ConvertVectorToLLVM.cpp 42 KB
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998
//===- VectorToLLVM.cpp - Conversion from Vector to the LLVM dialect ------===//
//
// Part of the MLIR Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//

#include "mlir/Conversion/VectorToLLVM/ConvertVectorToLLVM.h"
#include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h"
#include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/Dialect/StandardOps/Ops.h"
#include "mlir/Dialect/VectorOps/VectorOps.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/MLIRContext.h"
#include "mlir/IR/Module.h"
#include "mlir/IR/Operation.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/StandardTypes.h"
#include "mlir/IR/Types.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Pass/PassManager.h"
#include "mlir/Transforms/DialectConversion.h"
#include "mlir/Transforms/Passes.h"

#include "llvm/IR/DerivedTypes.h"
#include "llvm/IR/Module.h"
#include "llvm/IR/Type.h"
#include "llvm/Support/Allocator.h"
#include "llvm/Support/ErrorHandling.h"

using namespace mlir;
using namespace mlir::vector;

namespace {

template <typename T>
static LLVM::LLVMType getPtrToElementType(T containerType,
                                          LLVMTypeConverter &lowering) {
  return lowering.convertType(containerType.getElementType())
      .template cast<LLVM::LLVMType>()
      .getPointerTo();
}

// Helper to reduce vector type by one rank at front.
static VectorType reducedVectorTypeFront(VectorType tp) {
  assert((tp.getRank() > 1) && "unlowerable vector type");
  return VectorType::get(tp.getShape().drop_front(), tp.getElementType());
}

// Helper to reduce vector type by *all* but one rank at back.
static VectorType reducedVectorTypeBack(VectorType tp) {
  assert((tp.getRank() > 1) && "unlowerable vector type");
  return VectorType::get(tp.getShape().take_back(), tp.getElementType());
}

// Helper that picks the proper sequence for inserting.
static Value insertOne(ConversionPatternRewriter &rewriter,
                       LLVMTypeConverter &lowering, Location loc, Value val1,
                       Value val2, Type llvmType, int64_t rank, int64_t pos) {
  if (rank == 1) {
    auto idxType = rewriter.getIndexType();
    auto constant = rewriter.create<LLVM::ConstantOp>(
        loc, lowering.convertType(idxType),
        rewriter.getIntegerAttr(idxType, pos));
    return rewriter.create<LLVM::InsertElementOp>(loc, llvmType, val1, val2,
                                                  constant);
  }
  return rewriter.create<LLVM::InsertValueOp>(loc, llvmType, val1, val2,
                                              rewriter.getI64ArrayAttr(pos));
}

// Helper that picks the proper sequence for inserting.
static Value insertOne(PatternRewriter &rewriter, Location loc, Value from,
                       Value into, int64_t offset) {
  auto vectorType = into.getType().cast<VectorType>();
  if (vectorType.getRank() > 1)
    return rewriter.create<InsertOp>(loc, from, into, offset);
  return rewriter.create<vector::InsertElementOp>(
      loc, vectorType, from, into,
      rewriter.create<ConstantIndexOp>(loc, offset));
}

// Helper that picks the proper sequence for extracting.
static Value extractOne(ConversionPatternRewriter &rewriter,
                        LLVMTypeConverter &lowering, Location loc, Value val,
                        Type llvmType, int64_t rank, int64_t pos) {
  if (rank == 1) {
    auto idxType = rewriter.getIndexType();
    auto constant = rewriter.create<LLVM::ConstantOp>(
        loc, lowering.convertType(idxType),
        rewriter.getIntegerAttr(idxType, pos));
    return rewriter.create<LLVM::ExtractElementOp>(loc, llvmType, val,
                                                   constant);
  }
  return rewriter.create<LLVM::ExtractValueOp>(loc, llvmType, val,
                                               rewriter.getI64ArrayAttr(pos));
}

// Helper that picks the proper sequence for extracting.
static Value extractOne(PatternRewriter &rewriter, Location loc, Value vector,
                        int64_t offset) {
  auto vectorType = vector.getType().cast<VectorType>();
  if (vectorType.getRank() > 1)
    return rewriter.create<ExtractOp>(loc, vector, offset);
  return rewriter.create<vector::ExtractElementOp>(
      loc, vectorType.getElementType(), vector,
      rewriter.create<ConstantIndexOp>(loc, offset));
}

// Helper that returns a subset of `arrayAttr` as a vector of int64_t.
// TODO(rriddle): Better support for attribute subtype forwarding + slicing.
static SmallVector<int64_t, 4> getI64SubArray(ArrayAttr arrayAttr,
                                              unsigned dropFront = 0,
                                              unsigned dropBack = 0) {
  assert(arrayAttr.size() > dropFront + dropBack && "Out of bounds");
  auto range = arrayAttr.getAsRange<IntegerAttr>();
  SmallVector<int64_t, 4> res;
  res.reserve(arrayAttr.size() - dropFront - dropBack);
  for (auto it = range.begin() + dropFront, eit = range.end() - dropBack;
       it != eit; ++it)
    res.push_back((*it).getValue().getSExtValue());
  return res;
}

class VectorBroadcastOpConversion : public LLVMOpLowering {
public:
  explicit VectorBroadcastOpConversion(MLIRContext *context,
                                       LLVMTypeConverter &typeConverter)
      : LLVMOpLowering(vector::BroadcastOp::getOperationName(), context,
                       typeConverter) {}

