blob: c7065c2c6bf62caf20581fb20f9118dbdd508232 [file] [log] [blame]
//===-- lib/Evaluate/fold-reduction.h -------------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
// TODO: DOT_PRODUCT, NORM2, PARITY
#ifndef FORTRAN_EVALUATE_FOLD_REDUCTION_H_
#define FORTRAN_EVALUATE_FOLD_REDUCTION_H_
#include "fold-implementation.h"
namespace Fortran::evaluate {
// Fold and validate a DIM= argument. Returns false on error.
bool CheckReductionDIM(std::optional<int> &dim, FoldingContext &,
ActualArguments &, std::optional<int> dimIndex, int rank);
// Fold and validate a MASK= argument. Return null on error, absent MASK=, or
// non-constant MASK=.
Constant<LogicalResult> *GetReductionMASK(
std::optional<ActualArgument> &maskArg, const ConstantSubscripts &shape,
FoldingContext &);
// Common preprocessing for reduction transformational intrinsic function
// folding. If the intrinsic can have DIM= &/or MASK= arguments, extract
// and check them. If a MASK= is present, apply it to the array data and
// substitute identity values for elements corresponding to .FALSE. in
// the mask. If the result is present, the intrinsic call can be folded.
template <typename T>
static std::optional<Constant<T>> ProcessReductionArgs(FoldingContext &context,
ActualArguments &arg, std::optional<int> &dim, const Scalar<T> &identity,
int arrayIndex, std::optional<int> dimIndex = std::nullopt,
std::optional<int> maskIndex = std::nullopt) {
if (arg.empty()) {
return std::nullopt;
}
Constant<T> *folded{Folder<T>{context}.Folding(arg[arrayIndex])};
if (!folded || folded->Rank() < 1) {
return std::nullopt;
}
if (!CheckReductionDIM(dim, context, arg, dimIndex, folded->Rank())) {
return std::nullopt;
}
if (maskIndex && static_cast<std::size_t>(*maskIndex) < arg.size() &&
arg[*maskIndex]) {
if (const Constant<LogicalResult> *mask{
GetReductionMASK(arg[*maskIndex], folded->shape(), context)}) {
// Apply the mask in place to the array
std::size_t n{folded->size()};
std::vector<typename Constant<T>::Element> elements;
if (auto scalarMask{mask->GetScalarValue()}) {
if (scalarMask->IsTrue()) {
return Constant<T>{*folded};
} else { // MASK=.FALSE.
elements = std::vector<typename Constant<T>::Element>(n, identity);
}
} else { // mask is an array; test its elements
elements = std::vector<typename Constant<T>::Element>(n, identity);
ConstantSubscripts at{folded->lbounds()};
for (std::size_t j{0}; j < n; ++j, folded->IncrementSubscripts(at)) {
if (mask->values()[j].IsTrue()) {
elements[j] = folded->At(at);
}
}
}
if constexpr (T::category == TypeCategory::Character) {
return Constant<T>{static_cast<ConstantSubscript>(identity.size()),
std::move(elements), ConstantSubscripts{folded->shape()}};
} else {
return Constant<T>{
std::move(elements), ConstantSubscripts{folded->shape()}};
}
} else {
return std::nullopt;
}
} else {
return Constant<T>{*folded};
}
}
// Generalized reduction to an array of one dimension fewer (w/ DIM=)
// or to a scalar (w/o DIM=).
