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//===-- MathToLibm.cpp - conversion from Math to libm calls ---------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
#include "mlir/Conversion/MathToLibm/MathToLibm.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/Dialect/Math/IR/Math.h"
#include "mlir/Dialect/Utils/IndexingUtils.h"
#include "mlir/Dialect/Vector/IR/VectorOps.h"
#include "mlir/IR/BuiltinDialect.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/DialectConversion.h"
namespace mlir {
#define GEN_PASS_DEF_CONVERTMATHTOLIBM
#include "mlir/Conversion/Passes.h.inc"
} // namespace mlir
using namespace mlir;
namespace {
// Pattern to convert vector operations to scalar operations. This is needed as
// libm calls require scalars.
template <typename Op>
struct VecOpToScalarOp : public OpRewritePattern<Op> {
public:
using OpRewritePattern<Op>::OpRewritePattern;
LogicalResult matchAndRewrite(Op op, PatternRewriter &rewriter) const final;
};
// Pattern to promote an op of a smaller floating point type to F32.
template <typename Op>
struct PromoteOpToF32 : public OpRewritePattern<Op> {
public:
using OpRewritePattern<Op>::OpRewritePattern;
LogicalResult matchAndRewrite(Op op, PatternRewriter &rewriter) const final;
};
// Pattern to convert scalar math operations to calls to libm functions.
// Additionally the libm function signatures are declared.
template <typename Op>
struct ScalarOpToLibmCall : public OpRewritePattern<Op> {
public:
using OpRewritePattern<Op>::OpRewritePattern;
ScalarOpToLibmCall<Op>(MLIRContext *context, StringRef floatFunc,
StringRef doubleFunc)
: OpRewritePattern<Op>(context), floatFunc(floatFunc),
doubleFunc(doubleFunc){};
LogicalResult matchAndRewrite(Op op, PatternRewriter &rewriter) const final;
private:
std::string floatFunc, doubleFunc;
};
template <typename OpTy>
void populatePatternsForOp(RewritePatternSet &patterns, MLIRContext *ctx,
StringRef floatFunc, StringRef doubleFunc) {
patterns.add<VecOpToScalarOp<OpTy>, PromoteOpToF32<OpTy>>(ctx);
patterns.add<ScalarOpToLibmCall<OpTy>>(ctx, floatFunc, doubleFunc);
}
} // namespace
template <typename Op>
LogicalResult
VecOpToScalarOp<Op>::matchAndRewrite(Op op, PatternRewriter &rewriter) const {
auto opType = op.getType();
auto loc = op.getLoc();
auto vecType = dyn_cast<VectorType>(opType);
if (!vecType)
return failure();
if (!vecType.hasRank())
return failure();
auto shape = vecType.getShape();
int64_t numElements = vecType.getNumElements();
Value result = rewriter.create<arith::ConstantOp>(
loc, DenseElementsAttr::get(
vecType, FloatAttr::get(vecType.getElementType(), 0.0)));
SmallVector<int64_t> strides = computeStrides(shape);
for (auto linearIndex = 0; linearIndex < numElements; ++linearIndex) {
SmallVector<int64_t> positions = delinearize(linearIndex, strides);
SmallVector<Value> operands;
for (auto input : op->getOperands())
operands.push_back(
rewriter.create<vector::ExtractOp>(loc, input, positions));
Value scalarOp =
rewriter.create<Op>(loc, vecType.getElementType(), operands);
result =
rewriter.create<vector::InsertOp>(loc, scalarOp, result, positions);
}
rewriter.replaceOp(op, {result});
return success();
}
template <typename Op>
LogicalResult
PromoteOpToF32<Op>::matchAndRewrite(Op op, PatternRewriter &rewriter) const {
auto opType = op.getType();
if (!isa<Float16Type, BFloat16Type>(opType))
return failure();
auto loc = op.getLoc();
auto f32 = rewriter.getF32Type();
auto extendedOperands = llvm::to_vector(
llvm::map_range(op->getOperands(), [&](Value operand) -> Value {
