VBuffer

93 references to VBuffer

Microsoft.Data.Analysis.Tests (7)

DataFrame.IOTests.cs (3)

950new VBuffer<int> (3, new int[] { 1, 2, 3 }), 951new VBuffer<int> (3, new int[] { 2, 3, 4 }), 952new VBuffer<int> (3, new int[] { 3, 4, 5 }),

DataFrameTests.Utils.cs (1)

79var buffers = Enumerable.Repeat(new VBuffer<int>(5, new[] { 0, 1, 2, 3, 4 }), length).ToArray();

VBufferColumnTests.cs (3)

22var buffers = Enumerable.Repeat(new VBuffer<int>(5, new[] { 0, 1, 2, 3, 4 }), 10).ToArray(); 33var buffer = new VBuffer<int>(5, new[] { 4, 3, 2, 1, 0 }); 53vBufferColumn[index] = new VBuffer<int>(5, originalValues);

Microsoft.ML.AutoML (2)

Sweepers\SmacSweeper.cs (1)

334VBuffer<Float> features = new VBuffer<Float>(transformedParams.Length, transformedParams);

Tuner\SmacTuner.cs (1)

325var features = new VBuffer<float>(transformedParams.Length, transformedParams);

Microsoft.ML.Core (1)

Utilities\VBufferUtils.cs (1)

76return new VBuffer<T>(length, new T[length]);

Microsoft.ML.Core.Tests (14)

UnitTests\TestVBuffer.cs (14)

Microsoft.ML.Data (25)

Evaluators\BinaryClassifierEvaluator.cs (2)

184labelNames = new VBuffer<ReadOnlyMemory<char>>(2, new[] { "positive".AsMemory(), "negative".AsMemory() }); 363dst = new VBuffer<ReadOnlyMemory<char>>(aggregator.ClassNames.Length, aggregator.ClassNames);

Evaluators\EvaluatorUtils.cs (4)

494var reconciledSlotNames = new VBuffer<ReadOnlyMemory<char>>(slotNames.Count, slotNames.Keys.Select(k => k.AsMemory()).ToArray()); 615var keyNamesVBuffer = new VBuffer<ReadOnlyMemory<char>>(keyNames.Count, keyNames.Keys.ToArray()); 683var keyNamesVBuffer = new VBuffer<ReadOnlyMemory<char>>(keyNames.Count, keyNames.Keys.ToArray()); 1312var slotNames = new VBuffer<ReadOnlyMemory<char>>(type.Size, names);

Evaluators\MulticlassClassificationEvaluator.cs (2)

226dst = new VBuffer<ReadOnlyMemory<char>>(allTopK.First().Length, Enumerable.Range(1, allTopK.First().Length).Select(i => new ReadOnlyMemory<char>(i.ToString().ToCharArray())).ToArray()); 240dst = new VBuffer<ReadOnlyMemory<char>>(aggregator.ClassNames.Length, aggregator.ClassNames);

Evaluators\QuantileRegressionEvaluator.cs (3)

105return new VBuffer<Double>(_size, res); 119return new VBuffer<Double>(_size, res); 313_quantiles = new VBuffer<ReadOnlyMemory<char>>(quantiles.Length, quantiles);

Transforms\ColumnConcatenatingTransformer.cs (1)

615dst = new VBuffer<int>(allValues.Count, allValues.ToArray());

Transforms\InvertHashUtils.cs (1)

264return new VBuffer<ReadOnlyMemory<char>>(values.Length, values);

Transforms\KeyToVector.cs (1)

446dst = new VBuffer<int>(ranges.Length, ranges);

Transforms\NormalizeColumn.cs (4)

507var src = new VBuffer<TFloat>(Scale.Length, Scale); 514var src = new VBuffer<TFloat>(Offset.Length, Offset); 627var src = new VBuffer<TFloat>(Mean.Length, Mean); 633var src = new VBuffer<TFloat>(Stddev.Length, Stddev);

Transforms\NormalizeColumnDbl.cs (3)

1531_buffer = new VBuffer<TFloat>(1, new TFloat[1]); 1662_buffer = new VBuffer<TFloat>(1, new TFloat[1]); 2068_buffer = new VBuffer<double>(1, new double[1]);

Transforms\NormalizeColumnSng.cs (3)

1694_buffer = new VBuffer<TFloat>(1, new TFloat[1]); 1825_buffer = new VBuffer<TFloat>(1, new TFloat[1]); 2232_buffer = new VBuffer<TFloat>(1, new TFloat[1]);

Transforms\SlotsDroppingTransformer.cs (1)

702dst = new VBuffer<int>(newCategoricalSlotRanges.Count, newCategoricalSlotRanges.ToArray());

Microsoft.ML.FastTree (4)

Utils\RegressionTreeBaseUtils.cs (4)

85categoricalSplitFeatures.Add(new VBuffer<int>(categoricalSplitFeaturesArray.Length, categoricalSplitFeaturesArray)); 90categoricalCategoricalSplitFeatureRange.Add(new VBuffer<int>(categoricalCategoricalSplitFeatureRangeArray.Length, categoricalCategoricalSplitFeatureRangeArray)); 129leafSamples.Add(new VBuffer<double>(leafSamplesArray.Length, leafSamplesArray)); 133leafSampleWeights.Add(new VBuffer<double>(leafSampleWeightsArray.Length, leafSampleWeightsArray));

Microsoft.ML.ImageAnalytics (1)

ImageLoader.cs (1)

