xref: /llvm-project/mlir/lib/Conversion/PDLToPDLInterp/PDLToPDLInterp.cpp (revision 1a36588ec64ae8576e531e6f0b49eadb90ab0b11)
1 //===- PDLToPDLInterp.cpp - Lower a PDL module to the interpreter ---------===//
2 //
3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4 // See https://llvm.org/LICENSE.txt for license information.
5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6 //
7 //===----------------------------------------------------------------------===//
8 
9 #include "mlir/Conversion/PDLToPDLInterp/PDLToPDLInterp.h"
10 
11 #include "PredicateTree.h"
12 #include "mlir/Dialect/PDL/IR/PDL.h"
13 #include "mlir/Dialect/PDL/IR/PDLTypes.h"
14 #include "mlir/Dialect/PDLInterp/IR/PDLInterp.h"
15 #include "mlir/Pass/Pass.h"
16 #include "llvm/ADT/MapVector.h"
17 #include "llvm/ADT/ScopedHashTable.h"
18 #include "llvm/ADT/Sequence.h"
19 #include "llvm/ADT/SetVector.h"
20 #include "llvm/ADT/SmallVector.h"
21 #include "llvm/ADT/TypeSwitch.h"
22 
23 namespace mlir {
24 #define GEN_PASS_DEF_CONVERTPDLTOPDLINTERP
25 #include "mlir/Conversion/Passes.h.inc"
26 } // namespace mlir
27 
28 using namespace mlir;
29 using namespace mlir::pdl_to_pdl_interp;
30 
31 //===----------------------------------------------------------------------===//
32 // PatternLowering
33 //===----------------------------------------------------------------------===//
34 
35 namespace {
36 /// This class generators operations within the PDL Interpreter dialect from a
37 /// given module containing PDL pattern operations.
38 struct PatternLowering {
39 public:
40   PatternLowering(pdl_interp::FuncOp matcherFunc, ModuleOp rewriterModule,
41                   DenseMap<Operation *, PDLPatternConfigSet *> *configMap);
42 
43   /// Generate code for matching and rewriting based on the pattern operations
44   /// within the module.
45   void lower(ModuleOp module);
46 
47 private:
48   using ValueMap = llvm::ScopedHashTable<Position *, Value>;
49   using ValueMapScope = llvm::ScopedHashTableScope<Position *, Value>;
50 
51   /// Generate interpreter operations for the tree rooted at the given matcher
52   /// node, in the specified region.
53   Block *generateMatcher(MatcherNode &node, Region &region);
54 
55   /// Get or create an access to the provided positional value in the current
56   /// block. This operation may mutate the provided block pointer if nested
57   /// regions (i.e., pdl_interp.iterate) are required.
58   Value getValueAt(Block *&currentBlock, Position *pos);
59 
60   /// Create the interpreter predicate operations. This operation may mutate the
61   /// provided current block pointer if nested regions (iterates) are required.
62   void generate(BoolNode *boolNode, Block *&currentBlock, Value val);
63 
64   /// Create the interpreter switch / predicate operations, with several case
65   /// destinations. This operation never mutates the provided current block
66   /// pointer, because the switch operation does not need Values beyond `val`.
67   void generate(SwitchNode *switchNode, Block *currentBlock, Value val);
68 
69   /// Create the interpreter operations to record a successful pattern match
70   /// using the contained root operation. This operation may mutate the current
71   /// block pointer if nested regions (i.e., pdl_interp.iterate) are required.
72   void generate(SuccessNode *successNode, Block *&currentBlock);
73 
74   /// Generate a rewriter function for the given pattern operation, and returns
75   /// a reference to that function.
76   SymbolRefAttr generateRewriter(pdl::PatternOp pattern,
77                                  SmallVectorImpl<Position *> &usedMatchValues);
78 
79   /// Generate the rewriter code for the given operation.
80   void generateRewriter(pdl::ApplyNativeRewriteOp rewriteOp,
81                         DenseMap<Value, Value> &rewriteValues,
82                         function_ref<Value(Value)> mapRewriteValue);
83   void generateRewriter(pdl::AttributeOp attrOp,
84                         DenseMap<Value, Value> &rewriteValues,
85                         function_ref<Value(Value)> mapRewriteValue);
86   void generateRewriter(pdl::EraseOp eraseOp,
87                         DenseMap<Value, Value> &rewriteValues,
88                         function_ref<Value(Value)> mapRewriteValue);
89   void generateRewriter(pdl::OperationOp operationOp,
90                         DenseMap<Value, Value> &rewriteValues,
91                         function_ref<Value(Value)> mapRewriteValue);
92   void generateRewriter(pdl::RangeOp rangeOp,
93                         DenseMap<Value, Value> &rewriteValues,
94                         function_ref<Value(Value)> mapRewriteValue);
95   void generateRewriter(pdl::ReplaceOp replaceOp,
96                         DenseMap<Value, Value> &rewriteValues,
97                         function_ref<Value(Value)> mapRewriteValue);
98   void generateRewriter(pdl::ResultOp resultOp,
99                         DenseMap<Value, Value> &rewriteValues,
100                         function_ref<Value(Value)> mapRewriteValue);
101   void generateRewriter(pdl::ResultsOp resultOp,
102                         DenseMap<Value, Value> &rewriteValues,
103                         function_ref<Value(Value)> mapRewriteValue);
104   void generateRewriter(pdl::TypeOp typeOp,
105                         DenseMap<Value, Value> &rewriteValues,
106                         function_ref<Value(Value)> mapRewriteValue);
107   void generateRewriter(pdl::TypesOp typeOp,
108                         DenseMap<Value, Value> &rewriteValues,
109                         function_ref<Value(Value)> mapRewriteValue);
110 
111   /// Generate the values used for resolving the result types of an operation
112   /// created within a dag rewriter region. If the result types of the operation
113   /// should be inferred, `hasInferredResultTypes` is set to true.