  PatternMatchResult
  matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                  ConversionPatternRewriter &rewriter) const override {
    auto broadcastOp = cast<vector::BroadcastOp>(op);
    VectorType dstVectorType = broadcastOp.getVectorType();
    if (lowering.convertType(dstVectorType) == nullptr)
      return matchFailure();
    // Rewrite when the full vector type can be lowered (which
    // implies all 'reduced' types can be lowered too).
    auto adaptor = vector::BroadcastOpOperandAdaptor(operands);
    VectorType srcVectorType =
        broadcastOp.getSourceType().dyn_cast<VectorType>();
    rewriter.replaceOp(
        op, expandRanks(adaptor.source(), // source value to be expanded
                        op->getLoc(),     // location of original broadcast
                        srcVectorType, dstVectorType, rewriter));
    return matchSuccess();
  }

private:
  // Expands the given source value over all the ranks, as defined
  // by the source and destination type (a null source type denotes
  // expansion from a scalar value into a vector).
  //
  // TODO(ajcbik): consider replacing this one-pattern lowering
  //               with a two-pattern lowering using other vector
  //               ops once all insert/extract/shuffle operations
  //               are available with lowering implemention.
  //
  Value expandRanks(Value value, Location loc, VectorType srcVectorType,
                    VectorType dstVectorType,
                    ConversionPatternRewriter &rewriter) const {
    assert((dstVectorType != nullptr) && "invalid result type in broadcast");
    // Determine rank of source and destination.
    int64_t srcRank = srcVectorType ? srcVectorType.getRank() : 0;
    int64_t dstRank = dstVectorType.getRank();
    int64_t curDim = dstVectorType.getDimSize(0);
    if (srcRank < dstRank)
      // Duplicate this rank.
      return duplicateOneRank(value, loc, srcVectorType, dstVectorType, dstRank,
                              curDim, rewriter);
    // If all trailing dimensions are the same, the broadcast consists of
    // simply passing through the source value and we are done. Otherwise,
    // any non-matching dimension forces a stretch along this rank.
    assert((srcVectorType != nullptr) && (srcRank > 0) &&
           (srcRank == dstRank) && "invalid rank in broadcast");
    for (int64_t r = 0; r < dstRank; r++) {
      if (srcVectorType.getDimSize(r) != dstVectorType.getDimSize(r)) {
        return stretchOneRank(value, loc, srcVectorType, dstVectorType, dstRank,
                              curDim, rewriter);
      }
    }
    return value;
  }

  // Picks the best way to duplicate a single rank. For the 1-D case, a
  // single insert-elt/shuffle is the most efficient expansion. For higher
  // dimensions, however, we need dim x insert-values on a new broadcast
  // with one less leading dimension, which will be lowered "recursively"
  // to matching LLVM IR.
  // For example:
  //   v = broadcast s : f32 to vector<4x2xf32>
  // becomes:
  //   x = broadcast s : f32 to vector<2xf32>
  //   v = [x,x,x,x]
  // becomes:
  //   x = [s,s]
  //   v = [x,x,x,x]
  Value duplicateOneRank(Value value, Location loc, VectorType srcVectorType,
                         VectorType dstVectorType, int64_t rank, int64_t dim,
                         ConversionPatternRewriter &rewriter) const {
    Type llvmType = lowering.convertType(dstVectorType);
    assert((llvmType != nullptr) && "unlowerable vector type");
    if (rank == 1) {
      Value undef = rewriter.create<LLVM::UndefOp>(loc, llvmType);
      Value expand =
          insertOne(rewriter, lowering, loc, undef, value, llvmType, rank, 0);
      SmallVector<int32_t, 4> zeroValues(dim, 0);
      return rewriter.create<LLVM::ShuffleVectorOp>(
          loc, expand, undef, rewriter.getI32ArrayAttr(zeroValues));
    }
    Value expand = expandRanks(value, loc, srcVectorType,
                               reducedVectorTypeFront(dstVectorType), rewriter);
    Value result = rewriter.create<LLVM::UndefOp>(loc, llvmType);
    for (int64_t d = 0; d < dim; ++d) {
      result =
          insertOne(rewriter, lowering, loc, result, expand, llvmType, rank, d);
    }
    return result;
  }

  // Picks the best way to stretch a single rank. For the 1-D case, a
  // single insert-elt/shuffle is the most efficient expansion when at
  // a stretch. Otherwise, every dimension needs to be expanded
  // individually and individually inserted in the resulting vector.
  // For example:
  //   v = broadcast w : vector<4x1x2xf32> to vector<4x2x2xf32>
  // becomes:
  //   a = broadcast w[0] : vector<1x2xf32> to vector<2x2xf32>
  //   b = broadcast w[1] : vector<1x2xf32> to vector<2x2xf32>
  //   c = broadcast w[2] : vector<1x2xf32> to vector<2x2xf32>
  //   d = broadcast w[3] : vector<1x2xf32> to vector<2x2xf32>
  //   v = [a,b,c,d]
  // becomes:
  //   x = broadcast w[0][0] : vector<2xf32> to vector <2x2xf32>
  //   y = broadcast w[1][0] : vector<2xf32> to vector <2x2xf32>
  //   a = [x, y]
  //   etc.
  Value stretchOneRank(Value value, Location loc, VectorType srcVectorType,
                       VectorType dstVectorType, int64_t rank, int64_t dim,
                       ConversionPatternRewriter &rewriter) const {
    Type llvmType = lowering.convertType(dstVectorType);
    assert((llvmType != nullptr) && "unlowerable vector type");
    Value result = rewriter.create<LLVM::UndefOp>(loc, llvmType);
    bool atStretch = dim != srcVectorType.getDimSize(0);
    if (rank == 1) {
      assert(atStretch);
      Type redLlvmType = lowering.convertType(dstVectorType.getElementType());
      Value one =
          extractOne(rewriter, lowering, loc, value, redLlvmType, rank, 0);
      Value expand =
          insertOne(rewriter, lowering, loc, result, one, llvmType, rank, 0);
      SmallVector<int32_t, 4> zeroValues(dim, 0);
      return rewriter.create<LLVM::ShuffleVectorOp>(
          loc, expand, result, rewriter.getI32ArrayAttr(zeroValues));
    }
    VectorType redSrcType = reducedVectorTypeFront(srcVectorType);
    VectorType redDstType = reducedVectorTypeFront(dstVectorType);
    Type redLlvmType = lowering.convertType(redSrcType);
    for (int64_t d = 0; d < dim; ++d) {
      int64_t pos = atStretch ? 0 : d;
      Value one =
          extractOne(rewriter, lowering, loc, value, redLlvmType, rank, pos);
      Value expand = expandRanks(one, loc, redSrcType, redDstType, rewriter);
      result =
          insertOne(rewriter, lowering, loc, result, expand, llvmType, rank, d);
    }
    return result;
  }
};

