| 1 | //===- VectorTransferPermutationMapRewritePatterns.cpp - Xfer map rewrite -===// |
| 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 | // This file implements rewrite patterns for the permutation_map attribute of |
| 10 | // vector.transfer operations. |
| 11 | // |
| 12 | //===----------------------------------------------------------------------===// |
| 13 | |
| 14 | #include "mlir/Dialect/MemRef/IR/MemRef.h" |
| 15 | #include "mlir/Dialect/Vector/Transforms/LoweringPatterns.h" |
| 16 | |
| 17 | using namespace mlir; |
| 18 | using namespace mlir::vector; |
| 19 | |
| 20 | /// Transpose a vector transfer op's `in_bounds` attribute by applying reverse |
| 21 | /// permutation based on the given indices. |
| 22 | static ArrayAttr |
| 23 | inverseTransposeInBoundsAttr(OpBuilder &builder, ArrayAttr attr, |
| 24 | const SmallVector<unsigned> &permutation) { |
| 25 | SmallVector<bool> newInBoundsValues(permutation.size()); |
| 26 | size_t index = 0; |
| 27 | for (unsigned pos : permutation) |
| 28 | newInBoundsValues[pos] = |
| 29 | cast<BoolAttr>(Val: attr.getValue()[index++]).getValue(); |
| 30 | return builder.getBoolArrayAttr(values: newInBoundsValues); |
| 31 | } |
| 32 | |
| 33 | /// Extend the rank of a vector Value by `addedRanks` by adding outer unit |
| 34 | /// dimensions. |
| 35 | static Value extendVectorRank(OpBuilder &builder, Location loc, Value vec, |
| 36 | int64_t addedRank) { |
| 37 | auto originalVecType = cast<VectorType>(Val: vec.getType()); |
| 38 | SmallVector<int64_t> newShape(addedRank, 1); |
| 39 | newShape.append(in_start: originalVecType.getShape().begin(), |
| 40 | in_end: originalVecType.getShape().end()); |
| 41 | |
| 42 | SmallVector<bool> newScalableDims(addedRank, false); |
| 43 | newScalableDims.append(in_start: originalVecType.getScalableDims().begin(), |
| 44 | in_end: originalVecType.getScalableDims().end()); |
| 45 | VectorType newVecType = VectorType::get( |
| 46 | shape: newShape, elementType: originalVecType.getElementType(), scalableDims: newScalableDims); |
| 47 | return builder.create<vector::BroadcastOp>(location: loc, args&: newVecType, args&: vec); |
| 48 | } |
| 49 | |
| 50 | /// Extend the rank of a vector Value by `addedRanks` by adding inner unit |
| 51 | /// dimensions. |
| 52 | static Value extendMaskRank(OpBuilder &builder, Location loc, Value vec, |
| 53 | int64_t addedRank) { |
| 54 | Value broadcasted = extendVectorRank(builder, loc, vec, addedRank); |
| 55 | SmallVector<int64_t> permutation; |
| 56 | for (int64_t i = addedRank, |
| 57 | e = cast<VectorType>(Val: broadcasted.getType()).getRank(); |
| 58 | i < e; ++i) |
| 59 | permutation.push_back(Elt: i); |
| 60 | for (int64_t i = 0; i < addedRank; ++i) |
| 61 | permutation.push_back(Elt: i); |
| 62 | return builder.create<vector::TransposeOp>(location: loc, args&: broadcasted, args&: permutation); |
| 63 | } |
| 64 | |
| 65 | //===----------------------------------------------------------------------===// |
| 66 | // populateVectorTransferPermutationMapLoweringPatterns |
| 67 | //===----------------------------------------------------------------------===// |
| 68 | |
| 69 | namespace { |
| 70 | /// Lower transfer_read op with permutation into a transfer_read with a |
| 71 | /// permutation map composed of leading zeros followed by a minor identiy + |
| 72 | /// vector.transpose op. |
| 73 | /// Ex: |
| 74 | /// vector.transfer_read ... |
| 75 | /// permutation_map: (d0, d1, d2) -> (0, d1) |
| 76 | /// into: |
| 77 | /// %v = vector.transfer_read ... |
| 78 | /// permutation_map: (d0, d1, d2) -> (d1, 0) |
| 79 | /// vector.transpose %v, [1, 0] |
| 80 | /// |
| 81 | /// vector.transfer_read ... |
| 82 | /// permutation_map: (d0, d1, d2, d3) -> (0, 0, 0, d1, d3) |
| 83 | /// into: |
| 84 | /// %v = vector.transfer_read ... |