114   void generateOperationResultTypeRewriter(
115       pdl::OperationOp op, function_ref<Value(Value)> mapRewriteValue,
116       SmallVectorImpl<Value> &types, DenseMap<Value, Value> &rewriteValues,
117       bool &hasInferredResultTypes);
118 
119   /// A builder to use when generating interpreter operations.
120   OpBuilder builder;
121 
122   /// The matcher function used for all match related logic within PDL patterns.
123   pdl_interp::FuncOp matcherFunc;
124 
125   /// The rewriter module containing the all rewrite related logic within PDL
126   /// patterns.
127   ModuleOp rewriterModule;
128 
129   /// The symbol table of the rewriter module used for insertion.
130   SymbolTable rewriterSymbolTable;
131 
132   /// A scoped map connecting a position with the corresponding interpreter
133   /// value.
134   ValueMap values;
135 
136   /// A stack of blocks used as the failure destination for matcher nodes that
137   /// don't have an explicit failure path.
138   SmallVector<Block *, 8> failureBlockStack;
139 
140   /// A mapping between values defined in a pattern match, and the corresponding
141   /// positional value.
142   DenseMap<Value, Position *> valueToPosition;
143 
144   /// The set of operation values whose whose location will be used for newly
145   /// generated operations.
146   SetVector<Value> locOps;
147 
148   /// A mapping between pattern operations and the corresponding configuration
149   /// set.
150   DenseMap<Operation *, PDLPatternConfigSet *> *configMap;
151 };
152 } // namespace
153 
154 PatternLowering::PatternLowering(
155     pdl_interp::FuncOp matcherFunc, ModuleOp rewriterModule,
156     DenseMap<Operation *, PDLPatternConfigSet *> *configMap)
157     : builder(matcherFunc.getContext()), matcherFunc(matcherFunc),
158       rewriterModule(rewriterModule), rewriterSymbolTable(rewriterModule),
159       configMap(configMap) {}
160 
161 void PatternLowering::lower(ModuleOp module) {
162   PredicateUniquer predicateUniquer;
163   PredicateBuilder predicateBuilder(predicateUniquer, module.getContext());
164 
165   // Define top-level scope for the arguments to the matcher function.
166   ValueMapScope topLevelValueScope(values);
167 
168   // Insert the root operation, i.e. argument to the matcher, at the root
169   // position.
170   Block *matcherEntryBlock = &matcherFunc.front();
171   values.insert(predicateBuilder.getRoot(), matcherEntryBlock->getArgument(0));
172 
173   // Generate a root matcher node from the provided PDL module.
174   std::unique_ptr<MatcherNode> root = MatcherNode::generateMatcherTree(
175       module, predicateBuilder, valueToPosition);
176   Block *firstMatcherBlock = generateMatcher(*root, matcherFunc.getBody());
177   assert(failureBlockStack.empty() && "failed to empty the stack");
178 
179   // After generation, merged the first matched block into the entry.
180   matcherEntryBlock->getOperations().splice(matcherEntryBlock->end(),
181                                             firstMatcherBlock->getOperations());
182   firstMatcherBlock->erase();
183 }
184 
185 Block *PatternLowering::generateMatcher(MatcherNode &node, Region &region) {
186   // Push a new scope for the values used by this matcher.
187   Block *block = &region.emplaceBlock();
188   ValueMapScope scope(values);
189 
190   // If this is the return node, simply insert the corresponding interpreter
191   // finalize.
192   if (isa<ExitNode>(node)) {
193     builder.setInsertionPointToEnd(block);
194     builder.create<pdl_interp::FinalizeOp>(matcherFunc.getLoc());
195     return block;
196   }
197 
198   // Get the next block in the match sequence.
199   // This is intentionally executed first, before we get the value for the
200   // position associated with the node, so that we preserve an "there exist"
201   // semantics: if getting a value requires an upward traversal (going from a
202   // value to its consumers), we want to perform the check on all the consumers
203   // before we pass control to the failure node.
204   std::unique_ptr<MatcherNode> &failureNode = node.getFailureNode();
205   Block *failureBlock;
206   if (failureNode) {
207     failureBlock = generateMatcher(*failureNode, region);
208     failureBlockStack.push_back(failureBlock);
209   } else {
210     assert(!failureBlockStack.empty() && "expected valid failure block");
211     failureBlock = failureBlockStack.back();
212   }
213 
214   // If this node contains a position, get the corresponding value for this
215   // block.
216   Block *currentBlock = block;
217   Position *position = node.getPosition();
218   Value val = position ? getValueAt(currentBlock, position) : Value();
219 
220   // If this value corresponds to an operation, record that we are going to use
221   // its location as part of a fused location.
222   bool isOperationValue = val && val.getType().isa<pdl::OperationType>();
223   if (isOperationValue)
224     locOps.insert(val);
225 
226   // Dispatch to the correct method based on derived node type.
227   TypeSwitch<MatcherNode *>(&node)
228       .Case<BoolNode, SwitchNode>([&](auto *derivedNode) {
229         this->generate(derivedNode, currentBlock, val);
230       })
231       .Case([&](SuccessNode *successNode) {
232         generate(successNode, currentBlock);
233       });
234 
235   // Pop all the failure blocks that were inserted due to nesting of
236   // pdl_interp.iterate.
237   while (failureBlockStack.back() != failureBlock) {
238     failureBlockStack.pop_back();
239     assert(!failureBlockStack.empty() && "unable to locate failure block");
240   }
241 
242   // Pop the new failure block.
243   if (failureNode)
244     failureBlockStack.pop_back();
245 
246   if (isOperationValue)
247     locOps.remove(val);
248 
249   return block;
250 }
251 
252 Value PatternLowering::getValueAt(Block *&currentBlock, Position *pos) {
253   if (Value val = values.lookup(pos))
254     return val;
255 
256   // Get the value for the parent position.
