1 //===- VectorToLLVM.cpp - Conversion from Vector to the LLVM dialect ------===//
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/VectorToLLVM/ConvertVectorToLLVM.h"
10 #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h"
11 #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h"
12 #include "mlir/Dialect/LLVMIR/LLVMDialect.h"
13 #include "mlir/Dialect/StandardOps/Ops.h"
14 #include "mlir/Dialect/VectorOps/VectorOps.h"
15 #include "mlir/IR/Attributes.h"
16 #include "mlir/IR/Builders.h"
17 #include "mlir/IR/MLIRContext.h"
18 #include "mlir/IR/Module.h"
19 #include "mlir/IR/Operation.h"
20 #include "mlir/IR/PatternMatch.h"
21 #include "mlir/IR/StandardTypes.h"
22 #include "mlir/IR/Types.h"
23 #include "mlir/Pass/Pass.h"
24 #include "mlir/Pass/PassManager.h"
25 #include "mlir/Transforms/DialectConversion.h"
26 #include "mlir/Transforms/Passes.h"
27 
28 #include "llvm/IR/DerivedTypes.h"
29 #include "llvm/IR/Module.h"
30 #include "llvm/IR/Type.h"
31 #include "llvm/Support/Allocator.h"
32 #include "llvm/Support/ErrorHandling.h"
33 
34 using namespace mlir;
35 using namespace mlir::vector;
36 
37 template <typename T>
38 static LLVM::LLVMType getPtrToElementType(T containerType,
39                                           LLVMTypeConverter &lowering) {
40   return lowering.convertType(containerType.getElementType())
41       .template cast<LLVM::LLVMType>()
42       .getPointerTo();
43 }
44 
45 // Helper to reduce vector type by one rank at front.
46 static VectorType reducedVectorTypeFront(VectorType tp) {
47   assert((tp.getRank() > 1) && "unlowerable vector type");
48   return VectorType::get(tp.getShape().drop_front(), tp.getElementType());
49 }
50 
51 // Helper to reduce vector type by *all* but one rank at back.
52 static VectorType reducedVectorTypeBack(VectorType tp) {
53   assert((tp.getRank() > 1) && "unlowerable vector type");
54   return VectorType::get(tp.getShape().take_back(), tp.getElementType());
55 }
56 
57 // Helper that picks the proper sequence for inserting.
58 static Value insertOne(ConversionPatternRewriter &rewriter,
59                        LLVMTypeConverter &lowering, Location loc, Value val1,
60                        Value val2, Type llvmType, int64_t rank, int64_t pos) {
61   if (rank == 1) {
62     auto idxType = rewriter.getIndexType();
63     auto constant = rewriter.create<LLVM::ConstantOp>(
64         loc, lowering.convertType(idxType),
65         rewriter.getIntegerAttr(idxType, pos));
66     return rewriter.create<LLVM::InsertElementOp>(loc, llvmType, val1, val2,
67                                                   constant);
68   }
69   return rewriter.create<LLVM::InsertValueOp>(loc, llvmType, val1, val2,
70                                               rewriter.getI64ArrayAttr(pos));
71 }
72 
73 // Helper that picks the proper sequence for inserting.
74 static Value insertOne(PatternRewriter &rewriter, Location loc, Value from,
75                        Value into, int64_t offset) {
76   auto vectorType = into.getType().cast<VectorType>();
77   if (vectorType.getRank() > 1)
78     return rewriter.create<InsertOp>(loc, from, into, offset);
79   return rewriter.create<vector::InsertElementOp>(
80       loc, vectorType, from, into,
81       rewriter.create<ConstantIndexOp>(loc, offset));
82 }
83 
84 // Helper that picks the proper sequence for extracting.
85 static Value extractOne(ConversionPatternRewriter &rewriter,
86                         LLVMTypeConverter &lowering, Location loc, Value val,
87                         Type llvmType, int64_t rank, int64_t pos) {
88   if (rank == 1) {
89     auto idxType = rewriter.getIndexType();
90     auto constant = rewriter.create<LLVM::ConstantOp>(
91         loc, lowering.convertType(idxType),
92         rewriter.getIntegerAttr(idxType, pos));
93     return rewriter.create<LLVM::ExtractElementOp>(loc, llvmType, val,
94                                                    constant);
95   }
96   return rewriter.create<LLVM::ExtractValueOp>(loc, llvmType, val,
97                                                rewriter.getI64ArrayAttr(pos));
98 }
99 
100 // Helper that picks the proper sequence for extracting.
101 static Value extractOne(PatternRewriter &rewriter, Location loc, Value vector,
102                         int64_t offset) {
103   auto vectorType = vector.getType().cast<VectorType>();
104   if (vectorType.getRank() > 1)
105     return rewriter.create<ExtractOp>(loc, vector, offset);
106   return rewriter.create<vector::ExtractElementOp>(
107       loc, vectorType.getElementType(), vector,
108       rewriter.create<ConstantIndexOp>(loc, offset));
109 }
110 
111 // Helper that returns a subset of `arrayAttr` as a vector of int64_t.
112 // TODO(rriddle): Better support for attribute subtype forwarding + slicing.
113 static SmallVector<int64_t, 4> getI64SubArray(ArrayAttr arrayAttr,
114                                               unsigned dropFront = 0,
115                                               unsigned dropBack = 0) {
116   assert(arrayAttr.size() > dropFront + dropBack && "Out of bounds");
117   auto range = arrayAttr.getAsRange<IntegerAttr>();
118   SmallVector<int64_t, 4> res;
119   res.reserve(arrayAttr.size() - dropFront - dropBack);
120   for (auto it = range.begin() + dropFront, eit = range.end() - dropBack;
121        it != eit; ++it)
122     res.push_back((*it).getValue().getSExtValue());
123   return res;
124 }
125 
126 namespace {
127 class VectorBroadcastOpConversion : public LLVMOpLowering {
128 public:
129   explicit VectorBroadcastOpConversion(MLIRContext *context,
130                                        LLVMTypeConverter &typeConverter)
131       : LLVMOpLowering(vector::BroadcastOp::getOperationName(), context,
132                        typeConverter) {}
133 
134   PatternMatchResult
135   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
136                   ConversionPatternRewriter &rewriter) const override {
137     auto broadcastOp = cast<vector::BroadcastOp>(op);
138     VectorType dstVectorType = broadcastOp.getVectorType();
139     if (lowering.convertType(dstVectorType) == nullptr)
140       return matchFailure();
141     // Rewrite when the full vector type can be lowered (which
142     // implies all 'reduced' types can be lowered too).
