, _options.NumberOfIterations));
Microsoft.ML.TorchSharp (2)
AutoFormerV2\ObjectDetectionTrainer.cs (1)
170e.SetProgress(0, trainer.Updates, trainer.RowCount);
Roberta\QATrainer.cs (1)
159e.SetProgress(0, trainer.Updates, trainer.RowCount);
Microsoft.ML.Transforms (3)
CountFeatureSelection.cs (1)
329pch.SetHeader(header, e => { e.SetProgress(0, rowCur, rowCount); });
MutualInformationFeatureSelection.cs (1)
497pch.SetHeader(header, e => e.SetProgress(0, i, size));
Text\NgramTransform.cs (1)
269e => e.SetProgress(0, totalDocs, rowCount));
Microsoft.ML.Vision (1)
DnnRetrainTransform.cs (1)
343pch.SetHeader(new ProgressHeader(new[] { "Loss", "Metric" }, new[] { "Epoch" }), (e) => e.SetProgress(0, epoch, options.Epoch));