314imgData = new VBuffer<byte>(count, imageBuffer);

Microsoft.ML.Mkl.Components (1)

OlsLinearRegression.cs (1)

445var weights = new VBuffer<float>(weightsValues.Length, weightsValues);

Microsoft.ML.Parquet (2)

ParquetLoader.cs (2)

691public void Conv(in byte[] src, ref VBuffer<Byte> dst) => dst = src != null ? new VBuffer<byte>(src.Length, src) : new VBuffer<byte>(0, new byte[0]);

Microsoft.ML.PCA (1)

PcaTrainer.cs (1)

462_eigenVectors[i] = new VBuffer<float>(eigenVectors[i].Length, eigenVectors[i]);

Microsoft.ML.PerformanceTests (1)

HashBench.cs (1)

129var vbuf = new VBuffer<T>(vals.Length, vals);

Microsoft.ML.Predictor.Tests (1)

TestTransposer.cs (1)

119vecs[r] = new VBuffer<T>(slotCount, vals);

Microsoft.ML.StandardTrainers (6)

Standard\LogisticRegression\LbfgsPredictorBase.cs (3)

332init = new VBuffer<float>(initWeights.Length, initWeights); 560CurrentWeights = new VBuffer<float>(betaArray.Length, betaArray); 913return new VBuffer<float>(initWeights.Length, initWeights);

Standard\ModelStatistics.cs (1)

281_coeffStdError = new VBuffer<float>(length, stdErrorValues);

Standard\Online\OnlineLinear.cs (2)

158Weights = new VBuffer<float>(numFeatures, weightValues); 166Weights = new VBuffer<float>(numFeatures, weightValues);

Microsoft.ML.Sweeper (1)

Algorithms\SmacSweeper.cs (1)

344VBuffer<float> features = new VBuffer<float>(transformedParams.Length, transformedParams);

Microsoft.ML.TestFramework (2)

DataPipe\TestDataPipe.cs (2)

915expected[0] = new VBuffer<ReadOnlyMemory<char>>(values.Length, values); 917expected[1] = new VBuffer<ReadOnlyMemory<char>>(values1.Length, values1);

Microsoft.ML.Tests (7)

Scenarios\Api\TestApi.cs (3)

216var valueVBuffer = new VBuffer<float>(4, new float[] { 4, 6, 89, 5 }); 254VBuffer<float> retrievedFloatVBuffer = new VBuffer<float>(1, new float[] { 2 }); 256VBuffer<float> valueFloatVBuffer = new VBuffer<float>(valueFloatArray.Length, valueFloatArray);

SvmLightTests.cs (1)

162AnnotationUtils.Kinds.SlotNames, new VBuffer<ReadOnlyMemory<char>>(3, new[] { "aurora".AsMemory(), "beachwood".AsMemory(), "chagrin".AsMemory() }),

TrainerEstimators\TreeEnsembleFeaturizerTest.cs (3)

166var leafId = model.Model.SubModel.GetLeaf(treeIndex, new VBuffer<float>(10, features[dataPointIndex]), ref path); 217var leafId = model.Model.GetLeaf(treeIndex, new VBuffer<float>(10, features[dataPointIndex]), ref path); 281var leafId = model.Model.SubModel.GetLeaf(treeIndex, new VBuffer<float>(10, features[dataPointIndex]), ref path);

Microsoft.ML.TimeSeries (9)

SequentialAnomalyDetectionTransformBase.cs (1)

325_slotNames = new VBuffer<ReadOnlyMemory<char>>(4, new[] { "Alert".AsMemory(), "Raw Score".AsMemory(),

SrCnnTransformBase.cs (1)

168_slotNames = new VBuffer<ReadOnlyMemory<char>>(_parent.OutputLength, new[] { "Alert".AsMemory(), "Raw Score".AsMemory(),

SsaForecastingBase.cs (7)

266dst = new VBuffer<float>(LocalHorizon ?? _parentForecaster.Horizon, 281dst1 = new VBuffer<float>(_parentForecaster.Horizon, forecast); 282dst2 = new VBuffer<float>(_parentForecaster.Horizon, min); 283dst3 = new VBuffer<float>(_parentForecaster.Horizon, max); 289dst = new VBuffer<float>(horizon, ((AdaptiveSingularSpectrumSequenceModelerInternal)_model).Forecast(horizon)); 298dst = new VBuffer<float>(horizon, min); 307dst = new VBuffer<float>(horizon, max);

Microsoft.ML.TorchSharp (1)

NasBert\NerTrainer.cs (1)

131VBuffer<long> t = new VBuffer<long>(target.Length + 1, tl.ToArray());

Microsoft.ML.Transforms (7)

CountFeatureSelection.cs (1)

394_buffer = new VBuffer<T>(1, new T[1]);

Dracula\CountTableTransformer.cs (1)

644inputSlotNames = new VBuffer<ReadOnlyMemory<char>>(1, new[] { inputCol.Name.AsMemory() });

MissingValueReplacing.cs (1)

482return new VBuffer<T>(array.Length, array);

RandomFourierFeaturizing.cs (2)

316dst = new VBuffer<float>(1, new[] { val }); 537var oneDimensionalVector = new VBuffer<float>(1, new float[] { 0 });

SvmLight\SvmLightLoader.cs (2)

240intermediate.FeatureKeys = new VBuffer<ReadOnlyMemory<char>>(keys.Count, keys.ToArray()); 241intermediate.FeatureValues = new VBuffer<float>(values.Count, values.ToArray());