143     auto adaptor = vector::BroadcastOpOperandAdaptor(operands);
144     VectorType srcVectorType =
145         broadcastOp.getSourceType().dyn_cast<VectorType>();
146     rewriter.replaceOp(
147         op, expandRanks(adaptor.source(), // source value to be expanded
148                         op->getLoc(),     // location of original broadcast
149                         srcVectorType, dstVectorType, rewriter));
150     return matchSuccess();
151   }
152 
153 private:
154   // Expands the given source value over all the ranks, as defined
155   // by the source and destination type (a null source type denotes
156   // expansion from a scalar value into a vector).
157   //
158   // TODO(ajcbik): consider replacing this one-pattern lowering
159   //               with a two-pattern lowering using other vector
160   //               ops once all insert/extract/shuffle operations
161   //               are available with lowering implementation.
162   //
163   Value expandRanks(Value value, Location loc, VectorType srcVectorType,
164                     VectorType dstVectorType,
165                     ConversionPatternRewriter &rewriter) const {
166     assert((dstVectorType != nullptr) && "invalid result type in broadcast");
167     // Determine rank of source and destination.
168     int64_t srcRank = srcVectorType ? srcVectorType.getRank() : 0;
169     int64_t dstRank = dstVectorType.getRank();
170     int64_t curDim = dstVectorType.getDimSize(0);
171     if (srcRank < dstRank)
172       // Duplicate this rank.
173       return duplicateOneRank(value, loc, srcVectorType, dstVectorType, dstRank,
174                               curDim, rewriter);
175     // If all trailing dimensions are the same, the broadcast consists of
176     // simply passing through the source value and we are done. Otherwise,
177     // any non-matching dimension forces a stretch along this rank.
178     assert((srcVectorType != nullptr) && (srcRank > 0) &&
179            (srcRank == dstRank) && "invalid rank in broadcast");
180     for (int64_t r = 0; r < dstRank; r++) {
181       if (srcVectorType.getDimSize(r) != dstVectorType.getDimSize(r)) {
182         return stretchOneRank(value, loc, srcVectorType, dstVectorType, dstRank,
183                               curDim, rewriter);
184       }
185     }
186     return value;
187   }
188 
189   // Picks the best way to duplicate a single rank. For the 1-D case, a
190   // single insert-elt/shuffle is the most efficient expansion. For higher
191   // dimensions, however, we need dim x insert-values on a new broadcast
192   // with one less leading dimension, which will be lowered "recursively"
193   // to matching LLVM IR.
194   // For example:
195   //   v = broadcast s : f32 to vector<4x2xf32>
196   // becomes:
197   //   x = broadcast s : f32 to vector<2xf32>
198   //   v = [x,x,x,x]
199   // becomes:
200   //   x = [s,s]
201   //   v = [x,x,x,x]
202   Value duplicateOneRank(Value value, Location loc, VectorType srcVectorType,
203                          VectorType dstVectorType, int64_t rank, int64_t dim,
204                          ConversionPatternRewriter &rewriter) const {
205     Type llvmType = lowering.convertType(dstVectorType);
206     assert((llvmType != nullptr) && "unlowerable vector type");
207     if (rank == 1) {
208       Value undef = rewriter.create<LLVM::UndefOp>(loc, llvmType);
209       Value expand =
210           insertOne(rewriter, lowering, loc, undef, value, llvmType, rank, 0);
211       SmallVector<int32_t, 4> zeroValues(dim, 0);
212       return rewriter.create<LLVM::ShuffleVectorOp>(
213           loc, expand, undef, rewriter.getI32ArrayAttr(zeroValues));
214     }
215     Value expand = expandRanks(value, loc, srcVectorType,
216                                reducedVectorTypeFront(dstVectorType), rewriter);
217     Value result = rewriter.create<LLVM::UndefOp>(loc, llvmType);
218     for (int64_t d = 0; d < dim; ++d) {
219       result =
220           insertOne(rewriter, lowering, loc, result, expand, llvmType, rank, d);
221     }
222     return result;
223   }
224 
225   // Picks the best way to stretch a single rank. For the 1-D case, a
226   // single insert-elt/shuffle is the most efficient expansion when at
227   // a stretch. Otherwise, every dimension needs to be expanded
228   // individually and individually inserted in the resulting vector.
229   // For example:
230   //   v = broadcast w : vector<4x1x2xf32> to vector<4x2x2xf32>
231   // becomes:
232   //   a = broadcast w[0] : vector<1x2xf32> to vector<2x2xf32>
233   //   b = broadcast w[1] : vector<1x2xf32> to vector<2x2xf32>
234   //   c = broadcast w[2] : vector<1x2xf32> to vector<2x2xf32>
235   //   d = broadcast w[3] : vector<1x2xf32> to vector<2x2xf32>
236   //   v = [a,b,c,d]
237   // becomes:
238   //   x = broadcast w[0][0] : vector<2xf32> to vector <2x2xf32>
239   //   y = broadcast w[1][0] : vector<2xf32> to vector <2x2xf32>
240   //   a = [x, y]
241   //   etc.
242   Value stretchOneRank(Value value, Location loc, VectorType srcVectorType,
243                        VectorType dstVectorType, int64_t rank, int64_t dim,
244                        ConversionPatternRewriter &rewriter) const {
245     Type llvmType = lowering.convertType(dstVectorType);
246     assert((llvmType != nullptr) && "unlowerable vector type");
247     Value result = rewriter.create<LLVM::UndefOp>(loc, llvmType);
248     bool atStretch = dim != srcVectorType.getDimSize(0);
249     if (rank == 1) {
250       assert(atStretch);
251       Type redLlvmType = lowering.convertType(dstVectorType.getElementType());
252       Value one =
253           extractOne(rewriter, lowering, loc, value, redLlvmType, rank, 0);
254       Value expand =
255           insertOne(rewriter, lowering, loc, result, one, llvmType, rank, 0);
256       SmallVector<int32_t, 4> zeroValues(dim, 0);
257       return rewriter.create<LLVM::ShuffleVectorOp>(
258           loc, expand, result, rewriter.getI32ArrayAttr(zeroValues));
259     }
260     VectorType redSrcType = reducedVectorTypeFront(srcVectorType);
261     VectorType redDstType = reducedVectorTypeFront(dstVectorType);
262     Type redLlvmType = lowering.convertType(redSrcType);
263     for (int64_t d = 0; d < dim; ++d) {
264       int64_t pos = atStretch ? 0 : d;
265       Value one =
266           extractOne(rewriter, lowering, loc, value, redLlvmType, rank, pos);
267       Value expand = expandRanks(one, loc, redSrcType, redDstType, rewriter);
268       result =
269           insertOne(rewriter, lowering, loc, result, expand, llvmType, rank, d);
270     }
271     return result;
272   }
273 };
274 
275 class VectorShuffleOpConversion : public LLVMOpLowering {
276 public:
277   explicit VectorShuffleOpConversion(MLIRContext *context,
278                                      LLVMTypeConverter &typeConverter)
279       : LLVMOpLowering(vector::ShuffleOp::getOperationName(), context,
280                        typeConverter) {}
281 
282   PatternMatchResult
283   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
284                   ConversionPatternRewriter &rewriter) const override {
285     auto loc = op->getLoc();
286     auto adaptor = vector::ShuffleOpOperandAdaptor(operands);
287     auto shuffleOp = cast<vector::ShuffleOp>(op);
288     auto v1Type = shuffleOp.getV1VectorType();
289     auto v2Type = shuffleOp.getV2VectorType();
290     auto vectorType = shuffleOp.getVectorType();
291     Type llvmType = lowering.convertType(vectorType);
292     auto maskArrayAttr = shuffleOp.mask();
293 
294     // Bail if result type cannot be lowered.
