116 references to Info
Microsoft.ML.AutoML (7)
AutoMLExperiment\IMonitor.cs (5)
43_logger.Info($"Update Best Trial - Id: {result.TrialSettings.TrialId} - Metric: {result.Metric} - Pipeline: {_pipeline.ToString(result.TrialSettings.Parameter)}"); 50_logger.Info($"Update Completed Trial - Id: {result.TrialSettings.TrialId} - Raw Metric: {result.Metric + fResult.FairnessMetric} - Fairness Metric: {-fResult.FairnessMetric} - Total Metric: {result.Metric} - Pipeline: {this._pipeline} - Duration: {result.DurationInMilliseconds}"); 54_logger.Info($"Update Completed Trial - Id: {result.TrialSettings.TrialId} - Metric: {result.Metric} - Pipeline: {this._pipeline} - Duration: {result.DurationInMilliseconds}"); 62_logger.Info($"Update Failed Trial - Id: {settings.TrialId} - Pipeline: {_pipeline.ToString(settings.Parameter)}"); 67_logger.Info($"Update Running Trial - Id: {setting.TrialId}");
AutoMLExperiment\IStopTrainingManager.cs (1)
36_channel?.Info("cancel training because cancellation token is invoked...");
Experiment\Experiment.cs (1)
102_logger.Info(e.Message);
Microsoft.ML.AutoML.Tests (3)
AutoMLExperimentTests.cs (2)
447_logger.Info("Update Running Trial"); 451_logger.Info("Update Completed Trial");
MLContextManagerTests.cs (1)
60channel.Info("info");
Microsoft.ML.Core (2)
Utilities\ResourceManagerUtils.cs (2)
164ch.Info($"Downloading {fileName} from {url} to {filePath}"); 291ch.Info($"{fileName}: Download complete");
Microsoft.ML.Data (39)
Commands\CrossValidationCommand.cs (1)
128ch.Info(cmd);
Commands\SavePredictorCommand.cs (6)
152ch.Info("Saving predictor as binary"); 162ch.Info("Saving predictor summary"); 171ch.Info("Saving predictor as text"); 179ch.Info("Saving predictor as ini"); 195ch.Info("Saving predictor as code"); 204ch.Info("No files saved. Must specify at least one output file.");
Commands\ShowSchemaCommand.cs (1)
75ch.Info(str);
Commands\TrainCommand.cs (4)
119ch.Info(cmd); 454ch.Info("Not adding a normalizer."); 469ch.Info("Not adding a normalizer."); 478ch.Info("Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.");
Commands\TrainTestCommand.cs (1)
102ch.Info(cmd);
Commands\TypeInfoCommand.cs (1)
129ch.Info(srcStrings + " | " + dstStrings);
DataLoadSave\Binary\BinaryLoader.cs (1)
2229ch.Info(" "); // REVIEW: Ugh. Better way? Otherwise it's all smushed up.
DataLoadSave\Database\DatabaseLoader.cs (1)
490ch.Info("Duplicate name(s) specified - later columns will hide earlier ones");
DataLoadSave\LegacyCompositeDataLoader.cs (1)
359ch.Info("The data model doesn't contain transforms.");
DataLoadSave\Text\TextLoader.cs (1)
766ch.Info("Duplicate name(s) specified - later columns will hide earlier ones");
DataLoadSave\Text\TextLoaderParser.cs (2)
190_ch.Info(" Suppressing further bad value messages"); 201_ch.Info(" Suppressing further bad value messages");
Evaluators\AnomalyDetectionEvaluator.cs (1)
776ch.Info(MetricWriter.GetPerFoldResults(Host, fold, out weightedFold));
Evaluators\EvaluatorUtils.cs (1)
1708ch.Info(sb.ToString());
Evaluators\MamlEvaluator.cs (2)
179ch.Info(weightedMetrics); 180ch.Info(unweightedMetrics);
Evaluators\MulticlassClassificationEvaluator.cs (4)
945ch.Info(weightedConf); 946ch.Info(weightedFold); 948ch.Info(unweightedConf); 949ch.Info(unweightedFold);
Evaluators\MultiOutputRegressionEvaluator.cs (1)
766ch.Info(sb.ToString());
Evaluators\QuantileRegressionEvaluator.cs (2)
502ch.Info(weightedMetrics); 503ch.Info(unweightedMetrics);
Prediction\Calibrator.cs (7)
849ch.Info("Not training a calibrator because it is not needed."); 855ch.Info("Not training a calibrator because a valid calibrator trainer was not provided."); 861ch.Info("Not training a calibrator because there is no features column."); 867ch.Info("Not training a calibrator because there is no label column."); 873ch.Info("Not training a calibrator because the predictor does not implement IPredictorProducing<float>."); 883ch.Info("Not training a calibrator because the predictor does not output a score column."); 960ch.Info("Training calibrator.");
Transforms\ValueMapping.cs (1)
530ch.Info($"Found key values in the range {keyMin} to {keyMax} in the file '{fileName}'");
Microsoft.ML.Ensemble (1)
Selector\SubModelSelector\BaseSubModelSelector.cs (1)
32ch.Info("List of models and the metrics after sorted");
Microsoft.ML.FastTree (18)
FastTree.cs (10)
331ch.Info(GetTestGraphHeader()); 333ch.Info(GetTestGraphLine()); 616ch.Info("Randomizing start point"); 621ch.Info("Starting to train ..."); 706ch.Info("Reverting random score assignment"); 811ch.Info(sb.ToString()); 1369ch.Info("Changing data from row-wise to column-wise on disk"); 1812ch.Info("Changing data from row-wise to column-wise"); 2749ch.Info("Making per-feature arrays"); 2754ch.Info("Binning and forming Feature objects");
GamModelParameters.cs (3)
