1 //===- Bufferize.cpp - Bufferization utilities ----------------------------===//
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 "PassDetail.h"
10 
11 #include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"
12 #include "mlir/Dialect/Bufferization/IR/Bufferization.h"
13 #include "mlir/Dialect/Bufferization/Transforms/Bufferize.h"
14 #include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h"
15 #include "mlir/Dialect/Bufferization/Transforms/OneShotModuleBufferize.h"
16 #include "mlir/Dialect/Bufferization/Transforms/Passes.h"
17 #include "mlir/Dialect/Func/IR/FuncOps.h"
18 #include "mlir/Dialect/MemRef/IR/MemRef.h"
19 #include "mlir/IR/Operation.h"
20 #include "mlir/Pass/PassManager.h"
21 #include "mlir/Transforms/GreedyPatternRewriteDriver.h"
22 #include "mlir/Transforms/Passes.h"
23 
24 using namespace mlir;
25 using namespace mlir::bufferization;
26 
27 //===----------------------------------------------------------------------===//
28 // BufferizeTypeConverter
29 //===----------------------------------------------------------------------===//
30 
31 static Value materializeToTensor(OpBuilder &builder, TensorType type,
32                                  ValueRange inputs, Location loc) {
33   assert(inputs.size() == 1);
34   assert(inputs[0].getType().isa<BaseMemRefType>());
35   return builder.create<bufferization::ToTensorOp>(loc, type, inputs[0]);
36 }
37 
38 /// Registers conversions into BufferizeTypeConverter
39 BufferizeTypeConverter::BufferizeTypeConverter() {
40   // Keep all types unchanged.
41   addConversion([](Type type) { return type; });
42   // Convert RankedTensorType to MemRefType.
43   addConversion([](RankedTensorType type) -> Type {
44     return MemRefType::get(type.getShape(), type.getElementType());
45   });
46   // Convert UnrankedTensorType to UnrankedMemRefType.
47   addConversion([](UnrankedTensorType type) -> Type {
48     return UnrankedMemRefType::get(type.getElementType(), 0);
49   });
50   addArgumentMaterialization(materializeToTensor);
51   addSourceMaterialization(materializeToTensor);
52   addTargetMaterialization([](OpBuilder &builder, BaseMemRefType type,
53                               ValueRange inputs, Location loc) -> Value {
54     assert(inputs.size() == 1 && "expected exactly one input");
55 
56     if (auto inputType = inputs[0].getType().dyn_cast<MemRefType>()) {
57       // MemRef to MemRef cast.
58       assert(inputType != type && "expected different types");
59       // Unranked to ranked and ranked to unranked casts must be explicit.
60       auto rankedDestType = type.dyn_cast<MemRefType>();
61       if (!rankedDestType)
62         return nullptr;
63       FailureOr<Value> replacement =
64           castOrReallocMemRefValue(builder, inputs[0], rankedDestType);
65       if (failed(replacement))
66         return nullptr;
67       return *replacement;
68     }
69 
70     if (inputs[0].getType().isa<TensorType>()) {
71       // Tensor to MemRef cast.
72       return builder.create<bufferization::ToMemrefOp>(loc, type, inputs[0]);
73     }
74 
75     llvm_unreachable("only tensor/memref input types supported");
76   });
77 }
78 
79 void mlir::bufferization::populateBufferizeMaterializationLegality(
80     ConversionTarget &target) {
81   target.addLegalOp<bufferization::ToTensorOp, bufferization::ToMemrefOp>();
82 }
83 
84 namespace {
85 // In a finalizing bufferize conversion, we know that all tensors have been
86 // converted to memrefs, thus, this op becomes an identity.
87 class BufferizeToTensorOp
88     : public OpConversionPattern<bufferization::ToTensorOp> {
89 public:
90   using OpConversionPattern::OpConversionPattern;
91   LogicalResult
92   matchAndRewrite(bufferization::ToTensorOp op, OpAdaptor adaptor,
93                   ConversionPatternRewriter &rewriter) const override {
94     rewriter.replaceOp(op, adaptor.memref());
95     return success();
96   }
97 };
98 } // namespace
99 
100 namespace {
101 // In a finalizing bufferize conversion, we know that all tensors have been
102 // converted to memrefs, thus, this op becomes an identity.
