forked from OSchip/llvm-project
200 lines
6.4 KiB
C++
200 lines
6.4 KiB
C++
//===- UseDefAnalysis.cpp - Analysis for Transitive UseDef chains ---------===//
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//
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// Copyright 2019 The MLIR Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// =============================================================================
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//
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// This file implements Analysis functions specific to slicing in Function.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Analysis/SliceAnalysis.h"
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#include "mlir/Analysis/VectorAnalysis.h"
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#include "mlir/IR/BuiltinOps.h"
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#include "mlir/IR/Instructions.h"
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#include "mlir/Support/Functional.h"
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#include "mlir/Support/STLExtras.h"
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#include "llvm/ADT/SetVector.h"
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#include <type_traits>
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///
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/// Implements Analysis functions specific to slicing in Function.
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///
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using namespace mlir;
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using llvm::DenseSet;
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using llvm::SetVector;
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void mlir::getForwardSlice(Instruction *inst,
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SetVector<Instruction *> *forwardSlice,
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TransitiveFilter filter, bool topLevel) {
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if (!inst) {
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return;
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}
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// Evaluate whether we should keep this use.
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// This is useful in particular to implement scoping; i.e. return the
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// transitive forwardSlice in the current scope.
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if (!filter(inst)) {
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return;
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}
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if (auto *opInst = dyn_cast<OperationInst>(inst)) {
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assert(opInst->getNumResults() <= 1 && "NYI: multiple results");
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if (opInst->getNumResults() > 0) {
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for (auto &u : opInst->getResult(0)->getUses()) {
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auto *ownerInst = u.getOwner();
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if (forwardSlice->count(ownerInst) == 0) {
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getForwardSlice(ownerInst, forwardSlice, filter,
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/*topLevel=*/false);
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}
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}
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}
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} else if (auto *forInst = dyn_cast<ForInst>(inst)) {
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for (auto &u : forInst->getInductionVar()->getUses()) {
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auto *ownerInst = u.getOwner();
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if (forwardSlice->count(ownerInst) == 0) {
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getForwardSlice(ownerInst, forwardSlice, filter,
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/*topLevel=*/false);
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}
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}
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} else {
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assert(false && "NYI slicing case");
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}
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// At the top level we reverse to get back the actual topological order.
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if (topLevel) {
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// std::reverse does not work out of the box on SetVector and I want an
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// in-place swap based thing (the real std::reverse, not the LLVM adapter).
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// TODO(clattner): Consider adding an extra method?
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std::vector<Instruction *> v(forwardSlice->takeVector());
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forwardSlice->insert(v.rbegin(), v.rend());
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} else {
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forwardSlice->insert(inst);
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}
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}
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void mlir::getBackwardSlice(Instruction *inst,
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SetVector<Instruction *> *backwardSlice,
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TransitiveFilter filter, bool topLevel) {
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if (!inst) {
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return;
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}
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// Evaluate whether we should keep this def.
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// This is useful in particular to implement scoping; i.e. return the
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// transitive forwardSlice in the current scope.
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if (!filter(inst)) {
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return;
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}
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for (auto *operand : inst->getOperands()) {
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auto *inst = operand->getDefiningInst();
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if (backwardSlice->count(inst) == 0) {
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getBackwardSlice(inst, backwardSlice, filter,
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/*topLevel=*/false);
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}
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}
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// Don't insert the top level instruction, we just queried on it and don't
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// want it in the results.
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if (!topLevel) {
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backwardSlice->insert(inst);
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}
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}
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SetVector<Instruction *> mlir::getSlice(Instruction *inst,
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TransitiveFilter backwardFilter,
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TransitiveFilter forwardFilter) {
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SetVector<Instruction *> slice;
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slice.insert(inst);
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unsigned currentIndex = 0;
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SetVector<Instruction *> backwardSlice;
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SetVector<Instruction *> forwardSlice;
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while (currentIndex != slice.size()) {
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auto *currentInst = (slice)[currentIndex];
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// Compute and insert the backwardSlice starting from currentInst.
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backwardSlice.clear();
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getBackwardSlice(currentInst, &backwardSlice, backwardFilter);
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slice.insert(backwardSlice.begin(), backwardSlice.end());
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// Compute and insert the forwardSlice starting from currentInst.
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forwardSlice.clear();
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getForwardSlice(currentInst, &forwardSlice, forwardFilter);
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slice.insert(forwardSlice.begin(), forwardSlice.end());
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++currentIndex;
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}
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return topologicalSort(slice);
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}
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namespace {
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/// DFS post-order implementation that maintains a global count to work across
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/// multiple invocations, to help implement topological sort on multi-root DAGs.
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/// We traverse all instructions but only record the ones that appear in
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/// `toSort` for the final result.
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struct DFSState {
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DFSState(const SetVector<Instruction *> &set)
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: toSort(set), topologicalCounts(), seen() {}
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const SetVector<Instruction *> &toSort;
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SmallVector<Instruction *, 16> topologicalCounts;
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DenseSet<Instruction *> seen;
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};
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} // namespace
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static void DFSPostorder(Instruction *current, DFSState *state) {
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auto *opInst = cast<OperationInst>(current);
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assert(opInst->getNumResults() <= 1 && "NYI: multi-result");
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if (opInst->getNumResults() > 0) {
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for (auto &u : opInst->getResult(0)->getUses()) {
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auto *inst = u.getOwner();
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DFSPostorder(inst, state);
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}
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}
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bool inserted;
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using IterTy = decltype(state->seen.begin());
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IterTy iter;
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std::tie(iter, inserted) = state->seen.insert(current);
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if (inserted) {
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if (state->toSort.count(current) > 0) {
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state->topologicalCounts.push_back(current);
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}
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}
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}
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SetVector<Instruction *>
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mlir::topologicalSort(const SetVector<Instruction *> &toSort) {
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if (toSort.empty()) {
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return toSort;
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}
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// Run from each root with global count and `seen` set.
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DFSState state(toSort);
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for (auto *s : toSort) {
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assert(toSort.count(s) == 1 && "NYI: multi-sets not supported");
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DFSPostorder(s, &state);
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}
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// Reorder and return.
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SetVector<Instruction *> res;
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for (auto it = state.topologicalCounts.rbegin(),
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eit = state.topologicalCounts.rend();
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it != eit; ++it) {
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res.insert(*it);
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}
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return res;
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}
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