llvm-capstone/mlir/lib/Analysis/NestedMatcher.cpp
River Riddle 9db53a1827 [mlir][NFC] Remove usernames and google bug numbers from TODO comments.
These were largely leftover from when MLIR was a google project, and don't really follow LLVM guidelines.
2020-07-07 01:40:52 -07:00

153 lines
5.1 KiB
C++

//===- NestedMatcher.cpp - NestedMatcher Impl ----------------------------===//
//
// 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/Analysis/NestedMatcher.h"
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "llvm/ADT/ArrayRef.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/Support/Allocator.h"
#include "llvm/Support/raw_ostream.h"
using namespace mlir;
llvm::BumpPtrAllocator *&NestedMatch::allocator() {
thread_local llvm::BumpPtrAllocator *allocator = nullptr;
return allocator;
}
NestedMatch NestedMatch::build(Operation *operation,
ArrayRef<NestedMatch> nestedMatches) {
auto *result = allocator()->Allocate<NestedMatch>();
auto *children = allocator()->Allocate<NestedMatch>(nestedMatches.size());
std::uninitialized_copy(nestedMatches.begin(), nestedMatches.end(), children);
new (result) NestedMatch();
result->matchedOperation = operation;
result->matchedChildren =
ArrayRef<NestedMatch>(children, nestedMatches.size());
return *result;
}
llvm::BumpPtrAllocator *&NestedPattern::allocator() {
thread_local llvm::BumpPtrAllocator *allocator = nullptr;
return allocator;
}
NestedPattern::NestedPattern(ArrayRef<NestedPattern> nested,
FilterFunctionType filter)
: nestedPatterns(), filter(filter), skip(nullptr) {
if (!nested.empty()) {
auto *newNested = allocator()->Allocate<NestedPattern>(nested.size());
std::uninitialized_copy(nested.begin(), nested.end(), newNested);
nestedPatterns = ArrayRef<NestedPattern>(newNested, nested.size());
}
}
unsigned NestedPattern::getDepth() const {
if (nestedPatterns.empty()) {
return 1;
}
unsigned depth = 0;
for (auto &c : nestedPatterns) {
depth = std::max(depth, c.getDepth());
}
return depth + 1;
}
/// Matches a single operation in the following way:
/// 1. checks the kind of operation against the matcher, if different then
/// there is no match;
/// 2. calls the customizable filter function to refine the single operation
/// match with extra semantic constraints;
/// 3. if all is good, recursively matches the nested patterns;
/// 4. if all nested match then the single operation matches too and is
/// appended to the list of matches;
/// 5. TODO: Optionally applies actions (lambda), in which case we will want
/// to traverse in post-order DFS to avoid invalidating iterators.
void NestedPattern::matchOne(Operation *op,
SmallVectorImpl<NestedMatch> *matches) {
if (skip == op) {
return;
}
// Local custom filter function
if (!filter(*op)) {
return;
}
if (nestedPatterns.empty()) {
SmallVector<NestedMatch, 8> nestedMatches;
matches->push_back(NestedMatch::build(op, nestedMatches));
return;
}
// Take a copy of each nested pattern so we can match it.
for (auto nestedPattern : nestedPatterns) {
SmallVector<NestedMatch, 8> nestedMatches;
// Skip elem in the walk immediately following. Without this we would
// essentially need to reimplement walk here.
nestedPattern.skip = op;
nestedPattern.match(op, &nestedMatches);
// If we could not match even one of the specified nestedPattern, early exit
// as this whole branch is not a match.
if (nestedMatches.empty()) {
return;
}
matches->push_back(NestedMatch::build(op, nestedMatches));
}
}
static bool isAffineForOp(Operation &op) { return isa<AffineForOp>(op); }
static bool isAffineIfOp(Operation &op) { return isa<AffineIfOp>(op); }
namespace mlir {
namespace matcher {
NestedPattern Op(FilterFunctionType filter) {
return NestedPattern({}, filter);
}
NestedPattern If(NestedPattern child) {
return NestedPattern(child, isAffineIfOp);
}
NestedPattern If(FilterFunctionType filter, NestedPattern child) {
return NestedPattern(child, [filter](Operation &op) {
return isAffineIfOp(op) && filter(op);
});
}
NestedPattern If(ArrayRef<NestedPattern> nested) {
return NestedPattern(nested, isAffineIfOp);
}
NestedPattern If(FilterFunctionType filter, ArrayRef<NestedPattern> nested) {
return NestedPattern(nested, [filter](Operation &op) {
return isAffineIfOp(op) && filter(op);
});
}
NestedPattern For(NestedPattern child) {
return NestedPattern(child, isAffineForOp);
}
NestedPattern For(FilterFunctionType filter, NestedPattern child) {
return NestedPattern(
child, [=](Operation &op) { return isAffineForOp(op) && filter(op); });
}
NestedPattern For(ArrayRef<NestedPattern> nested) {
return NestedPattern(nested, isAffineForOp);
}
NestedPattern For(FilterFunctionType filter, ArrayRef<NestedPattern> nested) {
return NestedPattern(
nested, [=](Operation &op) { return isAffineForOp(op) && filter(op); });
}
bool isLoadOrStore(Operation &op) {
return isa<AffineLoadOp, AffineStoreOp>(op);
}
} // end namespace matcher
} // end namespace mlir