4 types derived from IntArray
Microsoft.ML.FastTree (4)
Dataset\DenseIntArray.cs (1)
23internal abstract class DenseIntArray : IntArray, IIntArrayForwardIndexer
Dataset\RepeatIntArray.cs (1)
18internal sealed class DeltaRepeatIntArray : IntArray
Dataset\SegmentIntArray.cs (1)
20internal sealed class SegmentIntArray : IntArray
Dataset\SparseIntArray.cs (1)
30internal sealed class DeltaSparseIntArray : IntArray
99 references to IntArray
Microsoft.ML.FastTree (99)
Dataset\DatasetUtils.cs (5)
35IntArray ratingAsFeature = IntArray.New( 53IntArray bins = IntArray.New( 54skel.NumDocs, IntArrayType.Dense, IntArray.NumBitsNeeded(uvalToOrder.Count),
Dataset\DenseIntArray.cs (8)
38/// Value must be in legal range 0...((2^<see cref="IntArray.BitsPerItem"/>)-1). 44public override IntArray Clone(IntArrayBits bitsPerItem, IntArrayType type) 56public override IntArray Clone(int[] itemIndices) 58return IntArray.New(itemIndices.Length, IntArrayType.Dense, BitsPerItem, itemIndices.Select(x => this[x])); 61public override IntArray[] Split(int[][] assignment) 64IntArray[] newArrays = new IntArray[numParts]; 68newArrays[p] = IntArray.New(assignment[p].Length, IntArrayType.Dense, BitsPerItem, assignment[p].Select(x => this[x]));
Dataset\Feature.cs (15)
16private IntArray _bins; 42protected Feature(IntArray bins) 96Bins = IntArray.New(buffer, ref position); 150public IntArray Bins 199public TsvFeature(IntArray bins, uint[] valueMap, string name) 298bitsPerItem = IntArray.NumBitsNeeded(parts[0].ValueMap.Length); 301IntArray b = parts[0].Bins; 302IntArray newBins = IntArray.New(b.Length, b.Type, bitsPerItem, b); 307bitsPerItem = IntArray.NumBitsNeeded(concatValueMap.Length); 308IntArray concatBins = ConcatBins(parts, concatValueMap); 327private static IntArray ConcatBins(TsvFeature[] parts, uint[] concatValueMap) 333IntArrayBits bitsPerItem = IntArray.NumBitsNeeded(concatValueMap.Length); 334DenseIntArray concatBins = (DenseIntArray)IntArray.New(length, IntArrayType.Dense, bitsPerItem); 340IntArray bins = parts[partIndex].Bins;
Dataset\FeatureFlock.cs (5)
1081/// <see cref="IntArray"/> instances. 1102/// A base class for a feature flock that wraps a single <see cref="IntArray"/> that contains multiple 1104/// that doing a <see cref="IntArray.Sumup"/> will accumulate sufficient statistics correctly for all 1109where TIntArray : IntArray 1121/// <see cref="IntArray"/>, where 0 indicates that all features are in the "cold" bin
Dataset\FeatureHistogram.cs (2)
28private readonly IntArray _bins; 36public FeatureHistogram(IntArray bins, int numBins, bool useWeights)
Dataset\IntArray.cs (12)
88public static IntArray New(int length, IntArrayType type, IntArrayBits bitsPerItem, IEnumerable<int> values) 124public static IntArray New(int length, IntArrayType type, IntArrayBits bitsPerItem) 157public static IntArray New(byte[] buffer, ref int position) 191public abstract IntArray Clone(IntArrayBits bitsPerItem, IntArrayType type); 198public abstract IntArray Clone(int[] itemIndices); 200public abstract IntArray[] Split(int[][] assignment); 288public IntArray Compress(uint[] workarray = null) 323IntArrayBits classicBits = IntArray.NumBitsNeeded(maxval + 1); 338if ((IntArray.CompatibilityLevel & 0x4) == 0) 364IntArray bins = null; 367bins = IntArray.New(Length, bestType, classicBits, this); 378/// Interface for objects that can index into an <see cref="IntArray"/>, but only with a non-decreasing sequence of indices.
