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 
11 #include "../PassDetail.h"
12 #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h"
13 #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h"
14 #include "mlir/Dialect/LLVMIR/LLVMDialect.h"
15 #include "mlir/Dialect/StandardOps/IR/Ops.h"
16 #include "mlir/Dialect/Vector/VectorOps.h"
17 #include "mlir/IR/Attributes.h"
18 #include "mlir/IR/Builders.h"
19 #include "mlir/IR/MLIRContext.h"
20 #include "mlir/IR/Module.h"
21 #include "mlir/IR/Operation.h"
22 #include "mlir/IR/PatternMatch.h"
23 #include "mlir/IR/StandardTypes.h"
24 #include "mlir/IR/Types.h"
25 #include "mlir/Transforms/DialectConversion.h"
26 #include "mlir/Transforms/Passes.h"
27 #include "llvm/IR/DerivedTypes.h"
28 #include "llvm/IR/Module.h"
29 #include "llvm/IR/Type.h"
30 #include "llvm/Support/Allocator.h"
31 #include "llvm/Support/ErrorHandling.h"
32 
33 using namespace mlir;
34 using namespace mlir::vector;
35 
36 template <typename T>
37 static LLVM::LLVMType getPtrToElementType(T containerType,
38                                           LLVMTypeConverter &typeConverter) {
39   return typeConverter.convertType(containerType.getElementType())
40       .template cast<LLVM::LLVMType>()
41       .getPointerTo();
42 }
43 
44 // Helper to reduce vector type by one rank at front.
45 static VectorType reducedVectorTypeFront(VectorType tp) {
46   assert((tp.getRank() > 1) && "unlowerable vector type");
47   return VectorType::get(tp.getShape().drop_front(), tp.getElementType());
48 }
49 
50 // Helper to reduce vector type by *all* but one rank at back.
51 static VectorType reducedVectorTypeBack(VectorType tp) {
52   assert((tp.getRank() > 1) && "unlowerable vector type");
53   return VectorType::get(tp.getShape().take_back(), tp.getElementType());
54 }
55 
56 // Helper that picks the proper sequence for inserting.
57 static Value insertOne(ConversionPatternRewriter &rewriter,
58                        LLVMTypeConverter &typeConverter, Location loc,
59                        Value val1, Value val2, Type llvmType, int64_t rank,
60                        int64_t pos) {
61   if (rank == 1) {
62     auto idxType = rewriter.getIndexType();
63     auto constant = rewriter.create<LLVM::ConstantOp>(
64         loc, typeConverter.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 &typeConverter, Location loc,
87                         Value val, 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, typeConverter.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 
128 class VectorBroadcastOpConversion : public ConvertToLLVMPattern {
129 public:
130   explicit VectorBroadcastOpConversion(MLIRContext *context,
131                                        LLVMTypeConverter &typeConverter)
132       : ConvertToLLVMPattern(vector::BroadcastOp::getOperationName(), context,
133                              typeConverter) {}
134 
135   LogicalResult
136   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
137                   ConversionPatternRewriter &rewriter) const override {
138     auto broadcastOp = cast<vector::BroadcastOp>(op);
139     VectorType dstVectorType = broadcastOp.getVectorType();
140     if (typeConverter.convertType(dstVectorType) == nullptr)
141       return failure();
142     // Rewrite when the full vector type can be lowered (which
143     // implies all 'reduced' types can be lowered too).
144     auto adaptor = vector::BroadcastOpOperandAdaptor(operands);
145     VectorType srcVectorType =
146         broadcastOp.getSourceType().dyn_cast<VectorType>();
147     rewriter.replaceOp(
148         op, expandRanks(adaptor.source(), // source value to be expanded
149                         op->getLoc(),     // location of original broadcast
150                         srcVectorType, dstVectorType, rewriter));
151     return success();
152   }
153 
154 private:
155   // Expands the given source value over all the ranks, as defined
156   // by the source and destination type (a null source type denotes
157   // expansion from a scalar value into a vector).
158   //
159   // TODO(ajcbik): consider replacing this one-pattern lowering
160   //               with a two-pattern lowering using other vector
161   //               ops once all insert/extract/shuffle operations
162   //               are available with lowering implementation.
163   //
164   Value expandRanks(Value value, Location loc, VectorType srcVectorType,
165                     VectorType dstVectorType,
166                     ConversionPatternRewriter &rewriter) const {
167     assert((dstVectorType != nullptr) && "invalid result type in broadcast");
168     // Determine rank of source and destination.
169     int64_t srcRank = srcVectorType ? srcVectorType.getRank() : 0;
170     int64_t dstRank = dstVectorType.getRank();
171     int64_t curDim = dstVectorType.getDimSize(0);
172     if (srcRank < dstRank)
173       // Duplicate this rank.
174       return duplicateOneRank(value, loc, srcVectorType, dstVectorType, dstRank,
175                               curDim, rewriter);
176     // If all trailing dimensions are the same, the broadcast consists of
177     // simply passing through the source value and we are done. Otherwise,
178     // any non-matching dimension forces a stretch along this rank.
179     assert((srcVectorType != nullptr) && (srcRank > 0) &&
180            (srcRank == dstRank) && "invalid rank in broadcast");
181     for (int64_t r = 0; r < dstRank; r++) {
182       if (srcVectorType.getDimSize(r) != dstVectorType.getDimSize(r)) {
183         return stretchOneRank(value, loc, srcVectorType, dstVectorType, dstRank,
184                               curDim, rewriter);
185       }
186     }
187     return value;
188   }
189 
190   // Picks the best way to duplicate a single rank. For the 1-D case, a
191   // single insert-elt/shuffle is the most efficient expansion. For higher
192   // dimensions, however, we need dim x insert-values on a new broadcast
193   // with one less leading dimension, which will be lowered "recursively"
194   // to matching LLVM IR.
