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//===- EraseUnusedOperandsAndResults.cpp ----------------------------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
#include "mlir/Dialect/Linalg/IR/Linalg.h"
using namespace mlir;
using namespace mlir::linalg;
/// Return `true` if the `result` of an operation `genericOp` is dead.
static bool isResultValueDead(linalg::GenericOp genericOp, OpResult result) {
if (!result.use_empty())
return false;
// If out operand not used in payload, we can drop it.
OpOperand *outputOpOperand =
genericOp.getDpsInitOperand(result.getResultNumber());
if (!genericOp.payloadUsesValueFromOperand(outputOpOperand))
return true;
// The out operand that is part of a payload can be dropped if
// these conditions are met:
// - Result from out operand is dead.
// - User of arg is yield.
// - outArg data is not being used by other outArgs.
// Check block arg and cycle from out operand has a single use.
BlockArgument outputArg =
genericOp.getRegionOutputArgs()[result.getResultNumber()];
if (!outputArg.hasOneUse())
return false;
Operation *argUserOp = *outputArg.user_begin();
// Check argUser has no other use.
if (!argUserOp->use_empty())
return false;
// Check that argUser is a yield.
auto yieldOp = dyn_cast<linalg::YieldOp>(argUserOp);
if (!yieldOp)
return false;
// Check outArg data is not being used by other outArgs.
if (yieldOp.getOperand(result.getResultNumber()) != outputArg)
return false;
return true;
}
namespace {
struct DeduplicateAndRemoveDeadOperandsAndResults
: public OpRewritePattern<GenericOp> {
DeduplicateAndRemoveDeadOperandsAndResults(MLIRContext *ctx,
bool removeOutputs)
: OpRewritePattern<GenericOp>(ctx), removeOutputs(removeOutputs) {}
LogicalResult matchAndRewrite(GenericOp genericOp,
PatternRewriter &rewriter) const override {
// Create a map from argument position in the original op to the argument
// position in the new op. If the argument is dropped it wont have an entry.
SmallVector<OpOperand *> droppedOpOperands;
// Information needed to build the new op.
SmallVector<Value> newInputOperands, newOutputOperands;
SmallVector<AffineMap> newIndexingMaps;
// Gather information about duplicate input operands.
llvm::SmallDenseMap<unsigned, unsigned> origInsToNewInsPos =
deduplicateInputOperands(genericOp, droppedOpOperands, newInputOperands,
newIndexingMaps);
// Gather information about the dropped outputs.
llvm::SmallDenseMap<unsigned, unsigned> origOutsToNewOutsPos =
deduplicateOutputOperands(genericOp, droppedOpOperands,
newOutputOperands, newIndexingMaps);
// Check if there is any change to operands.
if (newInputOperands.size() + newOutputOperands.size() ==
genericOp->getNumOperands())
return failure();
// Create the new op with the body being empty.
Location loc = genericOp.getLoc();
SmallVector<Type> newResultTypes;
for (Value v : newOutputOperands)
if (isa<TensorType>(v.getType()))
newResultTypes.push_back(v.getType());
auto newOp = rewriter.create<GenericOp>(
loc, newResultTypes, newInputOperands, newOutputOperands,
rewriter.getAffineMapArrayAttr(newIndexingMaps),
genericOp.getIteratorTypes(), genericOp.getDocAttr(),
genericOp.getLibraryCallAttr(),
[](OpBuilder & /*builder*/, Location /*loc*/, ValueRange /*args*/) {
return;
});
// Copy over unknown attributes. They might be load bearing for some flow.
ArrayRef<StringRef> odsAttrs = genericOp.getAttributeNames();
for (NamedAttribute kv : genericOp->getAttrs())
if (!llvm::is_contained(odsAttrs, kv.getName().getValue()))
newOp->setAttr(kv.getName(), kv.getValue());
// Fix up the payload of the canonicalized operation.
populateOpPayload(genericOp, newOp, origInsToNewInsPos,
origOutsToNewOutsPos, rewriter);
// Replace all live uses of the op.