class VectorShuffleOpConversion : public LLVMOpLowering {
public:
  explicit VectorShuffleOpConversion(MLIRContext *context,
                                     LLVMTypeConverter &typeConverter)
      : LLVMOpLowering(vector::ShuffleOp::getOperationName(), context,
                       typeConverter) {}

  PatternMatchResult
  matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                  ConversionPatternRewriter &rewriter) const override {
    auto loc = op->getLoc();
    auto adaptor = vector::ShuffleOpOperandAdaptor(operands);
    auto shuffleOp = cast<vector::ShuffleOp>(op);
    auto v1Type = shuffleOp.getV1VectorType();
    auto v2Type = shuffleOp.getV2VectorType();
    auto vectorType = shuffleOp.getVectorType();
    Type llvmType = lowering.convertType(vectorType);
    auto maskArrayAttr = shuffleOp.mask();

    // Bail if result type cannot be lowered.
    if (!llvmType)
      return matchFailure();

    // Get rank and dimension sizes.
    int64_t rank = vectorType.getRank();
    assert(v1Type.getRank() == rank);
    assert(v2Type.getRank() == rank);
    int64_t v1Dim = v1Type.getDimSize(0);

    // For rank 1, where both operands have *exactly* the same vector type,
    // there is direct shuffle support in LLVM. Use it!
    if (rank == 1 && v1Type == v2Type) {
      Value shuffle = rewriter.create<LLVM::ShuffleVectorOp>(
          loc, adaptor.v1(), adaptor.v2(), maskArrayAttr);
      rewriter.replaceOp(op, shuffle);
      return matchSuccess();
    }

    // For all other cases, insert the individual values individually.
    Value insert = rewriter.create<LLVM::UndefOp>(loc, llvmType);
    int64_t insPos = 0;
    for (auto en : llvm::enumerate(maskArrayAttr)) {
      int64_t extPos = en.value().cast<IntegerAttr>().getInt();
      Value value = adaptor.v1();
      if (extPos >= v1Dim) {
        extPos -= v1Dim;
        value = adaptor.v2();
      }
      Value extract =
          extractOne(rewriter, lowering, loc, value, llvmType, rank, extPos);
      insert = insertOne(rewriter, lowering, loc, insert, extract, llvmType,
                         rank, insPos++);
    }
    rewriter.replaceOp(op, insert);
    return matchSuccess();
  }
};

class VectorExtractElementOpConversion : public LLVMOpLowering {
public:
  explicit VectorExtractElementOpConversion(MLIRContext *context,
                                            LLVMTypeConverter &typeConverter)
      : LLVMOpLowering(vector::ExtractElementOp::getOperationName(), context,
                       typeConverter) {}

  PatternMatchResult
  matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                  ConversionPatternRewriter &rewriter) const override {
    auto adaptor = vector::ExtractElementOpOperandAdaptor(operands);
    auto extractEltOp = cast<vector::ExtractElementOp>(op);
    auto vectorType = extractEltOp.getVectorType();
    auto llvmType = lowering.convertType(vectorType.getElementType());

    // Bail if result type cannot be lowered.
    if (!llvmType)
      return matchFailure();

    rewriter.replaceOpWithNewOp<LLVM::ExtractElementOp>(
        op, llvmType, adaptor.vector(), adaptor.position());
    return matchSuccess();
  }
};

class VectorExtractOpConversion : public LLVMOpLowering {
public:
  explicit VectorExtractOpConversion(MLIRContext *context,
                                     LLVMTypeConverter &typeConverter)
      : LLVMOpLowering(vector::ExtractOp::getOperationName(), context,
                       typeConverter) {}

  PatternMatchResult
  matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                  ConversionPatternRewriter &rewriter) const override {
    auto loc = op->getLoc();
    auto adaptor = vector::ExtractOpOperandAdaptor(operands);
    auto extractOp = cast<vector::ExtractOp>(op);
    auto vectorType = extractOp.getVectorType();
    auto resultType = extractOp.getResult().getType();
    auto llvmResultType = lowering.convertType(resultType);
    auto positionArrayAttr = extractOp.position();

    // Bail if result type cannot be lowered.
    if (!llvmResultType)
      return matchFailure();

