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llvm/mlir/lib/Dialect/Vector/Transforms/LowerVectorGather.cpp
Jakub Kuderski 72c662a47f [mlir][vector][NFC] Clean up vector gather lowering comments
These got relocated recently.

Reviewed By: antiagainst

Differential Revision: https://reviews.llvm.org/D147257
2023-03-30 17:13:14 -04:00

174 lines
6.6 KiB
C++

//===- LowerVectorGather.cpp - Lower 'vector.gather' operation ------------===//
//
// 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 target-independent rewrites and utilities to lower the
// 'vector.gather' operation.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/Arith/Utils/Utils.h"
#include "mlir/Dialect/Linalg/IR/Linalg.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Utils/IndexingUtils.h"
#include "mlir/Dialect/Utils/StructuredOpsUtils.h"
#include "mlir/Dialect/Vector/IR/VectorOps.h"
#include "mlir/Dialect/Vector/Transforms/LoweringPatterns.h"
#include "mlir/Dialect/Vector/Utils/VectorUtils.h"
#include "mlir/IR/BuiltinAttributeInterfaces.h"
#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/ImplicitLocOpBuilder.h"
#include "mlir/IR/Location.h"
#include "mlir/IR/Matchers.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/TypeUtilities.h"
#include "mlir/Interfaces/VectorInterfaces.h"
#include "mlir/Support/LogicalResult.h"
#define DEBUG_TYPE "vector-broadcast-lowering"
using namespace mlir;
using namespace mlir::vector;
namespace {
/// Flattens 2 or more dimensional `vector.gather` ops by unrolling the
/// outermost dimension. For example:
/// ```
/// %g = vector.gather %base[%c0][%v], %mask, %pass_thru :
/// ... into vector<2x3xf32>
///
/// ==>
///
/// %0 = arith.constant dense<0.0> : vector<2x3xf32>
/// %g0 = vector.gather %base[%c0][%v0], %mask0, %pass_thru0 : ...
/// %1 = vector.insert %g0, %0 [0] : vector<3xf32> into vector<2x3xf32>
/// %g1 = vector.gather %base[%c0][%v1], %mask1, %pass_thru1 : ...
/// %g = vector.insert %g1, %1 [1] : vector<3xf32> into vector<2x3xf32>
/// ```
///
/// When applied exhaustively, this will produce a sequence of 1-d gather ops.
struct FlattenGather : OpRewritePattern<vector::GatherOp> {
using OpRewritePattern::OpRewritePattern;
LogicalResult matchAndRewrite(vector::GatherOp op,
PatternRewriter &rewriter) const override {
VectorType resultTy = op.getType();
if (resultTy.getRank() < 2)
return rewriter.notifyMatchFailure(op, "already flat");
Location loc = op.getLoc();
Value indexVec = op.getIndexVec();
Value maskVec = op.getMask();
Value passThruVec = op.getPassThru();
Value result = rewriter.create<arith::ConstantOp>(
loc, resultTy, rewriter.getZeroAttr(resultTy));
Type subTy = VectorType::get(resultTy.getShape().drop_front(),
resultTy.getElementType());
for (int64_t i = 0, e = resultTy.getShape().front(); i < e; ++i) {
int64_t thisIdx[1] = {i};
Value indexSubVec =
rewriter.create<vector::ExtractOp>(loc, indexVec, thisIdx);
Value maskSubVec =
rewriter.create<vector::ExtractOp>(loc, maskVec, thisIdx);
Value passThruSubVec =
rewriter.create<vector::ExtractOp>(loc, passThruVec, thisIdx);
Value subGather = rewriter.create<vector::GatherOp>(
loc, subTy, op.getBase(), op.getIndices(), indexSubVec, maskSubVec,
passThruSubVec);
result =
rewriter.create<vector::InsertOp>(loc, subGather, result, thisIdx);
}
rewriter.replaceOp(op, result);
return success();
}
};
/// Turns 1-d `vector.gather` into a scalarized sequence of `vector.loads` or
/// `tensor.extract`s. To avoid out-of-bounds memory accesses, these
/// loads/extracts are made conditional using `scf.if` ops.
struct Gather1DToConditionalLoads : OpRewritePattern<vector::GatherOp> {
using OpRewritePattern::OpRewritePattern;
LogicalResult matchAndRewrite(vector::GatherOp op,
PatternRewriter &rewriter) const override {
VectorType resultTy = op.getType();
if (resultTy.getRank() != 1)
return rewriter.notifyMatchFailure(op, "unsupported rank");
Location loc = op.getLoc();
Type elemTy = resultTy.getElementType();
// Vector type with a single element. Used to generate `vector.loads`.
VectorType elemVecTy = VectorType::get({1}, elemTy);
Value condMask = op.getMask();
Value base = op.getBase();
Value indexVec = rewriter.createOrFold<arith::IndexCastOp>(
loc, op.getIndexVectorType().clone(rewriter.getIndexType()),
op.getIndexVec());
auto baseOffsets = llvm::to_vector(op.getIndices());
Value lastBaseOffset = baseOffsets.back();
Value result = op.getPassThru();
// Emit a conditional access for each vector element.
for (int64_t i = 0, e = resultTy.getNumElements(); i < e; ++i) {
int64_t thisIdx[1] = {i};
Value condition =
rewriter.create<vector::ExtractOp>(loc, condMask, thisIdx);
Value index = rewriter.create<vector::ExtractOp>(loc, indexVec, thisIdx);
baseOffsets.back() =
rewriter.createOrFold<arith::AddIOp>(loc, lastBaseOffset, index);
auto loadBuilder = [&](OpBuilder &b, Location loc) {
Value extracted;
if (isa<MemRefType>(base.getType())) {
// `vector.load` does not support scalar result; emit a vector load
// and extract the single result instead.
Value load =
b.create<vector::LoadOp>(loc, elemVecTy, base, baseOffsets);
int64_t zeroIdx[1] = {0};
extracted = b.create<vector::ExtractOp>(loc, load, zeroIdx);
} else {
extracted = b.create<tensor::ExtractOp>(loc, base, baseOffsets);
}
Value newResult =
b.create<vector::InsertOp>(loc, extracted, result, thisIdx);
b.create<scf::YieldOp>(loc, newResult);
};
auto passThruBuilder = [result](OpBuilder &b, Location loc) {
b.create<scf::YieldOp>(loc, result);
};
result =
rewriter
.create<scf::IfOp>(loc, condition, /*thenBuilder=*/loadBuilder,
/*elseBuilder=*/passThruBuilder)
.getResult(0);
}
rewriter.replaceOp(op, result);
return success();
}
};
} // namespace
void mlir::vector::populateVectorGatherLoweringPatterns(
RewritePatternSet &patterns, PatternBenefit benefit) {
patterns.add<FlattenGather, Gather1DToConditionalLoads>(patterns.getContext(),
benefit);
}