195   // For example:
196   //   v = broadcast s : f32 to vector<4x2xf32>
197   // becomes:
198   //   x = broadcast s : f32 to vector<2xf32>
199   //   v = [x,x,x,x]
200   // becomes:
201   //   x = [s,s]
202   //   v = [x,x,x,x]
203   Value duplicateOneRank(Value value, Location loc, VectorType srcVectorType,
204                          VectorType dstVectorType, int64_t rank, int64_t dim,
205                          ConversionPatternRewriter &rewriter) const {
206     Type llvmType = typeConverter.convertType(dstVectorType);
207     assert((llvmType != nullptr) && "unlowerable vector type");
208     if (rank == 1) {
209       Value undef = rewriter.create<LLVM::UndefOp>(loc, llvmType);
210       Value expand = insertOne(rewriter, typeConverter, loc, undef, value,
211                                llvmType, rank, 0);
212       SmallVector<int32_t, 4> zeroValues(dim, 0);
213       return rewriter.create<LLVM::ShuffleVectorOp>(
214           loc, expand, undef, rewriter.getI32ArrayAttr(zeroValues));
215     }
216     Value expand = expandRanks(value, loc, srcVectorType,
217                                reducedVectorTypeFront(dstVectorType), rewriter);
218     Value result = rewriter.create<LLVM::UndefOp>(loc, llvmType);
219     for (int64_t d = 0; d < dim; ++d) {
220       result = insertOne(rewriter, typeConverter, loc, result, expand, llvmType,
221                          rank, d);
222     }
223     return result;
224   }
225 
226   // Picks the best way to stretch a single rank. For the 1-D case, a
227   // single insert-elt/shuffle is the most efficient expansion when at
228   // a stretch. Otherwise, every dimension needs to be expanded
229   // individually and individually inserted in the resulting vector.
230   // For example:
231   //   v = broadcast w : vector<4x1x2xf32> to vector<4x2x2xf32>
232   // becomes:
233   //   a = broadcast w[0] : vector<1x2xf32> to vector<2x2xf32>
234   //   b = broadcast w[1] : vector<1x2xf32> to vector<2x2xf32>
235   //   c = broadcast w[2] : vector<1x2xf32> to vector<2x2xf32>
236   //   d = broadcast w[3] : vector<1x2xf32> to vector<2x2xf32>
237   //   v = [a,b,c,d]
238   // becomes:
239   //   x = broadcast w[0][0] : vector<2xf32> to vector <2x2xf32>
240   //   y = broadcast w[1][0] : vector<2xf32> to vector <2x2xf32>
241   //   a = [x, y]
242   //   etc.
243   Value stretchOneRank(Value value, Location loc, VectorType srcVectorType,
244                        VectorType dstVectorType, int64_t rank, int64_t dim,
245                        ConversionPatternRewriter &rewriter) const {
246     Type llvmType = typeConverter.convertType(dstVectorType);
247     assert((llvmType != nullptr) && "unlowerable vector type");
248     Value result = rewriter.create<LLVM::UndefOp>(loc, llvmType);
249     bool atStretch = dim != srcVectorType.getDimSize(0);
250     if (rank == 1) {
251       assert(atStretch);
252       Type redLlvmType =
253           typeConverter.convertType(dstVectorType.getElementType());
254       Value one =
255           extractOne(rewriter, typeConverter, loc, value, redLlvmType, rank, 0);
256       Value expand = insertOne(rewriter, typeConverter, loc, result, one,
257                                llvmType, rank, 0);
258       SmallVector<int32_t, 4> zeroValues(dim, 0);
259       return rewriter.create<LLVM::ShuffleVectorOp>(
260           loc, expand, result, rewriter.getI32ArrayAttr(zeroValues));
261     }
262     VectorType redSrcType = reducedVectorTypeFront(srcVectorType);
263     VectorType redDstType = reducedVectorTypeFront(dstVectorType);
264     Type redLlvmType = typeConverter.convertType(redSrcType);
265     for (int64_t d = 0; d < dim; ++d) {
266       int64_t pos = atStretch ? 0 : d;
267       Value one = extractOne(rewriter, typeConverter, loc, value, redLlvmType,
268                              rank, pos);
269       Value expand = expandRanks(one, loc, redSrcType, redDstType, rewriter);
270       result = insertOne(rewriter, typeConverter, loc, result, expand, llvmType,
271                          rank, d);
272     }
273     return result;
274   }
275 };
276 
277 /// Conversion pattern for a vector.matrix_multiply.
278 /// This is lowered directly to the proper llvm.intr.matrix.multiply.
279 class VectorMatmulOpConversion : public ConvertToLLVMPattern {
280 public:
281   explicit VectorMatmulOpConversion(MLIRContext *context,
282                                     LLVMTypeConverter &typeConverter)
283       : ConvertToLLVMPattern(vector::MatmulOp::getOperationName(), context,
284                              typeConverter) {}
285 
286   LogicalResult
287   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
288                   ConversionPatternRewriter &rewriter) const override {
289     auto matmulOp = cast<vector::MatmulOp>(op);
290     auto adaptor = vector::MatmulOpOperandAdaptor(operands);
291     rewriter.replaceOpWithNewOp<LLVM::MatrixMultiplyOp>(
292         op, typeConverter.convertType(matmulOp.res().getType()), adaptor.lhs(),
293         adaptor.rhs(), matmulOp.lhs_rows(), matmulOp.lhs_columns(),
294         matmulOp.rhs_columns());
295     return success();
296   }
297 };
298 
299 class VectorReductionOpConversion : public ConvertToLLVMPattern {
300 public:
301   explicit VectorReductionOpConversion(MLIRContext *context,
302                                        LLVMTypeConverter &typeConverter)
303       : ConvertToLLVMPattern(vector::ReductionOp::getOperationName(), context,
304                              typeConverter) {}
305 
306   LogicalResult
307   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
308                   ConversionPatternRewriter &rewriter) const override {
309     auto reductionOp = cast<vector::ReductionOp>(op);
310     auto kind = reductionOp.kind();
311     Type eltType = reductionOp.dest().getType();
312     Type llvmType = typeConverter.convertType(eltType);
313     if (eltType.isSignlessInteger(32) || eltType.isSignlessInteger(64)) {
314       // Integer reductions: add/mul/min/max/and/or/xor.
315       if (kind == "add")
316         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_add>(
317             op, llvmType, operands[0]);
318       else if (kind == "mul")
319         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_mul>(
320             op, llvmType, operands[0]);
321       else if (kind == "min")
322         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_smin>(
323             op, llvmType, operands[0]);
324       else if (kind == "max")
325         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_smax>(
326             op, llvmType, operands[0]);
327       else if (kind == "and")
328         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_and>(
329             op, llvmType, operands[0]);
330       else if (kind == "or")
331         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_or>(
332             op, llvmType, operands[0]);
333       else if (kind == "xor")
334         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_xor>(
335             op, llvmType, operands[0]);
336       else
337         return failure();
338       return success();
339 
340     } else if (eltType.isF32() || eltType.isF64()) {
341       // Floating-point reductions: add/mul/min/max
342       if (kind == "add") {
343         // Optional accumulator (or zero).