257   Value parentVal;
258   if (Position *parent = pos->getParent())
259     parentVal = getValueAt(currentBlock, parent);
260 
261   // TODO: Use a location from the position.
262   Location loc = parentVal ? parentVal.getLoc() : builder.getUnknownLoc();
263   builder.setInsertionPointToEnd(currentBlock);
264   Value value;
265   switch (pos->getKind()) {
266   case Predicates::OperationPos: {
267     auto *operationPos = cast<OperationPosition>(pos);
268     if (operationPos->isOperandDefiningOp())
269       // Standard (downward) traversal which directly follows the defining op.
270       value = builder.create<pdl_interp::GetDefiningOpOp>(
271           loc, builder.getType<pdl::OperationType>(), parentVal);
272     else
273       // A passthrough operation position.
274       value = parentVal;
275     break;
276   }
277   case Predicates::UsersPos: {
278     auto *usersPos = cast<UsersPosition>(pos);
279 
280     // The first operation retrieves the representative value of a range.
281     // This applies only when the parent is a range of values and we were
282     // requested to use a representative value (e.g., upward traversal).
283     if (parentVal.getType().isa<pdl::RangeType>() &&
284         usersPos->useRepresentative())
285       value = builder.create<pdl_interp::ExtractOp>(loc, parentVal, 0);
286     else
287       value = parentVal;
288 
289     // The second operation retrieves the users.
290     value = builder.create<pdl_interp::GetUsersOp>(loc, value);
291     break;
292   }
293   case Predicates::ForEachPos: {
294     assert(!failureBlockStack.empty() && "expected valid failure block");
295     auto foreach = builder.create<pdl_interp::ForEachOp>(
296         loc, parentVal, failureBlockStack.back(), /*initLoop=*/true);
297     value = foreach.getLoopVariable();
298 
299     // Create the continuation block.
300     Block *continueBlock = builder.createBlock(&foreach.getRegion());
301     builder.create<pdl_interp::ContinueOp>(loc);
302     failureBlockStack.push_back(continueBlock);
303 
304     currentBlock = &foreach.getRegion().front();
305     break;
306   }
307   case Predicates::OperandPos: {
308     auto *operandPos = cast<OperandPosition>(pos);
309     value = builder.create<pdl_interp::GetOperandOp>(
310         loc, builder.getType<pdl::ValueType>(), parentVal,
311         operandPos->getOperandNumber());
312     break;
313   }
314   case Predicates::OperandGroupPos: {
315     auto *operandPos = cast<OperandGroupPosition>(pos);
316     Type valueTy = builder.getType<pdl::ValueType>();
317     value = builder.create<pdl_interp::GetOperandsOp>(
318         loc, operandPos->isVariadic() ? pdl::RangeType::get(valueTy) : valueTy,
319         parentVal, operandPos->getOperandGroupNumber());
320     break;
321   }
322   case Predicates::AttributePos: {
323     auto *attrPos = cast<AttributePosition>(pos);
324     value = builder.create<pdl_interp::GetAttributeOp>(
325         loc, builder.getType<pdl::AttributeType>(), parentVal,
326         attrPos->getName().strref());
327     break;
328   }
329   case Predicates::TypePos: {
330     if (parentVal.getType().isa<pdl::AttributeType>())
331       value = builder.create<pdl_interp::GetAttributeTypeOp>(loc, parentVal);
332     else
333       value = builder.create<pdl_interp::GetValueTypeOp>(loc, parentVal);
334     break;
335   }
336   case Predicates::ResultPos: {
337     auto *resPos = cast<ResultPosition>(pos);
338     value = builder.create<pdl_interp::GetResultOp>(
339         loc, builder.getType<pdl::ValueType>(), parentVal,
340         resPos->getResultNumber());
341     break;
342   }
343   case Predicates::ResultGroupPos: {
344     auto *resPos = cast<ResultGroupPosition>(pos);
345     Type valueTy = builder.getType<pdl::ValueType>();
346     value = builder.create<pdl_interp::GetResultsOp>(
347         loc, resPos->isVariadic() ? pdl::RangeType::get(valueTy) : valueTy,
348         parentVal, resPos->getResultGroupNumber());
349     break;
350   }
351   case Predicates::AttributeLiteralPos: {
352     auto *attrPos = cast<AttributeLiteralPosition>(pos);
353     value =
354         builder.create<pdl_interp::CreateAttributeOp>(loc, attrPos->getValue());
355     break;
356   }
357   case Predicates::TypeLiteralPos: {
358     auto *typePos = cast<TypeLiteralPosition>(pos);
359     Attribute rawTypeAttr = typePos->getValue();
360     if (TypeAttr typeAttr = rawTypeAttr.dyn_cast<TypeAttr>())
361       value = builder.create<pdl_interp::CreateTypeOp>(loc, typeAttr);
362     else
363       value = builder.create<pdl_interp::CreateTypesOp>(
364           loc, rawTypeAttr.cast<ArrayAttr>());
365     break;
366   }
367   default:
368     llvm_unreachable("Generating unknown Position getter");
369     break;
370   }
371 
372   values.insert(pos, value);
373   return value;
374 }
375 
376 void PatternLowering::generate(BoolNode *boolNode, Block *&currentBlock,
377                                Value val) {
378   Location loc = val.getLoc();
379   Qualifier *question = boolNode->getQuestion();
380   Qualifier *answer = boolNode->getAnswer();
381   Region *region = currentBlock->getParent();
382 
383   // Execute the getValue queries first, so that we create success
384   // matcher in the correct (possibly nested) region.
385   SmallVector<Value> args;
386   if (auto *equalToQuestion = dyn_cast<EqualToQuestion>(question)) {
387     args = {getValueAt(currentBlock, equalToQuestion->getValue())};
388   } else if (auto *cstQuestion = dyn_cast<ConstraintQuestion>(question)) {
389     for (Position *position : cstQuestion->getArgs())
390       args.push_back(getValueAt(currentBlock, position));
391   }
392 
393   // Generate the matcher in the current (potentially nested) region
394   // and get the failure successor.