295     if (!llvmType)
296       return matchFailure();
297 
298     // Get rank and dimension sizes.
299     int64_t rank = vectorType.getRank();
300     assert(v1Type.getRank() == rank);
301     assert(v2Type.getRank() == rank);
302     int64_t v1Dim = v1Type.getDimSize(0);
303 
304     // For rank 1, where both operands have *exactly* the same vector type,
305     // there is direct shuffle support in LLVM. Use it!
306     if (rank == 1 && v1Type == v2Type) {
307       Value shuffle = rewriter.create<LLVM::ShuffleVectorOp>(
308           loc, adaptor.v1(), adaptor.v2(), maskArrayAttr);
309       rewriter.replaceOp(op, shuffle);
310       return matchSuccess();
311     }
312 
313     // For all other cases, insert the individual values individually.
314     Value insert = rewriter.create<LLVM::UndefOp>(loc, llvmType);
315     int64_t insPos = 0;
316     for (auto en : llvm::enumerate(maskArrayAttr)) {
317       int64_t extPos = en.value().cast<IntegerAttr>().getInt();
318       Value value = adaptor.v1();
319       if (extPos >= v1Dim) {
320         extPos -= v1Dim;
321         value = adaptor.v2();
322       }
323       Value extract =
324           extractOne(rewriter, lowering, loc, value, llvmType, rank, extPos);
325       insert = insertOne(rewriter, lowering, loc, insert, extract, llvmType,
326                          rank, insPos++);
327     }
328     rewriter.replaceOp(op, insert);
329     return matchSuccess();
330   }
331 };
332 
333 class VectorExtractElementOpConversion : public LLVMOpLowering {
334 public:
335   explicit VectorExtractElementOpConversion(MLIRContext *context,
336                                             LLVMTypeConverter &typeConverter)
337       : LLVMOpLowering(vector::ExtractElementOp::getOperationName(), context,
338                        typeConverter) {}
339 
340   PatternMatchResult
341   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
342                   ConversionPatternRewriter &rewriter) const override {
343     auto adaptor = vector::ExtractElementOpOperandAdaptor(operands);
344     auto extractEltOp = cast<vector::ExtractElementOp>(op);
345     auto vectorType = extractEltOp.getVectorType();
346     auto llvmType = lowering.convertType(vectorType.getElementType());
347 
348     // Bail if result type cannot be lowered.
349     if (!llvmType)
350       return matchFailure();
351 
352     rewriter.replaceOpWithNewOp<LLVM::ExtractElementOp>(
353         op, llvmType, adaptor.vector(), adaptor.position());
354     return matchSuccess();
355   }
356 };
357 
358 class VectorExtractOpConversion : public LLVMOpLowering {
359 public:
360   explicit VectorExtractOpConversion(MLIRContext *context,
361                                      LLVMTypeConverter &typeConverter)
362       : LLVMOpLowering(vector::ExtractOp::getOperationName(), context,
363                        typeConverter) {}
364 
365   PatternMatchResult
366   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
367                   ConversionPatternRewriter &rewriter) const override {
368     auto loc = op->getLoc();
369     auto adaptor = vector::ExtractOpOperandAdaptor(operands);
370     auto extractOp = cast<vector::ExtractOp>(op);
371     auto vectorType = extractOp.getVectorType();
372     auto resultType = extractOp.getResult().getType();
373     auto llvmResultType = lowering.convertType(resultType);
374     auto positionArrayAttr = extractOp.position();
375 
376     // Bail if result type cannot be lowered.
377     if (!llvmResultType)
378       return matchFailure();
379 
380     // One-shot extraction of vector from array (only requires extractvalue).
381     if (resultType.isa<VectorType>()) {
382       Value extracted = rewriter.create<LLVM::ExtractValueOp>(
383           loc, llvmResultType, adaptor.vector(), positionArrayAttr);
384       rewriter.replaceOp(op, extracted);
385       return matchSuccess();
386     }
387 
388     // Potential extraction of 1-D vector from array.
389     auto *context = op->getContext();
390     Value extracted = adaptor.vector();
391     auto positionAttrs = positionArrayAttr.getValue();
392     if (positionAttrs.size() > 1) {
393       auto oneDVectorType = reducedVectorTypeBack(vectorType);
394       auto nMinusOnePositionAttrs =
395           ArrayAttr::get(positionAttrs.drop_back(), context);
396       extracted = rewriter.create<LLVM::ExtractValueOp>(
397           loc, lowering.convertType(oneDVectorType), extracted,
398           nMinusOnePositionAttrs);
399     }
400 
401     // Remaining extraction of element from 1-D LLVM vector
402     auto position = positionAttrs.back().cast<IntegerAttr>();
403     auto i64Type = LLVM::LLVMType::getInt64Ty(lowering.getDialect());
404     auto constant = rewriter.create<LLVM::ConstantOp>(loc, i64Type, position);
405     extracted =
406         rewriter.create<LLVM::ExtractElementOp>(loc, extracted, constant);
407     rewriter.replaceOp(op, extracted);
408 
409     return matchSuccess();
410   }
411 };
412 
413 /// Conversion pattern that turns a vector.fma on a 1-D vector
414 /// into an llvm.intr.fmuladd. This is a trivial 1-1 conversion.
415 /// This does not match vectors of n >= 2 rank.