344         Value acc = operands.size() > 1 ? operands[1]
345                                         : rewriter.create<LLVM::ConstantOp>(
346                                               op->getLoc(), llvmType,
347                                               rewriter.getZeroAttr(eltType));
348         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_v2_fadd>(
349             op, llvmType, acc, operands[0]);
350       } else if (kind == "mul") {
351         // Optional accumulator (or one).
352         Value acc = operands.size() > 1
353                         ? operands[1]
354                         : rewriter.create<LLVM::ConstantOp>(
355                               op->getLoc(), llvmType,
356                               rewriter.getFloatAttr(eltType, 1.0));
357         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_v2_fmul>(
358             op, llvmType, acc, operands[0]);
359       } else if (kind == "min")
360         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_fmin>(
361             op, llvmType, operands[0]);
362       else if (kind == "max")
363         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_fmax>(
364             op, llvmType, operands[0]);
365       else
366         return failure();
367       return success();
368     }
369     return failure();
370   }
371 };
372 
373 class VectorShuffleOpConversion : public ConvertToLLVMPattern {
374 public:
375   explicit VectorShuffleOpConversion(MLIRContext *context,
376                                      LLVMTypeConverter &typeConverter)
377       : ConvertToLLVMPattern(vector::ShuffleOp::getOperationName(), context,
378                              typeConverter) {}
379 
380   LogicalResult
381   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
382                   ConversionPatternRewriter &rewriter) const override {
383     auto loc = op->getLoc();
384     auto adaptor = vector::ShuffleOpOperandAdaptor(operands);
385     auto shuffleOp = cast<vector::ShuffleOp>(op);
386     auto v1Type = shuffleOp.getV1VectorType();
387     auto v2Type = shuffleOp.getV2VectorType();
388     auto vectorType = shuffleOp.getVectorType();
389     Type llvmType = typeConverter.convertType(vectorType);
390     auto maskArrayAttr = shuffleOp.mask();
391 
392     // Bail if result type cannot be lowered.
393     if (!llvmType)
394       return failure();
395 
396     // Get rank and dimension sizes.
397     int64_t rank = vectorType.getRank();
398     assert(v1Type.getRank() == rank);
399     assert(v2Type.getRank() == rank);
400     int64_t v1Dim = v1Type.getDimSize(0);
401 
402     // For rank 1, where both operands have *exactly* the same vector type,
403     // there is direct shuffle support in LLVM. Use it!
404     if (rank == 1 && v1Type == v2Type) {
405       Value shuffle = rewriter.create<LLVM::ShuffleVectorOp>(
406           loc, adaptor.v1(), adaptor.v2(), maskArrayAttr);
407       rewriter.replaceOp(op, shuffle);
408       return success();
409     }
410 
411     // For all other cases, insert the individual values individually.
412     Value insert = rewriter.create<LLVM::UndefOp>(loc, llvmType);
413     int64_t insPos = 0;
414     for (auto en : llvm::enumerate(maskArrayAttr)) {
415       int64_t extPos = en.value().cast<IntegerAttr>().getInt();
416       Value value = adaptor.v1();
417       if (extPos >= v1Dim) {
418         extPos -= v1Dim;
419         value = adaptor.v2();
420       }
421       Value extract = extractOne(rewriter, typeConverter, loc, value, llvmType,
422                                  rank, extPos);
423       insert = insertOne(rewriter, typeConverter, loc, insert, extract,
424                          llvmType, rank, insPos++);
425     }
426     rewriter.replaceOp(op, insert);
427     return success();
428   }
429 };
430 
431 class VectorExtractElementOpConversion : public ConvertToLLVMPattern {
432 public:
433   explicit VectorExtractElementOpConversion(MLIRContext *context,
434                                             LLVMTypeConverter &typeConverter)
435       : ConvertToLLVMPattern(vector::ExtractElementOp::getOperationName(),
436                              context, typeConverter) {}
437 
438   LogicalResult
439   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
440                   ConversionPatternRewriter &rewriter) const override {
441     auto adaptor = vector::ExtractElementOpOperandAdaptor(operands);
442     auto extractEltOp = cast<vector::ExtractElementOp>(op);
443     auto vectorType = extractEltOp.getVectorType();
444     auto llvmType = typeConverter.convertType(vectorType.getElementType());
445 
446     // Bail if result type cannot be lowered.
447     if (!llvmType)
448       return failure();
449 
450     rewriter.replaceOpWithNewOp<LLVM::ExtractElementOp>(
451         op, llvmType, adaptor.vector(), adaptor.position());
452     return success();
453   }
454 };
455 
456 class VectorExtractOpConversion : public ConvertToLLVMPattern {
457 public:
458   explicit VectorExtractOpConversion(MLIRContext *context,
459                                      LLVMTypeConverter &typeConverter)
460       : ConvertToLLVMPattern(vector::ExtractOp::getOperationName(), context,
461                              typeConverter) {}
462 
463   LogicalResult
464   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
465                   ConversionPatternRewriter &rewriter) const override {
466     auto loc = op->getLoc();
467     auto adaptor = vector::ExtractOpOperandAdaptor(operands);
468     auto extractOp = cast<vector::ExtractOp>(op);
469     auto vectorType = extractOp.getVectorType();
470     auto resultType = extractOp.getResult().getType();
471     auto llvmResultType = typeConverter.convertType(resultType);
472     auto positionArrayAttr = extractOp.position();
473 
474     // Bail if result type cannot be lowered.
475     if (!llvmResultType)
476       return failure();
477 
478     // One-shot extraction of vector from array (only requires extractvalue).
479     if (resultType.isa<VectorType>()) {
480       Value extracted = rewriter.create<LLVM::ExtractValueOp>(
481           loc, llvmResultType, adaptor.vector(), positionArrayAttr);
482       rewriter.replaceOp(op, extracted);
483       return success();
484     }
485 
486     // Potential extraction of 1-D vector from array.