395   Block *success = generateMatcher(*boolNode->getSuccessNode(), *region);
396   Block *failure = failureBlockStack.back();
397 
398   // Finally, create the predicate.
399   builder.setInsertionPointToEnd(currentBlock);
400   Predicates::Kind kind = question->getKind();
401   switch (kind) {
402   case Predicates::IsNotNullQuestion:
403     builder.create<pdl_interp::IsNotNullOp>(loc, val, success, failure);
404     break;
405   case Predicates::OperationNameQuestion: {
406     auto *opNameAnswer = cast<OperationNameAnswer>(answer);
407     builder.create<pdl_interp::CheckOperationNameOp>(
408         loc, val, opNameAnswer->getValue().getStringRef(), success, failure);
409     break;
410   }
411   case Predicates::TypeQuestion: {
412     auto *ans = cast<TypeAnswer>(answer);
413     if (val.getType().isa<pdl::RangeType>())
414       builder.create<pdl_interp::CheckTypesOp>(
415           loc, val, ans->getValue().cast<ArrayAttr>(), success, failure);
416     else
417       builder.create<pdl_interp::CheckTypeOp>(
418           loc, val, ans->getValue().cast<TypeAttr>(), success, failure);
419     break;
420   }
421   case Predicates::AttributeQuestion: {
422     auto *ans = cast<AttributeAnswer>(answer);
423     builder.create<pdl_interp::CheckAttributeOp>(loc, val, ans->getValue(),
424                                                  success, failure);
425     break;
426   }
427   case Predicates::OperandCountAtLeastQuestion:
428   case Predicates::OperandCountQuestion:
429     builder.create<pdl_interp::CheckOperandCountOp>(
430         loc, val, cast<UnsignedAnswer>(answer)->getValue(),
431         /*compareAtLeast=*/kind == Predicates::OperandCountAtLeastQuestion,
432         success, failure);
433     break;
434   case Predicates::ResultCountAtLeastQuestion:
435   case Predicates::ResultCountQuestion:
436     builder.create<pdl_interp::CheckResultCountOp>(
437         loc, val, cast<UnsignedAnswer>(answer)->getValue(),
438         /*compareAtLeast=*/kind == Predicates::ResultCountAtLeastQuestion,
439         success, failure);
440     break;
441   case Predicates::EqualToQuestion: {
442     bool trueAnswer = isa<TrueAnswer>(answer);
443     builder.create<pdl_interp::AreEqualOp>(loc, val, args.front(),
444                                            trueAnswer ? success : failure,
445                                            trueAnswer ? failure : success);
446     break;
447   }
448   case Predicates::ConstraintQuestion: {
449     auto *cstQuestion = cast<ConstraintQuestion>(question);
450     builder.create<pdl_interp::ApplyConstraintOp>(loc, cstQuestion->getName(),
451                                                   args, success, failure);
452     break;
453   }
454   default:
455     llvm_unreachable("Generating unknown Predicate operation");
456   }
457 }
458 
459 template <typename OpT, typename PredT, typename ValT = typename PredT::KeyTy>
460 static void createSwitchOp(Value val, Block *defaultDest, OpBuilder &builder,
461                            llvm::MapVector<Qualifier *, Block *> &dests) {
462   std::vector<ValT> values;
463   std::vector<Block *> blocks;
464   values.reserve(dests.size());
465   blocks.reserve(dests.size());
466   for (const auto &it : dests) {
467     blocks.push_back(it.second);
468     values.push_back(cast<PredT>(it.first)->getValue());
469   }
470   builder.create<OpT>(val.getLoc(), val, values, defaultDest, blocks);
471 }
472 
473 void PatternLowering::generate(SwitchNode *switchNode, Block *currentBlock,
474                                Value val) {
475   Qualifier *question = switchNode->getQuestion();
476   Region *region = currentBlock->getParent();
477   Block *defaultDest = failureBlockStack.back();
478 
479   // If the switch question is not an exact answer, i.e. for the `at_least`
480   // cases, we generate a special block sequence.
481   Predicates::Kind kind = question->getKind();
482   if (kind == Predicates::OperandCountAtLeastQuestion ||
483       kind == Predicates::ResultCountAtLeastQuestion) {
484     // Order the children such that the cases are in reverse numerical order.
485     SmallVector<unsigned> sortedChildren = llvm::to_vector<16>(
486         llvm::seq<unsigned>(0, switchNode->getChildren().size()));
487     llvm::sort(sortedChildren, [&](unsigned lhs, unsigned rhs) {
488       return cast<UnsignedAnswer>(switchNode->getChild(lhs).first)->getValue() >
489              cast<UnsignedAnswer>(switchNode->getChild(rhs).first)->getValue();
490     });
491 
492     // Build the destination for each child using the next highest child as a
493     // a failure destination. This essentially creates the following control
494     // flow:
495     //
496     // if (operand_count < 1)
497     //   goto failure
498     // if (child1.match())
499     //   ...
500     //
501     // if (operand_count < 2)
502     //   goto failure
503     // if (child2.match())
504     //   ...
505     //
506     // failure:
507     //   ...