416 ///
417 /// Example:
418 /// ```
419 ///  vector.fma %a, %a, %a : vector<8xf32>
420 /// ```
421 /// is converted to:
422 /// ```
423 ///  llvm.intr.fma %va, %va, %va:
424 ///    (!llvm<"<8 x float>">, !llvm<"<8 x float>">, !llvm<"<8 x float>">)
425 ///    -> !llvm<"<8 x float>">
426 /// ```
427 class VectorFMAOp1DConversion : public LLVMOpLowering {
428 public:
429   explicit VectorFMAOp1DConversion(MLIRContext *context,
430                                    LLVMTypeConverter &typeConverter)
431       : LLVMOpLowering(vector::FMAOp::getOperationName(), context,
432                        typeConverter) {}
433 
434   PatternMatchResult
435   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
436                   ConversionPatternRewriter &rewriter) const override {
437     auto adaptor = vector::FMAOpOperandAdaptor(operands);
438     vector::FMAOp fmaOp = cast<vector::FMAOp>(op);
439     VectorType vType = fmaOp.getVectorType();
440     if (vType.getRank() != 1)
441       return matchFailure();
442     rewriter.replaceOpWithNewOp<LLVM::FMAOp>(op, adaptor.lhs(), adaptor.rhs(),
443                                              adaptor.acc());
444     return matchSuccess();
445   }
446 };
447 
448 class VectorInsertElementOpConversion : public LLVMOpLowering {
449 public:
450   explicit VectorInsertElementOpConversion(MLIRContext *context,
451                                            LLVMTypeConverter &typeConverter)
452       : LLVMOpLowering(vector::InsertElementOp::getOperationName(), context,
453                        typeConverter) {}
454 
455   PatternMatchResult
456   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
457                   ConversionPatternRewriter &rewriter) const override {
458     auto adaptor = vector::InsertElementOpOperandAdaptor(operands);
459     auto insertEltOp = cast<vector::InsertElementOp>(op);
460     auto vectorType = insertEltOp.getDestVectorType();
461     auto llvmType = lowering.convertType(vectorType);
462 
463     // Bail if result type cannot be lowered.
464     if (!llvmType)
465       return matchFailure();
466 
467     rewriter.replaceOpWithNewOp<LLVM::InsertElementOp>(
468         op, llvmType, adaptor.dest(), adaptor.source(), adaptor.position());
469     return matchSuccess();
470   }
471 };
472 
473 class VectorInsertOpConversion : public LLVMOpLowering {
474 public:
475   explicit VectorInsertOpConversion(MLIRContext *context,
476                                     LLVMTypeConverter &typeConverter)
477       : LLVMOpLowering(vector::InsertOp::getOperationName(), context,
478                        typeConverter) {}
479 
480   PatternMatchResult
481   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
482                   ConversionPatternRewriter &rewriter) const override {
483     auto loc = op->getLoc();
484     auto adaptor = vector::InsertOpOperandAdaptor(operands);
485     auto insertOp = cast<vector::InsertOp>(op);
486     auto sourceType = insertOp.getSourceType();
487     auto destVectorType = insertOp.getDestVectorType();
488     auto llvmResultType = lowering.convertType(destVectorType);
489     auto positionArrayAttr = insertOp.position();
490 
491     // Bail if result type cannot be lowered.
492     if (!llvmResultType)
493       return matchFailure();
494 
495     // One-shot insertion of a vector into an array (only requires insertvalue).
496     if (sourceType.isa<VectorType>()) {
497       Value inserted = rewriter.create<LLVM::InsertValueOp>(
498           loc, llvmResultType, adaptor.dest(), adaptor.source(),
499           positionArrayAttr);
500       rewriter.replaceOp(op, inserted);
501       return matchSuccess();
502     }
503 
504     // Potential extraction of 1-D vector from array.
505     auto *context = op->getContext();
506     Value extracted = adaptor.dest();
507     auto positionAttrs = positionArrayAttr.getValue();
508     auto position = positionAttrs.back().cast<IntegerAttr>();
509     auto oneDVectorType = destVectorType;
510     if (positionAttrs.size() > 1) {
511       oneDVectorType = reducedVectorTypeBack(destVectorType);
512       auto nMinusOnePositionAttrs =
513           ArrayAttr::get(positionAttrs.drop_back(), context);
514       extracted = rewriter.create<LLVM::ExtractValueOp>(
515           loc, lowering.convertType(oneDVectorType), extracted,
516           nMinusOnePositionAttrs);
517     }
518 
519     // Insertion of an element into a 1-D LLVM vector.
520     auto i64Type = LLVM::LLVMType::getInt64Ty(lowering.getDialect());
521     auto constant = rewriter.create<LLVM::ConstantOp>(loc, i64Type, position);
522     Value inserted = rewriter.create<LLVM::InsertElementOp>(
523         loc, lowering.convertType(oneDVectorType), extracted, adaptor.source(),
524         constant);
525 
526     // Potential insertion of resulting 1-D vector into array.
527     if (positionAttrs.size() > 1) {
528       auto nMinusOnePositionAttrs =
529           ArrayAttr::get(positionAttrs.drop_back(), context);
530       inserted = rewriter.create<LLVM::InsertValueOp>(loc, llvmResultType,
531                                                       adaptor.dest(), inserted,
532                                                       nMinusOnePositionAttrs);
533     }
534 
535     rewriter.replaceOp(op, inserted);
536     return matchSuccess();
537   }
538 };
539 
540 /// Rank reducing rewrite for n-D FMA into (n-1)-D FMA where n > 1.
541 ///
542 /// Example:
543 /// ```
544 ///   %d = vector.fma %a, %b, %c : vector<2x4xf32>
545 /// ```
546 /// is rewritten into:
547 /// ```
548 ///  %r = splat %f0: vector<2x4xf32>
549 ///  %va = vector.extractvalue %a[0] : vector<2x4xf32>
550 ///  %vb = vector.extractvalue %b[0] : vector<2x4xf32>
551 ///  %vc = vector.extractvalue %c[0] : vector<2x4xf32>
552 ///  %vd = vector.fma %va, %vb, %vc : vector<4xf32>
553 ///  %r2 = vector.insertvalue %vd, %r[0] : vector<4xf32> into vector<2x4xf32>
554 ///  %va2 = vector.extractvalue %a2[1] : vector<2x4xf32>
555 ///  %vb2 = vector.extractvalue %b2[1] : vector<2x4xf32>
556 ///  %vc2 = vector.extractvalue %c2[1] : vector<2x4xf32>
557 ///  %vd2 = vector.fma %va2, %vb2, %vc2 : vector<4xf32>
558 ///  %r3 = vector.insertvalue %vd2, %r2[1] : vector<4xf32> into vector<2x4xf32>
559 ///  // %r3 holds the final value.
