llvm-project/mlir/lib/Dialect/Tensor/Transforms/SplitPaddingPatterns.cpp

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3.7 KiB
C++

//===- SplitPaddingPatterns.cpp - Splitting tensor.pad Op -----------------===//
//
// 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 patterns to wrap a tensor.pad op with an scf.if op
/// to separate the cases where we don't need padding (all pad sizes are
/// actually zeros) and where we indeed need padding.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Tensor/Transforms/Transforms.h"
#include "mlir/Dialect/Utils/StaticValueUtils.h"
#include "mlir/IR/PatternMatch.h"
#include "llvm/Support/Debug.h"
#define DEBUG_TYPE "mlir-tensor-split-padding"
using namespace mlir;
/// Returns true if the the given `attrOrValue` is a constant zero.
static bool isZero(OpFoldResult attrOrValue) {
if (Optional<int64_t> val = getConstantIntValue(attrOrValue))
return *val == 0;
return false;
}
/// Gets the given `attrOrValue` as a Value by creating constant ops for
/// attributes.
static Value getAsValue(OpFoldResult attrOrValue, OpBuilder &builder,
Location loc) {
if (Value val = attrOrValue.dyn_cast<Value>())
return val;
auto attr = attrOrValue.get<Attribute>().cast<IntegerAttr>();
return builder.create<arith::ConstantIndexOp>(loc, attr.getInt());
}
namespace {
struct SplitPadding final : public OpRewritePattern<tensor::PadOp> {
using OpRewritePattern::OpRewritePattern;
LogicalResult matchAndRewrite(tensor::PadOp padOp,
PatternRewriter &rewriter) const override {
// Avoid infinitely applying this pattern.
if (padOp->getParentOfType<scf::IfOp>())
return failure();
// If all padding sizes are zero, we don't need to do anything.
SmallVector<OpFoldResult> lowPads = padOp.getMixedLowPad();
SmallVector<OpFoldResult> highPads = padOp.getMixedHighPad();
if (llvm::all_of(lowPads, isZero) && llvm::all_of(highPads, isZero))
return failure();
// Build the condition for the scf.if op: all pad sizes are zero.
Location loc = padOp.getLoc();
Value cstZero = rewriter.create<arith::ConstantIndexOp>(loc, 0);
SmallVector<Value> eqZeroCmpVals;
for (OpFoldResult pad : llvm::concat<OpFoldResult>(lowPads, highPads)) {
if (!isZero(pad))
eqZeroCmpVals.push_back(rewriter.create<arith::CmpIOp>(
loc, arith::CmpIPredicate::eq, getAsValue(pad, rewriter, loc),
cstZero));
}
Value ifCond = eqZeroCmpVals.front();
for (Value cmp : llvm::makeArrayRef(eqZeroCmpVals).drop_front())
ifCond = rewriter.create<arith::AndIOp>(loc, ifCond, cmp);
// Build the scf.if op itself. For the "then" branch, we can elide the
// padding. For the "else" branch, we retain the clone op.
auto thenBuilder = [&padOp](OpBuilder &builder, Location loc) {
builder.create<scf::YieldOp>(loc, padOp.getSource());
};
auto elseBuilder = [&padOp](OpBuilder &builder, Location loc) {
Operation *newOp = builder.clone(*padOp);
builder.create<scf::YieldOp>(loc, newOp->getResults());
};
rewriter.replaceOpWithNewOp<scf::IfOp>(padOp, padOp.getType(), ifCond,
thenBuilder, elseBuilder);
return success();
}
};
} // namespace
void tensor::populateSplitPaddingPatterns(RewritePatternSet &patterns,
PatternBenefit baseBenefit) {
patterns.add<SplitPadding>(patterns.getContext(), baseBenefit);
}