508     //
509     failureBlockStack.push_back(defaultDest);
510     Location loc = val.getLoc();
511     for (unsigned idx : sortedChildren) {
512       auto &child = switchNode->getChild(idx);
513       Block *childBlock = generateMatcher(*child.second, *region);
514       Block *predicateBlock = builder.createBlock(childBlock);
515       builder.setInsertionPointToEnd(predicateBlock);
516       unsigned ans = cast<UnsignedAnswer>(child.first)->getValue();
517       switch (kind) {
518       case Predicates::OperandCountAtLeastQuestion:
519         builder.create<pdl_interp::CheckOperandCountOp>(
520             loc, val, ans, /*compareAtLeast=*/true, childBlock, defaultDest);
521         break;
522       case Predicates::ResultCountAtLeastQuestion:
523         builder.create<pdl_interp::CheckResultCountOp>(
524             loc, val, ans, /*compareAtLeast=*/true, childBlock, defaultDest);
525         break;
526       default:
527         llvm_unreachable("Generating invalid AtLeast operation");
528       }
529       failureBlockStack.back() = predicateBlock;
530     }
531     Block *firstPredicateBlock = failureBlockStack.pop_back_val();
532     currentBlock->getOperations().splice(currentBlock->end(),
533                                          firstPredicateBlock->getOperations());
534     firstPredicateBlock->erase();
535     return;
536   }
537 
538   // Otherwise, generate each of the children and generate an interpreter
539   // switch.
540   llvm::MapVector<Qualifier *, Block *> children;
541   for (auto &it : switchNode->getChildren())
542     children.insert({it.first, generateMatcher(*it.second, *region)});
543   builder.setInsertionPointToEnd(currentBlock);
544 
545   switch (question->getKind()) {
546   case Predicates::OperandCountQuestion:
547     return createSwitchOp<pdl_interp::SwitchOperandCountOp, UnsignedAnswer,
548                           int32_t>(val, defaultDest, builder, children);
549   case Predicates::ResultCountQuestion:
550     return createSwitchOp<pdl_interp::SwitchResultCountOp, UnsignedAnswer,
551                           int32_t>(val, defaultDest, builder, children);
552   case Predicates::OperationNameQuestion:
553     return createSwitchOp<pdl_interp::SwitchOperationNameOp,
554                           OperationNameAnswer>(val, defaultDest, builder,
555                                                children);
556   case Predicates::TypeQuestion:
557     if (val.getType().isa<pdl::RangeType>()) {
558       return createSwitchOp<pdl_interp::SwitchTypesOp, TypeAnswer>(
559           val, defaultDest, builder, children);
560     }
561     return createSwitchOp<pdl_interp::SwitchTypeOp, TypeAnswer>(
562         val, defaultDest, builder, children);
563   case Predicates::AttributeQuestion:
564     return createSwitchOp<pdl_interp::SwitchAttributeOp, AttributeAnswer>(
565         val, defaultDest, builder, children);
566   default:
567     llvm_unreachable("Generating unknown switch predicate.");
568   }
569 }
570 
571 void PatternLowering::generate(SuccessNode *successNode, Block *&currentBlock) {
572   pdl::PatternOp pattern = successNode->getPattern();
573   Value root = successNode->getRoot();
574 
575   // Generate a rewriter for the pattern this success node represents, and track
576   // any values used from the match region.
577   SmallVector<Position *, 8> usedMatchValues;
578   SymbolRefAttr rewriterFuncRef = generateRewriter(pattern, usedMatchValues);
579 
580   // Process any values used in the rewrite that are defined in the match.
581   std::vector<Value> mappedMatchValues;
582   mappedMatchValues.reserve(usedMatchValues.size());
583   for (Position *position : usedMatchValues)
584     mappedMatchValues.push_back(getValueAt(currentBlock, position));
585 
586   // Collect the set of operations generated by the rewriter.
587   SmallVector<StringRef, 4> generatedOps;
588   for (auto op :
589        pattern.getRewriter().getBodyRegion().getOps<pdl::OperationOp>())
590     generatedOps.push_back(*op.getOpName());
591   ArrayAttr generatedOpsAttr;
592   if (!generatedOps.empty())
593     generatedOpsAttr = builder.getStrArrayAttr(generatedOps);
594 
595   // Grab the root kind if present.
596   StringAttr rootKindAttr;
597   if (pdl::OperationOp rootOp = root.getDefiningOp<pdl::OperationOp>())
598     if (Optional<StringRef> rootKind = rootOp.getOpName())
599       rootKindAttr = builder.getStringAttr(*rootKind);
600 
601   builder.setInsertionPointToEnd(currentBlock);
602   auto matchOp = builder.create<pdl_interp::RecordMatchOp>(
603       pattern.getLoc(), mappedMatchValues, locOps.getArrayRef(),
604       rewriterFuncRef, rootKindAttr, generatedOpsAttr, pattern.getBenefitAttr(),
605       failureBlockStack.back());
606 
607   // Set the config of the lowered match to the parent pattern.
608   if (configMap)
609     configMap->try_emplace(matchOp, configMap->lookup(pattern));
610 }
611 
612 SymbolRefAttr PatternLowering::generateRewriter(
613     pdl::PatternOp pattern, SmallVectorImpl<Position *> &usedMatchValues) {
614   builder.setInsertionPointToEnd(rewriterModule.getBody());
615   auto rewriterFunc = builder.create<pdl_interp::FuncOp>(
616       pattern.getLoc(), "pdl_generated_rewriter",
617       builder.getFunctionType(std::nullopt, std::nullopt));
618   rewriterSymbolTable.insert(rewriterFunc);
619 
620   // Generate the rewriter function body.
621   builder.setInsertionPointToEnd(&rewriterFunc.front());
622 
623   // Map an input operand of the pattern to a generated interpreter value.
624   DenseMap<Value, Value> rewriteValues;
625   auto mapRewriteValue = [&](Value oldValue) {
626     Value &newValue = rewriteValues[oldValue];
627     if (newValue)
628       return newValue;
629 
630     // Prefer materializing constants directly when possible.
