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//===- Transforms.cpp - Implementation of the linalg Transformations ------===//
//
// Copyright 2019 The MLIR Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
//
// This file implements analyses and transformations for the linalg dialect.
//
//===----------------------------------------------------------------------===//
#include "linalg4/Transforms.h"
#include "linalg3/Intrinsics.h"
#include "linalg3/TensorOps.h"
#include "mlir/AffineOps/AffineOps.h"
#include "mlir/EDSC/Helpers.h"
#include "mlir/IR/OpImplementation.h"
#include "mlir/Transforms/LoopUtils.h"
using llvm::ArrayRef;
using llvm::SmallVector;
using namespace mlir;
using namespace mlir::edsc;
using namespace linalg;
using namespace linalg::intrinsics;
llvm::Optional<SmallVector<mlir::AffineForOp, 8>>
linalg::writeAsTiledLoops(Operation *op, ArrayRef<uint64_t> tileSizes) {
auto loops = writeAsLoops(op);
if (loops.hasValue())
return mlir::tile(*loops, tileSizes, loops->back());
return llvm::None;
}
void linalg::lowerToTiledLoops(mlir::Function f, ArrayRef<uint64_t> tileSizes) {
f.walk([tileSizes](Operation *op) {
if (writeAsTiledLoops(op, tileSizes).hasValue())
op->erase();
});
}
static bool isZeroIndex(Value *v) {
return isa_and_nonnull<ConstantIndexOp>(v->getDefiningOp()) &&
cast<ConstantIndexOp>(v->getDefiningOp()).getValue() == 0;
}
template <typename ConcreteOp>
static llvm::SmallVector<Value *, 4>
makeTiledRanges(TensorContractionBase<ConcreteOp> &contraction,
ArrayRef<Value *> allRanges, llvm::ArrayRef<Value *> ivs,
llvm::ArrayRef<Value *> tileSizes) {
assert(ivs.size() == tileSizes.size());
if (ivs.empty())
return RangeParts(allRanges).makeRanges();
auto *op = static_cast<ConcreteOp *>(&contraction);
RangeParts result(allRanges.size());
RangeParts rangeParts(allRanges);
for (auto map : op->loopsToOperandRangeMaps()) {
// 1. Take the first ivs results of the map, the other ones are not composed
// but merely copied over.
assert(map.getNumSymbols() == 0);
MLIRContext *context = ScopedContext::getContext();
unsigned numParallel = op->getNumParallelDims();
unsigned numReduction = op->getNumReductionDims();
if (ivs.size() < numParallel + numReduction) {
// Inject zeros in positions that are not tiled.
SmallVector<AffineExpr, 4> dimReplacements(numParallel + numReduction);
for (unsigned i = 0, e = numParallel + numReduction; i < e; ++i) {
dimReplacements[i] = (i < ivs.size())
? getAffineDimExpr(i, context)
: getAffineConstantExpr(0, context);
}
map = map.replaceDimsAndSymbols(dimReplacements, {}, ivs.size(), 0);
}
// 2. Apply the rewritten map to the ranges.
unsigned numDims = map.getNumDims();
for (auto en : llvm::enumerate(map.getResults())) {
auto index = en.index();
auto expr = en.value();
AffineMap exprMap = AffineMap::get(numDims, 0, expr);
ValueHandle offset(makeFoldedComposedAffineApply(exprMap, ivs));
// Offset is normally a function of loop induction variables.