    // One-shot extraction of vector from array (only requires extractvalue).
    if (resultType.isa<VectorType>()) {
      Value extracted = rewriter.create<LLVM::ExtractValueOp>(
          loc, llvmResultType, adaptor.vector(), positionArrayAttr);
      rewriter.replaceOp(op, extracted);
      return matchSuccess();
    }

    // Potential extraction of 1-D vector from array.
    auto *context = op->getContext();
    Value extracted = adaptor.vector();
    auto positionAttrs = positionArrayAttr.getValue();
    if (positionAttrs.size() > 1) {
      auto oneDVectorType = reducedVectorTypeBack(vectorType);
      auto nMinusOnePositionAttrs =
          ArrayAttr::get(positionAttrs.drop_back(), context);
      extracted = rewriter.create<LLVM::ExtractValueOp>(
          loc, lowering.convertType(oneDVectorType), extracted,
          nMinusOnePositionAttrs);
    }

    // Remaining extraction of element from 1-D LLVM vector
    auto position = positionAttrs.back().cast<IntegerAttr>();
    auto i64Type = LLVM::LLVMType::getInt64Ty(lowering.getDialect());
    auto constant = rewriter.create<LLVM::ConstantOp>(loc, i64Type, position);
    extracted =
        rewriter.create<LLVM::ExtractElementOp>(loc, extracted, constant);
    rewriter.replaceOp(op, extracted);

    return matchSuccess();
  }
};

class VectorInsertElementOpConversion : public LLVMOpLowering {
public:
  explicit VectorInsertElementOpConversion(MLIRContext *context,
                                           LLVMTypeConverter &typeConverter)
      : LLVMOpLowering(vector::InsertElementOp::getOperationName(), context,
                       typeConverter) {}

  PatternMatchResult
  matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                  ConversionPatternRewriter &rewriter) const override {
    auto adaptor = vector::InsertElementOpOperandAdaptor(operands);
    auto insertEltOp = cast<vector::InsertElementOp>(op);
    auto vectorType = insertEltOp.getDestVectorType();
    auto llvmType = lowering.convertType(vectorType);

    // Bail if result type cannot be lowered.
    if (!llvmType)
      return matchFailure();

    rewriter.replaceOpWithNewOp<LLVM::InsertElementOp>(
        op, llvmType, adaptor.dest(), adaptor.source(), adaptor.position());
    return matchSuccess();
  }
};

class VectorInsertOpConversion : public LLVMOpLowering {
public:
  explicit VectorInsertOpConversion(MLIRContext *context,
                                    LLVMTypeConverter &typeConverter)
      : LLVMOpLowering(vector::InsertOp::getOperationName(), context,
                       typeConverter) {}

  PatternMatchResult
  matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                  ConversionPatternRewriter &rewriter) const override {
    auto loc = op->getLoc();
    auto adaptor = vector::InsertOpOperandAdaptor(operands);
    auto insertOp = cast<vector::InsertOp>(op);
    auto sourceType = insertOp.getSourceType();
    auto destVectorType = insertOp.getDestVectorType();
    auto llvmResultType = lowering.convertType(destVectorType);
    auto positionArrayAttr = insertOp.position();

    // Bail if result type cannot be lowered.
    if (!llvmResultType)
      return matchFailure();

    // One-shot insertion of a vector into an array (only requires insertvalue).
    if (sourceType.isa<VectorType>()) {
      Value inserted = rewriter.create<LLVM::InsertValueOp>(
          loc, llvmResultType, adaptor.dest(), adaptor.source(),
          positionArrayAttr);
      rewriter.replaceOp(op, inserted);
      return matchSuccess();
    }

    // Potential extraction of 1-D vector from array.
    auto *context = op->getContext();
    Value extracted = adaptor.dest();
    auto positionAttrs = positionArrayAttr.getValue();
    auto position = positionAttrs.back().cast<IntegerAttr>();
    auto oneDVectorType = destVectorType;
    if (positionAttrs.size() > 1) {
      oneDVectorType = reducedVectorTypeBack(destVectorType);
      auto nMinusOnePositionAttrs =
          ArrayAttr::get(positionAttrs.drop_back(), context);
      extracted = rewriter.create<LLVM::ExtractValueOp>(
          loc, lowering.convertType(oneDVectorType), extracted,
          nMinusOnePositionAttrs);
    }

    // Insertion of an element into a 1-D LLVM vector.
    auto i64Type = LLVM::LLVMType::getInt64Ty(lowering.getDialect());
    auto constant = rewriter.create<LLVM::ConstantOp>(loc, i64Type, position);
    Value inserted = rewriter.create<LLVM::InsertElementOp>(
        loc, lowering.convertType(oneDVectorType), extracted, adaptor.source(),
        constant);

    // Potential insertion of resulting 1-D vector into array.
    if (positionAttrs.size() > 1) {
      auto nMinusOnePositionAttrs =
          ArrayAttr::get(positionAttrs.drop_back(), context);
      inserted = rewriter.create<LLVM::InsertValueOp>(loc, llvmResultType,
                                                      adaptor.dest(), inserted,
                                                      nMinusOnePositionAttrs);
    }

    rewriter.replaceOp(op, inserted);
    return matchSuccess();
  }
};