Dataset\OneHotFeatureFlock.cs (3)
14internal sealed class OneHotFeatureFlock : SinglePartitionedIntArrayFlockBase<IntArray> 16public OneHotFeatureFlock(IntArray bins, int[] hotFeatureStarts, double[][] binUpperBounds, bool categorical) 64/// <param name="indexer">The indexer into the "shared" <see cref="IntArray"/>, that we
Dataset\RepeatIntArray.cs (6)
65_values = IntArray.New(tempValueList.Count, IntArrayType.Dense, bitsPerItem, tempValueList) as DenseIntArray; 87_values = IntArray.New(buffer, ref position) as DenseIntArray; 111public override IntArray Clone(IntArrayBits bitsPerItem, IntArrayType type) 113return IntArray.New(_length, type, bitsPerItem, this); 184public override IntArray Clone(int[] itemIndices) 196public override IntArray[] Split(int[][] assignment)
Dataset\SegmentIntArray.cs (3)
261public override IntArray Clone(IntArrayBits bitsPerItem, IntArrayType type) 303public override IntArray[] Split(int[][] assignment) 317public override IntArray Clone(int[] itemIndices)
Dataset\SingletonFeatureFlock.cs (2)
17private readonly IntArray _bins; 22public SingletonFeatureFlock(IntArray bins, double[] binUpperBounds)
Dataset\SparseIntArray.cs (15)
20/// This <see cref="IntArray"/> implementation represents a sequence of values using parallel 25/// us to represent multiple values per row. In this case, <see cref="IntArray.GetEnumerator"/> 26/// and <see cref="IntArray.GetIndexer"/> will not have sensible values, but 27/// <see cref="IntArray.Sumup"/> will work and accumulate the same target into multiple bins. 83_values = IntArray.New(tempValueList.Count, IntArrayType.Dense, bitsPerItem, tempValueList) as DenseIntArray; 97_values = IntArray.New(buffer, ref position) as DenseIntArray; 166_values = IntArray.New(tempValueList.Count, IntArrayType.Dense, bitsPerItem, tempValueList) as DenseIntArray; 200public override IntArray[] Split(int[][] assignment) 202IntArray[] parts = new IntArray[assignment.Length]; 206parts[i] = IntArray.New(assignment[i].Length, IntArrayType.Sparse, BitsPerItem, assignment[i].Select(x => indexer[x])); 217public override IntArray Clone(int[] itemIndices) 221return IntArray.New(itemIndices.Length, IntArrayType.Sparse, BitsPerItem, itemIndices.Select(x => indexer[x])); 255public override IntArray Clone(IntArrayBits bitsPerItem, IntArrayType type) 266DenseIntArray dense = IntArray.New(Length, IntArrayType.Dense, BitsPerItem) as DenseIntArray;
FastTree.cs (15)
261IntArray.CompatibilityLevel = FastTreeTrainerOptions.FeatureCompressionLevel; 1050IntArrayBits flockBits = IntArray.NumBitsNeeded(hotFeatureStarts[hotFeatureStarts.Length - 1] + 1); 1101IntArray bins = IntArray.New(NumExamples, type, flockBits, binnedValues); 1126IntArrayBits flockBits = IntArray.NumBitsNeeded(hotFeatureStarts[hotFeatureStarts.Length - 1] + 1); 1175IntArray bins = IntArray.New(NumExamples, type, flockBits, binnedValues); 1204IntArray bins = null; 1207var numBitsNeeded = IntArray.NumBitsNeeded(binUpperBounds.Length); 1254bins = IntArray.New(values.Length, arrayType, IntArray.NumBitsNeeded(binUpperBounds.Length), binnedValues); 1953IntArrayBits flockBits = IntArray.NumBitsNeeded(hotFeatureStarts[hotFeatureStarts.Length - 1] + 1); 2032var denseBins = (DenseIntArray)IntArray.New(values.Count, IntArrayType.Dense, flockBits, values); 2257IntArrayBits newBits = IntArray.NumBitsNeeded(countBins); 2558IntArrayBits numBitsNeeded = IntArray.NumBitsNeeded(binUpperBounds.Length);
FastTreeRanking.cs (1)
796if (IntArray.UseFastTreeNative)
SumupPerformanceCommand.cs (6)
150private IntArray[] CreateRandomIntArrays(IChannel ch) 152IntArray[] arrays = new IntArray[_count]; 157IntArrayBits bits = IntArray.NumBitsNeeded(_bins); 178arrays[i] = IntArray.New(_len, _type, bits, createIntArray(ch, r)); 271IntArray[] arrays = CreateRandomIntArrays(ch);
Training\DocumentPartitioning.cs (1)
245public unsafe void Split(int leaf, IntArray bins, HashSet<int> categoricalIndices, int gtChildIndex)