560 /// ```
561 class VectorFMAOpNDRewritePattern : public OpRewritePattern<FMAOp> {
562 public:
563   using OpRewritePattern<FMAOp>::OpRewritePattern;
564 
565   PatternMatchResult matchAndRewrite(FMAOp op,
566                                      PatternRewriter &rewriter) const override {
567     auto vType = op.getVectorType();
568     if (vType.getRank() < 2)
569       return matchFailure();
570 
571     auto loc = op.getLoc();
572     auto elemType = vType.getElementType();
573     Value zero = rewriter.create<ConstantOp>(loc, elemType,
574                                              rewriter.getZeroAttr(elemType));
575     Value desc = rewriter.create<SplatOp>(loc, vType, zero);
576     for (int64_t i = 0, e = vType.getShape().front(); i != e; ++i) {
577       Value extrLHS = rewriter.create<ExtractOp>(loc, op.lhs(), i);
578       Value extrRHS = rewriter.create<ExtractOp>(loc, op.rhs(), i);
579       Value extrACC = rewriter.create<ExtractOp>(loc, op.acc(), i);
580       Value fma = rewriter.create<FMAOp>(loc, extrLHS, extrRHS, extrACC);
581       desc = rewriter.create<InsertOp>(loc, fma, desc, i);
582     }
583     rewriter.replaceOp(op, desc);
584     return matchSuccess();
585   }
586 };
587 
588 // When ranks are different, InsertStridedSlice needs to extract a properly
589 // ranked vector from the destination vector into which to insert. This pattern
590 // only takes care of this part and forwards the rest of the conversion to
591 // another pattern that converts InsertStridedSlice for operands of the same
592 // rank.
593 //
594 // RewritePattern for InsertStridedSliceOp where source and destination vectors
595 // have different ranks. In this case:
596 //   1. the proper subvector is extracted from the destination vector
597 //   2. a new InsertStridedSlice op is created to insert the source in the
598 //   destination subvector
599 //   3. the destination subvector is inserted back in the proper place
600 //   4. the op is replaced by the result of step 3.
601 // The new InsertStridedSlice from step 2. will be picked up by a
602 // `VectorInsertStridedSliceOpSameRankRewritePattern`.
603 class VectorInsertStridedSliceOpDifferentRankRewritePattern
604     : public OpRewritePattern<InsertStridedSliceOp> {
605 public:
606   using OpRewritePattern<InsertStridedSliceOp>::OpRewritePattern;
607 
608   PatternMatchResult matchAndRewrite(InsertStridedSliceOp op,
609                                      PatternRewriter &rewriter) const override {
610     auto srcType = op.getSourceVectorType();
611     auto dstType = op.getDestVectorType();
612 
613     if (op.offsets().getValue().empty())
614       return matchFailure();
615 
616     auto loc = op.getLoc();
617     int64_t rankDiff = dstType.getRank() - srcType.getRank();
618     assert(rankDiff >= 0);
619     if (rankDiff == 0)
620       return matchFailure();
621 
622     int64_t rankRest = dstType.getRank() - rankDiff;
623     // Extract / insert the subvector of matching rank and InsertStridedSlice
624     // on it.
625     Value extracted =
626         rewriter.create<ExtractOp>(loc, op.dest(),
627                                    getI64SubArray(op.offsets(), /*dropFront=*/0,
628                                                   /*dropFront=*/rankRest));
629     // A different pattern will kick in for InsertStridedSlice with matching
630     // ranks.
631     auto stridedSliceInnerOp = rewriter.create<InsertStridedSliceOp>(
632         loc, op.source(), extracted,
633         getI64SubArray(op.offsets(), /*dropFront=*/rankDiff),
634         getI64SubArray(op.strides(), /*dropFront=*/0));
635     rewriter.replaceOpWithNewOp<InsertOp>(
636         op, stridedSliceInnerOp.getResult(), op.dest(),
637         getI64SubArray(op.offsets(), /*dropFront=*/0,
638                        /*dropFront=*/rankRest));
639     return matchSuccess();
640   }
641 };
642 
643 // RewritePattern for InsertStridedSliceOp where source and destination vectors
644 // have the same rank. In this case, we reduce
645 //   1. the proper subvector is extracted from the destination vector
646 //   2. a new InsertStridedSlice op is created to insert the source in the
647 //   destination subvector
648 //   3. the destination subvector is inserted back in the proper place
649 //   4. the op is replaced by the result of step 3.
650 // The new InsertStridedSlice from step 2. will be picked up by a
651 // `VectorInsertStridedSliceOpSameRankRewritePattern`.
652 class VectorInsertStridedSliceOpSameRankRewritePattern
653     : public OpRewritePattern<InsertStridedSliceOp> {
654 public:
655   using OpRewritePattern<InsertStridedSliceOp>::OpRewritePattern;
656 
657   PatternMatchResult matchAndRewrite(InsertStridedSliceOp op,
658                                      PatternRewriter &rewriter) const override {
659     auto srcType = op.getSourceVectorType();
660     auto dstType = op.getDestVectorType();
661 
662     if (op.offsets().getValue().empty())
663       return matchFailure();
664 
665     int64_t rankDiff = dstType.getRank() - srcType.getRank();
666     assert(rankDiff >= 0);
667     if (rankDiff != 0)
668       return matchFailure();
669 
670     if (srcType == dstType) {
671       rewriter.replaceOp(op, op.source());
672       return matchSuccess();
673     }
674 
675     int64_t offset =
676         op.offsets().getValue().front().cast<IntegerAttr>().getInt();
677     int64_t size = srcType.getShape().front();
678     int64_t stride =
679         op.strides().getValue().front().cast<IntegerAttr>().getInt();
680 
681     auto loc = op.getLoc();
682     Value res = op.dest();
683     // For each slice of the source vector along the most major dimension.
684     for (int64_t off = offset, e = offset + size * stride, idx = 0; off < e;
685          off += stride, ++idx) {
686       // 1. extract the proper subvector (or element) from source
687       Value extractedSource = extractOne(rewriter, loc, op.source(), idx);
688       if (extractedSource.getType().isa<VectorType>()) {
689         // 2. If we have a vector, extract the proper subvector from destination
690         // Otherwise we are at the element level and no need to recurse.
691         Value extractedDest = extractOne(rewriter, loc, op.dest(), off);
692         // 3. Reduce the problem to lowering a new InsertStridedSlice op with
693         // smaller rank.
