GreedyPatternRewriteDriver.cpp
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//===- GreedyPatternRewriteDriver.cpp - A greedy rewriter -----------------===//
//
// 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 mlir::applyPatternsAndFoldGreedily.
//
//===----------------------------------------------------------------------===//
#include "mlir/IR/PatternMatch.h"
#include "mlir/Interfaces/SideEffectInterfaces.h"
#include "mlir/Transforms/FoldUtils.h"
#include "mlir/Transforms/RegionUtils.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
using namespace mlir;
#define DEBUG_TYPE "pattern-matcher"
/// The max number of iterations scanning for pattern match.
static unsigned maxPatternMatchIterations = 10;
//===----------------------------------------------------------------------===//
// GreedyPatternRewriteDriver
//===----------------------------------------------------------------------===//
namespace {
/// This is a worklist-driven driver for the PatternMatcher, which repeatedly
/// applies the locally optimal patterns in a roughly "bottom up" way.
class GreedyPatternRewriteDriver : public PatternRewriter {
public:
explicit GreedyPatternRewriteDriver(MLIRContext *ctx,
const OwningRewritePatternList &patterns)
: PatternRewriter(ctx), matcher(patterns), folder(ctx) {
worklist.reserve(64);
// Apply a simple cost model based solely on pattern benefit.
matcher.applyDefaultCostModel();
}
bool simplify(MutableArrayRef<Region> regions, int maxIterations);
void addToWorklist(Operation *op) {
// Check to see if the worklist already contains this op.
if (worklistMap.count(op))
return;
worklistMap[op] = worklist.size();
worklist.push_back(op);
}
Operation *popFromWorklist() {
auto *op = worklist.back();
worklist.pop_back();
// This operation is no longer in the worklist, keep worklistMap up to date.
if (op)
worklistMap.erase(op);
return op;
}
/// If the specified operation is in the worklist, remove it. If not, this is
/// a no-op.
void removeFromWorklist(Operation *op) {
auto it = worklistMap.find(op);
if (it != worklistMap.end()) {
assert(worklist[it->second] == op && "malformed worklist data structure");
worklist[it->second] = nullptr;
worklistMap.erase(it);
}
}
// These are hooks implemented for PatternRewriter.
protected:
// Implement the hook for inserting operations, and make sure that newly
// inserted ops are added to the worklist for processing.
void notifyOperationInserted(Operation *op) override { addToWorklist(op); }
// If an operation is about to be removed, make sure it is not in our
// worklist anymore because we'd get dangling references to it.
void notifyOperationRemoved(Operation *op) override {
addToWorklist(op->getOperands());
op->walk([this](Operation *operation) {
removeFromWorklist(operation);
folder.notifyRemoval(operation);
});
}
// When the root of a pattern is about to be replaced, it can trigger
// simplifications to its users - make sure to add them to the worklist
// before the root is changed.
void notifyRootReplaced(Operation *op) override {
for (auto result : op->getResults())
for (auto *user : result.getUsers())
addToWorklist(user);
}
private:
// Look over the provided operands for any defining operations that should
// be re-added to the worklist. This function should be called when an
// operation is modified or removed, as it may trigger further
// simplifications.
template <typename Operands> void addToWorklist(Operands &&operands) {
for (Value operand : operands) {
// If the use count of this operand is now < 2, we re-add the defining
// operation to the worklist.
// TODO: This is based on the fact that zero use operations
// may be deleted, and that single use values often have more
// canonicalization opportunities.
if (!operand.use_empty() && !operand.hasOneUse())
continue;
if (auto *defInst = operand.getDefiningOp())
addToWorklist(defInst);
}
}
/// The low-level pattern applicator.
PatternApplicator matcher;
/// The worklist for this transformation keeps track of the operations that
/// need to be revisited, plus their index in the worklist. This allows us to
/// efficiently remove operations from the worklist when they are erased, even
/// if they aren't the root of a pattern.
std::vector<Operation *> worklist;
DenseMap<Operation *, unsigned> worklistMap;
/// Non-pattern based folder for operations.
OperationFolder folder;
};
} // end anonymous namespace
/// Performs the rewrites while folding and erasing any dead ops. Returns true
/// if the rewrite converges in `maxIterations`.
bool GreedyPatternRewriteDriver::simplify(MutableArrayRef<Region> regions,
int maxIterations) {
// Add the given operation to the worklist.
auto collectOps = [this](Operation *op) { addToWorklist(op); };
bool changed = false;
int i = 0;
do {
// Add all nested operations to the worklist.
for (auto ®ion : regions)
region.walk(collectOps);
// These are scratch vectors used in the folding loop below.
SmallVector<Value, 8> originalOperands, resultValues;
changed = false;
while (!worklist.empty()) {
auto *op = popFromWorklist();
// Nulls get added to the worklist when operations are removed, ignore
// them.
if (op == nullptr)
continue;
// If the operation is trivially dead - remove it.
if (isOpTriviallyDead(op)) {
notifyOperationRemoved(op);
op->erase();
changed = true;
continue;
}
// Collects all the operands and result uses of the given `op` into work
// list. Also remove `op` and nested ops from worklist.
originalOperands.assign(op->operand_begin(), op->operand_end());
auto preReplaceAction = [&](Operation *op) {
// Add the operands to the worklist for visitation.
addToWorklist(originalOperands);
// Add all the users of the result to the worklist so we make sure
// to revisit them.
for (auto result : op->getResults())
for (auto *userOp : result.getUsers())
addToWorklist(userOp);
notifyOperationRemoved(op);
};
// Try to fold this op.