SmallVector<Value> replacementsVals(genericOp->getNumResults(), nullptr);
for (const auto &result : llvm::enumerate(genericOp.getResults())) {
auto it = origOutsToNewOutsPos.find(result.index());
if (it == origOutsToNewOutsPos.end())
continue;
replacementsVals[result.index()] = newOp.getResult(it->second);
}
rewriter.replaceOp(genericOp, replacementsVals);
return success();
}
private:
/// If unset, outputs are not modified by this pattern.
bool removeOutputs;
// Deduplicate input operands, and return the
// - Mapping from operand position in the original op, to operand position in
// the canonicalized op.
// - The preserved input operands list (by reference).
llvm::SmallDenseMap<unsigned, unsigned>
deduplicateInputOperands(GenericOp genericOp,
SmallVector<OpOperand *> &droppedOpOperands,
SmallVector<Value> &newInputOperands,
SmallVector<AffineMap> &newIndexingMaps) const {
llvm::SmallDenseMap<unsigned, unsigned> origToNewPos;
llvm::SmallDenseMap<std::pair<Value, AffineMap>, unsigned> dedupedInputs;
for (const auto &en : llvm::enumerate(genericOp.getDpsInputOperands())) {
OpOperand *inputOpOperand = en.value();
// Check if operand is dead and if dropping the indexing map makes the
// loops to shape computation invalid.
if (!genericOp.payloadUsesValueFromOperand(inputOpOperand)) {
// Add the current operands to the list of potentially droppable
// operands. If it cannot be dropped, this needs to be popped back.
droppedOpOperands.push_back(inputOpOperand);
if (genericOp.canOpOperandsBeDropped(droppedOpOperands))
continue;
droppedOpOperands.pop_back();
}
// Check if this operand is a duplicate.
AffineMap indexingMap = genericOp.getMatchingIndexingMap(inputOpOperand);
auto it = dedupedInputs.find(
std::make_pair(inputOpOperand->get(), indexingMap));
if (it != dedupedInputs.end()) {
origToNewPos[en.index()] = it->second;
droppedOpOperands.push_back(inputOpOperand);
continue;
}
// This is a preserved argument.
origToNewPos[en.index()] = newInputOperands.size();
dedupedInputs[{inputOpOperand->get(), indexingMap}] =
newInputOperands.size();
newInputOperands.push_back(inputOpOperand->get());
newIndexingMaps.push_back(indexingMap);
}
return origToNewPos;
}
// Deduplicate output operands, and return the
// - Mapping from operand position in the original op, to operand position in
// the canonicalized op.
// - The preserved output operands list (by reference).
llvm::SmallDenseMap<unsigned, unsigned>
deduplicateOutputOperands(GenericOp genericOp,
SmallVector<OpOperand *> &droppedOpOperands,
SmallVector<Value> &newOutputOperands,
SmallVector<AffineMap> &newIndexingMaps) const {
llvm::SmallDenseMap<unsigned, unsigned> origToNewPos;
llvm::SmallDenseMap<std::tuple<Value, AffineMap, Value>, unsigned>
dedupedOutpts;
// If the op doesn't have tensor semantics or outputs should not be removed,
// keep all the outputs as preserved.
if (!genericOp.hasTensorSemantics() || !removeOutputs) {
for (const auto &en : llvm::enumerate(genericOp.getDpsInitOperands())) {
origToNewPos[en.index()] = newOutputOperands.size();
newOutputOperands.push_back(en.value()->get());
newIndexingMaps.push_back(genericOp.getMatchingIndexingMap(en.value()));
}
return origToNewPos;
}
// Output argument can be dropped if the result has
// - no users, and
// - it is not used in the payload, and
// - the corresponding indexing maps are not needed for loop bound
// computation.
auto yieldOp = cast<YieldOp>(genericOp.getBody()->getTerminator());
for (const auto &outputOpOperand :
llvm::enumerate(genericOp.getDpsInitOperands())) {
OpResult result = genericOp.getTiedOpResult(outputOpOperand.value());
AffineMap indexingMap =
genericOp.getMatchingIndexingMap(outputOpOperand.value());
auto key = std::make_tuple(outputOpOperand.value()->get(), indexingMap,
yieldOp->getOperand(outputOpOperand.index()));
if (isResultValueDead(genericOp, result)) {
// Check if the opoperand can be dropped without affecting loop
// bound computation. Add the operand to the list of dropped op
// operand for checking. If it cannot be dropped, need to pop the
// value back.
