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416 lines
12 KiB
C++
416 lines
12 KiB
C++
/*******************************************************************************
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*
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* MIT License
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*
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* Copyright (C) 2022-2026 Advanced Micro Devices, Inc. All rights reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*
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*******************************************************************************/
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#pragma once
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#include <cmath>
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#include <tensilelitehost/export.h>
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namespace TensileLite
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{
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namespace Matching
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{
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/**
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* \ingroup PropertyMatching
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* \defgroup DistanceFunctions Distance Functions
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*/
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/**
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* \addtogroup DistanceFunctions
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* @{
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*/
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/**
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* @brief Abstract Distance function base class
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*/
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/**
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* Distance functions must implement the following methods:
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*
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* double operator()(Key const& p1, Key const& p2)
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*
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* Returns the distance between p1 and p2.
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*
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* bool improvementPossible(Key const& p1, Key const& p2, size_t idx,
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* double bestDistance) const
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*
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* May return `false` if it's impossible for `p1` and `p2` to be closer than
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* `bestDistance` based on `p1[idx]` and `p2[idx]` alone. This can be used to
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* exit early when searching a table sorted by element `idx`.
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*
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* If that doesn't apply to the given distance metric, returning `true` will
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* give the correct result.
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*/
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template <typename Key>
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class Distance
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{
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public:
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virtual std::string type() const = 0;
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virtual ~Distance() = default;
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};
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// Not really a distance, but defined as one for template specialization purposes
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template <typename Key>
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struct Equality : public Distance<Key>
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{
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enum
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{
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HasIndex = false,
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HasValue = false
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};
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static std::string Type()
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{
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return "Equality";
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}
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virtual std::string type() const override
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{
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return Type();
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}
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inline bool operator()(Key const& p1, Key const& p2) const
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{
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double distance = 0.0;
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for(int i = 0; i < p1.size(); i++)
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{
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double di = p1[i] - p2[i];
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distance += di * di;
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}
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return distance;
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}
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};
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// Not really a distance, but defined as one for template specialization purposes
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template <typename Key>
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struct Range : public Distance<Key>
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{
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enum
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{
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HasIndex = false,
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HasValue = false
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};
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static std::string Type()
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{
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return "Range";
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}
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virtual std::string type() const override
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{
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return Type();
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}
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inline bool operator()(Key const& p1, Key const& p2) const
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{
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double distance = 0.0;
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for(int i = 0; i < p1.size(); i++)
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{
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double di = p1[i] - p2[i];
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distance += di * di;
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}
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return distance;
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}
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};
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template <typename Key>
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struct RatioDistance : public Distance<Key>
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{
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enum
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{
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HasIndex = false,
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HasValue = false
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};
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static std::string Type()
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{
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return "Ratio";
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}
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virtual std::string type() const override
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{
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return Type();
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}
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inline double operator()(Key const& p1, Key const& p2) const
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{
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double distance = 1.0;
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for(int i = 0; i < p1.size(); i++)
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{
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distance += std::abs(std::log(double(p1[i]) / double(p2[i])));
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}
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return distance;
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}
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inline bool improvementPossible(Key const& p1,
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Key const& p2,
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size_t idx,
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double bestDistance) const
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{
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return true;
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}
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};
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template <typename Key>
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struct ManhattanDistance : public Distance<Key>
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{
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enum
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{
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HasIndex = false,
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HasValue = false
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};
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static std::string Type()
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{
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return "Manhattan";
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}
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virtual std::string type() const override
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{
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return Type();
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}
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inline double operator()(Key const& p1, Key const& p2) const
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{
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double distance = 0;
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for(int i = 0; i < p1.size(); i++)
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{
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distance += std::abs(p1[i] - p2[i]);
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}
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return distance;
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}
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inline bool improvementPossible(Key const& p1,
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Key const& p2,
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size_t idx,
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double bestDistance) const
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{
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double d0 = std::abs(p1[idx] - p2[idx]);
