//===- GIMatchTree.h - A decision tree to match GIMatchDag's --------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_UTILS_TABLEGEN_GIMATCHTREE_H
#define LLVM_UTILS_TABLEGEN_GIMATCHTREE_H
#include "GIMatchDag.h"
#include "llvm/ADT/BitVector.h"
namespace llvm {
class raw_ostream;
class GIMatchTreeBuilder;
class GIMatchTreePartitioner;
/// Describes the binding of a variable to the matched MIR
class GIMatchTreeVariableBinding {
/// The name of the variable described by this binding.
StringRef Name;
// The matched instruction it is bound to.
unsigned InstrID;
// The matched operand (if appropriate) it is bound to.
Optional<unsigned> OpIdx;
public:
GIMatchTreeVariableBinding(StringRef Name, unsigned InstrID,
Optional<unsigned> OpIdx = None)
: Name(Name), InstrID(InstrID), OpIdx(OpIdx) {}
bool isInstr() const { return !OpIdx; }
StringRef getName() const { return Name; }
unsigned getInstrID() const { return InstrID; }
unsigned getOpIdx() const {
assert(OpIdx && "Is not an operand binding");
return *OpIdx;
}
};
/// Associates a matchable with a leaf of the decision tree.
class GIMatchTreeLeafInfo {
public:
using const_var_binding_iterator =
std::vector<GIMatchTreeVariableBinding>::const_iterator;
using UntestedPredicatesTy = SmallVector<const GIMatchDagPredicate *, 1>;
using const_untested_predicates_iterator = UntestedPredicatesTy::const_iterator;
protected:
/// A name for the matchable. This is primarily for debugging.
StringRef Name;
/// Where rules have multiple roots, this is which root we're starting from.
unsigned RootIdx;
/// Opaque data the caller of the tree building code understands.
void *Data;
/// Has the decision tree covered every edge traversal? If it hasn't then this
/// is an unrecoverable error indicating there's something wrong with the
/// partitioners.
bool IsFullyTraversed;
/// Has the decision tree covered every predicate test? If it has, then
/// subsequent matchables on the same leaf are unreachable. If it hasn't, the
/// code that requested the GIMatchTree is responsible for finishing off any
/// remaining predicates.
bool IsFullyTested;
/// The variable bindings associated with this leaf so far.
std::vector<GIMatchTreeVariableBinding> VarBindings;
/// Any predicates left untested by the time we reach this leaf.
UntestedPredicatesTy UntestedPredicates;
public:
GIMatchTreeLeafInfo() { llvm_unreachable("Cannot default-construct"); }
GIMatchTreeLeafInfo(StringRef Name, unsigned RootIdx, void *Data)
: Name(Name), RootIdx(RootIdx), Data(Data), IsFullyTraversed(false),
IsFullyTested(false) {}
StringRef getName() const { return Name; }
unsigned getRootIdx() const { return RootIdx; }
template <class Ty> Ty *getTargetData() const {
return static_cast<Ty *>(Data);
}
bool isFullyTraversed() const { return IsFullyTraversed; }
void setIsFullyTraversed(bool V) { IsFullyTraversed = V; }
bool isFullyTested() const { return IsFullyTested; }
void setIsFullyTested(bool V) { IsFullyTested = V; }
void bindInstrVariable(StringRef Name, unsigned InstrID) {
VarBindings.emplace_back(Name, InstrID);
}
void bindOperandVariable(StringRef Name, unsigned InstrID, unsigned OpIdx) {
VarBindings.emplace_back(Name, InstrID, OpIdx);
}
const_var_binding_iterator var_bindings_begin() const {
return VarBindings.begin();
}
const_var_binding_iterator var_bindings_end() const {
return VarBindings.end();
}
iterator_range<const_var_binding_iterator> var_bindings() const {
return make_range(VarBindings.begin(), VarBindings.end());
}
iterator_range<const_untested_predicates_iterator> untested_predicates() const {
return make_range(UntestedPredicates.begin(), UntestedPredicates.end());
}
void addUntestedPredicate(const GIMatchDagPredicate *P) {
UntestedPredicates.push_back(P);
}
};
/// The nodes of a decision tree used to perform the match.
/// This will be used to generate the C++ code or state machine equivalent.