droppedOpOperands.push_back(outputOpOperand.value());
if (genericOp.canOpOperandsBeDropped(droppedOpOperands)) {
continue;
}
droppedOpOperands.pop_back();
}
if (!genericOp.payloadUsesValueFromOperand(outputOpOperand.value())) {
// The out operand can also be dropped if it is computed redundantly
// by another result, the conditions for that are
// - The same operand is used as the out operand
// - The same indexing map is used
// - The same yield value is used.
auto it = dedupedOutpts.find(key);
if (it != dedupedOutpts.end()) {
origToNewPos[outputOpOperand.index()] = it->second;
droppedOpOperands.push_back(outputOpOperand.value());
continue;
}
}
origToNewPos[outputOpOperand.index()] = newOutputOperands.size();
dedupedOutpts[key] = newOutputOperands.size();
newOutputOperands.push_back(outputOpOperand.value()->get());
newIndexingMaps.push_back(
genericOp.getMatchingIndexingMap(outputOpOperand.value()));
}
return origToNewPos;
}
// Populate the body of the canonicalized operation.
void populateOpPayload(
GenericOp genericOp, GenericOp newOp,
const llvm::SmallDenseMap<unsigned, unsigned> &origInsToNewInsPos,
const llvm::SmallDenseMap<unsigned, unsigned> &origOutsToNewOutsPos,
PatternRewriter &rewriter) const {
// Merge the body of the original op with the new op.
Block *newOpBlock = &newOp.getRegion().front();
assert(newOpBlock->empty() && "expected new op to have an empty payload");
Block *origOpBlock = &genericOp.getRegion().front();
SmallVector<Value> replacements(origOpBlock->getNumArguments(), nullptr);
// Replace all arguments in the original op, with arguments from the
// canonicalized op.
auto updateReplacements =
[&](OpOperandVector &origOperands, OpOperandVector &newOperands,
const llvm::SmallDenseMap<unsigned, unsigned> &map) {
for (const auto &origOperand : llvm::enumerate(origOperands)) {
auto it = map.find(origOperand.index());
if (it == map.end())
continue;
OpOperand *newOperand = newOperands[it->second];
replacements[origOperand.value()->getOperandNumber()] =
newOpBlock->getArgument(newOperand->getOperandNumber());
}
};
OpOperandVector origInputOperands = genericOp.getDpsInputOperands();
OpOperandVector newInputOperands = newOp.getDpsInputOperands();
updateReplacements(origInputOperands, newInputOperands, origInsToNewInsPos);
OpOperandVector origOutputOperands = genericOp.getDpsInitOperands();
OpOperandVector newOutputOperands = newOp.getDpsInitOperands();
updateReplacements(origOutputOperands, newOutputOperands,
origOutsToNewOutsPos);
// Drop the unused yield args.
if (newOp.getNumDpsInits() != genericOp.getNumDpsInits()) {
OpBuilder::InsertionGuard g(rewriter);
YieldOp origYieldOp = cast<YieldOp>(origOpBlock->getTerminator());
rewriter.setInsertionPoint(origYieldOp);
SmallVector<Value> newYieldVals(newOp.getNumDpsInits(), nullptr);
for (const auto &yieldOpOperands :
llvm::enumerate(origYieldOp.getValues())) {
auto it = origOutsToNewOutsPos.find(yieldOpOperands.index());
if (it == origOutsToNewOutsPos.end())
continue;
newYieldVals[it->second] = yieldOpOperands.value();
}
rewriter.replaceOpWithNewOp<YieldOp>(origYieldOp, newYieldVals);
}
rewriter.mergeBlocks(origOpBlock, newOpBlock, replacements);
}
};
/// Remove unused cycles.
/// We can remove unused cycle within a payload of generic region
/// if these conditions are met:
/// - Result from out operand is dead.
/// - Block arg from out operand has a single use in the %cycle
/// instruction.
