213 lines
8.3 KiB
C++
213 lines
8.3 KiB
C++
//===-- MathToLibm.cpp - conversion from Math to libm calls ---------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Conversion/MathToLibm/MathToLibm.h"
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#include "mlir/Dialect/Arith/IR/Arith.h"
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
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#include "mlir/Dialect/Math/IR/Math.h"
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#include "mlir/Dialect/Utils/IndexingUtils.h"
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#include "mlir/Dialect/Vector/IR/VectorOps.h"
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#include "mlir/IR/BuiltinDialect.h"
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#include "mlir/IR/PatternMatch.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Transforms/DialectConversion.h"
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namespace mlir {
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#define GEN_PASS_DEF_CONVERTMATHTOLIBM
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#include "mlir/Conversion/Passes.h.inc"
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} // namespace mlir
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using namespace mlir;
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namespace {
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// Pattern to convert vector operations to scalar operations. This is needed as
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// libm calls require scalars.
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template <typename Op>
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struct VecOpToScalarOp : public OpRewritePattern<Op> {
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public:
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using OpRewritePattern<Op>::OpRewritePattern;
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LogicalResult matchAndRewrite(Op op, PatternRewriter &rewriter) const final;
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};
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// Pattern to promote an op of a smaller floating point type to F32.
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template <typename Op>
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struct PromoteOpToF32 : public OpRewritePattern<Op> {
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public:
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using OpRewritePattern<Op>::OpRewritePattern;
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LogicalResult matchAndRewrite(Op op, PatternRewriter &rewriter) const final;
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};
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// Pattern to convert scalar math operations to calls to libm functions.
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// Additionally the libm function signatures are declared.
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template <typename Op>
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struct ScalarOpToLibmCall : public OpRewritePattern<Op> {
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public:
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using OpRewritePattern<Op>::OpRewritePattern;
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ScalarOpToLibmCall(MLIRContext *context, StringRef floatFunc,
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StringRef doubleFunc)
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: OpRewritePattern<Op>(context), floatFunc(floatFunc),
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doubleFunc(doubleFunc){};
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LogicalResult matchAndRewrite(Op op, PatternRewriter &rewriter) const final;
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private:
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std::string floatFunc, doubleFunc;
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};
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template <typename OpTy>
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void populatePatternsForOp(RewritePatternSet &patterns, MLIRContext *ctx,
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StringRef floatFunc, StringRef doubleFunc) {
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patterns.add<VecOpToScalarOp<OpTy>, PromoteOpToF32<OpTy>>(ctx);
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patterns.add<ScalarOpToLibmCall<OpTy>>(ctx, floatFunc, doubleFunc);
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}
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} // namespace
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template <typename Op>
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LogicalResult
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VecOpToScalarOp<Op>::matchAndRewrite(Op op, PatternRewriter &rewriter) const {
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auto opType = op.getType();
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auto loc = op.getLoc();
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auto vecType = dyn_cast<VectorType>(opType);
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if (!vecType)
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return failure();
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if (!vecType.hasRank())
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return failure();
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auto shape = vecType.getShape();
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int64_t numElements = vecType.getNumElements();
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Value result = rewriter.create<arith::ConstantOp>(
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loc, DenseElementsAttr::get(
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vecType, FloatAttr::get(vecType.getElementType(), 0.0)));
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SmallVector<int64_t> strides = computeStrides(shape);
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for (auto linearIndex = 0; linearIndex < numElements; ++linearIndex) {
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SmallVector<int64_t> positions = delinearize(linearIndex, strides);
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SmallVector<Value> operands;
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for (auto input : op->getOperands())
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operands.push_back(
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rewriter.create<vector::ExtractOp>(loc, input, positions));
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Value scalarOp =
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rewriter.create<Op>(loc, vecType.getElementType(), operands);
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result =
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rewriter.create<vector::InsertOp>(loc, scalarOp, result, positions);
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}
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rewriter.replaceOp(op, {result});
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return success();
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}
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template <typename Op>
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LogicalResult
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PromoteOpToF32<Op>::matchAndRewrite(Op op, PatternRewriter &rewriter) const {
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auto opType = op.getType();
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if (!isa<Float16Type, BFloat16Type>(opType))
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return failure();
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auto loc = op.getLoc();
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auto f32 = rewriter.getF32Type();
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auto extendedOperands = llvm::to_vector(
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llvm::map_range(op->getOperands(), [&](Value operand) -> Value {
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return rewriter.create<arith::ExtFOp>(loc, f32, operand);
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}));
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auto newOp = rewriter.create<Op>(loc, f32, extendedOperands);
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rewriter.replaceOpWithNewOp<arith::TruncFOp>(op, opType, newOp);
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return success();
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}
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template <typename Op>
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LogicalResult
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ScalarOpToLibmCall<Op>::matchAndRewrite(Op op,
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PatternRewriter &rewriter) const {
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auto module = SymbolTable::getNearestSymbolTable(op);
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auto type = op.getType();
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if (!isa<Float32Type, Float64Type>(type))
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return failure();
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auto name = type.getIntOrFloatBitWidth() == 64 ? doubleFunc : floatFunc;
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auto opFunc = dyn_cast_or_null<SymbolOpInterface>(
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SymbolTable::lookupSymbolIn(module, name));
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// Forward declare function if it hasn't already been
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if (!opFunc) {
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OpBuilder::InsertionGuard guard(rewriter);
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rewriter.setInsertionPointToStart(&module->getRegion(0).front());
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auto opFunctionTy = FunctionType::get(
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rewriter.getContext(), op->getOperandTypes(), op->getResultTypes());
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opFunc = rewriter.create<func::FuncOp>(rewriter.getUnknownLoc(), name,
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opFunctionTy);
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opFunc.setPrivate();
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// By definition Math dialect operations imply LLVM's "readnone"
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// function attribute, so we can set it here to provide more
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// optimization opportunities (e.g. LICM) for backends targeting LLVM IR.