631     Operation *oldOp = oldValue.getDefiningOp();
632     if (pdl::AttributeOp attrOp = dyn_cast<pdl::AttributeOp>(oldOp)) {
633       if (Attribute value = attrOp.getValueAttr()) {
634         return newValue = builder.create<pdl_interp::CreateAttributeOp>(
635                    attrOp.getLoc(), value);
636       }
637     } else if (pdl::TypeOp typeOp = dyn_cast<pdl::TypeOp>(oldOp)) {
638       if (TypeAttr type = typeOp.getConstantTypeAttr()) {
639         return newValue = builder.create<pdl_interp::CreateTypeOp>(
640                    typeOp.getLoc(), type);
641       }
642     } else if (pdl::TypesOp typeOp = dyn_cast<pdl::TypesOp>(oldOp)) {
643       if (ArrayAttr type = typeOp.getConstantTypesAttr()) {
644         return newValue = builder.create<pdl_interp::CreateTypesOp>(
645                    typeOp.getLoc(), typeOp.getType(), type);
646       }
647     }
648 
649     // Otherwise, add this as an input to the rewriter.
650     Position *inputPos = valueToPosition.lookup(oldValue);
651     assert(inputPos && "expected value to be a pattern input");
652     usedMatchValues.push_back(inputPos);
653     return newValue = rewriterFunc.front().addArgument(oldValue.getType(),
654                                                        oldValue.getLoc());
655   };
656 
657   // If this is a custom rewriter, simply dispatch to the registered rewrite
658   // method.
659   pdl::RewriteOp rewriter = pattern.getRewriter();
660   if (StringAttr rewriteName = rewriter.getNameAttr()) {
661     SmallVector<Value> args;
662     if (rewriter.getRoot())
663       args.push_back(mapRewriteValue(rewriter.getRoot()));
664     auto mappedArgs =
665         llvm::map_range(rewriter.getExternalArgs(), mapRewriteValue);
666     args.append(mappedArgs.begin(), mappedArgs.end());
667     builder.create<pdl_interp::ApplyRewriteOp>(
668         rewriter.getLoc(), /*resultTypes=*/TypeRange(), rewriteName, args);
669   } else {
670     // Otherwise this is a dag rewriter defined using PDL operations.
671     for (Operation &rewriteOp : *rewriter.getBody()) {
672       llvm::TypeSwitch<Operation *>(&rewriteOp)
673           .Case<pdl::ApplyNativeRewriteOp, pdl::AttributeOp, pdl::EraseOp,
674                 pdl::OperationOp, pdl::RangeOp, pdl::ReplaceOp, pdl::ResultOp,
675                 pdl::ResultsOp, pdl::TypeOp, pdl::TypesOp>([&](auto op) {
676             this->generateRewriter(op, rewriteValues, mapRewriteValue);
677           });
678     }
679   }
680 
681   // Update the signature of the rewrite function.
682   rewriterFunc.setType(builder.getFunctionType(
683       llvm::to_vector<8>(rewriterFunc.front().getArgumentTypes()),
684       /*results=*/std::nullopt));
685 
686   builder.create<pdl_interp::FinalizeOp>(rewriter.getLoc());
687   return SymbolRefAttr::get(
688       builder.getContext(),
689       pdl_interp::PDLInterpDialect::getRewriterModuleName(),
690       SymbolRefAttr::get(rewriterFunc));
691 }
692 
693 void PatternLowering::generateRewriter(
694     pdl::ApplyNativeRewriteOp rewriteOp, DenseMap<Value, Value> &rewriteValues,
695     function_ref<Value(Value)> mapRewriteValue) {
696   SmallVector<Value, 2> arguments;
697   for (Value argument : rewriteOp.getArgs())
698     arguments.push_back(mapRewriteValue(argument));
699   auto interpOp = builder.create<pdl_interp::ApplyRewriteOp>(
700       rewriteOp.getLoc(), rewriteOp.getResultTypes(), rewriteOp.getNameAttr(),
701       arguments);
702   for (auto it : llvm::zip(rewriteOp.getResults(), interpOp.getResults()))
703     rewriteValues[std::get<0>(it)] = std::get<1>(it);
704 }
705 
706 void PatternLowering::generateRewriter(
707     pdl::AttributeOp attrOp, DenseMap<Value, Value> &rewriteValues,
708     function_ref<Value(Value)> mapRewriteValue) {
709   Value newAttr = builder.create<pdl_interp::CreateAttributeOp>(
710       attrOp.getLoc(), attrOp.getValueAttr());
711   rewriteValues[attrOp] = newAttr;
712 }
713 
714 void PatternLowering::generateRewriter(
715     pdl::EraseOp eraseOp, DenseMap<Value, Value> &rewriteValues,
716     function_ref<Value(Value)> mapRewriteValue) {
717   builder.create<pdl_interp::EraseOp>(eraseOp.getLoc(),
718                                       mapRewriteValue(eraseOp.getOpValue()));
719 }
720 
721 void PatternLowering::generateRewriter(
722     pdl::OperationOp operationOp, DenseMap<Value, Value> &rewriteValues,
723     function_ref<Value(Value)> mapRewriteValue) {
724   SmallVector<Value, 4> operands;
725   for (Value operand : operationOp.getOperandValues())
726     operands.push_back(mapRewriteValue(operand));
727 
728   SmallVector<Value, 4> attributes;
729   for (Value attr : operationOp.getAttributeValues())
730     attributes.push_back(mapRewriteValue(attr));
731 
732   bool hasInferredResultTypes = false;
733   SmallVector<Value, 2> types;
734   generateOperationResultTypeRewriter(operationOp, mapRewriteValue, types,
735                                       rewriteValues, hasInferredResultTypes);
736 
737   // Create the new operation.
738   Location loc = operationOp.getLoc();
739   Value createdOp = builder.create<pdl_interp::CreateOperationOp>(
740       loc, *operationOp.getOpName(), types, hasInferredResultTypes, operands,
741       attributes, operationOp.getAttributeValueNames());
742   rewriteValues[operationOp.getOp()] = createdOp;
743 
744   // Generate accesses for any results that have their types constrained.
745   // Handle the case where there is a single range representing all of the
746   // result types.