/// - Cycle has a single use and it is in yield.
struct RemoveUnusedCycleInGenericOp : public OpRewritePattern<GenericOp> {
using OpRewritePattern<GenericOp>::OpRewritePattern;
LogicalResult matchAndRewrite(GenericOp genericOp,
PatternRewriter &rewriter) const override {
// If the op doesnt have tensor semantics, preserve the outputs as is.
if (!genericOp.hasTensorSemantics())
return failure();
bool hasRemovedCycles = false;
// Iterate over output operands and remove any unused cycles.
for (const auto &outputOpOperand :
llvm::enumerate(genericOp.getDpsInitOperands())) {
// Check that result from out operand is dead.
Value result = genericOp.getResult(outputOpOperand.index());
if (!result.use_empty())
continue;
// Check that outputArg has one use in cycle.
BlockArgument outputArg =
genericOp.getRegionOutputArgs()[outputOpOperand.index()];
if (!outputArg.hasOneUse())
continue;
// Check cycle has at most one use.
Operation *cycleOp = *outputArg.user_begin();
if (!cycleOp->hasOneUse())
continue;
// Check that the cycleUser is a yield.
Operation *cycleUserOp = *cycleOp->user_begin();
if (!isa<linalg::YieldOp>(cycleUserOp))
continue;
// Check that argIndex matches yieldIndex, else data is being used.
if (cycleUserOp->getOperand(outputOpOperand.index()) !=
cycleOp->getResult(0))
continue;
// Directly replace the cycle with the blockArg such that
// Deduplicate pattern can eliminate it along with unused yield.
rewriter.replaceOp(cycleOp, outputArg);
rewriter.updateRootInPlace(genericOp, [] {});
hasRemovedCycles = true;
}
if (hasRemovedCycles) {
return success();
}
return failure();
}
};
/// Fold uses of duplicate inputs in the body of a linalg.generic. E.g.:
/// ```
/// linalg.generic ins(%a, %b, %a, %b) outs(%a)
/// ^bb0(%in0, %in1, %in2, %in3, %out1)
/// ```
/// Assuming that all %a and %b have the same index map:
/// * All uses of %in0 and %in2 are replaced with %out1
/// * All uses of %in1 are replaced with %in3
/// This pattern can enable additional canonicalizations: In the above example,
/// %in0, %in1 and %in3 have no uses anymore and their corresponding operands
/// can be folded away. This pattern does not modify uses of output block args.
struct FoldDuplicateInputBbArgs : public OpRewritePattern<GenericOp> {
using OpRewritePattern<GenericOp>::OpRewritePattern;
LogicalResult matchAndRewrite(GenericOp genericOp,
PatternRewriter &rewriter) const override {
// Find replacement bbArgs for all input bbArg.
DenseMap<int, int> replacements;
for (int i = 0; i < genericOp.getNumDpsInputs(); ++i) {
// Skip bbArgs that have no uses.
if (genericOp.getBody()->getArgument(i).getUses().empty())
continue;
// Find replacement bbArg. This can be an input or an output bbArg.
for (int j = genericOp->getNumOperands() - 1; j > i; --j) {
if (genericOp->getOperand(i) == genericOp->getOperand(j) &&
genericOp.getIndexingMapsArray()[i] ==
genericOp.getIndexingMapsArray()[j]) {
replacements[i] = j;
break;
}
}
}
// Stop here if no replacements were found.
if (replacements.empty())
return failure();
// Rewrite the op.
rewriter.updateRootInPlace(genericOp, [&]() {
for (auto [before, after] : replacements) {
BlockArgument bbArg = genericOp.getBody()->getArgument(before);
BlockArgument replacement = genericOp.getBody()->getArgument(after);
rewriter.replaceAllUsesWith(bbArg, replacement);
}
});
return success();
}
};
} // namespace
void mlir::linalg::populateEraseUnusedOperandsAndResultsPatterns(
RewritePatternSet &patterns) {
patterns.insert<DeduplicateAndRemoveDeadOperandsAndResults>(
patterns.getContext(), /*removeOutputs=*/true);
patterns.insert<RemoveUnusedCycleInGenericOp>(patterns.getContext());
}
void mlir::linalg::populateEraseUnnecessaryInputsPatterns(
RewritePatternSet &patterns) {
patterns.insert<DeduplicateAndRemoveDeadOperandsAndResults>(
patterns.getContext(), /*removeOutputs=*/false);
patterns.insert<FoldDuplicateInputBbArgs>(patterns.getContext());
}
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