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// This will have to be changed, when strict FP behavior is supported
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// by Math dialect.
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opFunc->setAttr(LLVM::LLVMDialect::getReadnoneAttrName(),
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UnitAttr::get(rewriter.getContext()));
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}
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assert(isa<FunctionOpInterface>(SymbolTable::lookupSymbolIn(module, name)));
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rewriter.replaceOpWithNewOp<func::CallOp>(op, name, op.getType(),
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op->getOperands());
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return success();
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}
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void mlir::populateMathToLibmConversionPatterns(RewritePatternSet &patterns) {
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MLIRContext *ctx = patterns.getContext();
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populatePatternsForOp<math::AcosOp>(patterns, ctx, "acosf", "acos");
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populatePatternsForOp<math::AcoshOp>(patterns, ctx, "acoshf", "acosh");
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populatePatternsForOp<math::AsinOp>(patterns, ctx, "asinf", "asin");
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populatePatternsForOp<math::AsinhOp>(patterns, ctx, "asinhf", "asinh");
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populatePatternsForOp<math::Atan2Op>(patterns, ctx, "atan2f", "atan2");
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populatePatternsForOp<math::AtanOp>(patterns, ctx, "atanf", "atan");
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populatePatternsForOp<math::AtanhOp>(patterns, ctx, "atanhf", "atanh");
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populatePatternsForOp<math::CbrtOp>(patterns, ctx, "cbrtf", "cbrt");
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populatePatternsForOp<math::CeilOp>(patterns, ctx, "ceilf", "ceil");
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populatePatternsForOp<math::CosOp>(patterns, ctx, "cosf", "cos");
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populatePatternsForOp<math::CoshOp>(patterns, ctx, "coshf", "cosh");
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populatePatternsForOp<math::ErfOp>(patterns, ctx, "erff", "erf");
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populatePatternsForOp<math::ExpM1Op>(patterns, ctx, "expm1f", "expm1");
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populatePatternsForOp<math::FloorOp>(patterns, ctx, "floorf", "floor");
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populatePatternsForOp<math::Log1pOp>(patterns, ctx, "log1pf", "log1p");
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populatePatternsForOp<math::RoundEvenOp>(patterns, ctx, "roundevenf",
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"roundeven");
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populatePatternsForOp<math::RoundOp>(patterns, ctx, "roundf", "round");
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populatePatternsForOp<math::SinOp>(patterns, ctx, "sinf", "sin");
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populatePatternsForOp<math::SinhOp>(patterns, ctx, "sinhf", "sinh");
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populatePatternsForOp<math::TanOp>(patterns, ctx, "tanf", "tan");
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populatePatternsForOp<math::TanhOp>(patterns, ctx, "tanhf", "tanh");
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populatePatternsForOp<math::TruncOp>(patterns, ctx, "truncf", "trunc");
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}
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namespace {
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struct ConvertMathToLibmPass
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: public impl::ConvertMathToLibmBase<ConvertMathToLibmPass> {
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void runOnOperation() override;
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};
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} // namespace
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void ConvertMathToLibmPass::runOnOperation() {
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auto module = getOperation();
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RewritePatternSet patterns(&getContext());
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populateMathToLibmConversionPatterns(patterns);
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ConversionTarget target(getContext());
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target.addLegalDialect<arith::ArithDialect, BuiltinDialect, func::FuncDialect,
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vector::VectorDialect>();
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target.addIllegalDialect<math::MathDialect>();
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if (failed(applyPartialConversion(module, target, std::move(patterns))))
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signalPassFailure();
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}
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std::unique_ptr<OperationPass<ModuleOp>> mlir::createConvertMathToLibmPass() {
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return std::make_unique<ConvertMathToLibmPass>();
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}
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