58ceae9561
FuncOp has been moved to the `func` namespace for a little over a month, the using directive can be dropped now.
92 lines
3.5 KiB
C++
92 lines
3.5 KiB
C++
//===- Generalization.cpp - linalg named ops to generic ops --------------===//
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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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//
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// This file implements the Linalg generalization pass. It converts named
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// Linalg ops to linalg.generic ops.
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//
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//===----------------------------------------------------------------------===//
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#include "PassDetail.h"
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#include "mlir/Dialect/Linalg/IR/Linalg.h"
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#include "mlir/Dialect/Linalg/Passes.h"
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#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
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#include "mlir/IR/AffineMap.h"
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#include "mlir/IR/Attributes.h"
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#include "mlir/IR/Builders.h"
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#include "mlir/IR/ImplicitLocOpBuilder.h"
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#include "mlir/IR/PatternMatch.h"
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#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
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#include "llvm/ADT/SmallVector.h"
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#include "llvm/Support/Debug.h"
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#define DEBUG_TYPE "linalg-generalization"
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using namespace mlir;
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using namespace mlir::linalg;
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static LogicalResult generalizeNamedOpPrecondition(LinalgOp linalgOp) {
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// Check if the operation is a LinalgOp but not a GenericOp.
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if (isa<GenericOp>(linalgOp))
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return failure();
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// Check if the operation has a region builder.
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if (!linalgOp.getRegionBuilder())
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return failure();
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return success();
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}
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FailureOr<GenericOp> mlir::linalg::generalizeNamedOp(RewriterBase &rewriter,
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LinalgOp linalgOp) {
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if (failed(generalizeNamedOpPrecondition(linalgOp)))
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return rewriter.notifyMatchFailure(linalgOp, "preconditions not met");
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SmallVector<Value> inputOperands = linalgOp.getInputOperands();
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SmallVector<Value> outputOperands = linalgOp.getOutputOperands();
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SmallVector<AffineMap> indexingMaps = linalgOp.getIndexingMaps();
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SmallVector<StringRef> iterators = llvm::to_vector<4>(
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linalgOp.iterator_types().getAsValueRange<StringAttr>());
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SmallVector<RankedTensorType> resultTypes = linalgOp.getOutputTensorTypes();
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SmallVector<Type> types(resultTypes.begin(), resultTypes.end());
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// All named ops have a region attached that can be inlined.
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assert(linalgOp->getNumRegions() == 1 &&
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"expect named op to have one region attached");
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GenericOp genericOp =
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rewriter.create<GenericOp>(linalgOp.getLoc(), types, inputOperands,
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outputOperands, indexingMaps, iterators);
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rewriter.inlineRegionBefore(linalgOp->getRegion(0), genericOp.region(),
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genericOp.region().begin());
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rewriter.replaceOp(linalgOp, genericOp->getResults());
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return genericOp;
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}
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namespace {
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struct LinalgGeneralizationPass
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: public LinalgGeneralizationBase<LinalgGeneralizationPass> {
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void runOnOperation() override;
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};
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} // namespace
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void LinalgGeneralizationPass::runOnOperation() {
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func::FuncOp func = getOperation();
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RewritePatternSet patterns(&getContext());
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populateLinalgNamedOpsGeneralizationPatterns(patterns);
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(void)applyPatternsAndFoldGreedily(func.getBody(), std::move(patterns));
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}
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void mlir::linalg::populateLinalgNamedOpsGeneralizationPatterns(
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RewritePatternSet &patterns, const LinalgTransformationFilter &marker) {
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patterns.add<LinalgGeneralizationPattern>(patterns.getContext(), marker);
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}
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std::unique_ptr<OperationPass<func::FuncOp>>
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mlir::createLinalgGeneralizationPass() {
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return std::make_unique<LinalgGeneralizationPass>();
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}
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