///
/// It should be noted that some nodes of this tree (most notably nodes handling
/// def -> use edges) will need to iterate over several possible matches. As
/// such, code generated from this will sometimes need to support backtracking.
class GIMatchTree {
using LeafVector = std::vector<GIMatchTreeLeafInfo>;
/// The partitioner that has been chosen for this node. This may be nullptr if
/// a partitioner hasn't been chosen yet or if the node is a leaf.
std::unique_ptr<GIMatchTreePartitioner> Partitioner;
/// All the leaves that are possible for this node of the tree.
/// Note: This should be emptied after the tree is built when there are
/// children but this currently isn't done to aid debuggability of the DOT
/// graph for the decision tree.
LeafVector PossibleLeaves;
/// The children of this node. The index into this array must match the index
/// chosen by the partitioner.
std::vector<GIMatchTree> Children;
void writeDOTGraphNode(raw_ostream &OS) const;
void writeDOTGraphEdges(raw_ostream &OS) const;
public:
void writeDOTGraph(raw_ostream &OS) const;
void setNumChildren(unsigned Num) { Children.resize(Num); }
void addPossibleLeaf(const GIMatchTreeLeafInfo &V, bool IsFullyTraversed,
bool IsFullyTested) {
PossibleLeaves.push_back(V);
PossibleLeaves.back().setIsFullyTraversed(IsFullyTraversed);
PossibleLeaves.back().setIsFullyTested(IsFullyTested);
}
void dropLeavesAfter(size_t Length) {
if (PossibleLeaves.size() > Length)
PossibleLeaves.resize(Length);
}
void setPartitioner(std::unique_ptr<GIMatchTreePartitioner> &&V) {
Partitioner = std::move(V);
}
GIMatchTreePartitioner *getPartitioner() const { return Partitioner.get(); }
std::vector<GIMatchTree>::iterator children_begin() {
return Children.begin();
}
std::vector<GIMatchTree>::iterator children_end() { return Children.end(); }
iterator_range<std::vector<GIMatchTree>::iterator> children() {
return make_range(children_begin(), children_end());
}
std::vector<GIMatchTree>::const_iterator children_begin() const {
return Children.begin();
}
std::vector<GIMatchTree>::const_iterator children_end() const {
return Children.end();
}
iterator_range<std::vector<GIMatchTree>::const_iterator> children() const {
return make_range(children_begin(), children_end());
}
LeafVector::const_iterator possible_leaves_begin() const {
return PossibleLeaves.begin();
}
LeafVector::const_iterator possible_leaves_end() const {
return PossibleLeaves.end();
}
iterator_range<LeafVector::const_iterator>
possible_leaves() const {
return make_range(possible_leaves_begin(), possible_leaves_end());
}
LeafVector::iterator possible_leaves_begin() {
return PossibleLeaves.begin();
}
LeafVector::iterator possible_leaves_end() {
return PossibleLeaves.end();
}
iterator_range<LeafVector::iterator> possible_leaves() {
return make_range(possible_leaves_begin(), possible_leaves_end());
}
};
/// Record information that is known about the instruction bound to this ID and
/// GIMatchDagInstrNode. Every rule gets its own set of
/// GIMatchTreeInstrInfo to bind the shared IDs to an instr node in its
/// DAG.
///
/// For example, if we know that there are 3 operands. We can record it here to
/// elide duplicate checks.
class GIMatchTreeInstrInfo {
/// The instruction ID for the matched instruction.
unsigned ID;
/// The corresponding instruction node in the MatchDAG.
const GIMatchDagInstr *InstrNode;
public:
GIMatchTreeInstrInfo(unsigned ID, const GIMatchDagInstr *InstrNode)
: ID(ID), InstrNode(InstrNode) {}
unsigned getID() const { return ID; }
const GIMatchDagInstr *getInstrNode() const { return InstrNode; }
};
/// Record information that is known about the operand bound to this ID, OpIdx,
/// and GIMatchDagInstrNode. Every rule gets its own set of
/// GIMatchTreeOperandInfo to bind the shared IDs to an operand of an
/// instr node from its DAG.