103 class BufferizeToMemrefOp
104     : public OpConversionPattern<bufferization::ToMemrefOp> {
105 public:
106   using OpConversionPattern::OpConversionPattern;
107   LogicalResult
108   matchAndRewrite(bufferization::ToMemrefOp op, OpAdaptor adaptor,
109                   ConversionPatternRewriter &rewriter) const override {
110     rewriter.replaceOp(op, adaptor.tensor());
111     return success();
112   }
113 };
114 } // namespace
115 
116 void mlir::bufferization::populateEliminateBufferizeMaterializationsPatterns(
117     BufferizeTypeConverter &typeConverter, RewritePatternSet &patterns) {
118   patterns.add<BufferizeToTensorOp, BufferizeToMemrefOp>(typeConverter,
119                                                          patterns.getContext());
120 }
121 
122 namespace {
123 struct FinalizingBufferizePass
124     : public FinalizingBufferizeBase<FinalizingBufferizePass> {
125   using FinalizingBufferizeBase<
126       FinalizingBufferizePass>::FinalizingBufferizeBase;
127 
128   void runOnOperation() override {
129     auto func = getOperation();
130     auto *context = &getContext();
131 
132     BufferizeTypeConverter typeConverter;
133     RewritePatternSet patterns(context);
134     ConversionTarget target(*context);
135 
136     populateEliminateBufferizeMaterializationsPatterns(typeConverter, patterns);
137 
138     // If all result types are legal, and all block arguments are legal (ensured
139     // by func conversion above), then all types in the program are legal.
140     //
141     // We also check that the operand types are legal to avoid creating invalid
142     // IR. For example, this prevents
143     // populateEliminateBufferizeMaterializationsPatterns from updating the
144     // types of the operands to a return op without updating the enclosing
145     // function.
146     target.markUnknownOpDynamicallyLegal(
147         [&](Operation *op) { return typeConverter.isLegal(op); });
148 
149     if (failed(applyFullConversion(func, target, std::move(patterns))))
150       signalPassFailure();
151   }
152 };
153 
154 static BufferizationOptions::LayoutMapOption
155 parseLayoutMapOption(std::string s) {
156   if (s == "fully-dynamic-layout-map")
157     return BufferizationOptions::LayoutMapOption::FullyDynamicLayoutMap;
158   if (s == "identity-layout-map")
159     return BufferizationOptions::LayoutMapOption::IdentityLayoutMap;
160   if (s == "infer-layout-map")
161     return BufferizationOptions::LayoutMapOption::InferLayoutMap;
162   llvm_unreachable("invalid layout map option");
163 }
164 
165 struct OneShotBufferizePass
166     : public OneShotBufferizeBase<OneShotBufferizePass> {
167   OneShotBufferizePass() : OneShotBufferizeBase<OneShotBufferizePass>() {}
168 
169   explicit OneShotBufferizePass(const OneShotBufferizationOptions &options)
170       : options(options) {}
171 
172   void getDependentDialects(DialectRegistry &registry) const override {
173     registry
174         .insert<bufferization::BufferizationDialect, memref::MemRefDialect>();
175     registerAllocationOpInterfaceExternalModels(registry);
176   }
177 
178   void runOnOperation() override {
179     OneShotBufferizationOptions opt;
180     if (!options) {
181       // Make new bufferization options if none were provided when creating the
182       // pass.
183       opt.dropEquivalentFuncResults = dropEquivalentFuncResults;
184       opt.allowReturnAllocs = allowReturnAllocs;
185       opt.allowUnknownOps = allowUnknownOps;
186       opt.alwaysAliasingWithDest = alwaysAliasingWithDest;
187       opt.analysisFuzzerSeed = analysisFuzzerSeed;
188       opt.createDeallocs = createDeallocs;
189       opt.functionBoundaryTypeConversion =
190           parseLayoutMapOption(functionBoundaryTypeConversion);
191       opt.printConflicts = printConflicts;
192       opt.testAnalysisOnly = testAnalysisOnly;
193       opt.bufferizeFunctionBoundaries = bufferizeFunctionBoundaries;
194       opt.promoteBufferResultsToOutParams = promoteBufferResultsToOutParams;
195       opt.unknownTypeConversion = parseLayoutMapOption(unknownTypeConversion);
196 
197       BufferizationOptions::OpFilterEntry::FilterFn filterFn =
198           [&](Operation *op) {
199             // Filter may be specified via options.