| 85 | /// permutation_map: (d0, d1, d2, d3) -> (0, 0, d1, 0, d3) |
| 86 | /// vector.transpose %v, [0, 1, 3, 2, 4] |
| 87 | /// Note that an alternative is to transform it to linalg.transpose + |
| 88 | /// vector.transfer_read to do the transpose in memory instead. |
| 89 | struct TransferReadPermutationLowering |
| 90 | : public MaskableOpRewritePattern<vector::TransferReadOp> { |
| 91 | using MaskableOpRewritePattern::MaskableOpRewritePattern; |
| 92 | |
| 93 | FailureOr<mlir::Value> |
| 94 | matchAndRewriteMaskableOp(vector::TransferReadOp op, |
| 95 | MaskingOpInterface maskOp, |
| 96 | PatternRewriter &rewriter) const override { |
| 97 | // TODO: support 0-d corner case. |
| 98 | if (op.getTransferRank() == 0) |
| 99 | return rewriter.notifyMatchFailure(arg&: op, msg: "0-d corner case not supported" ); |
| 100 | // TODO: Support transfer_read inside MaskOp case. |
| 101 | if (maskOp) |
| 102 | return rewriter.notifyMatchFailure(arg&: op, msg: "Masked case not supported" ); |
| 103 | |
| 104 | SmallVector<unsigned> permutation; |
| 105 | AffineMap map = op.getPermutationMap(); |
| 106 | if (map.getNumResults() == 0) |
| 107 | return rewriter.notifyMatchFailure(arg&: op, msg: "0 result permutation map" ); |
| 108 | if (!map.isPermutationOfMinorIdentityWithBroadcasting(permutedDims&: permutation)) { |
| 109 | return rewriter.notifyMatchFailure( |
| 110 | arg&: op, msg: "map is not permutable to minor identity, apply another pattern" ); |
| 111 | } |
| 112 | AffineMap permutationMap = |
| 113 | map.getPermutationMap(permutation, context: op.getContext()); |
| 114 | if (permutationMap.isIdentity()) |
| 115 | return rewriter.notifyMatchFailure(arg&: op, msg: "map is not identity" ); |
| 116 | |
| 117 | permutationMap = map.getPermutationMap(permutation, context: op.getContext()); |
| 118 | // Caluclate the map of the new read by applying the inverse permutation. |
| 119 | permutationMap = inversePermutation(map: permutationMap); |
| 120 | AffineMap newMap = permutationMap.compose(map); |
| 121 | // Apply the reverse transpose to deduce the type of the transfer_read. |
| 122 | ArrayRef<int64_t> originalShape = op.getVectorType().getShape(); |
| 123 | SmallVector<int64_t> newVectorShape(originalShape.size()); |
| 124 | ArrayRef<bool> originalScalableDims = op.getVectorType().getScalableDims(); |
| 125 | SmallVector<bool> newScalableDims(originalShape.size()); |
| 126 | for (const auto &pos : llvm::enumerate(First&: permutation)) { |
| 127 | newVectorShape[pos.value()] = originalShape[pos.index()]; |
| 128 | newScalableDims[pos.value()] = originalScalableDims[pos.index()]; |
| 129 | } |
| 130 | |
| 131 | // Transpose in_bounds attribute. |
| 132 | ArrayAttr newInBoundsAttr = |
| 133 | inverseTransposeInBoundsAttr(builder&: rewriter, attr: op.getInBounds(), permutation); |
| 134 | |
| 135 | // Generate new transfer_read operation. |
| 136 | VectorType newReadType = VectorType::get( |
| 137 | shape: newVectorShape, elementType: op.getVectorType().getElementType(), scalableDims: newScalableDims); |
| 138 | Value newRead = rewriter.create<vector::TransferReadOp>( |
| 139 | location: op.getLoc(), args&: newReadType, args: op.getBase(), args: op.getIndices(), |
| 140 | args: AffineMapAttr::get(value: newMap), args: op.getPadding(), args: op.getMask(), |
| 141 | args&: newInBoundsAttr); |
| 142 | |
| 143 | // Transpose result of transfer_read. |
| 144 | SmallVector<int64_t> transposePerm(permutation.begin(), permutation.end()); |
| 145 | return rewriter |
| 146 | .create<vector::TransposeOp>(location: op.getLoc(), args&: newRead, args&: transposePerm) |
| 147 | .getResult(); |
| 148 | } |
| 149 | }; |
| 150 | |
| 151 | /// Lower transfer_write op with permutation into a transfer_write with a |
| 152 | /// minor identity permutation map. (transfer_write ops cannot have broadcasts.) |