694         InsertStridedSliceOp insertStridedSliceOp =
695             rewriter.create<InsertStridedSliceOp>(
696                 loc, extractedSource, extractedDest,
697                 getI64SubArray(op.offsets(), /* dropFront=*/1),
698                 getI64SubArray(op.strides(), /* dropFront=*/1));
699         // Call matchAndRewrite recursively from within the pattern. This
700         // circumvents the current limitation that a given pattern cannot
701         // be called multiple times by the PatternRewrite infrastructure (to
702         // avoid infinite recursion, but in this case, infinite recursion
703         // cannot happen because the rank is strictly decreasing).
704         // TODO(rriddle, nicolasvasilache) Implement something like a hook for
705         // a potential function that must decrease and allow the same pattern
706         // multiple times.
707         auto success = matchAndRewrite(insertStridedSliceOp, rewriter);
708         (void)success;
709         assert(success && "Unexpected failure");
710         extractedSource = insertStridedSliceOp;
711       }
712       // 4. Insert the extractedSource into the res vector.
713       res = insertOne(rewriter, loc, extractedSource, res, off);
714     }
715 
716     rewriter.replaceOp(op, res);
717     return matchSuccess();
718   }
719 };
720 
721 class VectorOuterProductOpConversion : public LLVMOpLowering {
722 public:
723   explicit VectorOuterProductOpConversion(MLIRContext *context,
724                                           LLVMTypeConverter &typeConverter)
725       : LLVMOpLowering(vector::OuterProductOp::getOperationName(), context,
726                        typeConverter) {}
727 
728   PatternMatchResult
729   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
730                   ConversionPatternRewriter &rewriter) const override {
731     auto loc = op->getLoc();
732     auto adaptor = vector::OuterProductOpOperandAdaptor(operands);
733     auto *ctx = op->getContext();
734     auto vLHS = adaptor.lhs().getType().cast<LLVM::LLVMType>();
735     auto vRHS = adaptor.rhs().getType().cast<LLVM::LLVMType>();
736     auto rankLHS = vLHS.getUnderlyingType()->getVectorNumElements();
737     auto rankRHS = vRHS.getUnderlyingType()->getVectorNumElements();
738     auto llvmArrayOfVectType = lowering.convertType(
739         cast<vector::OuterProductOp>(op).getResult().getType());
740     Value desc = rewriter.create<LLVM::UndefOp>(loc, llvmArrayOfVectType);
741     Value a = adaptor.lhs(), b = adaptor.rhs();
742     Value acc = adaptor.acc().empty() ? nullptr : adaptor.acc().front();
743     SmallVector<Value, 8> lhs, accs;
744     lhs.reserve(rankLHS);
745     accs.reserve(rankLHS);
746     for (unsigned d = 0, e = rankLHS; d < e; ++d) {
747       // shufflevector explicitly requires i32.
748       auto attr = rewriter.getI32IntegerAttr(d);
749       SmallVector<Attribute, 4> bcastAttr(rankRHS, attr);
750       auto bcastArrayAttr = ArrayAttr::get(bcastAttr, ctx);
751       Value aD = nullptr, accD = nullptr;
752       // 1. Broadcast the element a[d] into vector aD.
753       aD = rewriter.create<LLVM::ShuffleVectorOp>(loc, a, a, bcastArrayAttr);
754       // 2. If acc is present, extract 1-d vector acc[d] into accD.
755       if (acc)
756         accD = rewriter.create<LLVM::ExtractValueOp>(
757             loc, vRHS, acc, rewriter.getI64ArrayAttr(d));
758       // 3. Compute aD outer b (plus accD, if relevant).
759       Value aOuterbD =
760           accD
761               ? rewriter.create<LLVM::FMAOp>(loc, vRHS, aD, b, accD).getResult()
762               : rewriter.create<LLVM::FMulOp>(loc, aD, b).getResult();
763       // 4. Insert as value `d` in the descriptor.
764       desc = rewriter.create<LLVM::InsertValueOp>(loc, llvmArrayOfVectType,
765                                                   desc, aOuterbD,
766                                                   rewriter.getI64ArrayAttr(d));
767     }
768     rewriter.replaceOp(op, desc);
769     return matchSuccess();
770   }
771 };
772 
773 class VectorTypeCastOpConversion : public LLVMOpLowering {
774 public:
775   explicit VectorTypeCastOpConversion(MLIRContext *context,
776                                       LLVMTypeConverter &typeConverter)
777       : LLVMOpLowering(vector::TypeCastOp::getOperationName(), context,
778                        typeConverter) {}
779 
780   PatternMatchResult
781   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
782                   ConversionPatternRewriter &rewriter) const override {
783     auto loc = op->getLoc();
784     vector::TypeCastOp castOp = cast<vector::TypeCastOp>(op);
785     MemRefType sourceMemRefType =
786         castOp.getOperand().getType().cast<MemRefType>();
787     MemRefType targetMemRefType =
788         castOp.getResult().getType().cast<MemRefType>();
789 
790     // Only static shape casts supported atm.
791     if (!sourceMemRefType.hasStaticShape() ||
792         !targetMemRefType.hasStaticShape())
793       return matchFailure();
794 
795     auto llvmSourceDescriptorTy =
796         operands[0].getType().dyn_cast<LLVM::LLVMType>();
797     if (!llvmSourceDescriptorTy || !llvmSourceDescriptorTy.isStructTy())
798       return matchFailure();
799     MemRefDescriptor sourceMemRef(operands[0]);
800 
801     auto llvmTargetDescriptorTy = lowering.convertType(targetMemRefType)
802                                       .dyn_cast_or_null<LLVM::LLVMType>();
803     if (!llvmTargetDescriptorTy || !llvmTargetDescriptorTy.isStructTy())
804       return matchFailure();
805 
806     int64_t offset;
807     SmallVector<int64_t, 4> strides;
808     auto successStrides =
809         getStridesAndOffset(sourceMemRefType, strides, offset);
810     bool isContiguous = (strides.back() == 1);
811     if (isContiguous) {
812       auto sizes = sourceMemRefType.getShape();
813       for (int index = 0, e = strides.size() - 2; index < e; ++index) {
814         if (strides[index] != strides[index + 1] * sizes[index + 1]) {
815           isContiguous = false;
816           break;
817         }
818       }
819     }
820     // Only contiguous source tensors supported atm.
821     if (failed(successStrides) || !isContiguous)
822       return matchFailure();
823 
824     auto int64Ty = LLVM::LLVMType::getInt64Ty(lowering.getDialect());
825 
826     // Create descriptor.
827     auto desc = MemRefDescriptor::undef(rewriter, loc, llvmTargetDescriptorTy);
828     Type llvmTargetElementTy = desc.getElementType();
829     // Set allocated ptr.