// When ranks are different, InsertStridedSlice needs to extract a properly
// ranked vector from the destination vector into which to insert. This pattern
// only takes care of this part and forwards the rest of the conversion to
// another pattern that converts InsertStridedSlice for operands of the same
// rank.
//
// RewritePattern for InsertStridedSliceOp where source and destination vectors
// have different ranks. In this case:
//   1. the proper subvector is extracted from the destination vector
//   2. a new InsertStridedSlice op is created to insert the source in the
//   destination subvector
//   3. the destination subvector is inserted back in the proper place
//   4. the op is replaced by the result of step 3.
// The new InsertStridedSlice from step 2. will be picked up by a
// `VectorInsertStridedSliceOpSameRankRewritePattern`.
class VectorInsertStridedSliceOpDifferentRankRewritePattern
    : public OpRewritePattern<InsertStridedSliceOp> {
public:
  using OpRewritePattern<InsertStridedSliceOp>::OpRewritePattern;

  PatternMatchResult matchAndRewrite(InsertStridedSliceOp op,
                                     PatternRewriter &rewriter) const override {
    auto srcType = op.getSourceVectorType();
    auto dstType = op.getDestVectorType();

    if (op.offsets().getValue().empty())
      return matchFailure();

    auto loc = op.getLoc();
    int64_t rankDiff = dstType.getRank() - srcType.getRank();
    assert(rankDiff >= 0);
    if (rankDiff == 0)
      return matchFailure();

    int64_t rankRest = dstType.getRank() - rankDiff;
    // Extract / insert the subvector of matching rank and InsertStridedSlice
    // on it.
    Value extracted =
        rewriter.create<ExtractOp>(loc, op.dest(),
                                   getI64SubArray(op.offsets(), /*dropFront=*/0,
                                                  /*dropFront=*/rankRest));
    // A different pattern will kick in for InsertStridedSlice with matching
    // ranks.
    auto stridedSliceInnerOp = rewriter.create<InsertStridedSliceOp>(
        loc, op.source(), extracted,
        getI64SubArray(op.offsets(), /*dropFront=*/rankDiff),
        getI64SubArray(op.strides(), /*dropFront=*/rankDiff));
    rewriter.replaceOpWithNewOp<InsertOp>(
        op, stridedSliceInnerOp.getResult(), op.dest(),
        getI64SubArray(op.offsets(), /*dropFront=*/0,
                       /*dropFront=*/rankRest));
    return matchSuccess();
  }
};

// RewritePattern for InsertStridedSliceOp where source and destination vectors
// have the same rank. In this case, we reduce
//   1. the proper subvector is extracted from the destination vector
//   2. a new InsertStridedSlice op is created to insert the source in the
//   destination subvector
//   3. the destination subvector is inserted back in the proper place
//   4. the op is replaced by the result of step 3.
// The new InsertStridedSlice from step 2. will be picked up by a
// `VectorInsertStridedSliceOpSameRankRewritePattern`.
class VectorInsertStridedSliceOpSameRankRewritePattern
    : public OpRewritePattern<InsertStridedSliceOp> {
public:
  using OpRewritePattern<InsertStridedSliceOp>::OpRewritePattern;

  PatternMatchResult matchAndRewrite(InsertStridedSliceOp op,
                                     PatternRewriter &rewriter) const override {
    auto srcType = op.getSourceVectorType();
    auto dstType = op.getDestVectorType();

    if (op.offsets().getValue().empty())
      return matchFailure();

    int64_t rankDiff = dstType.getRank() - srcType.getRank();
    assert(rankDiff >= 0);
    if (rankDiff != 0)
      return matchFailure();

    if (srcType == dstType) {
      rewriter.replaceOp(op, op.source());
      return matchSuccess();
    }

    int64_t offset =
        op.offsets().getValue().front().cast<IntegerAttr>().getInt();
    int64_t size = srcType.getShape().front();
    int64_t stride =
        op.strides().getValue().front().cast<IntegerAttr>().getInt();

    auto loc = op.getLoc();
    Value res = op.dest();
    // For each slice of the source vector along the most major dimension.
    for (int64_t off = offset, e = offset + size * stride, idx = 0; off < e;
         off += stride, ++idx) {
      // 1. extract the proper subvector (or element) from source
      Value extractedSource = extractOne(rewriter, loc, op.source(), idx);
      if (extractedSource.getType().isa<VectorType>()) {
        // 2. If we have a vector, extract the proper subvector from destination
        // Otherwise we are at the element level and no need to recurse.
        Value extractedDest = extractOne(rewriter, loc, op.dest(), off);
        // 3. Reduce the problem to lowering a new InsertStridedSlice op with
        // smaller rank.
        InsertStridedSliceOp insertStridedSliceOp =
            rewriter.create<InsertStridedSliceOp>(
                loc, extractedSource, extractedDest,
                getI64SubArray(op.offsets(), /* dropFront=*/1),
                getI64SubArray(op.strides(), /* dropFront=*/1));
        // Call matchAndRewrite recursively from within the pattern. This
        // circumvents the current limitation that a given pattern cannot
        // be called multiple times by the PatternRewrite infrastructure (to
        // avoid infinite recursion, but in this case, infinite recursion
        // cannot happen because the rank is strictly decreasing).
        // TODO(rriddle, nicolasvasilache) Implement something like a hook for
        // a potential function that must decrease and allow the same pattern
        // multiple times.
        auto success = matchAndRewrite(insertStridedSliceOp, rewriter);
        (void)success;
        assert(success && "Unexpected failure");
        extractedSource = insertStridedSliceOp;
      }
      // 4. Insert the extractedSource into the res vector.
      res = insertOne(rewriter, loc, extractedSource, res, off);
    }

    rewriter.replaceOp(op, res);
    return matchSuccess();
  }
};

class VectorOuterProductOpConversion : public LLVMOpLowering {
public:
  explicit VectorOuterProductOpConversion(MLIRContext *context,
                                          LLVMTypeConverter &typeConverter)
      : LLVMOpLowering(vector::OuterProductOp::getOperationName(), context,
                       typeConverter) {}