952ch.Info("GAM viz server is ready and waiting."); 958ch.Info("Quit signal received. Quitter."); 961ch.Info("No server, exiting immediately.");
GamTrainer.cs (4)
299ch.Info("Starting to train ..."); 429ch.Info("Pruning"); 439ch.Info($"Best Iteration ({lossFunctionName}): {bestIteration} @ {bestLoss:G6} (vs {GamTrainerOptions.NumberOfIterations} @ {finalResult.FinalValue:G6})."); 441ch.Info("No pruning necessary. More iterations may be necessary.");
Training\EnsembleCompression\LassoBasedEnsembleCompressor.cs (1)
545ch.Info("Compression R2 values:");
Microsoft.ML.KMeansClustering (3)
KMeansPlusPlusTrainer.cs (3)
225ch.Info("Initializing centroids"); 257ch.Info("Centroids initialized, starting main trainer"); 597ch.Info("There was not enough room to store distances of clusters from each other for acceleration of KMeans|| initialization. A memory efficient approach is used instead.");
Microsoft.ML.LightGbm (9)
LightGbmMulticlassTrainer.cs (4)
326ch.Info("Auto-tuning parameters: " + nameof(LightGbmTrainerOptions.LearningRate) + " = " + GbmOptions["learning_rate"]); 328ch.Info("Auto-tuning parameters: " + nameof(LightGbmTrainerOptions.NumberOfLeaves) + " = " + numberOfLeaves); 330ch.Info("Auto-tuning parameters: " + nameof(LightGbmTrainerOptions.MinimumExampleCountPerLeaf) + " = " + minimumExampleCountPerLeaf); 349ch.Info("Auto-tuning parameters: " + nameof(LightGbmTrainerOptions.UseSoftmax) + " = " + useSoftmax);
LightGbmTrainerBase.cs (4)
540ch.Info("Auto-tuning parameters: " + nameof(LightGbmTrainerOptions.LearningRate) + " = " + learningRate); 542ch.Info("Auto-tuning parameters: " + nameof(LightGbmTrainerOptions.NumberOfLeaves) + " = " + numberOfLeaves); 544ch.Info("Auto-tuning parameters: " + nameof(LightGbmTrainerOptions.MinimumExampleCountPerLeaf) + " = " + minimumExampleCountPerLeaf); 642ch.Info("Auto-tuning parameters: " + nameof(LightGbmTrainerOptions.UseCategoricalSplit) + " = " + useCat);
WrappedLightGbmTraining.cs (1)
84ch.Info($"Met early stopping, best iteration: {bestIter + 1}, best score: {bestScore / factorToSmallerBetter}");
Microsoft.ML.Maml (7)
ChainCommand.cs (5)
61chCmd.Info("====================================================================================="); 63chCmd.Info("====================================================================================="); 69chCmd.Info(" "); 75ch.Info("====================================================================================="); 77ch.Info("=====================================================================================");
HelpCommand.cs (1)
129ch.Info(sw.ToString());
VersionCommand.cs (1)
34ch.Info(version);
Microsoft.ML.Mkl.Components (7)
OlsLinearRegression.cs (1)
451ch.Info("Number of examples equals number of parameters, solution is exact but no statistics can be derived");
SymSgdClassificationTrainer.cs (3)
750ch.Info("Data fully loaded into memory."); 760stateGCHandle, ch.Info); 782stateGCHandle, ch.Info);
VectorWhitening.cs (3)
394ch.Info("Computing covariance matrix..."); 398ch.Info("Computing SVD..."); 411ch.Info("Scaling eigenvectors...");
Microsoft.ML.StandardTrainers (11)
Optimizer\Optimizer.cs (1)
607ch.Info("Beginning optimization");
Standard\LogisticRegression\LbfgsPredictorBase.cs (1)
582ch.Info("LBFGS multi-threading will attempt to load dataset into memory. In case of out-of-memory " +
Standard\MulticlassClassification\OneVersusAllTrainer.cs (2)
157ch.Info($"Training learner {i}"); 225ch.Info($"Training learner {i}");
Standard\MulticlassClassification\PairwiseCouplingTrainer.cs (2)
137ch.Info($"Training learner ({i},{j})"); 206ch.Info($"Training learner ({i},{j})");
Standard\Online\AveragedLinear.cs (2)
210ch.Info("Resetting weights to average weights"); 269ch.Info("Resetting weights to average weights");
Standard\Online\OnlineLinear.cs (1)
146ch.Info("Initializing weights and bias to " + parent.OnlineLinearTrainerOptions.InitialWeights);
Standard\SdcaBinary.cs (2)
346ch.Info("Using 1 thread to train."); 672ch.Info("Using model from last iteration.");
Microsoft.ML.Sweeper (1)
SweepCommand.cs (1)
100ch.Info("Outputs of finished runs can be found in the specified output folder");
Microsoft.ML.TorchSharp (3)
AutoFormerV2\ObjectDetectionTrainer.cs (1)
358_channel.Info($"Row: {Updates}, Loss: {lossValue.ToDouble()}");
Roberta\QATrainer.cs (1)
378_channel.Info($"Row: {Updates}, Loss: {loss.ToDouble()}");
TorchSharpBaseTrainer.cs (1)
218ch.Info($"Accuracy for epoch {epoch}: {Accuracy}");
Microsoft.ML.Transforms (5)
LearnerFeatureSelection.cs (1)
105ch.Info("No features are being dropped.");
MutualInformationFeatureSelection.cs (2)
174ch.Info("Computing mutual information"); 189ch.Info("Selecting features to drop");
PermutationFeatureImportance.cs (2)
55ch.Info("Number of slots: " + numSlots); 118ch.Info(msgFilteredOutFeatures.ToString());