830     Value allocated = sourceMemRef.allocatedPtr(rewriter, loc);
831     allocated =
832         rewriter.create<LLVM::BitcastOp>(loc, llvmTargetElementTy, allocated);
833     desc.setAllocatedPtr(rewriter, loc, allocated);
834     // Set aligned ptr.
835     Value ptr = sourceMemRef.alignedPtr(rewriter, loc);
836     ptr = rewriter.create<LLVM::BitcastOp>(loc, llvmTargetElementTy, ptr);
837     desc.setAlignedPtr(rewriter, loc, ptr);
838     // Fill offset 0.
839     auto attr = rewriter.getIntegerAttr(rewriter.getIndexType(), 0);
840     auto zero = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, attr);
841     desc.setOffset(rewriter, loc, zero);
842 
843     // Fill size and stride descriptors in memref.
844     for (auto indexedSize : llvm::enumerate(targetMemRefType.getShape())) {
845       int64_t index = indexedSize.index();
846       auto sizeAttr =
847           rewriter.getIntegerAttr(rewriter.getIndexType(), indexedSize.value());
848       auto size = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, sizeAttr);
849       desc.setSize(rewriter, loc, index, size);
850       auto strideAttr =
851           rewriter.getIntegerAttr(rewriter.getIndexType(), strides[index]);
852       auto stride = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, strideAttr);
853       desc.setStride(rewriter, loc, index, stride);
854     }
855 
856     rewriter.replaceOp(op, {desc});
857     return matchSuccess();
858   }
859 };
860 
861 class VectorPrintOpConversion : public LLVMOpLowering {
862 public:
863   explicit VectorPrintOpConversion(MLIRContext *context,
864                                    LLVMTypeConverter &typeConverter)
865       : LLVMOpLowering(vector::PrintOp::getOperationName(), context,
866                        typeConverter) {}
867 
868   // Proof-of-concept lowering implementation that relies on a small
869   // runtime support library, which only needs to provide a few
870   // printing methods (single value for all data types, opening/closing
871   // bracket, comma, newline). The lowering fully unrolls a vector
872   // in terms of these elementary printing operations. The advantage
873   // of this approach is that the library can remain unaware of all
874   // low-level implementation details of vectors while still supporting
875   // output of any shaped and dimensioned vector. Due to full unrolling,
876   // this approach is less suited for very large vectors though.
877   //
878   // TODO(ajcbik): rely solely on libc in future? something else?
879   //
880   PatternMatchResult
881   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
882                   ConversionPatternRewriter &rewriter) const override {
883     auto printOp = cast<vector::PrintOp>(op);
884     auto adaptor = vector::PrintOpOperandAdaptor(operands);
885     Type printType = printOp.getPrintType();
886 
887     if (lowering.convertType(printType) == nullptr)
888       return matchFailure();
889 
890     // Make sure element type has runtime support (currently just Float/Double).
891     VectorType vectorType = printType.dyn_cast<VectorType>();
892     Type eltType = vectorType ? vectorType.getElementType() : printType;
893     int64_t rank = vectorType ? vectorType.getRank() : 0;
894     Operation *printer;
895     if (eltType.isInteger(32))
896       printer = getPrintI32(op);
897     else if (eltType.isInteger(64))
898       printer = getPrintI64(op);
899     else if (eltType.isF32())
900       printer = getPrintFloat(op);
901     else if (eltType.isF64())
902       printer = getPrintDouble(op);
903     else
904       return matchFailure();
905 
906     // Unroll vector into elementary print calls.
907     emitRanks(rewriter, op, adaptor.source(), vectorType, printer, rank);
908     emitCall(rewriter, op->getLoc(), getPrintNewline(op));
909     rewriter.eraseOp(op);
910     return matchSuccess();
911   }
912 
913 private:
914   void emitRanks(ConversionPatternRewriter &rewriter, Operation *op,
915                  Value value, VectorType vectorType, Operation *printer,
916                  int64_t rank) const {
917     Location loc = op->getLoc();
918     if (rank == 0) {
919       emitCall(rewriter, loc, printer, value);
920       return;
921     }
922 
923     emitCall(rewriter, loc, getPrintOpen(op));
924     Operation *printComma = getPrintComma(op);
925     int64_t dim = vectorType.getDimSize(0);
926     for (int64_t d = 0; d < dim; ++d) {
927       auto reducedType =
928           rank > 1 ? reducedVectorTypeFront(vectorType) : nullptr;
929       auto llvmType = lowering.convertType(
930           rank > 1 ? reducedType : vectorType.getElementType());
931       Value nestedVal =
932           extractOne(rewriter, lowering, loc, value, llvmType, rank, d);
933       emitRanks(rewriter, op, nestedVal, reducedType, printer, rank - 1);
934       if (d != dim - 1)
935         emitCall(rewriter, loc, printComma);
936     }
937     emitCall(rewriter, loc, getPrintClose(op));
938   }
939 
940   // Helper to emit a call.
941   static void emitCall(ConversionPatternRewriter &rewriter, Location loc,
942                        Operation *ref, ValueRange params = ValueRange()) {
943     rewriter.create<LLVM::CallOp>(loc, ArrayRef<Type>{},
944                                   rewriter.getSymbolRefAttr(ref), params);
945   }
946 
947   // Helper for printer method declaration (first hit) and lookup.
948   static Operation *getPrint(Operation *op, LLVM::LLVMDialect *dialect,
949                              StringRef name, ArrayRef<LLVM::LLVMType> params) {
950     auto module = op->getParentOfType<ModuleOp>();
951     auto func = module.lookupSymbol<LLVM::LLVMFuncOp>(name);
952     if (func)
953       return func;
954     OpBuilder moduleBuilder(module.getBodyRegion());
955     return moduleBuilder.create<LLVM::LLVMFuncOp>(
956         op->getLoc(), name,
957         LLVM::LLVMType::getFunctionTy(LLVM::LLVMType::getVoidTy(dialect),
958                                       params, /*isVarArg=*/false));
959   }
960 
961   // Helpers for method names.
