River Riddle 3e98fbf4f5 [mlir] Refactor RewritePatternMatcher into a new PatternApplicator class.
This class enables for abstracting more of the details for the rewrite process, and will allow for clients to apply specific cost models to the pattern list. This allows for DialectConversion and the GreedyPatternRewriter to share the same underlying matcher implementation. This also simplifies the plumbing necessary to support dynamic patterns.

Differential Revision: https://reviews.llvm.org/D81985
2020-06-18 13:58:47 -07:00

238 lines
8.9 KiB
C++

//===- LinalgTransforms.cpp - Linalg transformations as patterns ----------===//
//
// 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 logic and helpers to expose Linalg transforms as rewrite
// patterns.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
#include "mlir/Dialect/Linalg/Analysis/DependenceAnalysis.h"
#include "mlir/Dialect/Linalg/IR/LinalgOps.h"
#include "mlir/Dialect/Linalg/Utils/Utils.h"
#include "mlir/Dialect/StandardOps/EDSC/Intrinsics.h"
#include "mlir/Dialect/Utils/StructuredOpsUtils.h"
#include "mlir/Dialect/Vector/EDSC/Intrinsics.h"
#include "mlir/Dialect/Vector/VectorOps.h"
#include "mlir/IR/AffineExpr.h"
#include "mlir/IR/Matchers.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Support/LLVM.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include <type_traits>
#define DEBUG_TYPE "linalg-transforms"
using namespace mlir;
using namespace mlir::edsc;
using namespace mlir::edsc::intrinsics;
using namespace mlir::linalg;
#define DBGS() (llvm::dbgs() << "[" DEBUG_TYPE << "]: ")
//===----------------------------------------------------------------------===//
// Transformations exposed as rewrite patterns.
//===----------------------------------------------------------------------===//
// Marker used as attribute name in generated Linalg rewriting transformations.
const StringLiteral mlir::linalg::LinalgTransforms::kLinalgTransformMarker =
"__internal_linalg_transform__";
mlir::linalg::LinalgMarker::LinalgMarker(ArrayRef<Identifier> matchDisjunction,
Optional<Identifier> replacement)
: matchDisjunction(matchDisjunction.begin(), matchDisjunction.end()),
replacement(replacement) {}
LogicalResult
mlir::linalg::LinalgMarker::checkAndNotify(PatternRewriter &rewriter,
Operation *op) const {
auto attr = op->template getAttrOfType<StringAttr>(
LinalgTransforms::kLinalgTransformMarker);
if (!attr) {
// 1. Has no marker case and matchDisjunction is empty.
if (matchDisjunction.empty())
return success();
// 2. Has no marker but was expecting a marker.
return rewriter.notifyMatchFailure(op, [&](Diagnostic &diag) {
diag << " does not have any marker from list: ";
interleaveComma(matchDisjunction, diag);
});
}
// 4. Match explicit marker.
for (auto marker : matchDisjunction)
if (attr.getValue() == marker)
return success();
// 5. Fail to match.
return rewriter.notifyMatchFailure(op, [&](Diagnostic &diag) {
diag << " does not have any marker from list: ";
interleaveComma(matchDisjunction, diag);
});
}
void mlir::linalg::LinalgMarker::replaceLinalgMarker(PatternRewriter &rewriter,
Operation *op) const {
if (replacement.hasValue())
op->setAttr(LinalgTransforms::kLinalgTransformMarker,
rewriter.getStringAttr(replacement.getValue()));
else
op->removeAttr(Identifier::get(LinalgTransforms::kLinalgTransformMarker,
rewriter.getContext()));
}
LinalgTilingOptions &
mlir::linalg::LinalgTilingOptions::setTileSizes(ArrayRef<int64_t> ts) {
SmallVector<int64_t, 4> tileSizes(ts.begin(), ts.end());
tileSizeComputationFunction = [tileSizes](OpBuilder &b, Operation *op) {
OpBuilder::InsertionGuard guard(b);
b.setInsertionPointToStart(
&op->getParentOfType<FuncOp>().getBody().front());
return llvm::to_vector<4>(map_range(tileSizes, [&](int64_t s) {
Value v = b.create<ConstantIndexOp>(op->getLoc(), s);
return v;
}));
};
return *this;
}
/// Linalg base tiling pattern.
mlir::linalg::LinalgBaseTilingPattern::LinalgBaseTilingPattern(
StringRef opName, MLIRContext *context, LinalgTilingOptions options,
LinalgMarker marker, PatternBenefit benefit)
: RewritePattern(opName, {}, benefit, context), marker(marker),
options(options) {}
LogicalResult mlir::linalg::LinalgBaseTilingPattern::matchAndRewrite(