200             if (this->dialectFilter.hasValue())
201               return llvm::find(this->dialectFilter,
202                                 op->getDialect()->getNamespace()) !=
203                      this->dialectFilter.end();
204             // No filter specified: All other ops are allowed.
205             return true;
206           };
207       opt.allowOperationInFilter(filterFn);
208     } else {
209       opt = *options;
210     }
211 
212     ModuleOp moduleOp = getOperation();
213     if (opt.bufferizeFunctionBoundaries) {
214       if (failed(runOneShotModuleBufferize(moduleOp, opt))) {
215         signalPassFailure();
216         return;
217       }
218     } else {
219       if (failed(runOneShotBufferize(moduleOp, opt))) {
220         signalPassFailure();
221         return;
222       }
223     }
224 
225     if (opt.testAnalysisOnly)
226       return;
227 
228     OpPassManager cleanupPipeline("builtin.module");
229     cleanupPipeline.addPass(createCanonicalizerPass());
230     cleanupPipeline.addPass(createCSEPass());
231     cleanupPipeline.addPass(createLoopInvariantCodeMotionPass());
232     (void)runPipeline(cleanupPipeline, moduleOp);
233   }
234 
235 private:
236   llvm::Optional<OneShotBufferizationOptions> options;
237 };
238 } // namespace
239 
240 std::unique_ptr<Pass> mlir::bufferization::createOneShotBufferizePass() {
241   return std::make_unique<OneShotBufferizePass>();
242 }
243 
244 std::unique_ptr<Pass> mlir::bufferization::createOneShotBufferizePass(
245     const OneShotBufferizationOptions &options) {
246   return std::make_unique<OneShotBufferizePass>(options);
247 }
248 
249 std::unique_ptr<OperationPass<func::FuncOp>>
250 mlir::bufferization::createFinalizingBufferizePass() {
251   return std::make_unique<FinalizingBufferizePass>();
252 }
253 
254 //===----------------------------------------------------------------------===//
255 // BufferizableOpInterface-based Bufferization
256 //===----------------------------------------------------------------------===//
257 
258 static bool isaTensor(Type t) { return t.isa<TensorType>(); }
259 
260 /// Return true if the given op has a tensor result or a tensor operand.
261 static bool hasTensorSemantics(Operation *op) {
262   if (auto funcOp = dyn_cast<FunctionOpInterface>(op)) {
263     bool hasTensorArg = any_of(funcOp.getArgumentTypes(), isaTensor);
264     bool hasTensorResult = any_of(funcOp.getResultTypes(), isaTensor);
265     return hasTensorArg || hasTensorResult;
266   }
267 
268   bool hasTensorResult = any_of(op->getResultTypes(), isaTensor);
269   bool hasTensorOperand = any_of(op->getOperandTypes(), isaTensor);
270   return hasTensorResult || hasTensorOperand;
271 }
272 
273 LogicalResult
274 bufferization::finalizeBuffers(Operation *op,
275                                const BufferizationOptions &options) {
276   // Hoist buffers.
277   if (failed(hoistBufferAllocations(op, options)))
278     return failure();
279 
280   // Create allocation ops for "leaking buffers", i.e., buffer allocations that
281   // escape block boundaries. If there are no leaking allocs, `hasLeakingAllocs`
282   // is set to `false`.
283   bool hasLeakingAllocs = false;
284   if (failed(createAllocDeallocOps(op, options, /*onlyLeakingAllocs=*/true,
285                                    &hasLeakingAllocs)))
286     return failure();
287 
288   if (hasLeakingAllocs) {
289     // Promote returned buffers to "out" parameters.
290     // TODO: Pass options to support custom dealloc ops.
