blob: dedc3b3f3020144270e236396f14f2bcb42e2bab [file] [log] [blame]
//===- LowerVectorBroadcast.cpp - Lower 'vector.broadcast' 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.broadcast' operation.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/UB/IR/UBOps.h"
#include "mlir/Dialect/Vector/IR/VectorOps.h"
#include "mlir/Dialect/Vector/Transforms/LoweringPatterns.h"
#include "mlir/Dialect/Vector/Transforms/VectorRewritePatterns.h"
#include "mlir/Dialect/Vector/Utils/VectorUtils.h"
#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/Location.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/TypeUtilities.h"
#define DEBUG_TYPE "vector-broadcast-lowering"
using namespace mlir;
using namespace mlir::vector;
namespace {
/// Convert a vector.broadcast with a vector operand to a lower rank
/// vector.broadcast. vector.broadcast with a scalar operand is expected to be
/// convertible to the lower level target dialect (LLVM, SPIR-V, etc.) directly.
class BroadcastOpLowering : public OpRewritePattern<vector::BroadcastOp> {
public:
using OpRewritePattern::OpRewritePattern;
LogicalResult matchAndRewrite(vector::BroadcastOp op,
PatternRewriter &rewriter) const override {
auto loc = op.getLoc();
VectorType dstType = op.getResultVectorType();
VectorType srcType = dyn_cast<VectorType>(op.getSourceType());
Type eltType = dstType.getElementType();
// A broadcast from a scalar is considered to be in the lowered form.
if (!srcType)
return rewriter.notifyMatchFailure(
op, "broadcast from scalar already in lowered form");
// Determine rank of source and destination.
int64_t srcRank = srcType.getRank();
int64_t dstRank = dstType.getRank();
// Here we are broadcasting to a rank-1 vector. Ensure that the source is a
// scalar.
if (srcRank <= 1 && dstRank == 1) {
SmallVector<int64_t> fullRankPosition(srcRank, 0);
Value ext = vector::ExtractOp::create(rewriter, loc, op.getSource(),
fullRankPosition);
assert(!isa<VectorType>(ext.getType()) && "expected scalar");
rewriter.replaceOpWithNewOp<vector::BroadcastOp>(op, dstType, ext);
return success();
}
// Duplicate this rank.
// For example:
// %x = broadcast %y : k-D to n-D, k < n
// becomes:
// %b = broadcast %y : k-D to (n-1)-D
// %x = [%b,%b,%b,%b] : n-D
// becomes:
// %b = [%y,%y] : (n-1)-D
// %x = [%b,%b,%b,%b] : n-D
if (srcRank < dstRank) {
// Duplication.
VectorType resType = VectorType::Builder(dstType).dropDim(0);
Value bcst =
vector::BroadcastOp::create(rewriter, loc, resType, op.getSource());
Value result = ub::PoisonOp::create(rewriter, loc, dstType);
for (int64_t d = 0, dim = dstType.getDimSize(0); d < dim; ++d)
result = vector::InsertOp::create(rewriter, loc, bcst, result, d);
rewriter.replaceOp(op, result);
return success();
}
// Find non-matching dimension, if any.
assert(srcRank == dstRank);
int64_t m = -1;
for (int64_t r = 0; r < dstRank; r++)
if (srcType.getDimSize(r) != dstType.getDimSize(r)) {
m = r;
break;
}
// All trailing dimensions are the same. Simply pass through.
if (m == -1) {
rewriter.replaceOp(op, op.getSource());
return success();
}
// Any non-matching dimension forces a stretch along this rank.
// For example:
// %x = broadcast %y : vector<4x1x2xf32> to vector<4x2x2xf32>
// becomes:
// %a = broadcast %y[0] : vector<1x2xf32> to vector<2x2xf32>
// %b = broadcast %y[1] : vector<1x2xf32> to vector<2x2xf32>
// %c = broadcast %y[2] : vector<1x2xf32> to vector<2x2xf32>
// %d = broadcast %y[3] : vector<1x2xf32> to vector<2x2xf32>
// %x = [%a,%b,%c,%d]
// becomes:
// %u = broadcast %y[0][0] : vector<2xf32> to vector <2x2xf32>
// %v = broadcast %y[1][0] : vector<2xf32> to vector <2x2xf32>
// %a = [%u, %v]
// ..
// %x = [%a,%b,%c,%d]
VectorType resType =
VectorType::get(dstType.getShape().drop_front(), eltType,
dstType.getScalableDims().drop_front());
Value result = ub::PoisonOp::create(rewriter, loc, dstType);
if (m == 0) {
// Stetch at start.
Value ext = vector::ExtractOp::create(rewriter, loc, op.getSource(), 0);
Value bcst = vector::BroadcastOp::create(rewriter, loc, resType, ext);
for (int64_t d = 0, dim = dstType.getDimSize(0); d < dim; ++d)
result = vector::InsertOp::create(rewriter, loc, bcst, result, d);
} else {
// Stetch not at start.
if (dstType.getScalableDims()[0]) {
// TODO: For scalable vectors we should emit an scf.for loop.
return failure();
}
for (int64_t d = 0, dim = dstType.getDimSize(0); d < dim; ++d) {
Value ext = vector::ExtractOp::create(rewriter, loc, op.getSource(), d);
Value bcst = vector::BroadcastOp::create(rewriter, loc, resType, ext);
result = vector::InsertOp::create(rewriter, loc, bcst, result, d);
}
}
rewriter.replaceOp(op, result);
return success();
}
};
} // namespace
void mlir::vector::populateVectorBroadcastLoweringPatterns(
RewritePatternSet &patterns, PatternBenefit benefit) {
patterns.add<BroadcastOpLowering>(patterns.getContext(), benefit);
}