487     auto *context = op->getContext();
488     Value extracted = adaptor.vector();
489     auto positionAttrs = positionArrayAttr.getValue();
490     if (positionAttrs.size() > 1) {
491       auto oneDVectorType = reducedVectorTypeBack(vectorType);
492       auto nMinusOnePositionAttrs =
493           ArrayAttr::get(positionAttrs.drop_back(), context);
494       extracted = rewriter.create<LLVM::ExtractValueOp>(
495           loc, typeConverter.convertType(oneDVectorType), extracted,
496           nMinusOnePositionAttrs);
497     }
498 
499     // Remaining extraction of element from 1-D LLVM vector
500     auto position = positionAttrs.back().cast<IntegerAttr>();
501     auto i64Type = LLVM::LLVMType::getInt64Ty(typeConverter.getDialect());
502     auto constant = rewriter.create<LLVM::ConstantOp>(loc, i64Type, position);
503     extracted =
504         rewriter.create<LLVM::ExtractElementOp>(loc, extracted, constant);
505     rewriter.replaceOp(op, extracted);
506 
507     return success();
508   }
509 };
510 
511 /// Conversion pattern that turns a vector.fma on a 1-D vector
512 /// into an llvm.intr.fmuladd. This is a trivial 1-1 conversion.
513 /// This does not match vectors of n >= 2 rank.
514 ///
515 /// Example:
516 /// ```
517 ///  vector.fma %a, %a, %a : vector<8xf32>
518 /// ```
519 /// is converted to:
520 /// ```
521 ///  llvm.intr.fma %va, %va, %va:
522 ///    (!llvm<"<8 x float>">, !llvm<"<8 x float>">, !llvm<"<8 x float>">)
523 ///    -> !llvm<"<8 x float>">
524 /// ```
525 class VectorFMAOp1DConversion : public ConvertToLLVMPattern {
526 public:
527   explicit VectorFMAOp1DConversion(MLIRContext *context,
528                                    LLVMTypeConverter &typeConverter)
529       : ConvertToLLVMPattern(vector::FMAOp::getOperationName(), context,
530                              typeConverter) {}
531 
532   LogicalResult
533   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
534                   ConversionPatternRewriter &rewriter) const override {
535     auto adaptor = vector::FMAOpOperandAdaptor(operands);
536     vector::FMAOp fmaOp = cast<vector::FMAOp>(op);
537     VectorType vType = fmaOp.getVectorType();
538     if (vType.getRank() != 1)
539       return failure();
540     rewriter.replaceOpWithNewOp<LLVM::FMAOp>(op, adaptor.lhs(), adaptor.rhs(),
541                                              adaptor.acc());
542     return success();
543   }
544 };
545 
546 class VectorInsertElementOpConversion : public ConvertToLLVMPattern {
547 public:
548   explicit VectorInsertElementOpConversion(MLIRContext *context,
549                                            LLVMTypeConverter &typeConverter)
550       : ConvertToLLVMPattern(vector::InsertElementOp::getOperationName(),
551                              context, typeConverter) {}
552 
553   LogicalResult
554   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
555                   ConversionPatternRewriter &rewriter) const override {
556     auto adaptor = vector::InsertElementOpOperandAdaptor(operands);
557     auto insertEltOp = cast<vector::InsertElementOp>(op);
558     auto vectorType = insertEltOp.getDestVectorType();
559     auto llvmType = typeConverter.convertType(vectorType);
560 
561     // Bail if result type cannot be lowered.
562     if (!llvmType)
563       return failure();
564 
565     rewriter.replaceOpWithNewOp<LLVM::InsertElementOp>(
566         op, llvmType, adaptor.dest(), adaptor.source(), adaptor.position());
567     return success();
568   }
569 };
570 
571 class VectorInsertOpConversion : public ConvertToLLVMPattern {
572 public:
573   explicit VectorInsertOpConversion(MLIRContext *context,
574                                     LLVMTypeConverter &typeConverter)
575       : ConvertToLLVMPattern(vector::InsertOp::getOperationName(), context,
576                              typeConverter) {}
577 
578   LogicalResult
579   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
580                   ConversionPatternRewriter &rewriter) const override {
581     auto loc = op->getLoc();
582     auto adaptor = vector::InsertOpOperandAdaptor(operands);
583     auto insertOp = cast<vector::InsertOp>(op);
584     auto sourceType = insertOp.getSourceType();
585     auto destVectorType = insertOp.getDestVectorType();
586     auto llvmResultType = typeConverter.convertType(destVectorType);
587     auto positionArrayAttr = insertOp.position();
588 
589     // Bail if result type cannot be lowered.
590     if (!llvmResultType)
591       return failure();
592 
593     // One-shot insertion of a vector into an array (only requires insertvalue).
594     if (sourceType.isa<VectorType>()) {
595       Value inserted = rewriter.create<LLVM::InsertValueOp>(
596           loc, llvmResultType, adaptor.dest(), adaptor.source(),
597           positionArrayAttr);
598       rewriter.replaceOp(op, inserted);
599       return success();
600     }
601 
602     // Potential extraction of 1-D vector from array.
603     auto *context = op->getContext();
604     Value extracted = adaptor.dest();
605     auto positionAttrs = positionArrayAttr.getValue();
606     auto position = positionAttrs.back().cast<IntegerAttr>();
607     auto oneDVectorType = destVectorType;
608     if (positionAttrs.size() > 1) {
609       oneDVectorType = reducedVectorTypeBack(destVectorType);
610       auto nMinusOnePositionAttrs =
611           ArrayAttr::get(positionAttrs.drop_back(), context);
612       extracted = rewriter.create<LLVM::ExtractValueOp>(
613           loc, typeConverter.convertType(oneDVectorType), extracted,
614           nMinusOnePositionAttrs);
615     }
616 
617     // Insertion of an element into a 1-D LLVM vector.
618     auto i64Type = LLVM::LLVMType::getInt64Ty(typeConverter.getDialect());
619     auto constant = rewriter.create<LLVM::ConstantOp>(loc, i64Type, position);
620     Value inserted = rewriter.create<LLVM::InsertElementOp>(
621         loc, typeConverter.convertType(oneDVectorType), extracted,
622         adaptor.source(), constant);
623 
624     // Potential insertion of resulting 1-D vector into array.
