| 1 | //===--- DecisionForest.cpp --------------------------------------*- C++-*-===// |
|---|---|
| 2 | // |
| 3 | // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
| 4 | // See https://llvm.org/LICENSE.txt for license information. |
| 5 | // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
| 6 | // |
| 7 | //===----------------------------------------------------------------------===// |
| 8 | |
| 9 | #include "Features.inc" |
| 10 | |
| 11 | #if !CLANGD_DECISION_FOREST |
| 12 | #include "Quality.h" |
| 13 | #include <cstdlib> |
| 14 | |
| 15 | namespace clang { |
| 16 | namespace clangd { |
| 17 | DecisionForestScores |
| 18 | evaluateDecisionForest(const SymbolQualitySignals &Quality, |
| 19 | const SymbolRelevanceSignals &Relevance, float Base) { |
| 20 | llvm::errs() << "Clangd was compiled without decision forest support.\n"; |
| 21 | std::abort(); |
| 22 | } |
| 23 | |
| 24 | } // namespace clangd |
| 25 | } // namespace clang |
| 26 | |
| 27 | #else // !CLANGD_DECISION_FOREST |
| 28 | |
| 29 | #include "CompletionModel.h" |
| 30 | #include "Quality.h" |
| 31 | #include <cmath> |
| 32 | |
| 33 | namespace clang { |
| 34 | namespace clangd { |
| 35 | |
| 36 | DecisionForestScores |
| 37 | evaluateDecisionForest(const SymbolQualitySignals &Quality, |
| 38 | const SymbolRelevanceSignals &Relevance, float Base) { |
| 39 | Example E; |
| 40 | E.setIsDeprecated(Quality.Deprecated); |
| 41 | E.setIsReservedName(Quality.ReservedName); |
| 42 | E.setIsImplementationDetail(Quality.ImplementationDetail); |
| 43 | E.setNumReferences(Quality.References); |
| 44 | E.setSymbolCategory(Quality.Category); |
| 45 | |
| 46 | SymbolRelevanceSignals::DerivedSignals Derived = |
| 47 | Relevance.calculateDerivedSignals(); |
| 48 | int NumMatch = 0; |
| 49 | if (Relevance.ContextWords) { |
| 50 | for (const auto &Word : Relevance.ContextWords->keys()) { |
| 51 | if (Relevance.Name.contains_insensitive(Other: Word)) { |
| 52 | ++NumMatch; |
| 53 | } |
| 54 | } |
| 55 | } |
| 56 | E.setIsNameInContext(NumMatch > 0); |
| 57 | E.setNumNameInContext(NumMatch); |
| 58 | E.setFractionNameInContext( |
| 59 | Relevance.ContextWords && !Relevance.ContextWords->empty() |
| 60 | ? NumMatch * 1.0 / Relevance.ContextWords->size() |
| 61 | : 0); |
| 62 | E.setIsInBaseClass(Relevance.InBaseClass); |
| 63 | E.setFileProximityDistanceCost(Derived.FileProximityDistance); |
| 64 | E.setSemaFileProximityScore(Relevance.SemaFileProximityScore); |
| 65 | E.setSymbolScopeDistanceCost(Derived.ScopeProximityDistance); |
| 66 | E.setSemaSaysInScope(Relevance.SemaSaysInScope); |
| 67 | E.setScope(Relevance.Scope); |
| 68 | E.setContextKind(Relevance.Context); |
| 69 | E.setIsInstanceMember(Relevance.IsInstanceMember); |
| 70 | E.setHadContextType(Relevance.HadContextType); |
| 71 | E.setHadSymbolType(Relevance.HadSymbolType); |
| 72 | E.setTypeMatchesPreferred(Relevance.TypeMatchesPreferred); |
| 73 | |
| 74 | DecisionForestScores Scores; |
| 75 | // Exponentiating DecisionForest prediction makes the score of each tree a |
| 76 | // multiplciative boost (like NameMatch). This allows us to weigh the |
| 77 | // prediction score and NameMatch appropriately. |
| 78 | Scores.ExcludingName = pow(Base, Evaluate(E)); |
| 79 | // Following cases are not part of the generated training dataset: |
| 80 | // - Symbols with `NeedsFixIts`. |
| 81 | // - Forbidden symbols. |
| 82 | // - Keywords: Dataset contains only macros and decls. |
| 83 | if (Relevance.NeedsFixIts) |
| 84 | Scores.ExcludingName *= 0.5; |
| 85 | if (Relevance.Forbidden) |
| 86 | Scores.ExcludingName *= 0; |
| 87 | if (Quality.Category == SymbolQualitySignals::Keyword) |
| 88 | Scores.ExcludingName *= 4; |
| 89 | |
| 90 | // NameMatch should be a multiplier on total score to support rescoring. |
| 91 | Scores.Total = Relevance.NameMatch * Scores.ExcludingName; |
| 92 | return Scores; |
| 93 | } |
| 94 | |
| 95 | } // namespace clangd |
| 96 | } // namespace clang |
| 97 | |
| 98 | #endif // !CLANGD_DECISION_FOREST |
| 99 |
