46 lines
1.7 KiB
C++
46 lines
1.7 KiB
C++
//===- SwapExtractSliceWithFillPatterns.cpp -------------------------------===//
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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/Dialect/Linalg/Transforms/Transforms.h"
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#include "mlir/IR/PatternMatch.h"
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using namespace mlir;
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using namespace mlir::linalg;
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/// swaps:
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/// `tensor.extract_slice(linalg.fill(%cst, %init))`
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/// with:
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/// `linalg.fill(%cst, tensor.extract_slice(%init))`
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///
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/// when the linalg.fill op have no other users.
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/// This helps to reduce the fill footprint.
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struct SwapExtractSliceOfFill final
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: public OpRewritePattern<tensor::ExtractSliceOp> {
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using OpRewritePattern::OpRewritePattern;
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LogicalResult matchAndRewrite(tensor::ExtractSliceOp extractOp,
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PatternRewriter &rewriter) const override {
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auto fillOp = extractOp.getSource().getDefiningOp<FillOp>();
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if (!fillOp || !fillOp->hasOneUse())
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return failure();
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auto newExtractOp = tensor::ExtractSliceOp::create(
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rewriter, extractOp.getLoc(), extractOp.getType(),
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fillOp.getOutputs()[0], extractOp.getMixedOffsets(),
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extractOp.getMixedSizes(), extractOp.getMixedStrides());
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rewriter.replaceOpWithNewOp<FillOp>(extractOp, fillOp.getInputs(),
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ValueRange{newExtractOp.getResult()});
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return success();
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}
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};
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void mlir::linalg::populateSwapExtractSliceWithFillPatterns(
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RewritePatternSet &patterns) {
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patterns.add<SwapExtractSliceOfFill>(patterns.getContext());
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}
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