625     if (positionAttrs.size() > 1) {
626       auto nMinusOnePositionAttrs =
627           ArrayAttr::get(positionAttrs.drop_back(), context);
628       inserted = rewriter.create<LLVM::InsertValueOp>(loc, llvmResultType,
629                                                       adaptor.dest(), inserted,
630                                                       nMinusOnePositionAttrs);
631     }
632 
633     rewriter.replaceOp(op, inserted);
634     return success();
635   }
636 };
637 
638 /// Rank reducing rewrite for n-D FMA into (n-1)-D FMA where n > 1.
639 ///
640 /// Example:
641 /// ```
642 ///   %d = vector.fma %a, %b, %c : vector<2x4xf32>
643 /// ```
644 /// is rewritten into:
645 /// ```
646 ///  %r = splat %f0: vector<2x4xf32>
647 ///  %va = vector.extractvalue %a[0] : vector<2x4xf32>
648 ///  %vb = vector.extractvalue %b[0] : vector<2x4xf32>
649 ///  %vc = vector.extractvalue %c[0] : vector<2x4xf32>
650 ///  %vd = vector.fma %va, %vb, %vc : vector<4xf32>
651 ///  %r2 = vector.insertvalue %vd, %r[0] : vector<4xf32> into vector<2x4xf32>
652 ///  %va2 = vector.extractvalue %a2[1] : vector<2x4xf32>
653 ///  %vb2 = vector.extractvalue %b2[1] : vector<2x4xf32>
654 ///  %vc2 = vector.extractvalue %c2[1] : vector<2x4xf32>
655 ///  %vd2 = vector.fma %va2, %vb2, %vc2 : vector<4xf32>
656 ///  %r3 = vector.insertvalue %vd2, %r2[1] : vector<4xf32> into vector<2x4xf32>
657 ///  // %r3 holds the final value.
658 /// ```
659 class VectorFMAOpNDRewritePattern : public OpRewritePattern<FMAOp> {
660 public:
661   using OpRewritePattern<FMAOp>::OpRewritePattern;
662 
663   LogicalResult matchAndRewrite(FMAOp op,
664                                 PatternRewriter &rewriter) const override {
665     auto vType = op.getVectorType();
666     if (vType.getRank() < 2)
667       return failure();
668 
669     auto loc = op.getLoc();
670     auto elemType = vType.getElementType();
671     Value zero = rewriter.create<ConstantOp>(loc, elemType,
672                                              rewriter.getZeroAttr(elemType));
673     Value desc = rewriter.create<SplatOp>(loc, vType, zero);
674     for (int64_t i = 0, e = vType.getShape().front(); i != e; ++i) {
675       Value extrLHS = rewriter.create<ExtractOp>(loc, op.lhs(), i);
676       Value extrRHS = rewriter.create<ExtractOp>(loc, op.rhs(), i);
677       Value extrACC = rewriter.create<ExtractOp>(loc, op.acc(), i);
678       Value fma = rewriter.create<FMAOp>(loc, extrLHS, extrRHS, extrACC);
679       desc = rewriter.create<InsertOp>(loc, fma, desc, i);
680     }
681     rewriter.replaceOp(op, desc);
682     return success();
683   }
684 };
685 
686 // When ranks are different, InsertStridedSlice needs to extract a properly
687 // ranked vector from the destination vector into which to insert. This pattern
688 // only takes care of this part and forwards the rest of the conversion to
689 // another pattern that converts InsertStridedSlice for operands of the same
690 // rank.
691 //
692 // RewritePattern for InsertStridedSliceOp where source and destination vectors
693 // have different ranks. In this case:
694 //   1. the proper subvector is extracted from the destination vector
695 //   2. a new InsertStridedSlice op is created to insert the source in the
696 //   destination subvector
697 //   3. the destination subvector is inserted back in the proper place
698 //   4. the op is replaced by the result of step 3.
699 // The new InsertStridedSlice from step 2. will be picked up by a
700 // `VectorInsertStridedSliceOpSameRankRewritePattern`.
701 class VectorInsertStridedSliceOpDifferentRankRewritePattern
702     : public OpRewritePattern<InsertStridedSliceOp> {
703 public:
704   using OpRewritePattern<InsertStridedSliceOp>::OpRewritePattern;
705 
706   LogicalResult matchAndRewrite(InsertStridedSliceOp op,
707                                 PatternRewriter &rewriter) const override {
708     auto srcType = op.getSourceVectorType();
709     auto dstType = op.getDestVectorType();
710 
711     if (op.offsets().getValue().empty())
712       return failure();
713 
714     auto loc = op.getLoc();
715     int64_t rankDiff = dstType.getRank() - srcType.getRank();
716     assert(rankDiff >= 0);
717     if (rankDiff == 0)
718       return failure();
719 
720     int64_t rankRest = dstType.getRank() - rankDiff;
721     // Extract / insert the subvector of matching rank and InsertStridedSlice
722     // on it.
723     Value extracted =
724         rewriter.create<ExtractOp>(loc, op.dest(),
725                                    getI64SubArray(op.offsets(), /*dropFront=*/0,
726                                                   /*dropFront=*/rankRest));
727     // A different pattern will kick in for InsertStridedSlice with matching
728     // ranks.
729     auto stridedSliceInnerOp = rewriter.create<InsertStridedSliceOp>(
730         loc, op.source(), extracted,
731         getI64SubArray(op.offsets(), /*dropFront=*/rankDiff),
732         getI64SubArray(op.strides(), /*dropFront=*/0));
733     rewriter.replaceOpWithNewOp<InsertOp>(
734         op, stridedSliceInnerOp.getResult(), op.dest(),
735         getI64SubArray(op.offsets(), /*dropFront=*/0,
736                        /*dropFront=*/rankRest));
737     return success();
738   }
739 };
740 
741 // RewritePattern for InsertStridedSliceOp where source and destination vectors
742 // have the same rank. In this case, we reduce
743 //   1. the proper subvector is extracted from the destination vector
744 //   2. a new InsertStridedSlice op is created to insert the source in the
745 //   destination subvector
746 //   3. the destination subvector is inserted back in the proper place
747 //   4. the op is replaced by the result of step 3.
748 // The new InsertStridedSlice from step 2. will be picked up by a
749 // `VectorInsertStridedSliceOpSameRankRewritePattern`.