  PatternMatchResult
  matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                  ConversionPatternRewriter &rewriter) const override {
    auto loc = op->getLoc();
    auto adaptor = vector::OuterProductOpOperandAdaptor(operands);
    auto *ctx = op->getContext();
    auto vLHS = adaptor.lhs().getType().cast<LLVM::LLVMType>();
    auto vRHS = adaptor.rhs().getType().cast<LLVM::LLVMType>();
    auto rankLHS = vLHS.getUnderlyingType()->getVectorNumElements();
    auto rankRHS = vRHS.getUnderlyingType()->getVectorNumElements();
    auto llvmArrayOfVectType = lowering.convertType(
        cast<vector::OuterProductOp>(op).getResult().getType());
    Value desc = rewriter.create<LLVM::UndefOp>(loc, llvmArrayOfVectType);
    Value a = adaptor.lhs(), b = adaptor.rhs();
    Value acc = adaptor.acc().empty() ? nullptr : adaptor.acc().front();
    SmallVector<Value, 8> lhs, accs;
    lhs.reserve(rankLHS);
    accs.reserve(rankLHS);
    for (unsigned d = 0, e = rankLHS; d < e; ++d) {
      // shufflevector explicitly requires i32.
      auto attr = rewriter.getI32IntegerAttr(d);
      SmallVector<Attribute, 4> bcastAttr(rankRHS, attr);
      auto bcastArrayAttr = ArrayAttr::get(bcastAttr, ctx);
      Value aD = nullptr, accD = nullptr;
      // 1. Broadcast the element a[d] into vector aD.
      aD = rewriter.create<LLVM::ShuffleVectorOp>(loc, a, a, bcastArrayAttr);
      // 2. If acc is present, extract 1-d vector acc[d] into accD.
      if (acc)
        accD = rewriter.create<LLVM::ExtractValueOp>(
            loc, vRHS, acc, rewriter.getI64ArrayAttr(d));
      // 3. Compute aD outer b (plus accD, if relevant).
      Value aOuterbD =
          accD ? rewriter.create<LLVM::FMulAddOp>(loc, vRHS, aD, b, accD)
                     .getResult()
               : rewriter.create<LLVM::FMulOp>(loc, aD, b).getResult();
      // 4. Insert as value `d` in the descriptor.
      desc = rewriter.create<LLVM::InsertValueOp>(loc, llvmArrayOfVectType,
                                                  desc, aOuterbD,
                                                  rewriter.getI64ArrayAttr(d));
    }
    rewriter.replaceOp(op, desc);
    return matchSuccess();
  }
};

class VectorTypeCastOpConversion : public LLVMOpLowering {
public:
  explicit VectorTypeCastOpConversion(MLIRContext *context,
                                      LLVMTypeConverter &typeConverter)
      : LLVMOpLowering(vector::TypeCastOp::getOperationName(), context,
                       typeConverter) {}

  PatternMatchResult
  matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                  ConversionPatternRewriter &rewriter) const override {
    auto loc = op->getLoc();
    vector::TypeCastOp castOp = cast<vector::TypeCastOp>(op);
    MemRefType sourceMemRefType =
        castOp.getOperand().getType().cast<MemRefType>();
    MemRefType targetMemRefType =
        castOp.getResult().getType().cast<MemRefType>();

    // Only static shape casts supported atm.
    if (!sourceMemRefType.hasStaticShape() ||
        !targetMemRefType.hasStaticShape())
      return matchFailure();

    auto llvmSourceDescriptorTy =
        operands[0].getType().dyn_cast<LLVM::LLVMType>();
    if (!llvmSourceDescriptorTy || !llvmSourceDescriptorTy.isStructTy())
      return matchFailure();
    MemRefDescriptor sourceMemRef(operands[0]);

    auto llvmTargetDescriptorTy = lowering.convertType(targetMemRefType)
                                      .dyn_cast_or_null<LLVM::LLVMType>();
    if (!llvmTargetDescriptorTy || !llvmTargetDescriptorTy.isStructTy())
      return matchFailure();

    int64_t offset;
    SmallVector<int64_t, 4> strides;
    auto successStrides =
        getStridesAndOffset(sourceMemRefType, strides, offset);
    bool isContiguous = (strides.back() == 1);
    if (isContiguous) {
      auto sizes = sourceMemRefType.getShape();
      for (int index = 0, e = strides.size() - 2; index < e; ++index) {
        if (strides[index] != strides[index + 1] * sizes[index + 1]) {
          isContiguous = false;
          break;
        }
      }
    }
    // Only contiguous source tensors supported atm.
    if (failed(successStrides) || !isContiguous)
      return matchFailure();

    auto int64Ty = LLVM::LLVMType::getInt64Ty(lowering.getDialect());