template <typename T, typename ACCUMULATOR, typename ARRAY>
static Constant<T> DoReduction(const Constant<ARRAY> &array,
std::optional<int> &dim, const Scalar<T> &identity,
ACCUMULATOR &accumulator) {
ConstantSubscripts at{array.lbounds()};
std::vector<typename Constant<T>::Element> elements;
ConstantSubscripts resultShape; // empty -> scalar
if (dim) { // DIM= is present, so result is an array
resultShape = array.shape();
resultShape.erase(resultShape.begin() + (*dim - 1));
ConstantSubscript dimExtent{array.shape().at(*dim - 1)};
ConstantSubscript &dimAt{at[*dim - 1]};
ConstantSubscript dimLbound{dimAt};
for (auto n{GetSize(resultShape)}; n-- > 0;
IncrementSubscripts(at, array.shape())) {
dimAt = dimLbound;
elements.push_back(identity);
for (ConstantSubscript j{0}; j < dimExtent; ++j, ++dimAt) {
accumulator(elements.back(), at);
}
}
} else { // no DIM=, result is scalar
elements.push_back(identity);
for (auto n{array.size()}; n-- > 0;
IncrementSubscripts(at, array.shape())) {
accumulator(elements.back(), at);
}
}
if constexpr (T::category == TypeCategory::Character) {
return {static_cast<ConstantSubscript>(identity.size()),
std::move(elements), std::move(resultShape)};
} else {
return {std::move(elements), std::move(resultShape)};
}
}
// MAXVAL & MINVAL
template <typename T>
static Expr<T> FoldMaxvalMinval(FoldingContext &context, FunctionRef<T> &&ref,
RelationalOperator opr, const Scalar<T> &identity) {
static_assert(T::category == TypeCategory::Integer ||
T::category == TypeCategory::Real ||
T::category == TypeCategory::Character);
using Element = Scalar<T>;
std::optional<int> dim;
if (std::optional<Constant<T>> array{
ProcessReductionArgs<T>(context, ref.arguments(), dim, identity,
/*ARRAY=*/0, /*DIM=*/1, /*MASK=*/2)}) {
auto accumulator{[&](Element &element, const ConstantSubscripts &at) {
Expr<LogicalResult> test{PackageRelation(opr,
Expr<T>{Constant<T>{array->At(at)}}, Expr<T>{Constant<T>{element}})};
auto folded{GetScalarConstantValue<LogicalResult>(
test.Rewrite(context, std::move(test)))};
CHECK(folded.has_value());
if (folded->IsTrue()) {
element = array->At(at);
}
}};
return Expr<T>{DoReduction<T>(*array, dim, identity, accumulator)};
}
return Expr<T>{std::move(ref)};
}
// PRODUCT
template <typename T>
static Expr<T> FoldProduct(
FoldingContext &context, FunctionRef<T> &&ref, Scalar<T> identity) {
static_assert(T::category == TypeCategory::Integer ||
T::category == TypeCategory::Real ||
T::category == TypeCategory::Complex);
using Element = typename Constant<T>::Element;
std::optional<int> dim;
if (std::optional<Constant<T>> array{
ProcessReductionArgs<T>(context, ref.arguments(), dim, identity,
/*ARRAY=*/0, /*DIM=*/1, /*MASK=*/2)}) {
bool overflow{false};
auto accumulator{[&](Element &element, const ConstantSubscripts &at) {
if constexpr (T::category == TypeCategory::Integer) {
auto prod{element.MultiplySigned(array->At(at))};
overflow |= prod.SignedMultiplicationOverflowed();
element = prod.lower;
} else { // Real & Complex
auto prod{element.Multiply(array->At(at))};
overflow |= prod.flags.test(RealFlag::Overflow);
element = prod.value;
}
}};
if (overflow) {
context.messages().Say(
"PRODUCT() of %s data overflowed"_en_US, T::AsFortran());
} else {
return Expr<T>{DoReduction<T>(*array, dim, identity, accumulator)};
}
}
return Expr<T>{std::move(ref)};
}
// SUM
template <typename T>
static Expr<T> FoldSum(FoldingContext &context, FunctionRef<T> &&ref) {
static_assert(T::category == TypeCategory::Integer ||
T::category == TypeCategory::Real ||
T::category == TypeCategory::Complex);
using Element = typename Constant<T>::Element;
std::optional<int> dim;
Element identity{}, correction{};
if (std::optional<Constant<T>> array{
ProcessReductionArgs<T>(context, ref.arguments(), dim, identity,
/*ARRAY=*/0, /*DIM=*/1, /*MASK=*/2)}) {
bool overflow{false};
auto accumulator{[&](Element &element, const ConstantSubscripts &at) {
if constexpr (T::category == TypeCategory::Integer) {
auto sum{element.AddSigned(array->At(at))};
overflow |= sum.overflow;
element = sum.value;
} else { // Real & Complex: use Kahan summation
auto next{array->At(at).Add(correction)};
overflow |= next.flags.test(RealFlag::Overflow);
auto sum{element.Add(next.value)};
overflow |= sum.flags.test(RealFlag::Overflow);
// correction = (sum - element) - next; algebraically zero
correction =
sum.value.Subtract(element).value.Subtract(next.value).value;
element = sum.value;
}
}};
if (overflow) {
context.messages().Say(
"SUM() of %s data overflowed"_en_US, T::AsFortran());
} else {
return Expr<T>{DoReduction<T>(*array, dim, identity, accumulator)};
}
}
return Expr<T>{std::move(ref)};
}
} // namespace Fortran::evaluate
#endif // FORTRAN_EVALUATE_FOLD_REDUCTION_H_