1 //===- LinalgTransformOps.cpp - Implementation of Linalg transform ops ----===//
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/Dialect/Linalg/TransformOps/LinalgTransformOps.h"
10 
11 #include "mlir/Dialect/Linalg/IR/Linalg.h"
12 #include "mlir/Dialect/Linalg/Transforms/Transforms.h"
13 #include "mlir/Dialect/PDL/IR/PDL.h"
14 #include "mlir/Dialect/PDL/IR/PDLTypes.h"
15 #include "mlir/Dialect/Transform/IR/TransformDialect.h"
16 #include "mlir/Interfaces/SideEffectInterfaces.h"
17 #include "mlir/Parser/Parser.h"
18 #include "mlir/Transforms/GreedyPatternRewriteDriver.h"
19 #include "llvm/Support/FormatVariadic.h"
20 
21 using namespace mlir;
22 using namespace mlir::linalg;
23 using namespace mlir::transform;
24 
25 /// Extracts a vector of int64_t from an array attribute. Asserts if the
26 /// attribute contains values other than integers.
27 static SmallVector<int64_t> extractI64Array(ArrayAttr attr) {
28   SmallVector<int64_t> result;
29   result.reserve(attr.size());
30   for (APInt value : attr.getAsValueRange<IntegerAttr>())
31     result.push_back(value.getSExtValue());
32   return result;
33 }
34 
35 /// Extracts a vector of unsigned from an array attribute. Asserts if the
36 /// attribute contains values other than intergers. May truncate.
37 static SmallVector<unsigned> extractUIntArray(ArrayAttr attr) {
38   SmallVector<unsigned> result;
39   result.reserve(attr.size());
40   for (APInt value : attr.getAsValueRange<IntegerAttr>())
41     result.push_back(value.getZExtValue());
42   return result;
43 }
44 
45 namespace {
46 /// A simple pattern rewriter that implements no special logic.
47 class SimpleRewriter : public PatternRewriter {
48 public:
49   SimpleRewriter(MLIRContext *context) : PatternRewriter(context) {}
50 };
51 } // namespace
52 
53 /// Attempts to apply the pattern specified as template argument to the given
54 /// operation. The pattern is expected to have a `returningMatchAndRewrite`
55 /// function that returns the "main" result or failure. Returns failure if the
56 /// pattern failed to apply. Extra arguments are forwarded to the pattern
57 /// constructor.
58 template <typename PatternTy, typename... Args>
59 static FailureOr<LinalgOp> tryApply(Operation *operation, Args &&...args) {
60   // Check if the given operation has the type expected by the pattern.
61   using OpTy = typename llvm::function_traits<
62       decltype(&PatternTy::returningMatchAndRewrite)>::template arg_t<0>;
63   auto op = dyn_cast<OpTy>(operation);
64   if (!op)
65     return failure();
66 
67   // Apply the pattern directly to the op.
68   PatternTy pattern(operation->getContext(), std::forward<Args>(args)...);
69   SimpleRewriter rewriter(operation->getContext());
70   rewriter.setInsertionPoint(operation);
71   auto result = pattern.returningMatchAndRewrite(op, rewriter);
72   if (failed(result))
73     return failure();
74   return cast<LinalgOp>(result->getOperation());
75 }
76 
77 //===----------------------------------------------------------------------===//
78 // DecomposeOp
79 //===----------------------------------------------------------------------===//
80 
81 FailureOr<LinalgOp> transform::DecomposeOp::applyToOne(LinalgOp target) {
82   FailureOr<LinalgOp> windowed =
83       tryApply<DownscaleSizeOneWindowed2DConvolution>(target);
84   if (succeeded(windowed))
85     return windowed;
86 
87   FailureOr<LinalgOp> depthwise =
88       tryApply<DownscaleDepthwiseConv2DNhwcHwcOp>(target);
89   if (succeeded(depthwise))
90     return depthwise;
91 
92   return reportUnknownTransformError(target);
93 }
94 
95 //===----------------------------------------------------------------------===//
96 // GeneralizeOp
97 //===----------------------------------------------------------------------===//
98 
99 FailureOr<LinalgOp> transform::GeneralizeOp::applyToOne(LinalgOp target) {
100   // Exit early if no transformation is needed.
