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//===- AffineExpandIndexOpsAsAffine.cpp - Expand index ops to apply pass --===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// This file implements a pass to expand affine index ops into one or more more
// fundamental operations.
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Affine/Transforms/Passes.h"
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Affine/Transforms/Transforms.h"
#include "mlir/Dialect/Affine/Utils.h"
#include "mlir/Dialect/Arith/Utils/Utils.h"
#include "mlir/Dialect/UB/IR/UBOps.h"
#include "mlir/Dialect/Utils/IndexingUtils.h"
#include "mlir/Dialect/Vector/IR/VectorOps.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
namespace mlir {
namespace affine {
#define GEN_PASS_DEF_AFFINEEXPANDINDEXOPSASAFFINE
#include "mlir/Dialect/Affine/Transforms/Passes.h.inc"
} // namespace affine
} // namespace mlir
using namespace mlir;
using namespace mlir::affine;
namespace {
/// Lowers `affine.delinearize_index` into a sequence of division and remainder
/// operations via affine.apply. For vector types, unrolls to per-element
/// scalar affine.apply operations.
struct LowerDelinearizeIndexOps
: public OpRewritePattern<AffineDelinearizeIndexOp> {
using OpRewritePattern<AffineDelinearizeIndexOp>::OpRewritePattern;
LogicalResult matchAndRewrite(AffineDelinearizeIndexOp op,
PatternRewriter &rewriter) const override {
Location loc = op.getLoc();
Value linearIndex = op.getLinearIndex();
auto vecTy = dyn_cast<VectorType>(linearIndex.getType());
// Scalar case: use the existing affine lowering path.
if (!vecTy) {
FailureOr<SmallVector<Value>> multiIndex =
delinearizeIndex(rewriter, loc, linearIndex, op.getEffectiveBasis(),
/*hasOuterBound=*/false);
if (failed(multiIndex))
return failure();
rewriter.replaceOp(op, *multiIndex);
return success();
}
// Vector case: unroll to per-element scalar affine.apply operations
// using StaticTileOffsetRange for multi-dimensional vector support.
if (vecTy.isScalable())
return rewriter.notifyMatchFailure(op, "scalable vectors not supported");
unsigned numResults = op.getNumResults();
ArrayRef<int64_t> shape = vecTy.getShape();
SmallVector<int64_t> tileShape(shape.size(), 1);
SmallVector<Value> resultVecs(numResults);
Value poison = ub::PoisonOp::create(rewriter, loc, vecTy);
for (unsigned r = 0; r < numResults; ++r)
resultVecs[r] = poison;
for (SmallVector<int64_t> pos : StaticTileOffsetRange(shape, tileShape)) {
Value scalar = vector::ExtractOp::create(rewriter, loc, linearIndex, pos);
FailureOr<SmallVector<Value>> scalarResults =
delinearizeIndex(rewriter, loc, scalar, op.getEffectiveBasis(),
/*hasOuterBound=*/false);
if (failed(scalarResults))
return failure();
for (unsigned r = 0; r < numResults; ++r)
resultVecs[r] = vector::InsertOp::create(
rewriter, loc, (*scalarResults)[r], resultVecs[r], pos);
}
rewriter.replaceOp(op, resultVecs);
return success();
}
};
/// Lowers `affine.linearize_index` into a sequence of multiplications and
/// additions via affine.apply. For vector types, unrolls to per-element
/// scalar affine.apply operations.
struct LowerLinearizeIndexOps final : OpRewritePattern<AffineLinearizeIndexOp> {
using OpRewritePattern::OpRewritePattern;
LogicalResult matchAndRewrite(AffineLinearizeIndexOp op,
PatternRewriter &rewriter) const override {
Location loc = op.getLoc();
auto vecTy = dyn_cast<VectorType>(op.getLinearIndex().getType());
// Scalar case: use the existing affine lowering path.
if (!vecTy) {
// Should be folded away, included here for safety.
if (op.getMultiIndex().empty()) {
rewriter.replaceOpWithNewOp<arith::ConstantIndexOp>(op, 0);
return success();
}
SmallVector<OpFoldResult> multiIndex =
getAsOpFoldResult(op.getMultiIndex());
OpFoldResult linearIndex =
linearizeIndex(rewriter, loc, multiIndex, op.getMixedBasis());
Value linearIndexValue =
getValueOrCreateConstantIntOp(rewriter, loc, linearIndex);
rewriter.replaceOp(op, linearIndexValue);
return success();
}
// Vector case: unroll to per-element scalar affine.apply operations
// using StaticTileOffsetRange for multi-dimensional vector support.
if (vecTy.isScalable())
return rewriter.notifyMatchFailure(op, "scalable vectors not supported");
ArrayRef<int64_t> shape = vecTy.getShape();
SmallVector<int64_t> tileShape(shape.size(), 1);
ValueRange multiIndex = op.getMultiIndex();
Value result = ub::PoisonOp::create(rewriter, loc, vecTy);
for (SmallVector<int64_t> pos : StaticTileOffsetRange(shape, tileShape)) {
SmallVector<OpFoldResult> scalarIndices;
for (Value vec : multiIndex)
scalarIndices.push_back(
vector::ExtractOp::create(rewriter, loc, vec, pos).getResult());
OpFoldResult linearIndex =
linearizeIndex(rewriter, loc, scalarIndices, op.getMixedBasis());
Value scalarResult =
getValueOrCreateConstantIntOp(rewriter, loc, linearIndex);
result =
vector::InsertOp::create(rewriter, loc, scalarResult, result, pos);
}
rewriter.replaceOp(op, result);
return success();
}
};
class ExpandAffineIndexOpsAsAffinePass
: public affine::impl::AffineExpandIndexOpsAsAffineBase<
ExpandAffineIndexOpsAsAffinePass> {
public:
ExpandAffineIndexOpsAsAffinePass() = default;
void runOnOperation() override {
MLIRContext *context = &getContext();
RewritePatternSet patterns(context);
populateAffineExpandIndexOpsAsAffinePatterns(patterns);
if (failed(applyPatternsGreedily(getOperation(), std::move(patterns))))
return signalPassFailure();
}
};
} // namespace
void mlir::affine::populateAffineExpandIndexOpsAsAffinePatterns(
RewritePatternSet &patterns) {
patterns.insert<LowerDelinearizeIndexOps, LowerLinearizeIndexOps>(
patterns.getContext());
}
std::unique_ptr<Pass> mlir::affine::createAffineExpandIndexOpsAsAffinePass() {
return std::make_unique<ExpandAffineIndexOpsAsAffinePass>();
}