Operation *op, PatternRewriter &rewriter) const {
LinalgOp linalgOp = dyn_cast<LinalgOp>(op);
if (!linalgOp)
return failure();
if (failed(marker.checkAndNotify(rewriter, linalgOp)))
return failure();
Optional<TiledLinalgOp> res = tileLinalgOp(rewriter, linalgOp, options);
if (!res)
return failure();
// New marker if specified.
marker.replaceLinalgMarker(rewriter, res->op.getOperation());
rewriter.eraseOp(op);
return success();
}
/// Linalg base interchange pattern.
mlir::linalg::LinalgBaseInterchangePattern::LinalgBaseInterchangePattern(
StringRef opName, MLIRContext *context,
ArrayRef<unsigned> interchangeVector, LinalgMarker marker,
PatternBenefit benefit)
: RewritePattern(opName, {}, benefit, context), marker(marker),
interchangeVector(interchangeVector.begin(), interchangeVector.end()) {}
LogicalResult mlir::linalg::LinalgBaseInterchangePattern::matchAndRewrite(
Operation *op, PatternRewriter &rewriter) const {
LinalgOp linalgOp = dyn_cast<LinalgOp>(op);
if (!linalgOp)
return failure();
if (failed(marker.checkAndNotify(rewriter, linalgOp)))
return failure();
if (failed(interchangeGenericLinalgOpPrecondition(op, interchangeVector)))
return failure();
// TODO: figure out how this interplays with named ops. In particular this
// should break the named op property.
rewriter.updateRootInPlace(op, [&]() {
interchange(linalgOp, interchangeVector);
// New marker if specified.
marker.replaceLinalgMarker(rewriter, op);
});
return success();
}
mlir::linalg::LinalgBasePromotionPattern::LinalgBasePromotionPattern(
StringRef opName, MLIRContext *context, LinalgPromotionOptions options,
LinalgMarker marker, PatternBenefit benefit)
: RewritePattern(opName, {}, benefit, context), marker(marker),
options(options) {}
LogicalResult mlir::linalg::LinalgBasePromotionPattern::matchAndRewrite(
Operation *op, PatternRewriter &rewriter) const {
if (failed(marker.checkAndNotify(rewriter, op)))
return failure();
if (failed(promoteSubviewsPrecondition(op, options)))
return failure();
// TODO: We cannot use root update here. This pattern is creating other ops,
// so if the promotion fails, those need to be cleaned up, which doesnt seem
// to be happening here. So to fail properly, we should be cloning the op and
// deleting the previous op. This needs more investigation.
rewriter.startRootUpdate(op);
Optional<LinalgOp> promotedOp = promoteSubViews(rewriter, op, options);
if (!promotedOp) {
rewriter.cancelRootUpdate(op);
return op->emitError("subview promotion failed");
}
rewriter.finalizeRootUpdate(op);
marker.replaceLinalgMarker(rewriter, op);
return success();
}
mlir::linalg::LinalgBaseVectorizationPattern::LinalgBaseVectorizationPattern(
StringRef opName, MLIRContext *context, LinalgMarker marker,
PatternBenefit benefit)
: RewritePattern(opName, {}, benefit, context), marker(marker) {}
LogicalResult mlir::linalg::LinalgBaseVectorizationPattern::matchAndRewrite(
Operation *op, PatternRewriter &rewriter) const {
LinalgOp linalgOp = dyn_cast<LinalgOp>(op);
if (!linalgOp)
return failure();
if (failed(marker.checkAndNotify(rewriter, linalgOp)))
return failure();
if (failed(vectorizeLinalgOpPrecondition(op)))
return failure();
vectorizeLinalgOp(rewriter, op);
rewriter.eraseOp(op);
return success();
}
LogicalResult mlir::linalg::applyStagedPatterns(
Operation *op, ArrayRef<OwningRewritePatternList> stage1Patterns,
const OwningRewritePatternList &stage2Patterns,
function_ref<LogicalResult(Operation *)> stage3Lambda) {
unsigned iteration = 0;
(void)iteration;
for (const auto &patterns : stage1Patterns) {
LLVM_DEBUG(DBGS() << "Before 1st stage, iter: " << ++iteration << "\n"
<< *op);
if (failed(applyPatternsAndFoldGreedily(op, patterns))) {
LLVM_DEBUG(DBGS() << "Underlying first stage rewrite did not converge");
return failure();
}
LLVM_DEBUG(DBGS() << "After 1st stage, iter: " << ++iteration << "\n"
<< *op);
if (failed(applyPatternsAndFoldGreedily(op, stage2Patterns))) {
LLVM_DEBUG(DBGS() << "Underlying 2nd stage rewrite did not converge");
return failure();
}
LLVM_DEBUG(DBGS() << "After 2nd stage, iter : " << iteration << "\n"
<< *op);
if (stage3Lambda) {
if (failed(stage3Lambda(op)))
return failure();
LLVM_DEBUG(DBGS() << "After 3rd stage, iter : " << iteration << "\n"
<< *op);
}
}
return success();
}