return rewriter.create<arith::ExtFOp>(loc, f32, operand);
}));
auto newOp = rewriter.create<Op>(loc, f32, extendedOperands);
rewriter.replaceOpWithNewOp<arith::TruncFOp>(op, opType, newOp);
return success();
}
template <typename Op>
LogicalResult
ScalarOpToLibmCall<Op>::matchAndRewrite(Op op,
PatternRewriter &rewriter) const {
auto module = SymbolTable::getNearestSymbolTable(op);
auto type = op.getType();
if (!isa<Float32Type, Float64Type>(type))
return failure();
auto name = type.getIntOrFloatBitWidth() == 64 ? doubleFunc : floatFunc;
auto opFunc = dyn_cast_or_null<SymbolOpInterface>(
SymbolTable::lookupSymbolIn(module, name));
// Forward declare function if it hasn't already been
if (!opFunc) {
OpBuilder::InsertionGuard guard(rewriter);
rewriter.setInsertionPointToStart(&module->getRegion(0).front());
auto opFunctionTy = FunctionType::get(
rewriter.getContext(), op->getOperandTypes(), op->getResultTypes());
opFunc = rewriter.create<func::FuncOp>(rewriter.getUnknownLoc(), name,
opFunctionTy);
opFunc.setPrivate();
// By definition Math dialect operations imply LLVM's "readnone"
// function attribute, so we can set it here to provide more
// optimization opportunities (e.g. LICM) for backends targeting LLVM IR.
// This will have to be changed, when strict FP behavior is supported
// by Math dialect.
opFunc->setAttr(LLVM::LLVMDialect::getReadnoneAttrName(),
UnitAttr::get(rewriter.getContext()));
}
assert(isa<FunctionOpInterface>(SymbolTable::lookupSymbolIn(module, name)));
rewriter.replaceOpWithNewOp<func::CallOp>(op, name, op.getType(),
op->getOperands());
return success();
}
void mlir::populateMathToLibmConversionPatterns(RewritePatternSet &patterns) {
MLIRContext *ctx = patterns.getContext();
populatePatternsForOp<math::Atan2Op>(patterns, ctx, "atan2f", "atan2");
populatePatternsForOp<math::AtanOp>(patterns, ctx, "atanf", "atan");
populatePatternsForOp<math::CbrtOp>(patterns, ctx, "cbrtf", "cbrt");
populatePatternsForOp<math::CeilOp>(patterns, ctx, "ceilf", "ceil");
populatePatternsForOp<math::CosOp>(patterns, ctx, "cosf", "cos");
populatePatternsForOp<math::ErfOp>(patterns, ctx, "erff", "erf");
populatePatternsForOp<math::ExpM1Op>(patterns, ctx, "expm1f", "expm1");
populatePatternsForOp<math::FloorOp>(patterns, ctx, "floorf", "floor");
populatePatternsForOp<math::Log1pOp>(patterns, ctx, "log1pf", "log1p");
populatePatternsForOp<math::RoundEvenOp>(patterns, ctx, "roundevenf",
"roundeven");
populatePatternsForOp<math::RoundOp>(patterns, ctx, "roundf", "round");
populatePatternsForOp<math::SinOp>(patterns, ctx, "sinf", "sin");
populatePatternsForOp<math::TanOp>(patterns, ctx, "tanf", "tan");
populatePatternsForOp<math::TanhOp>(patterns, ctx, "tanhf", "tanh");
populatePatternsForOp<math::TruncOp>(patterns, ctx, "truncf", "trunc");
}
namespace {
struct ConvertMathToLibmPass
: public impl::ConvertMathToLibmBase<ConvertMathToLibmPass> {
void runOnOperation() override;
};
} // namespace
void ConvertMathToLibmPass::runOnOperation() {
auto module = getOperation();
RewritePatternSet patterns(&getContext());
populateMathToLibmConversionPatterns(patterns);
ConversionTarget target(getContext());
target.addLegalDialect<arith::ArithDialect, BuiltinDialect, func::FuncDialect,
vector::VectorDialect>();
target.addIllegalDialect<math::MathDialect>();
if (failed(applyPartialConversion(module, target, std::move(patterns))))
signalPassFailure();
}
std::unique_ptr<OperationPass<ModuleOp>> mlir::createConvertMathToLibmPass() {
return std::make_unique<ConvertMathToLibmPass>();
}
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