747   OperandRange resultTys = operationOp.getTypeValues();
748   if (resultTys.size() == 1 && resultTys[0].getType().isa<pdl::RangeType>()) {
749     Value &type = rewriteValues[resultTys[0]];
750     if (!type) {
751       auto results = builder.create<pdl_interp::GetResultsOp>(loc, createdOp);
752       type = builder.create<pdl_interp::GetValueTypeOp>(loc, results);
753     }
754     return;
755   }
756 
757   // Otherwise, populate the individual results.
758   bool seenVariableLength = false;
759   Type valueTy = builder.getType<pdl::ValueType>();
760   Type valueRangeTy = pdl::RangeType::get(valueTy);
761   for (const auto &it : llvm::enumerate(resultTys)) {
762     Value &type = rewriteValues[it.value()];
763     if (type)
764       continue;
765     bool isVariadic = it.value().getType().isa<pdl::RangeType>();
766     seenVariableLength |= isVariadic;
767 
768     // After a variable length result has been seen, we need to use result
769     // groups because the exact index of the result is not statically known.
770     Value resultVal;
771     if (seenVariableLength)
772       resultVal = builder.create<pdl_interp::GetResultsOp>(
773           loc, isVariadic ? valueRangeTy : valueTy, createdOp, it.index());
774     else
775       resultVal = builder.create<pdl_interp::GetResultOp>(
776           loc, valueTy, createdOp, it.index());
777     type = builder.create<pdl_interp::GetValueTypeOp>(loc, resultVal);
778   }
779 }
780 
781 void PatternLowering::generateRewriter(
782     pdl::RangeOp rangeOp, DenseMap<Value, Value> &rewriteValues,
783     function_ref<Value(Value)> mapRewriteValue) {
784   SmallVector<Value, 4> replOperands;
785   for (Value operand : rangeOp.getArguments())
786     replOperands.push_back(mapRewriteValue(operand));
787   rewriteValues[rangeOp] = builder.create<pdl_interp::CreateRangeOp>(
788       rangeOp.getLoc(), rangeOp.getType(), replOperands);
789 }
790 
791 void PatternLowering::generateRewriter(
792     pdl::ReplaceOp replaceOp, DenseMap<Value, Value> &rewriteValues,
793     function_ref<Value(Value)> mapRewriteValue) {
794   SmallVector<Value, 4> replOperands;
795 
796   // If the replacement was another operation, get its results. `pdl` allows
797   // for using an operation for simplicitly, but the interpreter isn't as
798   // user facing.
799   if (Value replOp = replaceOp.getReplOperation()) {
800     // Don't use replace if we know the replaced operation has no results.
801     auto opOp = replaceOp.getOpValue().getDefiningOp<pdl::OperationOp>();
802     if (!opOp || !opOp.getTypeValues().empty()) {
803       replOperands.push_back(builder.create<pdl_interp::GetResultsOp>(
804           replOp.getLoc(), mapRewriteValue(replOp)));
805     }
806   } else {
807     for (Value operand : replaceOp.getReplValues())
808       replOperands.push_back(mapRewriteValue(operand));
809   }
810 
811   // If there are no replacement values, just create an erase instead.
812   if (replOperands.empty()) {
813     builder.create<pdl_interp::EraseOp>(
814         replaceOp.getLoc(), mapRewriteValue(replaceOp.getOpValue()));
815     return;
816   }
817 
818   builder.create<pdl_interp::ReplaceOp>(replaceOp.getLoc(),
819                                         mapRewriteValue(replaceOp.getOpValue()),
820                                         replOperands);
821 }
822 
823 void PatternLowering::generateRewriter(
824     pdl::ResultOp resultOp, DenseMap<Value, Value> &rewriteValues,
825     function_ref<Value(Value)> mapRewriteValue) {
826   rewriteValues[resultOp] = builder.create<pdl_interp::GetResultOp>(
827       resultOp.getLoc(), builder.getType<pdl::ValueType>(),
828       mapRewriteValue(resultOp.getParent()), resultOp.getIndex());
829 }
830 
831 void PatternLowering::generateRewriter(
832     pdl::ResultsOp resultOp, DenseMap<Value, Value> &rewriteValues,
833     function_ref<Value(Value)> mapRewriteValue) {
834   rewriteValues[resultOp] = builder.create<pdl_interp::GetResultsOp>(
835       resultOp.getLoc(), resultOp.getType(),
836       mapRewriteValue(resultOp.getParent()), resultOp.getIndex());
837 }
838 
839 void PatternLowering::generateRewriter(
840     pdl::TypeOp typeOp, DenseMap<Value, Value> &rewriteValues,
841     function_ref<Value(Value)> mapRewriteValue) {
842   // If the type isn't constant, the users (e.g. OperationOp) will resolve this
843   // type.
844   if (TypeAttr typeAttr = typeOp.getConstantTypeAttr()) {
845     rewriteValues[typeOp] =
846         builder.create<pdl_interp::CreateTypeOp>(typeOp.getLoc(), typeAttr);
847   }
848 }
849 
850 void PatternLowering::generateRewriter(
851     pdl::TypesOp typeOp, DenseMap<Value, Value> &rewriteValues,
852     function_ref<Value(Value)> mapRewriteValue) {
853   // If the type isn't constant, the users (e.g. OperationOp) will resolve this
854   // type.
855   if (ArrayAttr typeAttr = typeOp.getConstantTypesAttr()) {
856     rewriteValues[typeOp] = builder.create<pdl_interp::CreateTypesOp>(
857         typeOp.getLoc(), typeOp.getType(), typeAttr);
858   }
859 }
860 
861 void PatternLowering::generateOperationResultTypeRewriter(
862     pdl::OperationOp op, function_ref<Value(Value)> mapRewriteValue,
863     SmallVectorImpl<Value> &types, DenseMap<Value, Value> &rewriteValues,
864     bool &hasInferredResultTypes) {
865   Block *rewriterBlock = op->getBlock();
866 
867   // Try to handle resolution for each of the result types individually. This is
868   // preferred over type inferrence because it will allow for us to use existing
869   // types directly, as opposed to trying to rebuild the type list.