750 class VectorInsertStridedSliceOpSameRankRewritePattern
751     : public OpRewritePattern<InsertStridedSliceOp> {
752 public:
753   using OpRewritePattern<InsertStridedSliceOp>::OpRewritePattern;
754 
755   LogicalResult matchAndRewrite(InsertStridedSliceOp op,
756                                 PatternRewriter &rewriter) const override {
757     auto srcType = op.getSourceVectorType();
758     auto dstType = op.getDestVectorType();
759 
760     if (op.offsets().getValue().empty())
761       return failure();
762 
763     int64_t rankDiff = dstType.getRank() - srcType.getRank();
764     assert(rankDiff >= 0);
765     if (rankDiff != 0)
766       return failure();
767 
768     if (srcType == dstType) {
769       rewriter.replaceOp(op, op.source());
770       return success();
771     }
772 
773     int64_t offset =
774         op.offsets().getValue().front().cast<IntegerAttr>().getInt();
775     int64_t size = srcType.getShape().front();
776     int64_t stride =
777         op.strides().getValue().front().cast<IntegerAttr>().getInt();
778 
779     auto loc = op.getLoc();
780     Value res = op.dest();
781     // For each slice of the source vector along the most major dimension.
782     for (int64_t off = offset, e = offset + size * stride, idx = 0; off < e;
783          off += stride, ++idx) {
784       // 1. extract the proper subvector (or element) from source
785       Value extractedSource = extractOne(rewriter, loc, op.source(), idx);
786       if (extractedSource.getType().isa<VectorType>()) {
787         // 2. If we have a vector, extract the proper subvector from destination
788         // Otherwise we are at the element level and no need to recurse.
789         Value extractedDest = extractOne(rewriter, loc, op.dest(), off);
790         // 3. Reduce the problem to lowering a new InsertStridedSlice op with
791         // smaller rank.
792         InsertStridedSliceOp insertStridedSliceOp =
793             rewriter.create<InsertStridedSliceOp>(
794                 loc, extractedSource, extractedDest,
795                 getI64SubArray(op.offsets(), /* dropFront=*/1),
796                 getI64SubArray(op.strides(), /* dropFront=*/1));
797         // Call matchAndRewrite recursively from within the pattern. This
798         // circumvents the current limitation that a given pattern cannot
799         // be called multiple times by the PatternRewrite infrastructure (to
800         // avoid infinite recursion, but in this case, infinite recursion
801         // cannot happen because the rank is strictly decreasing).
802         // TODO(rriddle, nicolasvasilache) Implement something like a hook for
803         // a potential function that must decrease and allow the same pattern
804         // multiple times.
805         auto success = matchAndRewrite(insertStridedSliceOp, rewriter);
806         (void)success;
807         assert(succeeded(success) && "Unexpected failure");
808         extractedSource = insertStridedSliceOp;
809       }
810       // 4. Insert the extractedSource into the res vector.
811       res = insertOne(rewriter, loc, extractedSource, res, off);
812     }
813 
814     rewriter.replaceOp(op, res);
815     return success();
816   }
817 };
818 
819 class VectorTypeCastOpConversion : public ConvertToLLVMPattern {
820 public:
821   explicit VectorTypeCastOpConversion(MLIRContext *context,
822                                       LLVMTypeConverter &typeConverter)
823       : ConvertToLLVMPattern(vector::TypeCastOp::getOperationName(), context,
824                              typeConverter) {}
825 
826   LogicalResult
827   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
828                   ConversionPatternRewriter &rewriter) const override {
829     auto loc = op->getLoc();
830     vector::TypeCastOp castOp = cast<vector::TypeCastOp>(op);
831     MemRefType sourceMemRefType =
832         castOp.getOperand().getType().cast<MemRefType>();
833     MemRefType targetMemRefType =
834         castOp.getResult().getType().cast<MemRefType>();
835 
836     // Only static shape casts supported atm.
837     if (!sourceMemRefType.hasStaticShape() ||
838         !targetMemRefType.hasStaticShape())
839       return failure();
840 
841     auto llvmSourceDescriptorTy =
842         operands[0].getType().dyn_cast<LLVM::LLVMType>();
843     if (!llvmSourceDescriptorTy || !llvmSourceDescriptorTy.isStructTy())
844       return failure();
845     MemRefDescriptor sourceMemRef(operands[0]);
846 
847     auto llvmTargetDescriptorTy = typeConverter.convertType(targetMemRefType)
848                                       .dyn_cast_or_null<LLVM::LLVMType>();
849     if (!llvmTargetDescriptorTy || !llvmTargetDescriptorTy.isStructTy())
850       return failure();
851 
852     int64_t offset;
853     SmallVector<int64_t, 4> strides;
854     auto successStrides =
855         getStridesAndOffset(sourceMemRefType, strides, offset);
856     bool isContiguous = (strides.back() == 1);
857     if (isContiguous) {
858       auto sizes = sourceMemRefType.getShape();
859       for (int index = 0, e = strides.size() - 2; index < e; ++index) {
860         if (strides[index] != strides[index + 1] * sizes[index + 1]) {
861           isContiguous = false;
862           break;
863         }
864       }
865     }
866     // Only contiguous source tensors supported atm.
867     if (failed(successStrides) || !isContiguous)
868       return failure();
869 
870     auto int64Ty = LLVM::LLVMType::getInt64Ty(typeConverter.getDialect());
871 
872     // Create descriptor.
873     auto desc = MemRefDescriptor::undef(rewriter, loc, llvmTargetDescriptorTy);
874     Type llvmTargetElementTy = desc.getElementType();
875     // Set allocated ptr.
876     Value allocated = sourceMemRef.allocatedPtr(rewriter, loc);
877     allocated =
878         rewriter.create<LLVM::BitcastOp>(loc, llvmTargetElementTy, allocated);
879     desc.setAllocatedPtr(rewriter, loc, allocated);
880     // Set aligned ptr.
881     Value ptr = sourceMemRef.alignedPtr(rewriter, loc);
882     ptr = rewriter.create<LLVM::BitcastOp>(loc, llvmTargetElementTy, ptr);
883     desc.setAlignedPtr(rewriter, loc, ptr);
884     // Fill offset 0.
885     auto attr = rewriter.getIntegerAttr(rewriter.getIndexType(), 0);
886     auto zero = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, attr);
887     desc.setOffset(rewriter, loc, zero);
888 
889     // Fill size and stride descriptors in memref.