    // Create descriptor.
    auto desc = MemRefDescriptor::undef(rewriter, loc, llvmTargetDescriptorTy);
    Type llvmTargetElementTy = desc.getElementType();
    // Set allocated ptr.
    Value allocated = sourceMemRef.allocatedPtr(rewriter, loc);
    allocated =
        rewriter.create<LLVM::BitcastOp>(loc, llvmTargetElementTy, allocated);
    desc.setAllocatedPtr(rewriter, loc, allocated);
    // Set aligned ptr.
    Value ptr = sourceMemRef.alignedPtr(rewriter, loc);
    ptr = rewriter.create<LLVM::BitcastOp>(loc, llvmTargetElementTy, ptr);
    desc.setAlignedPtr(rewriter, loc, ptr);
    // Fill offset 0.
    auto attr = rewriter.getIntegerAttr(rewriter.getIndexType(), 0);
    auto zero = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, attr);
    desc.setOffset(rewriter, loc, zero);

    // Fill size and stride descriptors in memref.
    for (auto indexedSize : llvm::enumerate(targetMemRefType.getShape())) {
      int64_t index = indexedSize.index();
      auto sizeAttr =
          rewriter.getIntegerAttr(rewriter.getIndexType(), indexedSize.value());
      auto size = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, sizeAttr);
      desc.setSize(rewriter, loc, index, size);
      auto strideAttr =
          rewriter.getIntegerAttr(rewriter.getIndexType(), strides[index]);
      auto stride = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, strideAttr);
      desc.setStride(rewriter, loc, index, stride);
    }

    rewriter.replaceOp(op, {desc});
    return matchSuccess();
  }
};

class VectorPrintOpConversion : public LLVMOpLowering {
public:
  explicit VectorPrintOpConversion(MLIRContext *context,
                                   LLVMTypeConverter &typeConverter)
      : LLVMOpLowering(vector::PrintOp::getOperationName(), context,
                       typeConverter) {}

  // Proof-of-concept lowering implementation that relies on a small
  // runtime support library, which only needs to provide a few
  // printing methods (single value for all data types, opening/closing
  // bracket, comma, newline). The lowering fully unrolls a vector
  // in terms of these elementary printing operations. The advantage
  // of this approach is that the library can remain unaware of all
  // low-level implementation details of vectors while still supporting
  // output of any shaped and dimensioned vector. Due to full unrolling,
  // this approach is less suited for very large vectors though.
  //
  // TODO(ajcbik): rely solely on libc in future? something else?
  //
  PatternMatchResult
  matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                  ConversionPatternRewriter &rewriter) const override {
    auto printOp = cast<vector::PrintOp>(op);
    auto adaptor = vector::PrintOpOperandAdaptor(operands);
    Type printType = printOp.getPrintType();

    if (lowering.convertType(printType) == nullptr)
      return matchFailure();

    // Make sure element type has runtime support (currently just Float/Double).
    VectorType vectorType = printType.dyn_cast<VectorType>();
    Type eltType = vectorType ? vectorType.getElementType() : printType;
    int64_t rank = vectorType ? vectorType.getRank() : 0;
    Operation *printer;
    if (eltType.isF32())
      printer = getPrintFloat(op);
    else if (eltType.isF64())
      printer = getPrintDouble(op);
    else
      return matchFailure();

    // Unroll vector into elementary print calls.
    emitRanks(rewriter, op, adaptor.source(), vectorType, printer, rank);
    emitCall(rewriter, op->getLoc(), getPrintNewline(op));
    rewriter.eraseOp(op);
    return matchSuccess();
  }

private:
  void emitRanks(ConversionPatternRewriter &rewriter, Operation *op,
                 Value value, VectorType vectorType, Operation *printer,
                 int64_t rank) const {
    Location loc = op->getLoc();
    if (rank == 0) {
      emitCall(rewriter, loc, printer, value);
      return;
    }

    emitCall(rewriter, loc, getPrintOpen(op));
    Operation *printComma = getPrintComma(op);
    int64_t dim = vectorType.getDimSize(0);
    for (int64_t d = 0; d < dim; ++d) {
      auto reducedType =
          rank > 1 ? reducedVectorTypeFront(vectorType) : nullptr;
      auto llvmType = lowering.convertType(
          rank > 1 ? reducedType : vectorType.getElementType());
      Value nestedVal =
          extractOne(rewriter, lowering, loc, value, llvmType, rank, d);
      emitRanks(rewriter, op, nestedVal, reducedType, printer, rank - 1);
      if (d != dim - 1)
        emitCall(rewriter, loc, printComma);
    }
    emitCall(rewriter, loc, getPrintClose(op));
  }

  // Helper to emit a call.
  static void emitCall(ConversionPatternRewriter &rewriter, Location loc,
                       Operation *ref, ValueRange params = ValueRange()) {
    rewriter.create<LLVM::CallOp>(loc, ArrayRef<Type>{},
                                  rewriter.getSymbolRefAttr(ref), params);
  }

  // Helper for printer method declaration (first hit) and lookup.
  static Operation *getPrint(Operation *op, LLVM::LLVMDialect *dialect,
                             StringRef name, ArrayRef<LLVM::LLVMType> params) {
    auto module = op->getParentOfType<ModuleOp>();
    auto func = module.lookupSymbol<LLVM::LLVMFuncOp>(name);
    if (func)
      return func;
    OpBuilder moduleBuilder(module.getBodyRegion());
    return moduleBuilder.create<LLVM::LLVMFuncOp>(
        op->getLoc(), name,
        LLVM::LLVMType::getFunctionTy(LLVM::LLVMType::getVoidTy(dialect),
                                      params, /*isVarArg=*/false));
  }