///
/// For example, if we know that there the operand is a register. We can record
/// it here to elide duplicate checks.
class GIMatchTreeOperandInfo {
/// The corresponding instruction node in the MatchDAG that the operand
/// belongs to.
const GIMatchDagInstr *InstrNode;
unsigned OpIdx;
public:
GIMatchTreeOperandInfo(const GIMatchDagInstr *InstrNode, unsigned OpIdx)
: InstrNode(InstrNode), OpIdx(OpIdx) {}
const GIMatchDagInstr *getInstrNode() const { return InstrNode; }
unsigned getOpIdx() const { return OpIdx; }
};
/// Represent a leaf of the match tree and any working data we need to build the
/// tree.
///
/// It's important to note that each rule can have multiple
/// GIMatchTreeBuilderLeafInfo's since the partitioners do not always partition
/// into mutually-exclusive partitions. For example:
/// R1: (FOO ..., ...)
/// R2: (oneof(FOO, BAR) ..., ...)
/// will partition by opcode into two partitions FOO=>[R1, R2], and BAR=>[R2]
///
/// As an optimization, all instructions, edges, and predicates in the DAGs are
/// numbered and tracked in BitVectors. As such, the GIMatchDAG must not be
/// modified once construction of the tree has begun.
class GIMatchTreeBuilderLeafInfo {
protected:
GIMatchTreeBuilder &Builder;
GIMatchTreeLeafInfo Info;
const GIMatchDag &MatchDag;
/// The association between GIMatchDagInstr* and GIMatchTreeInstrInfo.
/// The primary reason for this members existence is to allow the use of
/// InstrIDToInfo.lookup() since that requires that the value is
/// default-constructible.
DenseMap<const GIMatchDagInstr *, GIMatchTreeInstrInfo> InstrNodeToInfo;
/// The instruction information for a given ID in the context of this
/// particular leaf.
DenseMap<unsigned, GIMatchTreeInstrInfo *> InstrIDToInfo;
/// The operand information for a given ID and OpIdx in the context of this
/// particular leaf.
DenseMap<std::pair<unsigned, unsigned>, GIMatchTreeOperandInfo>
OperandIDToInfo;
public:
/// The remaining instrs/edges/predicates to visit
BitVector RemainingInstrNodes;
BitVector RemainingEdges;
BitVector RemainingPredicates;
// The remaining predicate dependencies for each predicate
std::vector<BitVector> UnsatisfiedPredDepsForPred;
/// The edges/predicates we can visit as a result of the declare*() calls we
/// have already made. We don't need an instrs version since edges imply the
/// instr.
BitVector TraversableEdges;
BitVector TestablePredicates;
/// Map predicates from the DAG to their position in the DAG predicate
/// iterators.
DenseMap<GIMatchDagPredicate *, unsigned> PredicateIDs;
/// Map predicate dependency edges from the DAG to their position in the DAG
/// predicate dependency iterators.
DenseMap<GIMatchDagPredicateDependencyEdge *, unsigned> PredicateDepIDs;
public:
GIMatchTreeBuilderLeafInfo(GIMatchTreeBuilder &Builder, StringRef Name,
unsigned RootIdx, const GIMatchDag &MatchDag,
void *Data);
StringRef getName() const { return Info.getName(); }
GIMatchTreeLeafInfo &getInfo() { return Info; }
const GIMatchTreeLeafInfo &getInfo() const { return Info; }
const GIMatchDag &getMatchDag() const { return MatchDag; }
unsigned getRootIdx() const { return Info.getRootIdx(); }
/// Has this DAG been fully traversed. This must be true by the time the tree
/// builder finishes.
bool isFullyTraversed() const {
// We don't need UnsatisfiedPredDepsForPred because RemainingPredicates
// can't be all-zero without satisfying all the dependencies. The same is
// almost true for Edges and Instrs but it's possible to have Instrs without
// Edges.
return RemainingInstrNodes.none() && RemainingEdges.none();
}
/// Has this DAG been fully tested. This hould be true by the time the tree
/// builder finishes but clients can finish any untested predicates left over
/// if it's not true.
bool isFullyTested() const {
// We don't need UnsatisfiedPredDepsForPred because RemainingPredicates
// can't be all-zero without satisfying all the dependencies. The same is
// almost true for Edges and Instrs but it's possible to have Instrs without
// Edges.