890     for (auto indexedSize : llvm::enumerate(targetMemRefType.getShape())) {
891       int64_t index = indexedSize.index();
892       auto sizeAttr =
893           rewriter.getIntegerAttr(rewriter.getIndexType(), indexedSize.value());
894       auto size = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, sizeAttr);
895       desc.setSize(rewriter, loc, index, size);
896       auto strideAttr =
897           rewriter.getIntegerAttr(rewriter.getIndexType(), strides[index]);
898       auto stride = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, strideAttr);
899       desc.setStride(rewriter, loc, index, stride);
900     }
901 
902     rewriter.replaceOp(op, {desc});
903     return success();
904   }
905 };
906 
907 class VectorPrintOpConversion : public ConvertToLLVMPattern {
908 public:
909   explicit VectorPrintOpConversion(MLIRContext *context,
910                                    LLVMTypeConverter &typeConverter)
911       : ConvertToLLVMPattern(vector::PrintOp::getOperationName(), context,
912                              typeConverter) {}
913 
914   // Proof-of-concept lowering implementation that relies on a small
915   // runtime support library, which only needs to provide a few
916   // printing methods (single value for all data types, opening/closing
917   // bracket, comma, newline). The lowering fully unrolls a vector
918   // in terms of these elementary printing operations. The advantage
919   // of this approach is that the library can remain unaware of all
920   // low-level implementation details of vectors while still supporting
921   // output of any shaped and dimensioned vector. Due to full unrolling,
922   // this approach is less suited for very large vectors though.
923   //
924   // TODO(ajcbik): rely solely on libc in future? something else?
925   //
926   LogicalResult
927   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
928                   ConversionPatternRewriter &rewriter) const override {
929     auto printOp = cast<vector::PrintOp>(op);
930     auto adaptor = vector::PrintOpOperandAdaptor(operands);
931     Type printType = printOp.getPrintType();
932 
933     if (typeConverter.convertType(printType) == nullptr)
934       return failure();
935 
936     // Make sure element type has runtime support (currently just Float/Double).
937     VectorType vectorType = printType.dyn_cast<VectorType>();
938     Type eltType = vectorType ? vectorType.getElementType() : printType;
939     int64_t rank = vectorType ? vectorType.getRank() : 0;
940     Operation *printer;
941     if (eltType.isSignlessInteger(32))
942       printer = getPrintI32(op);
943     else if (eltType.isSignlessInteger(64))
944       printer = getPrintI64(op);
945     else if (eltType.isF32())
946       printer = getPrintFloat(op);
947     else if (eltType.isF64())
948       printer = getPrintDouble(op);
949     else
950       return failure();
951 
952     // Unroll vector into elementary print calls.
953     emitRanks(rewriter, op, adaptor.source(), vectorType, printer, rank);
954     emitCall(rewriter, op->getLoc(), getPrintNewline(op));
955     rewriter.eraseOp(op);
956     return success();
957   }
958 
959 private:
960   void emitRanks(ConversionPatternRewriter &rewriter, Operation *op,
961                  Value value, VectorType vectorType, Operation *printer,
962                  int64_t rank) const {
963     Location loc = op->getLoc();
964     if (rank == 0) {
965       emitCall(rewriter, loc, printer, value);
966       return;
967     }
968 
969     emitCall(rewriter, loc, getPrintOpen(op));
970     Operation *printComma = getPrintComma(op);
971     int64_t dim = vectorType.getDimSize(0);
972     for (int64_t d = 0; d < dim; ++d) {
973       auto reducedType =
974           rank > 1 ? reducedVectorTypeFront(vectorType) : nullptr;
975       auto llvmType = typeConverter.convertType(
976           rank > 1 ? reducedType : vectorType.getElementType());
977       Value nestedVal =
978           extractOne(rewriter, typeConverter, loc, value, llvmType, rank, d);
979       emitRanks(rewriter, op, nestedVal, reducedType, printer, rank - 1);
980       if (d != dim - 1)
981         emitCall(rewriter, loc, printComma);
982     }
983     emitCall(rewriter, loc, getPrintClose(op));
984   }
985 
986   // Helper to emit a call.
987   static void emitCall(ConversionPatternRewriter &rewriter, Location loc,
988                        Operation *ref, ValueRange params = ValueRange()) {
989     rewriter.create<LLVM::CallOp>(loc, ArrayRef<Type>{},
990                                   rewriter.getSymbolRefAttr(ref), params);
991   }
992 
993   // Helper for printer method declaration (first hit) and lookup.
994   static Operation *getPrint(Operation *op, LLVM::LLVMDialect *dialect,
995                              StringRef name, ArrayRef<LLVM::LLVMType> params) {
996     auto module = op->getParentOfType<ModuleOp>();
997     auto func = module.lookupSymbol<LLVM::LLVMFuncOp>(name);
998     if (func)
999       return func;
1000     OpBuilder moduleBuilder(module.getBodyRegion());
1001     return moduleBuilder.create<LLVM::LLVMFuncOp>(
1002         op->getLoc(), name,
1003         LLVM::LLVMType::getFunctionTy(LLVM::LLVMType::getVoidTy(dialect),
1004                                       params, /*isVarArg=*/false));
1005   }
1006 
1007   // Helpers for method names.
1008   Operation *getPrintI32(Operation *op) const {
1009     LLVM::LLVMDialect *dialect = typeConverter.getDialect();
1010     return getPrint(op, dialect, "print_i32",
1011                     LLVM::LLVMType::getInt32Ty(dialect));
1012   }
1013   Operation *getPrintI64(Operation *op) const {
1014     LLVM::LLVMDialect *dialect = typeConverter.getDialect();
1015     return getPrint(op, dialect, "print_i64",
1016                     LLVM::LLVMType::getInt64Ty(dialect));
1017   }
1018   Operation *getPrintFloat(Operation *op) const {
1019     LLVM::LLVMDialect *dialect = typeConverter.getDialect();
1020     return getPrint(op, dialect, "print_f32",
1021                     LLVM::LLVMType::getFloatTy(dialect));
1022   }
1023   Operation *getPrintDouble(Operation *op) const {
1024     LLVM::LLVMDialect *dialect = typeConverter.getDialect();
1025     return getPrint(op, dialect, "print_f64",
1026                     LLVM::LLVMType::getDoubleTy(dialect));
1027   }
1028   Operation *getPrintOpen(Operation *op) const {
1029     return getPrint(op, typeConverter.getDialect(), "print_open", {});
1030   }
1031   Operation *getPrintClose(Operation *op) const {
1032     return getPrint(op, typeConverter.getDialect(), "print_close", {});
1033   }
1034   Operation *getPrintComma(Operation *op) const {
1035     return getPrint(op, typeConverter.getDialect(), "print_comma", {});
1036   }
1037   Operation *getPrintNewline(Operation *op) const {
1038     return getPrint(op, typeConverter.getDialect(), "print_newline", {});
1039   }
1040 };
1041 
1042 /// Progressive lowering of StridedSliceOp to either:
1043 ///   1. extractelement + insertelement for the 1-D case
1044 ///   2. extract + optional strided_slice + insert for the n-D case.
