136 lines
5.8 KiB
C++
136 lines
5.8 KiB
C++
// Copyright Epic Games, Inc. All Rights Reserved.
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#pragma once
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#include "LearningArray.h"
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#define UE_API LEARNING_API
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namespace UE::Learning::KMeans
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{
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/**
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* Initialize a set of KMean Cluster centers by taking random points
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* from a set of samples
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*
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* @param Centers Output cluster centers of shape (ClusterNum, DimensionNum)
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* @param Samples Samples to be clustered of shape (SamplesNum, DimensionNum)
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* @param Seed Random Seed
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*/
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UE_API void InitCenters(
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TLearningArrayView<2, float> OutCenters,
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const TLearningArrayView<2, const float> Samples,
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const uint32 Seed);
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/**
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* Updates the assignments of each sample to each cluster
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*
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* @param OutAssignments For each sample, the index of the cluster it is assigned to - shape (SamplesNum)
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* @param Centers Cluster centers of shape (ClusterNum, DimensionNum)
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* @param Samples Samples to be clustered of shape (SamplesNum, DimensionNum)
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* @param bParallelEvaluation If to allow for multi-threaded evaluation
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* @param MinParallelBatchSize Minimum batch size to use for multi-threaded evaluation
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*/
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UE_API void UpdateAssignmentsFromCenters(
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TLearningArrayView<1, int32> OutAssignments,
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const TLearningArrayView<2, const float> Centers,
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const TLearningArrayView<2, const float> Samples,
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const bool bParallelEvaluation = true,
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const uint16 MinParallelBatchSize = 16);
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/**
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* Counters the number of assignments in each cluster
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*
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* @param OutAssignmentCounts Number of samples assigned to each cluster - shape (ClusterNum)
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* @param Assignments Index of the cluster assigned to each sample - shape (SamplesNum
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*/
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UE_API void CountClusterAssignments(
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TLearningArrayView<1, int32> OutAssignmentCounts,
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const TLearningArrayView<1, const int32> Assignments);
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/**
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* Updates the cluster centers based on the samples and their assignments
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*
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* @param OutCenters New cluster centers of shape (ClusterNum, DimensionNum)
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* @param Assignments Index of the cluster assigned to each sample - shape (SamplesNum)
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* @param AssignmentCounts Number of samples assigned to each cluster - shape (ClusterNum)
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* @param Samples Samples to be clustered of shape (SamplesNum, DimensionNum)
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*/
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UE_API void UpdateCenters(
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TLearningArrayView<2, float> OutCenters,
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const TLearningArrayView<1, const int32> Assignments,
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const TLearningArrayView<1, const int32> AssignmentCounts,
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const TLearningArrayView<2, const float> Samples);
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/**
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* Initialize a set of KMean Cluster bounds by taking random points
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* from a set of samples
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*
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* @param OutMins Output cluster mins of shape (ClusterNum, DimensionNum)
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* @param OutMaxs Output cluster maxs of shape (ClusterNum, DimensionNum)
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* @param Samples Samples to be clustered of shape (SamplesNum, DimensionNum)
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* @param Seed Random Seed
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*/
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UE_API void InitBounds(
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TLearningArrayView<2, float> OutMins,
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TLearningArrayView<2, float> OutMaxs,
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const TLearningArrayView<2, const float> Samples,
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const uint32 Seed);
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/**
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* Updates the assignments of each sample to each cluster
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*
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* @param OutAssignments For each sample, the index of the cluster it is assigned to - shape (SamplesNum)
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* @param Mins Cluster mins of shape (ClusterNum, DimensionNum)
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* @param Maxs Cluster maxs of shape (ClusterNum, DimensionNum)
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* @param Samples Samples to be clustered of shape (SamplesNum, DimensionNum)
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* @param bParallelEvaluation If to allow for multi-threaded evaluation
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* @param MinParallelBatchSize Minimum batch size to use for multi-threaded evaluation
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*/
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UE_API void UpdateAssignmentsFromBounds(
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TLearningArrayView<1, int32> OutAssignments,
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const TLearningArrayView<2, const float> Mins,
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const TLearningArrayView<2, const float> Maxs,
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const TLearningArrayView<2, const float> Samples,
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const bool bParallelEvaluation = true,
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const uint16 MinParallelBatchSize = 16);
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/**
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* Updates the cluster bounds based on the samples and their assignments
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*
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* @param OutMins New cluster mins of shape (ClusterNum, DimensionNum)
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* @param OutMaxs New cluster maxs of shape (ClusterNum, DimensionNum)
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* @param Assignments Index of the cluster assigned to each sample - shape (SamplesNum)
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* @param AssignmentCounts Number of samples assigned to each cluster - shape (ClusterNum)
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* @param Samples Samples to be clustered of shape (SamplesNum, DimensionNum)
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*/
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UE_API void UpdateBounds(
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TLearningArrayView<2, float> OutMins,
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TLearningArrayView<2, float> OutMaxs,
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const TLearningArrayView<1, const int32> Assignments,
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const TLearningArrayView<2, const float> Samples);
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/**
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* Generates an array of samples points, re-ordered and grouped into their clusters
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*
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* @param OutClusteredSamples Array of samples, grouped into their clusters of shape (SamplesNum, DimensionNum)
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* @param OutClusterStarts Start index into OutClusteredSamples for each cluster of shape (ClusterNum)
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* @param OutClusterLengths Number of samples in each cluster of shape (ClusterNum)
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* @param OutSampleMapping Index mapping into OutClusteredSamples for each sample in the original array - shape (SamplesNum)
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* @param OutInverseSampleMapping Index mapping from OutClusteredSamples into the original array for each sample - shape (SamplesNum)
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* @param Assignments Index of the cluster assigned to each sample - shape (SamplesNum)
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* @param AssignmentCounts Number of samples assigned to each cluster - shape (ClusterNum)
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* @param Samples Samples to be clustered of shape (SamplesNum, DimensionNum)
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*/
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UE_API void ComputeClusteredIndex(
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TLearningArrayView<2, float> OutClusteredSamples,
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TLearningArrayView<1, int32> OutClusterStarts,
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TLearningArrayView<1, int32> OutClusterLengths,
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TLearningArrayView<1, int32> OutSampleMapping,
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TLearningArrayView<1, int32> OutInverseSampleMapping,
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const TLearningArrayView<1, const int32> Assignments,
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const TLearningArrayView<1, const int32> AssignmentCounts,
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const TLearningArrayView<2, const float> Samples);
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}
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#undef UE_API |