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The `differentiability_witness_function` instruction looks up a differentiability witness function (JVP, VJP, or transpose) for a referenced function via SIL differentiability witnesses. Add round-trip parsing/serialization and IRGen tests. Notes: - Differentiability witnesses for linear functions require more support. `differentiability_witness_function [transpose]` instructions do not yet have IRGen. - Nothing currently generates `differentiability_witness_function` instructions. The differentiation transform does, but it hasn't been upstreamed yet. Resolves TF-1141.
158 lines
5.7 KiB
C++
158 lines
5.7 KiB
C++
//===--- AutoDiff.cpp - Swift automatic differentiation utilities ---------===//
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//
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// This source file is part of the Swift.org open source project
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//
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// Copyright (c) 2019 - 2020 Apple Inc. and the Swift project authors
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// Licensed under Apache License v2.0 with Runtime Library Exception
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//
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// See https://swift.org/LICENSE.txt for license information
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// See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors
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//
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//===----------------------------------------------------------------------===//
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#include "swift/AST/AutoDiff.h"
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#include "swift/AST/ASTContext.h"
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#include "swift/AST/Module.h"
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#include "swift/AST/TypeCheckRequests.h"
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#include "swift/AST/Types.h"
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using namespace swift;
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DifferentiabilityWitnessFunctionKind::DifferentiabilityWitnessFunctionKind(
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StringRef string) {
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Optional<innerty> result = llvm::StringSwitch<Optional<innerty>>(string)
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.Case("jvp", JVP)
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.Case("vjp", VJP)
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.Case("transpose", Transpose);
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assert(result && "Invalid string");
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rawValue = *result;
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}
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Optional<AutoDiffDerivativeFunctionKind>
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DifferentiabilityWitnessFunctionKind::getAsDerivativeFunctionKind() const {
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switch (rawValue) {
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case JVP:
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return {AutoDiffDerivativeFunctionKind::JVP};
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case VJP:
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return {AutoDiffDerivativeFunctionKind::VJP};
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case Transpose:
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return None;
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}
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}
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void AutoDiffConfig::print(llvm::raw_ostream &s) const {
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s << "(parameters=";
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parameterIndices->print(s);
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s << " results=";
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resultIndices->print(s);
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if (derivativeGenericSignature) {
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s << " where=";
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derivativeGenericSignature->print(s);
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}
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s << ')';
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}
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// TODO(TF-874): This helper is inefficient and should be removed. Unwrapping at
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// most once (for curried method types) is sufficient.
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static void unwrapCurryLevels(AnyFunctionType *fnTy,
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SmallVectorImpl<AnyFunctionType *> &results) {
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while (fnTy != nullptr) {
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results.push_back(fnTy);
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fnTy = fnTy->getResult()->getAs<AnyFunctionType>();
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}
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}
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static unsigned countNumFlattenedElementTypes(Type type) {
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if (auto *tupleTy = type->getCanonicalType()->getAs<TupleType>())
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return accumulate(tupleTy->getElementTypes(), 0,
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[&](unsigned num, Type type) {
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return num + countNumFlattenedElementTypes(type);
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});
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return 1;
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}
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// TODO(TF-874): Simplify this helper and remove the `reverseCurryLevels` flag.
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// See TF-874 for WIP.
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void autodiff::getSubsetParameterTypes(IndexSubset *subset,
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AnyFunctionType *type,
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SmallVectorImpl<Type> &results,
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bool reverseCurryLevels) {
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SmallVector<AnyFunctionType *, 2> curryLevels;
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unwrapCurryLevels(type, curryLevels);
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SmallVector<unsigned, 2> curryLevelParameterIndexOffsets(curryLevels.size());
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unsigned currentOffset = 0;
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for (unsigned curryLevelIndex : llvm::reverse(indices(curryLevels))) {
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curryLevelParameterIndexOffsets[curryLevelIndex] = currentOffset;
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currentOffset += curryLevels[curryLevelIndex]->getNumParams();
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}
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// If `reverseCurryLevels` is true, reverse the curry levels and offsets.
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if (reverseCurryLevels) {
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std::reverse(curryLevels.begin(), curryLevels.end());
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std::reverse(curryLevelParameterIndexOffsets.begin(),
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curryLevelParameterIndexOffsets.end());
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}
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for (unsigned curryLevelIndex : indices(curryLevels)) {
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auto *curryLevel = curryLevels[curryLevelIndex];
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unsigned parameterIndexOffset =
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curryLevelParameterIndexOffsets[curryLevelIndex];
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for (unsigned paramIndex : range(curryLevel->getNumParams()))
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if (subset->contains(parameterIndexOffset + paramIndex))
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results.push_back(curryLevel->getParams()[paramIndex].getOldType());
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}
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}
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GenericSignature autodiff::getConstrainedDerivativeGenericSignature(
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SILFunctionType *originalFnTy, IndexSubset *diffParamIndices,
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GenericSignature derivativeGenSig, LookupConformanceFn lookupConformance,
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bool isTranspose) {
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if (!derivativeGenSig)
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derivativeGenSig = originalFnTy->getSubstGenericSignature();
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if (!derivativeGenSig)
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return nullptr;
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auto &ctx = originalFnTy->getASTContext();
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auto *diffableProto = ctx.getProtocol(KnownProtocolKind::Differentiable);
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SmallVector<Requirement, 4> requirements;
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for (unsigned paramIdx : diffParamIndices->getIndices()) {
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// Require differentiability parameters to conform to `Differentiable`.
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auto paramType = originalFnTy->getParameters()[paramIdx].getInterfaceType();
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Requirement req(RequirementKind::Conformance, paramType,
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diffableProto->getDeclaredType());
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requirements.push_back(req);
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if (isTranspose) {
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// Require linearity parameters to additionally satisfy
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// `Self == Self.TangentVector`.
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auto tanSpace = paramType->getAutoDiffTangentSpace(lookupConformance);
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auto paramTanType = tanSpace->getCanonicalType();
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Requirement req(RequirementKind::SameType, paramType, paramTanType);
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requirements.push_back(req);
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}
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}
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return evaluateOrDefault(
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ctx.evaluator,
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AbstractGenericSignatureRequest{derivativeGenSig.getPointer(),
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/*addedGenericParams*/ {},
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std::move(requirements)},
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nullptr);
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}
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Type TangentSpace::getType() const {
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switch (kind) {
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case Kind::TangentVector:
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return value.tangentVectorType;
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case Kind::Tuple:
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return value.tupleType;
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}
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}
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CanType TangentSpace::getCanonicalType() const {
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return getType()->getCanonicalType();
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}
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NominalTypeDecl *TangentSpace::getNominal() const {
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assert(isTangentVector());
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return getTangentVector()->getNominalOrBoundGenericNominal();
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}
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