1045 class VectorStridedSliceOpConversion : public OpRewritePattern<StridedSliceOp> {
1046 public:
1047   using OpRewritePattern<StridedSliceOp>::OpRewritePattern;
1048 
1049   LogicalResult matchAndRewrite(StridedSliceOp op,
1050                                 PatternRewriter &rewriter) const override {
1051     auto dstType = op.getResult().getType().cast<VectorType>();
1052 
1053     assert(!op.offsets().getValue().empty() && "Unexpected empty offsets");
1054 
1055     int64_t offset =
1056         op.offsets().getValue().front().cast<IntegerAttr>().getInt();
1057     int64_t size = op.sizes().getValue().front().cast<IntegerAttr>().getInt();
1058     int64_t stride =
1059         op.strides().getValue().front().cast<IntegerAttr>().getInt();
1060 
1061     auto loc = op.getLoc();
1062     auto elemType = dstType.getElementType();
1063     assert(elemType.isSignlessIntOrIndexOrFloat());
1064     Value zero = rewriter.create<ConstantOp>(loc, elemType,
1065                                              rewriter.getZeroAttr(elemType));
1066     Value res = rewriter.create<SplatOp>(loc, dstType, zero);
1067     for (int64_t off = offset, e = offset + size * stride, idx = 0; off < e;
1068          off += stride, ++idx) {
1069       Value extracted = extractOne(rewriter, loc, op.vector(), off);
1070       if (op.offsets().getValue().size() > 1) {
1071         StridedSliceOp stridedSliceOp = rewriter.create<StridedSliceOp>(
1072             loc, extracted, getI64SubArray(op.offsets(), /* dropFront=*/1),
1073             getI64SubArray(op.sizes(), /* dropFront=*/1),
1074             getI64SubArray(op.strides(), /* dropFront=*/1));
1075         // Call matchAndRewrite recursively from within the pattern. This
1076         // circumvents the current limitation that a given pattern cannot
1077         // be called multiple times by the PatternRewrite infrastructure (to
1078         // avoid infinite recursion, but in this case, infinite recursion
1079         // cannot happen because the rank is strictly decreasing).
1080         // TODO(rriddle, nicolasvasilache) Implement something like a hook for
1081         // a potential function that must decrease and allow the same pattern
1082         // multiple times.
1083         auto success = matchAndRewrite(stridedSliceOp, rewriter);
1084         (void)success;
1085         assert(succeeded(success) && "Unexpected failure");
1086         extracted = stridedSliceOp;
1087       }
1088       res = insertOne(rewriter, loc, extracted, res, idx);
1089     }
1090     rewriter.replaceOp(op, {res});
1091     return success();
1092   }
1093 };
1094 
1095 } // namespace
1096 
1097 /// Populate the given list with patterns that convert from Vector to LLVM.
1098 void mlir::populateVectorToLLVMConversionPatterns(
1099     LLVMTypeConverter &converter, OwningRewritePatternList &patterns) {
1100   MLIRContext *ctx = converter.getDialect()->getContext();
1101   patterns.insert<VectorFMAOpNDRewritePattern,
1102                   VectorInsertStridedSliceOpDifferentRankRewritePattern,
1103                   VectorInsertStridedSliceOpSameRankRewritePattern,
1104                   VectorStridedSliceOpConversion>(ctx);
1105   patterns.insert<VectorBroadcastOpConversion, VectorReductionOpConversion,
1106                   VectorShuffleOpConversion, VectorExtractElementOpConversion,
1107                   VectorExtractOpConversion, VectorFMAOp1DConversion,
1108                   VectorInsertElementOpConversion, VectorInsertOpConversion,
1109                   VectorTypeCastOpConversion, VectorPrintOpConversion>(
1110       ctx, converter);
1111 }
1112 
1113 void mlir::populateVectorToLLVMMatrixConversionPatterns(
1114     LLVMTypeConverter &converter, OwningRewritePatternList &patterns) {
1115   MLIRContext *ctx = converter.getDialect()->getContext();
1116   patterns.insert<VectorMatmulOpConversion>(ctx, converter);
1117 }
1118 
1119 namespace {
1120 struct LowerVectorToLLVMPass
1121     : public ConvertVectorToLLVMBase<LowerVectorToLLVMPass> {
1122   void runOnOperation() override;
1123 };
1124 } // namespace
1125 
1126 void LowerVectorToLLVMPass::runOnOperation() {
1127   // Perform progressive lowering of operations on slices and
1128   // all contraction operations. Also applies folding and DCE.
1129   {
1130     OwningRewritePatternList patterns;
1131     populateVectorSlicesLoweringPatterns(patterns, &getContext());
1132     populateVectorContractLoweringPatterns(patterns, &getContext());
1133     applyPatternsGreedily(getOperation(), patterns);
1134   }
1135 
1136   // Convert to the LLVM IR dialect.
1137   LLVMTypeConverter converter(&getContext());
1138   OwningRewritePatternList patterns;
1139   populateVectorToLLVMMatrixConversionPatterns(converter, patterns);
1140   populateVectorToLLVMConversionPatterns(converter, patterns);
1141   populateVectorToLLVMMatrixConversionPatterns(converter, patterns);
1142   populateStdToLLVMConversionPatterns(converter, patterns);
1143 
1144   LLVMConversionTarget target(getContext());
1145   target.addDynamicallyLegalOp<FuncOp>(
1146       [&](FuncOp op) { return converter.isSignatureLegal(op.getType()); });
1147   if (failed(applyPartialConversion(getOperation(), target, patterns,
1148                                     &converter))) {
1149     signalPassFailure();
1150   }
1151 }
1152 
1153 std::unique_ptr<OperationPass<ModuleOp>> mlir::createConvertVectorToLLVMPass() {
1154   return std::make_unique<LowerVectorToLLVMPass>();
1155 }
1156