962   Operation *getPrintI32(Operation *op) const {
963     LLVM::LLVMDialect *dialect = lowering.getDialect();
964     return getPrint(op, dialect, "print_i32",
965                     LLVM::LLVMType::getInt32Ty(dialect));
966   }
967   Operation *getPrintI64(Operation *op) const {
968     LLVM::LLVMDialect *dialect = lowering.getDialect();
969     return getPrint(op, dialect, "print_i64",
970                     LLVM::LLVMType::getInt64Ty(dialect));
971   }
972   Operation *getPrintFloat(Operation *op) const {
973     LLVM::LLVMDialect *dialect = lowering.getDialect();
974     return getPrint(op, dialect, "print_f32",
975                     LLVM::LLVMType::getFloatTy(dialect));
976   }
977   Operation *getPrintDouble(Operation *op) const {
978     LLVM::LLVMDialect *dialect = lowering.getDialect();
979     return getPrint(op, dialect, "print_f64",
980                     LLVM::LLVMType::getDoubleTy(dialect));
981   }
982   Operation *getPrintOpen(Operation *op) const {
983     return getPrint(op, lowering.getDialect(), "print_open", {});
984   }
985   Operation *getPrintClose(Operation *op) const {
986     return getPrint(op, lowering.getDialect(), "print_close", {});
987   }
988   Operation *getPrintComma(Operation *op) const {
989     return getPrint(op, lowering.getDialect(), "print_comma", {});
990   }
991   Operation *getPrintNewline(Operation *op) const {
992     return getPrint(op, lowering.getDialect(), "print_newline", {});
993   }
994 };
995 
996 /// Progressive lowering of StridedSliceOp to either:
997 ///   1. extractelement + insertelement for the 1-D case
998 ///   2. extract + optional strided_slice + insert for the n-D case.
999 class VectorStridedSliceOpConversion : public OpRewritePattern<StridedSliceOp> {
1000 public:
1001   using OpRewritePattern<StridedSliceOp>::OpRewritePattern;
1002 
1003   PatternMatchResult matchAndRewrite(StridedSliceOp op,
1004                                      PatternRewriter &rewriter) const override {
1005     auto dstType = op.getResult().getType().cast<VectorType>();
1006 
1007     assert(!op.offsets().getValue().empty() && "Unexpected empty offsets");
1008 
1009     int64_t offset =
1010         op.offsets().getValue().front().cast<IntegerAttr>().getInt();
1011     int64_t size = op.sizes().getValue().front().cast<IntegerAttr>().getInt();
1012     int64_t stride =
1013         op.strides().getValue().front().cast<IntegerAttr>().getInt();
1014 
1015     auto loc = op.getLoc();
1016     auto elemType = dstType.getElementType();
1017     assert(elemType.isIntOrIndexOrFloat());
1018     Value zero = rewriter.create<ConstantOp>(loc, elemType,
1019                                              rewriter.getZeroAttr(elemType));
1020     Value res = rewriter.create<SplatOp>(loc, dstType, zero);
1021     for (int64_t off = offset, e = offset + size * stride, idx = 0; off < e;
1022          off += stride, ++idx) {
1023       Value extracted = extractOne(rewriter, loc, op.vector(), off);
1024       if (op.offsets().getValue().size() > 1) {
1025         StridedSliceOp stridedSliceOp = rewriter.create<StridedSliceOp>(
1026             loc, extracted, getI64SubArray(op.offsets(), /* dropFront=*/1),
1027             getI64SubArray(op.sizes(), /* dropFront=*/1),
1028             getI64SubArray(op.strides(), /* dropFront=*/1));
1029         // Call matchAndRewrite recursively from within the pattern. This
1030         // circumvents the current limitation that a given pattern cannot
1031         // be called multiple times by the PatternRewrite infrastructure (to
1032         // avoid infinite recursion, but in this case, infinite recursion
1033         // cannot happen because the rank is strictly decreasing).
1034         // TODO(rriddle, nicolasvasilache) Implement something like a hook for
1035         // a potential function that must decrease and allow the same pattern
1036         // multiple times.
1037         auto success = matchAndRewrite(stridedSliceOp, rewriter);
1038         (void)success;
1039         assert(success && "Unexpected failure");
1040         extracted = stridedSliceOp;
1041       }
1042       res = insertOne(rewriter, loc, extracted, res, idx);
1043     }
1044     rewriter.replaceOp(op, {res});
1045     return matchSuccess();
1046   }
1047 };
1048 
1049 } // namespace
1050 
1051 /// Populate the given list with patterns that convert from Vector to LLVM.
1052 void mlir::populateVectorToLLVMConversionPatterns(
1053     LLVMTypeConverter &converter, OwningRewritePatternList &patterns) {
1054   MLIRContext *ctx = converter.getDialect()->getContext();
1055   patterns.insert<VectorFMAOpNDRewritePattern,
1056                   VectorInsertStridedSliceOpDifferentRankRewritePattern,
1057                   VectorInsertStridedSliceOpSameRankRewritePattern,
1058                   VectorStridedSliceOpConversion>(ctx);
1059   patterns.insert<VectorBroadcastOpConversion, VectorShuffleOpConversion,
1060                   VectorExtractElementOpConversion, VectorExtractOpConversion,
1061                   VectorFMAOp1DConversion, VectorInsertElementOpConversion,
1062                   VectorInsertOpConversion, VectorOuterProductOpConversion,
1063                   VectorTypeCastOpConversion, VectorPrintOpConversion>(
1064       ctx, converter);
1065 }
1066 
1067 namespace {
1068 struct LowerVectorToLLVMPass : public ModulePass<LowerVectorToLLVMPass> {
1069   void runOnModule() override;
1070 };
1071 } // namespace
1072 
1073 void LowerVectorToLLVMPass::runOnModule() {
1074   // Perform progressive lowering of operations on "slices".
1075   // Folding and DCE get rid of all non-leaking tuple ops.
1076   {
1077     OwningRewritePatternList patterns;
1078     populateVectorSlicesLoweringPatterns(patterns, &getContext());
1079     applyPatternsGreedily(getModule(), patterns);
1080   }
1081 
1082   // Convert to the LLVM IR dialect.
1083   LLVMTypeConverter converter(&getContext());
1084   OwningRewritePatternList patterns;
1085   populateVectorToLLVMConversionPatterns(converter, patterns);
1086   populateStdToLLVMConversionPatterns(converter, patterns);
1087 
1088   ConversionTarget target(getContext());
1089   target.addLegalDialect<LLVM::LLVMDialect>();
1090   target.addDynamicallyLegalOp<FuncOp>(
1091       [&](FuncOp op) { return converter.isSignatureLegal(op.getType()); });
1092   if (failed(
1093           applyPartialConversion(getModule(), target, patterns, &converter))) {
1094     signalPassFailure();
1095   }
1096 }
1097 
1098 OpPassBase<ModuleOp> *mlir::createLowerVectorToLLVMPass() {
1099   return new LowerVectorToLLVMPass();
1100 }
1101 
1102 static PassRegistration<LowerVectorToLLVMPass>
1103     pass("convert-vector-to-llvm",
1104          "Lower the operations from the vector dialect into the LLVM dialect");
1105