101   if (isa<GenericOp>(target))
102     return target;
103 
104   FailureOr<LinalgOp> generic = tryApply<LinalgGeneralizationPattern>(target);
105   if (succeeded(generic))
106     return generic;
107 
108   return reportUnknownTransformError(target);
109 }
110 
111 //===----------------------------------------------------------------------===//
112 // InterchangeOp
113 //===----------------------------------------------------------------------===//
114 
115 FailureOr<LinalgOp> transform::InterchangeOp::applyToOne(LinalgOp target) {
116   SmallVector<unsigned> interchangeVector =
117       extractUIntArray(getIteratorInterchange());
118   // Exit early if no transformation is needed.
119   if (interchangeVector.empty())
120     return target;
121 
122   auto genericTarget = dyn_cast<GenericOp>(target.getOperation());
123   if (!genericTarget) {
124     InFlightDiagnostic diag = emitOpError()
125                               << "applies to " << GenericOp::getOperationName()
126                               << " ops";
127     diag.attachNote(target.getLoc()) << "attempted to apply to this op";
128     return diag;
129   }
130 
131   return tryApply<GenericOpInterchangePattern>(target, interchangeVector);
132 }
133 
134 LogicalResult transform::InterchangeOp::verify() {
135   SmallVector<unsigned> permutation =
136       extractUIntArray(getIteratorInterchange());
137   auto sequence = llvm::to_vector(llvm::seq<unsigned>(0, permutation.size()));
138   if (!std::is_permutation(sequence.begin(), sequence.end(),
139                            permutation.begin(), permutation.end())) {
140     return emitOpError()
141            << "expects iterator_interchange to be a permutation, found "
142            << getIteratorInterchange();
143   }
144   return success();
145 }
146 
147 //===---------------------------------------------------------------------===//
148 // PadOp
149 //===---------------------------------------------------------------------===//
150 
151 FailureOr<LinalgOp> transform::PadOp::applyToOne(LinalgOp target) {
152   // Convert the integer packing flags to booleans.
153   SmallVector<bool> packPaddings;
154   for (int64_t packPadding : extractI64Array(getPackPaddings()))
155     packPaddings.push_back(static_cast<bool>(packPadding));
156 
157   // Convert the padding values to attributes.
158   SmallVector<Attribute> paddingValues;
159   for (auto const &it :
160        llvm::zip(getPaddingValues(), target->getOperandTypes())) {
161     Attribute attr = std::get<0>(it);
162     Type elementType = getElementTypeOrSelf(std::get<1>(it));
163     // Try to parse string attributes to obtain an attribute of element type.
164     if (auto stringAttr = attr.dyn_cast<StringAttr>()) {
165       paddingValues.push_back(
166           parseAttribute(attr.cast<StringAttr>(), elementType));
167       if (!paddingValues.back()) {
168         InFlightDiagnostic diag = emitOpError()
169                                   << "expects a padding value that parses to "
170                                   << elementType << ", got " << std::get<0>(it);
171         diag.attachNote(target.getLoc()) << "when applied to this op";
172         return diag;
173       }
174       continue;
175     }
176     // Otherwise, add the attribute directly.
177     if (attr.getType() != elementType) {
178       InFlightDiagnostic diag = emitOpError()
179                                 << "expects a padding value of type "
180                                 << elementType << ", got " << attr;
181       diag.attachNote(target.getLoc()) << "when applied to this op";
182       return diag;
183     }
184     paddingValues.push_back(attr);
185   }
186 
187   // Extract the transpose vectors.