bool inPlaceUpdate;
if ((succeeded(folder.tryToFold(op, collectOps, preReplaceAction,
&inPlaceUpdate)))) {
changed = true;
if (!inPlaceUpdate)
continue;
}
// Try to match one of the patterns. The rewriter is automatically
// notified of any necessary changes, so there is nothing else to do here.
changed |= succeeded(matcher.matchAndRewrite(op, *this));
}
// After applying patterns, make sure that the CFG of each of the regions is
// kept up to date.
if (succeeded(simplifyRegions(regions))) {
folder.clear();
changed = true;
}
} while (changed && ++i < maxIterations);
// Whether the rewrite converges, i.e. wasn't changed in the last iteration.
return !changed;
}
/// Rewrite the regions of the specified operation, which must be isolated from
/// above, by repeatedly applying the highest benefit patterns in a greedy
/// work-list driven manner. Return success if no more patterns can be matched
/// in the result operation regions. Note: This does not apply patterns to the
/// top-level operation itself.
///
LogicalResult
mlir::applyPatternsAndFoldGreedily(Operation *op,
const OwningRewritePatternList &patterns) {
return applyPatternsAndFoldGreedily(op->getRegions(), patterns);
}
/// Rewrite the given regions, which must be isolated from above.
LogicalResult
mlir::applyPatternsAndFoldGreedily(MutableArrayRef<Region> regions,
const OwningRewritePatternList &patterns) {
if (regions.empty())
return success();
// The top-level operation must be known to be isolated from above to
// prevent performing canonicalizations on operations defined at or above
// the region containing 'op'.
auto regionIsIsolated = [](Region ®ion) {
return region.getParentOp()->isKnownIsolatedFromAbove();
};
(void)regionIsIsolated;
assert(llvm::all_of(regions, regionIsIsolated) &&
"patterns can only be applied to operations IsolatedFromAbove");
// Start the pattern driver.
GreedyPatternRewriteDriver driver(regions[0].getContext(), patterns);
bool converged = driver.simplify(regions, maxPatternMatchIterations);
LLVM_DEBUG(if (!converged) {
llvm::dbgs() << "The pattern rewrite doesn't converge after scanning "
<< maxPatternMatchIterations << " times";
});
return success(converged);
}
//===----------------------------------------------------------------------===//
// OpPatternRewriteDriver
//===----------------------------------------------------------------------===//
namespace {
/// This is a simple driver for the PatternMatcher to apply patterns and perform
/// folding on a single op. It repeatedly applies locally optimal patterns.
class OpPatternRewriteDriver : public PatternRewriter {
public:
explicit OpPatternRewriteDriver(MLIRContext *ctx,
const OwningRewritePatternList &patterns)
: PatternRewriter(ctx), matcher(patterns), folder(ctx) {
// Apply a simple cost model based solely on pattern benefit.
matcher.applyDefaultCostModel();
}
/// Performs the rewrites and folding only on `op`. The simplification
/// converges if the op is erased as a result of being folded, replaced, or
/// dead, or no more changes happen in an iteration. Returns success if the
/// rewrite converges in `maxIterations`. `erased` is set to true if `op` gets
/// erased.
LogicalResult simplifyLocally(Operation *op, int maxIterations, bool &erased);
// These are hooks implemented for PatternRewriter.
protected:
/// If an operation is about to be removed, mark it so that we can let clients
/// know.
void notifyOperationRemoved(Operation *op) override {
opErasedViaPatternRewrites = true;
}
// When a root is going to be replaced, its removal will be notified as well.
// So there is nothing to do here.
void notifyRootReplaced(Operation *op) override {}
private:
/// The low-level pattern applicator.
PatternApplicator matcher;
/// Non-pattern based folder for operations.
OperationFolder folder;
/// Set to true if the operation has been erased via pattern rewrites.
bool opErasedViaPatternRewrites = false;
};
} // anonymous namespace
LogicalResult OpPatternRewriteDriver::simplifyLocally(Operation *op,
int maxIterations,
bool &erased) {
bool changed = false;
erased = false;
opErasedViaPatternRewrites = false;
int i = 0;
// Iterate until convergence or until maxIterations. Deletion of the op as
// a result of being dead or folded is convergence.
do {
// If the operation is trivially dead - remove it.
if (isOpTriviallyDead(op)) {
op->erase();
erased = true;
return success();
}
// Try to fold this op.
bool inPlaceUpdate;
if (succeeded(folder.tryToFold(op, /*processGeneratedConstants=*/nullptr,
/*preReplaceAction=*/nullptr,
&inPlaceUpdate))) {
changed = true;
if (!inPlaceUpdate) {
erased = true;
return success();
}
}
// Try to match one of the patterns. The rewriter is automatically
// notified of any necessary changes, so there is nothing else to do here.
changed |= succeeded(matcher.matchAndRewrite(op, *this));
if ((erased = opErasedViaPatternRewrites))
return success();
} while (changed && ++i < maxIterations);
// Whether the rewrite converges, i.e. wasn't changed in the last iteration.
return failure(changed);
}
/// Rewrites only `op` using the supplied canonicalization patterns and
/// folding. `erased` is set to true if the op is erased as a result of being
/// folded, replaced, or dead.
LogicalResult mlir::applyOpPatternsAndFold(
Operation *op, const OwningRewritePatternList &patterns, bool *erased) {
// Start the pattern driver.
OpPatternRewriteDriver driver(op->getContext(), patterns);
bool opErased;
LogicalResult converged =
driver.simplifyLocally(op, maxPatternMatchIterations, opErased);
if (erased)
*erased = opErased;
LLVM_DEBUG(if (failed(converged)) {
llvm::dbgs() << "The pattern rewrite doesn't converge after scanning "
<< maxPatternMatchIterations << " times";
});
return converged;
}