  // Helpers for method names.
  Operation *getPrintFloat(Operation *op) const {
    LLVM::LLVMDialect *dialect = lowering.getDialect();
    return getPrint(op, dialect, "print_f32",
                    LLVM::LLVMType::getFloatTy(dialect));
  }
  Operation *getPrintDouble(Operation *op) const {
    LLVM::LLVMDialect *dialect = lowering.getDialect();
    return getPrint(op, dialect, "print_f64",
                    LLVM::LLVMType::getDoubleTy(dialect));
  }
  Operation *getPrintOpen(Operation *op) const {
    return getPrint(op, lowering.getDialect(), "print_open", {});
  }
  Operation *getPrintClose(Operation *op) const {
    return getPrint(op, lowering.getDialect(), "print_close", {});
  }
  Operation *getPrintComma(Operation *op) const {
    return getPrint(op, lowering.getDialect(), "print_comma", {});
  }
  Operation *getPrintNewline(Operation *op) const {
    return getPrint(op, lowering.getDialect(), "print_newline", {});
  }
};

/// Progressive lowering of StridedSliceOp to either:
///   1. extractelement + insertelement for the 1-D case
///   2. extract + optional strided_slice + insert for the n-D case.
class VectorStridedSliceOpConversion : public OpRewritePattern<StridedSliceOp> {
public:
  using OpRewritePattern<StridedSliceOp>::OpRewritePattern;

  PatternMatchResult matchAndRewrite(StridedSliceOp op,
                                     PatternRewriter &rewriter) const override {
    auto dstType = op.getResult().getType().cast<VectorType>();

    assert(!op.offsets().getValue().empty() && "Unexpected empty offsets");

    int64_t offset =
        op.offsets().getValue().front().cast<IntegerAttr>().getInt();
    int64_t size = op.sizes().getValue().front().cast<IntegerAttr>().getInt();
    int64_t stride =
        op.strides().getValue().front().cast<IntegerAttr>().getInt();

    auto loc = op.getLoc();
    auto elemType = dstType.getElementType();
    assert(elemType.isIntOrIndexOrFloat());
    Value zero = rewriter.create<ConstantOp>(loc, elemType,
                                             rewriter.getZeroAttr(elemType));
    Value res = rewriter.create<SplatOp>(loc, dstType, zero);
    for (int64_t off = offset, e = offset + size * stride, idx = 0; off < e;
         off += stride, ++idx) {
      Value extracted = extractOne(rewriter, loc, op.vector(), off);
      if (op.offsets().getValue().size() > 1) {
        StridedSliceOp stridedSliceOp = rewriter.create<StridedSliceOp>(
            loc, extracted, getI64SubArray(op.offsets(), /* dropFront=*/1),
            getI64SubArray(op.sizes(), /* dropFront=*/1),
            getI64SubArray(op.strides(), /* dropFront=*/1));
        // Call matchAndRewrite recursively from within the pattern. This
        // circumvents the current limitation that a given pattern cannot
        // be called multiple times by the PatternRewrite infrastructure (to
        // avoid infinite recursion, but in this case, infinite recursion
        // cannot happen because the rank is strictly decreasing).
        // TODO(rriddle, nicolasvasilache) Implement something like a hook for
        // a potential function that must decrease and allow the same pattern
        // multiple times.
        auto success = matchAndRewrite(stridedSliceOp, rewriter);
        (void)success;
        assert(success && "Unexpected failure");
        extracted = stridedSliceOp;
      }
      res = insertOne(rewriter, loc, extracted, res, idx);
    }
    rewriter.replaceOp(op, {res});
    return matchSuccess();
  }
};

} // namespace

/// Populate the given list with patterns that convert from Vector to LLVM.
void mlir::populateVectorToLLVMConversionPatterns(
    LLVMTypeConverter &converter, OwningRewritePatternList &patterns) {
  MLIRContext *ctx = converter.getDialect()->getContext();
  patterns.insert<VectorInsertStridedSliceOpDifferentRankRewritePattern,
                  VectorInsertStridedSliceOpSameRankRewritePattern,
                  VectorStridedSliceOpConversion>(ctx);
  patterns.insert<VectorBroadcastOpConversion, VectorShuffleOpConversion,
                  VectorExtractElementOpConversion, VectorExtractOpConversion,
                  VectorInsertElementOpConversion, VectorInsertOpConversion,
                  VectorOuterProductOpConversion, VectorTypeCastOpConversion,
                  VectorPrintOpConversion>(ctx, converter);
}

namespace {
struct LowerVectorToLLVMPass : public ModulePass<LowerVectorToLLVMPass> {
  void runOnModule() override;
};
} // namespace

void LowerVectorToLLVMPass::runOnModule() {
  // Convert to the LLVM IR dialect using the converter defined above.
  OwningRewritePatternList patterns;
  LLVMTypeConverter converter(&getContext());
  populateVectorToLLVMConversionPatterns(converter, patterns);
  populateStdToLLVMConversionPatterns(converter, patterns);

  ConversionTarget target(getContext());
  target.addLegalDialect<LLVM::LLVMDialect>();
  target.addDynamicallyLegalOp<FuncOp>(
      [&](FuncOp op) { return converter.isSignatureLegal(op.getType()); });
  if (failed(
          applyPartialConversion(getModule(), target, patterns, &converter))) {
    signalPassFailure();
  }
}

OpPassBase<ModuleOp> *mlir::createLowerVectorToLLVMPass() {
  return new LowerVectorToLLVMPass();
}

static PassRegistration<LowerVectorToLLVMPass>
    pass("convert-vector-to-llvm",
         "Lower the operations from the vector dialect into the LLVM dialect");