// If it is 0, it must come from a dimension that was not tiled.
if (isZeroIndex(offset)) {
result.mins.push_back(rangeParts.mins[index]);
result.maxes.push_back(rangeParts.maxes[index]);
continue;
}
ValueHandle step(makeFoldedComposedAffineApply(exprMap, tileSizes));
ValueHandle min(rangeParts.mins[index]);
using edsc::op::operator+;
result.mins.push_back(min + offset);
// Ideally this should be:
// `min(rangeParts.max, rangeParts.min + offset + step)`
// but that breaks the current limitations of the affine dialect.
result.maxes.push_back(min + offset + step);
}
}
// Note that for the purpose of tiled ranges and views, the steps do not
// change in our representation.
result.steps = rangeParts.steps;
return result.makeRanges();
}
template <class ConcreteOp>
static SmallVector<Value *, 4>
makeTiledViews(linalg::TensorContractionBase<ConcreteOp> &contraction,
ArrayRef<Value *> ivs, ArrayRef<Value *> tileSizes) {
auto tiledRanges =
makeTiledRanges(contraction, getRanges(contraction), ivs, tileSizes);
SmallVector<Value *, 4> res;
unsigned currentRange = 0;
for (auto *in : contraction.getInputsAndOutputs()) {
unsigned runningSliceDim = 0;
auto *runningSlice = in;
assert(runningSlice->getType().template isa<ViewType>());
for (unsigned d = 0, e = getViewRank(runningSlice); d < e; ++d) {
auto *r = tiledRanges[currentRange++];
runningSlice = slice(runningSlice, r, runningSliceDim++).getValue();
}
res.push_back(runningSlice);
}
return res;
}
template <class ConcreteOp>
static SmallVector<mlir::AffineForOp, 8>
writeContractionAsTiledViews(TensorContractionBase<ConcreteOp> &contraction,
ArrayRef<Value *> tileSizes) {
assert(tileSizes.size() <=
contraction.getNumParallelDims() + contraction.getNumReductionDims());
auto *op = static_cast<ConcreteOp *>(&contraction);
mlir::OpBuilder builder(op->getOperation());
ScopedContext scope(builder, op->getLoc());
SmallVector<IndexHandle, 4> ivs(tileSizes.size());
auto pivs = IndexHandle::makeIndexHandlePointers(ivs);
// clang-format off
using linalg::common::LoopNestRangeBuilder;
auto ranges = makeGenericLoopRanges(operandRangesToLoopsMap(contraction),
getRanges(contraction), tileSizes);
linalg::common::LoopNestRangeBuilder(pivs, ranges)(
[&contraction, &tileSizes, &ivs]() {
SmallVector<Value *, 4> ivValues(ivs.begin(), ivs.end());
auto views = makeTiledViews(contraction, ivValues, tileSizes);
ScopedContext::getBuilder().create<ConcreteOp>(
ScopedContext::getLocation(), views);
});
// clang-format on
SmallVector<mlir::AffineForOp, 8> res;
res.reserve(ivs.size());
for (auto iv : ivs)
res.push_back(getForInductionVarOwner(iv.getValue()));
return res;
}
llvm::Optional<SmallVector<mlir::AffineForOp, 8>>
linalg::writeAsTiledViews(Operation *op, ArrayRef<Value *> tileSizes) {
if (auto matmulOp = dyn_cast<linalg::MatmulOp>(op)) {
return writeContractionAsTiledViews(matmulOp, tileSizes);
} else if (auto matvecOp = dyn_cast<linalg::MatvecOp>(op)) {
return writeContractionAsTiledViews(matvecOp, tileSizes);
} else if (auto dotOp = dyn_cast<linalg::DotOp>(op)) {
return writeContractionAsTiledViews(dotOp, tileSizes);
}
return llvm::None;
}
void linalg::lowerToTiledViews(mlir::Function f, ArrayRef<Value *> tileSizes) {
f.walk([tileSizes](Operation *op) {
if (auto matmulOp = dyn_cast<linalg::MatmulOp>(op)) {
writeAsTiledViews(matmulOp, tileSizes);
} else if (auto matvecOp = dyn_cast<linalg::MatvecOp>(op)) {
writeAsTiledViews(matvecOp, tileSizes);
} else if (auto dotOp = dyn_cast<linalg::DotOp>(op)) {
writeAsTiledViews(dotOp, tileSizes);
} else {
return;
}
op->erase();
});
}
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