291     if (options.promoteBufferResultsToOutParams && isa<ModuleOp>(op) &&
292         failed(promoteBufferResultsToOutParams(cast<ModuleOp>(op))))
293       return failure();
294 
295     // Create deallocation ops for all "leaking buffers" and all buffer
296     // allocations that were added during the above promotion process.
297     // TODO: Pass options to support custom dealloc ops.
298     if (options.createDeallocs && failed(deallocateBuffers(op)))
299       return failure();
300   }
301 
302   // Deallocate all remaining buffers at the end of their parent blocks.
303   if (failed(createAllocDeallocOps(op, options)))
304     return failure();
305 
306   return success();
307 }
308 
309 LogicalResult bufferization::bufferizeOp(Operation *op,
310                                          const AnalysisState &analysisState) {
311   // Catch incorrect API usage.
312   assert((analysisState.hasDialectState(
313               func::FuncDialect::getDialectNamespace()) ||
314           !analysisState.getOptions().bufferizeFunctionBoundaries) &&
315          "must use ModuleBufferize to bufferize function boundaries");
316 
317   BufferizationState bufferizationState(analysisState);
318   if (failed(bufferizeOp(op, bufferizationState)))
319     return failure();
320   if (failed(finalizeBuffers(op, analysisState.getOptions())))
321     return failure();
322   return success();
323 }
324 
325 namespace {
326 /// A rewriter that keeps track of extra information during bufferization.
327 class BufferizationRewriter : public IRRewriter {
328 public:
329   BufferizationRewriter(MLIRContext *ctx, DenseSet<Operation *> &erasedOps,
330                         DenseSet<Operation *> &toMemrefOps,
331                         const BufferizationOptions &options)
332       : IRRewriter(ctx), erasedOps(erasedOps), toMemrefOps(toMemrefOps),
333         options(options) {}
334 
335 protected:
336   void notifyOperationRemoved(Operation *op) override {
337     IRRewriter::notifyOperationRemoved(op);
338     erasedOps.insert(op);
339     // Erase if present.
340     toMemrefOps.erase(op);
341   }
342 
343   void notifyOperationInserted(Operation *op) override {
344     IRRewriter::notifyOperationInserted(op);
345 
346     // Keep track of to_memref ops.
347     if (isa<ToMemrefOp>(op)) {
348       toMemrefOps.insert(op);
349       return;
350     }
351 
352     // Skip to_tensor ops.
353     if (isa<ToTensorOp>(op))
354       return;
355 
356     // Adding new bufferizable ops is not allowed during bufferization. Such ops
357     // would not be analyzed and can lead to surprising behavior.
358     assert((!hasTensorSemantics(op) || !options.isOpAllowed(op)) &&
359            "creating new tensor ops is not allowed during bufferization");
360   }
361 
362 private:
363   /// A set of all erased ops.
364   DenseSet<Operation *> &erasedOps;
365 
366   /// A set of all to_memref ops.
367   DenseSet<Operation *> &toMemrefOps;
368 
369   /// The bufferization options.
370   const BufferizationOptions &options;
371 };
372 } // namespace
373 
374 LogicalResult
375 bufferization::bufferizeOp(Operation *op,
376                            BufferizationState &bufferizationState) {
377   const auto &options = bufferizationState.getOptions();
378   assert(options.unknownTypeConversion !=
379              BufferizationOptions::LayoutMapOption::InferLayoutMap &&
380          "invalid layout map option");
381 
382   // Keep track of to_memref ops.
383   DenseSet<Operation *> toMemrefOps;
384   op->walk([&](ToMemrefOp toMemrefOp) { toMemrefOps.insert(toMemrefOp); });
385 
386   // Gather all bufferizable ops in top-to-bottom order.
387   //
388   // We should ideally know the exact memref type of all operands when
389   // bufferizing an op. (This is the case when bufferizing top-to-bottom.)
390   // Otherwise, we have to use a memref type with a fully dynamic layout map to
391   // avoid copies. We are currently missing patterns for layout maps to
392   // canonicalize away (or canonicalize to more precise layouts).