188   SmallVector<SmallVector<int64_t>> transposePaddings;
189   for (Attribute transposeVector : getTransposePaddings().cast<ArrayAttr>())
190     transposePaddings.push_back(
191         extractI64Array(transposeVector.cast<ArrayAttr>()));
192 
193   LinalgPaddingOptions paddingOptions;
194   paddingOptions.setPaddingValues(paddingValues);
195   paddingOptions.setPaddingDimensions(extractI64Array(getPaddingDimensions()));
196   paddingOptions.setPackPaddings(packPaddings);
197   paddingOptions.setHoistPaddings(extractI64Array(getHoistPaddings()));
198   paddingOptions.setTransposePaddings(transposePaddings);
199 
200   FailureOr<LinalgOp> result =
201       tryApply<LinalgPaddingPattern>(target, paddingOptions);
202   if (succeeded(result))
203     return result;
204 
205   InFlightDiagnostic diag = emitError()
206                             << "failed to apply pattern to target op";
207   diag.attachNote(target.getLoc()) << "target op";
208   return diag;
209 }
210 
211 LogicalResult transform::PadOp::verify() {
212   SmallVector<int64_t> packPaddings = extractI64Array(getPackPaddings());
213   if (any_of(packPaddings, [](int64_t packPadding) {
214         return packPadding != 0 && packPadding != 1;
215       })) {
216     return emitOpError()
217            << "expects pack_paddings to contain booleans (0/1), found "
218            << getPackPaddings();
219   }
220 
221   SmallVector<int64_t> paddingDimensions =
222       extractI64Array(getPaddingDimensions());
223   if (any_of(paddingDimensions,
224              [](int64_t paddingDimension) { return paddingDimension < 0; })) {
225     return emitOpError()
226            << "expects padding_dimensions to contain positive integers, found "
227            << getPaddingDimensions();
228   }
229 
230   SmallVector<int64_t> hoistPaddings = extractI64Array(getHoistPaddings());
231   if (any_of(hoistPaddings,
232              [](int64_t hoistPadding) { return hoistPadding < 0; })) {
233     return emitOpError()
234            << "expects hoist_paddings to contain positive integers, found "
235            << getHoistPaddings();
236   }
237 
238   ArrayAttr transposes = getTransposePaddings();
239   for (Attribute attr : transposes) {
240     SmallVector<int64_t> transpose = extractFromI64ArrayAttr(attr);
241     auto sequence = llvm::to_vector(llvm::seq<int64_t>(0, transpose.size()));
242     if (!std::is_permutation(sequence.begin(), sequence.end(),
243                              transpose.begin(), transpose.end())) {
244       return emitOpError()
245              << "expects transpose_paddings to be a permutation, found "
246              << attr;
247     }
248   }
249   return success();
250 }
251 
252 //===----------------------------------------------------------------------===//
253 // ScalarizeOp
254 //===----------------------------------------------------------------------===//
255 
256 FailureOr<LinalgOp> transform::ScalarizeOp::applyToOne(LinalgOp target) {
257   LinalgTilingOptions tilingOptions;
258   tilingOptions.scalarizeDynamicDims();
259   // Tiling with "scalarize_dyn_dims" actually sets the same lambda as the tile
260   // sizes and asserts that it is not already set.
261   SmallVector<int64_t> emptyTileSizes;
262   LinalgTilingPattern pattern(getContext(), tilingOptions);
263   SimpleRewriter rewriter(getContext());
264   rewriter.setInsertionPoint(target);
265   FailureOr<TiledLinalgOp> result =
266       pattern.returningMatchAndRewrite(target, rewriter);
267   if (failed(result))
268     return failure();
269 
270   return result->op;
271 }
272 
273 //===----------------------------------------------------------------------===//
274 // TileOp
275 //===----------------------------------------------------------------------===//
276 
277 /// Apply a tiling transformation to all payload ops and store both the
278 /// tiled operation as well as the created tile loops.