870   OperandRange resultTypeValues = op.getTypeValues();
871   auto tryResolveResultTypes = [&] {
872     types.reserve(resultTypeValues.size());
873     for (const auto &it : llvm::enumerate(resultTypeValues)) {
874       Value resultType = it.value();
875 
876       // Check for an already translated value.
877       if (Value existingRewriteValue = rewriteValues.lookup(resultType)) {
878         types.push_back(existingRewriteValue);
879         continue;
880       }
881 
882       // Check for an input from the matcher.
883       if (resultType.getDefiningOp()->getBlock() != rewriterBlock) {
884         types.push_back(mapRewriteValue(resultType));
885         continue;
886       }
887 
888       // Otherwise, we couldn't infer the result types. Bail out here to see if
889       // we can infer the types for this operation from another way.
890       types.clear();
891       return failure();
892     }
893     return success();
894   };
895   if (!resultTypeValues.empty() && succeeded(tryResolveResultTypes()))
896     return;
897 
898   // Otherwise, check if the operation has type inference support itself.
899   if (op.hasTypeInference()) {
900     hasInferredResultTypes = true;
901     return;
902   }
903 
904   // Look for an operation that was replaced by `op`. The result types will be
905   // inferred from the results that were replaced.
906   for (OpOperand &use : op.getOp().getUses()) {
907     // Check that the use corresponds to a ReplaceOp and that it is the
908     // replacement value, not the operation being replaced.
909     pdl::ReplaceOp replOpUser = dyn_cast<pdl::ReplaceOp>(use.getOwner());
910     if (!replOpUser || use.getOperandNumber() == 0)
911       continue;
912     // Make sure the replaced operation was defined before this one. PDL
913     // rewrites only have single block regions, so if the op isn't in the
914     // rewriter block (i.e. the current block of the operation) we already know
915     // it dominates (i.e. it's in the matcher).
916     Value replOpVal = replOpUser.getOpValue();
917     Operation *replacedOp = replOpVal.getDefiningOp();
918     if (replacedOp->getBlock() == rewriterBlock &&
919         !replacedOp->isBeforeInBlock(op))
920       continue;
921 
922     Value replacedOpResults = builder.create<pdl_interp::GetResultsOp>(
923         replacedOp->getLoc(), mapRewriteValue(replOpVal));
924     types.push_back(builder.create<pdl_interp::GetValueTypeOp>(
925         replacedOp->getLoc(), replacedOpResults));
926     return;
927   }
928 
929   // If the types could not be inferred from any context and there weren't any
930   // explicit result types, assume the user actually meant for the operation to
931   // have no results.
932   if (resultTypeValues.empty())
933     return;
934 
935   // The verifier asserts that the result types of each pdl.getOperation can be
936   // inferred. If we reach here, there is a bug either in the logic above or
937   // in the verifier for pdl.getOperation.
938   op->emitOpError() << "unable to infer result type for operation";
939   llvm_unreachable("unable to infer result type for operation");
940 }
941 
942 //===----------------------------------------------------------------------===//
943 // Conversion Pass
944 //===----------------------------------------------------------------------===//
945 
946 namespace {
947 struct PDLToPDLInterpPass
948     : public impl::ConvertPDLToPDLInterpBase<PDLToPDLInterpPass> {
949   PDLToPDLInterpPass() = default;
950   PDLToPDLInterpPass(const PDLToPDLInterpPass &rhs) = default;
951   PDLToPDLInterpPass(DenseMap<Operation *, PDLPatternConfigSet *> &configMap)
952       : configMap(&configMap) {}
953   void runOnOperation() final;
954 
955   /// A map containing the configuration for each pattern.
956   DenseMap<Operation *, PDLPatternConfigSet *> *configMap = nullptr;
957 };
958 } // namespace
959 
960 /// Convert the given module containing PDL pattern operations into a PDL
961 /// Interpreter operations.
962 void PDLToPDLInterpPass::runOnOperation() {
963   ModuleOp module = getOperation();
964 
965   // Create the main matcher function This function contains all of the match
966   // related functionality from patterns in the module.
967   OpBuilder builder = OpBuilder::atBlockBegin(module.getBody());
968   auto matcherFunc = builder.create<pdl_interp::FuncOp>(
969       module.getLoc(), pdl_interp::PDLInterpDialect::getMatcherFunctionName(),
970       builder.getFunctionType(builder.getType<pdl::OperationType>(),
971                               /*results=*/std::nullopt),
972       /*attrs=*/std::nullopt);
973 
974   // Create a nested module to hold the functions invoked for rewriting the IR
975   // after a successful match.
976   ModuleOp rewriterModule = builder.create<ModuleOp>(
977       module.getLoc(), pdl_interp::PDLInterpDialect::getRewriterModuleName());
978 
979   // Generate the code for the patterns within the module.
980   PatternLowering generator(matcherFunc, rewriterModule, configMap);
981   generator.lower(module);
982 
983   // After generation, delete all of the pattern operations.
984   for (pdl::PatternOp pattern :
985        llvm::make_early_inc_range(module.getOps<pdl::PatternOp>())) {
986     // Drop the now dead config mappings.
987     if (configMap)
988       configMap->erase(pattern);
989 
990     pattern.erase();
991   }
992 }
993 
994 std::unique_ptr<OperationPass<ModuleOp>> mlir::createPDLToPDLInterpPass() {
995   return std::make_unique<PDLToPDLInterpPass>();
996 }
997 std::unique_ptr<OperationPass<ModuleOp>> mlir::createPDLToPDLInterpPass(
998     DenseMap<Operation *, PDLPatternConfigSet *> &configMap) {
999   return std::make_unique<PDLToPDLInterpPass>(configMap);
1000 }
1001