393   SmallVector<Operation *> worklist;
394   op->walk<WalkOrder::PreOrder>([&](Operation *op) {
395     if (hasTensorSemantics(op))
396       worklist.push_back(op);
397   });
398 
399   // Keep track of all erased ops.
400   DenseSet<Operation *> erasedOps;
401 
402   // Bufferize all ops.
403   BufferizationRewriter rewriter(op->getContext(), erasedOps, toMemrefOps,
404                                  bufferizationState.getOptions());
405   for (unsigned i = 0; i < worklist.size(); ++i) {
406     Operation *op = worklist[i];
407     // Skip ops that were erased.
408     if (erasedOps.contains(op))
409       continue;
410     // Skip ops that are not bufferizable or not allowed.
411     auto bufferizableOp = options.dynCastBufferizableOp(op);
412     if (!bufferizableOp)
413       continue;
414     // Skip ops that no longer have tensor semantics.
415     if (!hasTensorSemantics(op))
416       continue;
417     // Bufferize the op.
418     rewriter.setInsertionPoint(op);
419     (void)bufferizableOp.bufferize(rewriter, bufferizationState);
420   }
421 
422   // Fold all to_memref(to_tensor(x)) pairs.
423   for (Operation *op : toMemrefOps) {
424     rewriter.setInsertionPoint(op);
425     (void)bufferization::foldToMemrefToTensorPair(rewriter,
426                                                   cast<ToMemrefOp>(op));
427   }
428 
429   /// Check the result of bufferization. Return an error if an op was not
430   /// bufferized, unless partial bufferization is allowed.
431   if (bufferizationState.getOptions().allowUnknownOps)
432     return success();
433 
434   for (Operation *op : worklist) {
435     // Skip ops that are entirely gone.
436     if (erasedOps.contains(op))
437       continue;
438     // Ops that no longer have tensor semantics (because they were updated
439     // in-place) are allowed.
440     if (!hasTensorSemantics(op))
441       continue;
442     // Continue ops that are not allowed.
443     if (!options.isOpAllowed(op))
444       continue;
445     // Ops without any uses and no side effects will fold away.
446     if (op->getUses().empty() && MemoryEffectOpInterface::hasNoEffect(op))
447       continue;
448     return op->emitError("op was not bufferized");
449   }
450 
451   return success();
452 }
453 
454 namespace {
455 /// This a "no analysis, always copy" AnalysisState. In the absence of an
456 /// analysis, a buffer must be copied each time it is written to. Therefore, all
457 /// OpOperands that bufferize to a memory write must bufferize out-of-place.
458 class AlwaysCopyAnalysisState : public AnalysisState {
459 public:
460   AlwaysCopyAnalysisState(const BufferizationOptions &options)
461       : AnalysisState(options) {}
462 
463   AlwaysCopyAnalysisState(const AlwaysCopyAnalysisState &) = delete;
464 
465   virtual ~AlwaysCopyAnalysisState() = default;
466 
467   /// Return `true` if the given OpResult has been decided to bufferize inplace.
468   bool isInPlace(OpOperand &opOperand) const override {
469     // OpOperands that bufferize to a memory write are out-of-place, i.e., an
470     // alloc and copy is inserted.
471     return !bufferizesToMemoryWrite(opOperand);
472   }
473 
474   /// Return true if `v1` and `v2` bufferize to equivalent buffers.
475   bool areEquivalentBufferizedValues(Value v1, Value v2) const override {
476     // There is no analysis, so we do not know if the values are equivalent. The
477     // conservative answer is "false".
478     return false;
479   }
480 };
481 } // namespace
482 
483 LogicalResult bufferization::bufferizeOp(Operation *op,
484                                          const BufferizationOptions &options) {
485   AlwaysCopyAnalysisState state(options);
486   return bufferizeOp(op, state);
487 }
488 
489 BufferizationOptions bufferization::getPartialBufferizationOptions() {
490   BufferizationOptions options;
491   options.allowUnknownOps = true;
492   options.createDeallocs = false;
493   options.unknownTypeConversion =
494       BufferizationOptions::LayoutMapOption::IdentityLayoutMap;
495   return options;
496 }
497