279 static LogicalResult
280 applyTilingToAll(Operation *transformOp, Value target,
281                  ArrayRef<int64_t> tileSizes,
282                  transform::TransformResults &transformResults,
283                  transform::TransformState &state,
284                  function_ref<FailureOr<TiledLinalgOp>(LinalgOp)> applyFn) {
285   // Number of loops: Number of tiles sizes that are not zero.
286   size_t numLoops = tileSizes.size() - llvm::count(tileSizes, 0);
287   // All payload ops. These should all be LinalgOps for now.
288   ArrayRef<Operation *> payloadOps = state.getPayloadOps(target);
289 
290   SmallVector<Operation *> tiledLinalgOps;
291   SmallVector<SmallVector<Operation *>> loopOps(numLoops);
292   for (unsigned int i = 0; i < numLoops; ++i)
293     loopOps[i].reserve(payloadOps.size());
294 
295   for (Operation *target : payloadOps) {
296     auto linalgOp = dyn_cast<linalg::LinalgOp>(target);
297     if (!linalgOp)
298       return transformOp->emitError("only LinalgOps are supported");
299 
300     FailureOr<TiledLinalgOp> tiled = applyFn(linalgOp);
301     if (failed(tiled))
302       return failure();
303 
304     tiledLinalgOps.push_back(tiled->op);
305     if (tiled->loops.size() != numLoops)
306       // Not enough loops were generated. This usually means that the input size
307       // was smaller than the tiling size.
308       // TODO: LinalgTilingPattern should return failure().
309       return failure();
310     for (unsigned int i = 0; i < numLoops; ++i)
311       loopOps[i].push_back(tiled->loops[i]);
312   }
313 
314   transformResults.set(transformOp->getOpResult(0), tiledLinalgOps);
315   for (unsigned int i = 0; i < numLoops; ++i)
316     transformResults.set(transformOp->getOpResult(i + 1), loopOps[i]);
317   return success();
318 }
319 
320 LogicalResult transform::TileOp::apply(TransformResults &transformResults,
321                                        TransformState &state) {
322   LinalgTilingOptions tilingOptions;
323   SmallVector<int64_t> tileSizes = extractI64Array(getSizes());
324 
325   if (!tileSizes.empty())
326     tilingOptions.setTileSizes(tileSizes);
327   tilingOptions.setInterchange(extractUIntArray(getInterchange()));
328   LinalgTilingPattern pattern(getContext(), tilingOptions);
329 
330   return applyTilingToAll(getOperation(), getTarget(), tileSizes,
331                           transformResults, state, [&](LinalgOp linalgOp) {
332                             SimpleRewriter rewriter(linalgOp.getContext());
333                             return pattern.returningMatchAndRewrite(linalgOp,
334                                                                     rewriter);
335                           });
336 }
337 
338 ParseResult transform::TileOp::parse(OpAsmParser &parser,
339                                      OperationState &result) {
340   StringRef sizesAttrName = TileOp::getSizesAttrName(result.name).getValue();
341   OpAsmParser::UnresolvedOperand targetOperand;
342   SMLoc opLoc = parser.getCurrentLocation();
343   if (parser.parseOperand(targetOperand) ||
344       parser.parseOptionalAttrDict(result.attributes))
345     return failure();
346   Attribute sizesAttr = result.attributes.get(sizesAttrName);
347   if (!sizesAttr)
348     return parser.emitError(opLoc)
349            << "expected '" << sizesAttrName << "' attribute";
350   auto sizesArrayAttr = sizesAttr.dyn_cast<ArrayAttr>();
351   if (!sizesArrayAttr)
352     return parser.emitError(opLoc)
353            << "'" << sizesAttrName << "' attribute must be an array";
354   Type pdlOpType = parser.getBuilder().getType<pdl::OperationType>();
355   size_t numExpectedLoops =
356       sizesArrayAttr.size() - llvm::count(extractI64Array(sizesArrayAttr), 0);
357   result.addTypes(SmallVector<Type>(numExpectedLoops + 1, pdlOpType));
358   if (parser.resolveOperand(targetOperand, pdlOpType, result.operands))
359     return failure();
360   return success();
361 }
362 
363 void TileOp::print(OpAsmPrinter &p) {
364   p << ' ';
365   p << getTarget();
366   p.printOptionalAttrDict((*this)->getAttrs());
367 }
368 
369 void TileOp::getEffects(
370     SmallVectorImpl<SideEffects::EffectInstance<MemoryEffects::Effect>>
371         &effects) {
372   // `target` arg is consumed and can no longer be used.