return RemainingInstrNodes.none() && RemainingEdges.none() &&
RemainingPredicates.none();
}
const GIMatchDagInstr *getInstr(unsigned Idx) const {
return *(MatchDag.instr_nodes_begin() + Idx);
}
const GIMatchDagEdge *getEdge(unsigned Idx) const {
return *(MatchDag.edges_begin() + Idx);
}
GIMatchDagEdge *getEdge(unsigned Idx) {
return *(MatchDag.edges_begin() + Idx);
}
const GIMatchDagPredicate *getPredicate(unsigned Idx) const {
return *(MatchDag.predicates_begin() + Idx);
}
iterator_range<llvm::BitVector::const_set_bits_iterator>
untested_instrs() const {
return RemainingInstrNodes.set_bits();
}
iterator_range<llvm::BitVector::const_set_bits_iterator>
untested_edges() const {
return RemainingEdges.set_bits();
}
iterator_range<llvm::BitVector::const_set_bits_iterator>
untested_predicates() const {
return RemainingPredicates.set_bits();
}
/// Bind an instr node to the given ID and clear any blocking dependencies
/// that were waiting for it.
void declareInstr(const GIMatchDagInstr *Instr, unsigned ID);
/// Bind an operand to the given ID and OpIdx and clear any blocking
/// dependencies that were waiting for it.
void declareOperand(unsigned InstrID, unsigned OpIdx);
GIMatchTreeInstrInfo *getInstrInfo(unsigned ID) const {
return InstrIDToInfo.lookup(ID);
}
void dump(raw_ostream &OS) const {
OS << "Leaf " << getName() << " for root #" << getRootIdx() << "\n";
MatchDag.print(OS);
for (const auto &I : InstrIDToInfo)
OS << "Declared Instr #" << I.first << "\n";
for (const auto &I : OperandIDToInfo)
OS << "Declared Instr #" << I.first.first << ", Op #" << I.first.second
<< "\n";
OS << RemainingInstrNodes.count() << " untested instrs of "
<< RemainingInstrNodes.size() << "\n";
OS << RemainingEdges.count() << " untested edges of "
<< RemainingEdges.size() << "\n";
OS << RemainingPredicates.count() << " untested predicates of "
<< RemainingPredicates.size() << "\n";
OS << TraversableEdges.count() << " edges could be traversed\n";
OS << TestablePredicates.count() << " predicates could be tested\n";
}
};
/// The tree builder has a fairly tough job. It's purpose is to merge all the
/// DAGs from the ruleset into a decision tree that walks all of them
/// simultaneously and identifies the rule that was matched. In addition to
/// that, it also needs to find the most efficient order to make decisions
/// without violating any dependencies and ensure that every DAG covers every
/// instr/edge/predicate.
class GIMatchTreeBuilder {
public:
using LeafVec = std::vector<GIMatchTreeBuilderLeafInfo>;
protected:
/// The leaves that the resulting decision tree will distinguish.
LeafVec Leaves;
/// The tree node being constructed.
GIMatchTree *TreeNode;
/// The builders for each subtree resulting from the current decision.
std::vector<GIMatchTreeBuilder> SubtreeBuilders;
/// The possible partitioners we could apply right now.
std::vector<std::unique_ptr<GIMatchTreePartitioner>> Partitioners;
/// The next instruction ID to allocate when requested by the chosen
/// Partitioner.
unsigned NextInstrID;
/// Use any context we have stored to cull partitioners that only test things
/// we already know. At the time of writing, there's no need to do anything
/// here but it will become important once, for example, there is a
/// num-operands and an opcode partitioner. This is because applying an opcode
/// partitioner (usually) makes the number of operands known which makes
/// additional checking pointless.
void filterRedundantPartitioners();
/// Evaluate the available partioners and select the best one at the moment.
void evaluatePartitioners();
/// Construct the current tree node.
void runStep();
public:
GIMatchTreeBuilder(unsigned NextInstrID) : NextInstrID(NextInstrID) {}
GIMatchTreeBuilder(GIMatchTree *TreeNode, unsigned NextInstrID)
: TreeNode(TreeNode), NextInstrID(NextInstrID) {}
void addLeaf(StringRef Name, unsigned RootIdx, const GIMatchDag &MatchDag,
void *Data) {
Leaves.emplace_back(*this, Name, RootIdx, MatchDag, Data);
}
void addLeaf(const GIMatchTreeBuilderLeafInfo &L) { Leaves.push_back(L); }
void addPartitioner(std::unique_ptr<GIMatchTreePartitioner> P) {
Partitioners.push_back(std::move(P));
}
void addPartitionersForInstr(unsigned InstrIdx);
void addPartitionersForOperand(unsigned InstrID, unsigned OpIdx);
LeafVec &getPossibleLeaves() { return Leaves; }
unsigned allocInstrID() { return NextInstrID++; }
/// Construct the decision tree.