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return (d0 < bestDistance) || (p1 == p2);
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}
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};
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template <typename Key>
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struct EuclideanDistance : public Distance<Key>
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{
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enum
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{
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HasIndex = false,
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HasValue = false
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};
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static std::string Type()
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{
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return "Euclidean";
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}
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virtual std::string type() const override
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{
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return Type();
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}
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inline double operator()(Key const& p1, Key const& p2) const
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{
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double distance = 0.0;
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for(int i = 0; i < p1.size(); i++)
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{
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double di = p1[i] - p2[i];
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distance += di * di;
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}
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return distance;
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}
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inline bool improvementPossible(Key const& p1,
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Key const& p2,
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size_t idx,
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double bestDistance) const
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{
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double d0 = p1[idx] - p2[idx];
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return ((d0 * d0) < bestDistance) || (p1 == p2);
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}
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};
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template <typename Key>
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struct JSDivergence : public Distance<Key>
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{
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enum
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{
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HasIndex = false,
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HasValue = false
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};
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static std::string Type()
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{
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return "JSD";
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}
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virtual std::string type() const override
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{
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return Type();
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}
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double kl_divergence(double* p, double* q) const
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{
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double acc = 0.0;
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int dims = 3;
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for(int i = 0; i < dims; i++)
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acc += p[i] * std::log(p[i] / q[i]);
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return acc;
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}
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void normalize(Key const& p, Key const& q, double* norm_p, double* norm_q) const
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{
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int const dims = 3;
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double sum_p = 0.0;
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double sum_q = 0.0;
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for(int i = 0; i < dims; i++)
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{
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sum_p += p[i];
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sum_q += q[i];
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}
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for(int i = 0; i < dims; i++)
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{
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norm_p[i] = p[i] / sum_p;
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norm_q[i] = q[i] / sum_q;
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}
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}
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inline double operator()(Key const& p1, Key const& p2) const
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{
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double distance = 0.0;
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double norm_p[3];
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double norm_q[3];
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double m[3];
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this->normalize(p1, p2, norm_p, norm_q);
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for(int i = 0; i < p1.size(); i++)
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m[i] = 0.5 * (norm_p[i] + norm_q[i]);
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distance
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= 0.5 * this->kl_divergence(norm_p, m) + 0.5 * this->kl_divergence(norm_q, m);
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return distance;
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}
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inline bool improvementPossible(Key const& p1,
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Key const& p2,
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size_t idx,
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double bestDistance) const
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{
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double norm_p[3];
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double norm_q[3];
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double m;
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this->normalize(p1, p2, norm_p, norm_q);
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m = 0.5 * (norm_p[idx] + norm_q[idx]);
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double d0 = 0.5 * (norm_p[idx] * std::log(norm_p[idx] / m))
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+ 0.5 * (norm_q[idx] * std::log(norm_q[idx] / m));
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return (d0 < bestDistance) || (p1 == p2);
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}
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};
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template <typename Key>
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struct RandomDistance : public Distance<Key>
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{
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enum
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{
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HasIndex = false,
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HasValue = false
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};
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static std::string Type()
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{
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return "Random";
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}
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virtual std::string type() const override
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{
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return Type();
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}
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inline double operator()(Key const& p1, Key const& p2) const
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{
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return double(rand());
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}
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inline bool improvementPossible(Key const& p1,
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Key const& p2,
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size_t idx,
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double bestDistance) const
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{
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return true;
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}
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};
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template <typename Key>
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struct GridBasedDistance : public Distance<Key>
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{
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enum
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{
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HasIndex = false,
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HasValue = false
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};
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static std::string Type()
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{
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return "GridBased";
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}
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virtual std::string type() const override
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{
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return Type();
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}
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inline double operator()(Key const& p1, Key const& p2) const
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{
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double distance = 0.0;
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double gridK = p2.size() > 3 ? p2[3] : p2[2];
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// and nearest K
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double K = p1.size() > 3 ? p1[3] : p1[2];
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distance = std::abs(K - gridK);
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return distance;
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}
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inline bool improvementPossible(Key const& p1,
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Key const& p2,
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size_t idx,
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double bestDistance) const
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{
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return true;
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}
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};
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/**
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* @}
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*/
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} // namespace Matching
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} // namespace TensileLite
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