373   effects.emplace_back(MemoryEffects::Read::get(), getTarget(),
374                        TransformMappingResource::get());
375   effects.emplace_back(MemoryEffects::Free::get(), getTarget(),
376                        TransformMappingResource::get());
377 
378   for (Value r : getResults()) {
379     effects.emplace_back(MemoryEffects::Write::get(), r,
380                          TransformMappingResource::get());
381     effects.emplace_back(MemoryEffects::Allocate::get(), r,
382                          TransformMappingResource::get());
383   }
384 
385   effects.emplace_back(MemoryEffects::Read::get(), PayloadIRResource::get());
386   effects.emplace_back(MemoryEffects::Write::get(), PayloadIRResource::get());
387 }
388 
389 //===----------------------------------------------------------------------===//
390 // VectorizeOp
391 //===----------------------------------------------------------------------===//
392 
393 FailureOr<Operation *> VectorizeOp::applyToOne(Operation *target) {
394   if (!target->hasTrait<OpTrait::IsIsolatedFromAbove>()) {
395     InFlightDiagnostic diag = emitOpError()
396                               << "applies only to isolated-from-above targets";
397     diag.attachNote(target->getLoc()) << "non-isolated target";
398     return diag;
399   }
400 
401   MLIRContext *ctx = getContext();
402   RewritePatternSet patterns(ctx);
403   patterns.add<LinalgVectorizationPattern>(ctx);
404 
405   vector::populateVectorTransferPermutationMapLoweringPatterns(patterns);
406   vector::populateVectorReductionToContractPatterns(patterns);
407   patterns.add<linalg::LinalgCopyVTRForwardingPattern,
408                linalg::LinalgCopyVTWForwardingPattern>(ctx,
409                                                        /*benefit=*/2);
410   vector::TransferReadOp::getCanonicalizationPatterns(patterns, ctx);
411   vector::TransferWriteOp::getCanonicalizationPatterns(patterns, ctx);
412   if (getVectorizePadding())
413     linalg::populatePadOpVectorizationPatterns(patterns);
414 
415   if (failed(applyPatternsAndFoldGreedily(target, std::move(patterns))))
416     return reportUnknownTransformError(target);
417   return target;
418 }
419 
420 //===----------------------------------------------------------------------===//
421 // Transform op registration
422 //===----------------------------------------------------------------------===//
423 
424 namespace {
425 /// Registers new ops and declares PDL as dependent dialect since the additional
426 /// ops are using PDL types for operands and results.
427 class LinalgTransformDialectExtension
428     : public transform::TransformDialectExtension<
429           LinalgTransformDialectExtension> {
430 public:
431   LinalgTransformDialectExtension() {
432     declareDependentDialect<pdl::PDLDialect>();
433     declareDependentDialect<scf::SCFDialect>();
434     declareDependentDialect<vector::VectorDialect>();
435     registerTransformOps<
436 #define GET_OP_LIST
437 #include "mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp.inc"
438         >();
439   }
440 };
441 } // namespace
442 
443 #define GET_OP_CLASSES
444 #include "mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp.inc"
445 
446 void mlir::linalg::registerTransformDialectExtension(
447     DialectRegistry &registry) {
448   registry.addExtensions<LinalgTransformDialectExtension>();
449 }
450