std::unique_ptr<GIMatchTree> run();
};
/// Partitioners are the core of the tree builder and are unfortunately rather
/// tricky to write.
class GIMatchTreePartitioner {
protected:
/// The partitions resulting from applying the partitioner to the possible
/// leaves. The keys must be consecutive integers starting from 0. This can
/// lead to some unfortunate situations where partitioners test a predicate
/// and use 0 for success and 1 for failure if the ruleset encounters a
/// success case first but is necessary to assign the partition to one of the
/// tree nodes children. As a result, you usually need some kind of
/// indirection to map the natural keys (e.g. ptrs/bools) to this linear
/// sequence. The values are a bitvector indicating which leaves belong to
/// this partition.
DenseMap<unsigned, BitVector> Partitions;
public:
virtual ~GIMatchTreePartitioner() {}
virtual std::unique_ptr<GIMatchTreePartitioner> clone() const = 0;
/// Determines which partitions the given leaves belong to. A leaf may belong
/// to multiple partitions in which case it will be duplicated during
/// applyForPartition().
///
/// This function can be rather complicated. A few particular things to be
/// aware of include:
/// * One leaf can be assigned to multiple partitions when there's some
/// ambiguity.
/// * Not all DAG's for the leaves may be able to perform the test. For
/// example, the opcode partitiioner must account for one DAG being a
/// superset of another such as [(ADD ..., ..., ...)], and [(MUL t, ...,
/// ...), (ADD ..., t, ...)]
/// * Attaching meaning to a particular partition index will generally not
/// work due to the '0, 1, ..., n' requirement. You might encounter cases
/// where only partition 1 is seen, leaving a missing 0.
/// * Finding a specific predicate such as the opcode predicate for a specific
/// instruction is non-trivial. It's often O(NumPredicates), leading to
/// O(NumPredicates*NumRules) when applied to the whole ruleset. The good
/// news there is that n is typically small thanks to predicate dependencies
/// limiting how many are testable at once. Also, with opcode and type
/// predicates being so frequent the value of m drops very fast too. It
/// wouldn't be terribly surprising to see a 10k ruleset drop down to an
/// average of 100 leaves per partition after a single opcode partitioner.
/// * The same goes for finding specific edges. The need to traverse them in
/// dependency order dramatically limits the search space at any given
/// moment.
/// * If you need to add a leaf to all partitions, make sure you don't forget
/// them when adding partitions later.
virtual void repartition(GIMatchTreeBuilder::LeafVec &Leaves) = 0;
/// Delegate the leaves for a given partition to the corresponding subbuilder,
/// update any recorded context for this partition (e.g. allocate instr id's
/// for instrs recorder by the current node), and clear any blocking
/// dependencies this partitioner resolved.
virtual void applyForPartition(unsigned PartitionIdx,
GIMatchTreeBuilder &Builder,
GIMatchTreeBuilder &SubBuilder) = 0;
/// Return a BitVector indicating which leaves should be transferred to the
/// specified partition. Note that the same leaf can be indicated for multiple
/// partitions.
BitVector getPossibleLeavesForPartition(unsigned Idx) {
const auto &I = Partitions.find(Idx);
assert(I != Partitions.end() && "Requested non-existant partition");
return I->second;
}
size_t getNumPartitions() const { return Partitions.size(); }
size_t getNumLeavesWithDupes() const {
size_t S = 0;
for (const auto &P : Partitions)
S += P.second.size();
return S;
}
/// Emit a brief description of the partitioner suitable for debug printing or
/// use in a DOT graph.
virtual void emitDescription(raw_ostream &OS) const = 0;
/// Emit a label for the given partition suitable for debug printing or use in
/// a DOT graph.
virtual void emitPartitionName(raw_ostream &OS, unsigned Idx) const = 0;
/// Emit a long description of how the partitioner partitions the leaves.
virtual void emitPartitionResults(raw_ostream &OS) const = 0;
/// Generate code to select between partitions based on the MIR being matched.
/// This is typically a switch statement that picks a partition index.
virtual void generatePartitionSelectorCode(raw_ostream &OS,
StringRef Indent) const = 0;
};
/// Partition according to the opcode of the instruction.
///
/// Numbers CodeGenInstr ptrs for use as partition ID's. One special partition,
/// nullptr, represents the case where the instruction isn't known.
///
/// * If the opcode can be tested and is a single opcode, create the partition
/// for that opcode and assign the leaf to it. This partition no longer needs
/// to test the opcode, and many details about the instruction will usually
/// become known (e.g. number of operands for non-variadic instrs) via the
/// CodeGenInstr ptr.
/// * (not implemented yet) If the opcode can be tested and is a choice of
/// opcodes, then the leaf can be treated like the single-opcode case but must
/// be added to all relevant partitions and not quite as much becomes known as
/// a result. That said, multiple-choice opcodes are likely similar enough
/// (because if they aren't then handling them together makes little sense)
/// that plenty still becomes known. The main implementation issue with this
/// is having a description to represent the commonality between instructions.
/// * If the opcode is not tested, the leaf must be added to all partitions
/// including the wildcard nullptr partition. What becomes known as a result
/// varies between partitions.
/// * If the instruction to be tested is not declared then add the leaf to all
/// partitions. This occurs when we encounter one rule that is a superset of
/// the other and we are still matching the remainder of the superset. The
/// result is that the cases that don't match the superset will match the
/// subset rule, while the ones that do match the superset will match either
/// (which one is algorithm dependent but will usually be the superset).
class GIMatchTreeOpcodePartitioner : public GIMatchTreePartitioner {
unsigned InstrID;
DenseMap<const CodeGenInstruction *, unsigned> InstrToPartition;
std::vector<const CodeGenInstruction *> PartitionToInstr;
std::vector<BitVector> TestedPredicates;
public:
GIMatchTreeOpcodePartitioner(unsigned InstrID) : InstrID(InstrID) {}
std::unique_ptr<GIMatchTreePartitioner> clone() const override {
return std::make_unique<GIMatchTreeOpcodePartitioner>(*this);
}
void emitDescription(raw_ostream &OS) const override {
OS << "MI[" << InstrID << "].getOpcode()";
}
void emitPartitionName(raw_ostream &OS, unsigned Idx) const override;
void repartition(GIMatchTreeBuilder::LeafVec &Leaves) override;
void applyForPartition(unsigned Idx, GIMatchTreeBuilder &SubBuilder,
GIMatchTreeBuilder &Builder) override;
void emitPartitionResults(raw_ostream &OS) const override;
void generatePartitionSelectorCode(raw_ostream &OS,
StringRef Indent) const override;
};
class GIMatchTreeVRegDefPartitioner : public GIMatchTreePartitioner {
unsigned NewInstrID = -1;
unsigned InstrID;
unsigned OpIdx;
std::vector<BitVector> TraversedEdges;
DenseMap<unsigned, unsigned> ResultToPartition;
BitVector PartitionToResult;
void addToPartition(bool Result, unsigned LeafIdx);
public:
GIMatchTreeVRegDefPartitioner(unsigned InstrID, unsigned OpIdx)
: InstrID(InstrID), OpIdx(OpIdx) {}
std::unique_ptr<GIMatchTreePartitioner> clone() const override {
return std::make_unique<GIMatchTreeVRegDefPartitioner>(*this);
}
void emitDescription(raw_ostream &OS) const override {
OS << "MI[" << NewInstrID << "] = getVRegDef(MI[" << InstrID
<< "].getOperand(" << OpIdx << "))";
}
void emitPartitionName(raw_ostream &OS, unsigned Idx) const override {
bool Result = PartitionToResult[Idx];
if (Result)
OS << "true";
else
OS << "false";
}
void repartition(GIMatchTreeBuilder::LeafVec &Leaves) override;
void applyForPartition(unsigned PartitionIdx, GIMatchTreeBuilder &Builder,
GIMatchTreeBuilder &SubBuilder) override;
void emitPartitionResults(raw_ostream &OS) const override;
void generatePartitionSelectorCode(raw_ostream &OS,
StringRef Indent) const override;
};
} // end namespace llvm
#endif // ifndef LLVM_UTILS_TABLEGEN_GIMATCHTREE_H