| 153 | /// Ex: |
| 154 | /// vector.transfer_write %v ... |
| 155 | /// permutation_map: (d0, d1, d2) -> (d2, d0, d1) |
| 156 | /// into: |
| 157 | /// %tmp = vector.transpose %v, [2, 0, 1] |
| 158 | /// vector.transfer_write %tmp ... |
| 159 | /// permutation_map: (d0, d1, d2) -> (d0, d1, d2) |
| 160 | /// |
| 161 | /// vector.transfer_write %v ... |
| 162 | /// permutation_map: (d0, d1, d2, d3) -> (d3, d2) |
| 163 | /// into: |
| 164 | /// %tmp = vector.transpose %v, [1, 0] |
| 165 | /// %v = vector.transfer_write %tmp ... |
| 166 | /// permutation_map: (d0, d1, d2, d3) -> (d2, d3) |
| 167 | struct TransferWritePermutationLowering |
| 168 | : public MaskableOpRewritePattern<vector::TransferWriteOp> { |
| 169 | using MaskableOpRewritePattern::MaskableOpRewritePattern; |
| 170 | |
| 171 | FailureOr<mlir::Value> |
| 172 | matchAndRewriteMaskableOp(vector::TransferWriteOp op, |
| 173 | MaskingOpInterface maskOp, |
| 174 | PatternRewriter &rewriter) const override { |
| 175 | // TODO: support 0-d corner case. |
| 176 | if (op.getTransferRank() == 0) |
| 177 | return rewriter.notifyMatchFailure(arg&: op, msg: "0-d corner case not supported" ); |
| 178 | // TODO: Support transfer_write inside MaskOp case. |
| 179 | if (maskOp) |
| 180 | return rewriter.notifyMatchFailure(arg&: op, msg: "Masked case not supported" ); |
| 181 | |
| 182 | SmallVector<unsigned> permutation; |
| 183 | AffineMap map = op.getPermutationMap(); |
| 184 | if (map.isMinorIdentity()) |
| 185 | return rewriter.notifyMatchFailure(arg&: op, msg: "map is already minor identity" ); |
| 186 | |
| 187 | if (!map.isPermutationOfMinorIdentityWithBroadcasting(permutedDims&: permutation)) { |
| 188 | return rewriter.notifyMatchFailure( |
| 189 | arg&: op, msg: "map is not permutable to minor identity, apply another pattern" ); |
| 190 | } |
| 191 | |
| 192 | // Remove unused dims from the permutation map. E.g.: |
| 193 | // E.g.: (d0, d1, d2, d3, d4, d5) -> (d5, d3, d4) |
| 194 | // comp = (d0, d1, d2) -> (d2, d0, d1) |
| 195 | auto comp = compressUnusedDims(map); |
| 196 | AffineMap permutationMap = inversePermutation(map: comp); |
| 197 | // Get positions of remaining result dims. |
| 198 | SmallVector<int64_t> indices; |
| 199 | llvm::transform(Range: permutationMap.getResults(), d_first: std::back_inserter(x&: indices), |
| 200 | F: [](AffineExpr expr) { |
| 201 | return dyn_cast<AffineDimExpr>(Val&: expr).getPosition(); |
| 202 | }); |
| 203 | |
| 204 | // Transpose in_bounds attribute. |
| 205 | ArrayAttr newInBoundsAttr = |
| 206 | inverseTransposeInBoundsAttr(builder&: rewriter, attr: op.getInBounds(), permutation); |
| 207 | |
| 208 | // Generate new transfer_write operation. |
| 209 | Value newVec = rewriter.create<vector::TransposeOp>( |
| 210 | location: op.getLoc(), args: op.getVector(), args&: indices); |
| 211 | auto newMap = AffineMap::getMinorIdentityMap( |
| 212 | dims: map.getNumDims(), results: map.getNumResults(), context: rewriter.getContext()); |
| 213 | auto newWrite = rewriter.create<vector::TransferWriteOp>( |
| 214 | location: op.getLoc(), args&: newVec, args: op.getBase(), args: op.getIndices(), |
| 215 | args: AffineMapAttr::get(value: newMap), args: op.getMask(), args&: newInBoundsAttr); |
| 216 | if (newWrite.hasPureTensorSemantics()) |
| 217 | return newWrite.getResult(); |
| 218 | // In the memref case there's no return value. Use empty value to signal |
| 219 | // success. |
| 220 | return Value(); |
| 221 | } |
| 222 | }; |
| 223 | |
| 224 | /// Convert a transfer.write op with a map which isn't the permutation of a |
| 225 | /// minor identity into a vector.broadcast + transfer_write with permutation of |
| 226 | /// minor identity map by adding unit dim on inner dimension. Ex: |
| 227 | /// ``` |
| 228 | /// vector.transfer_write %v |
| 229 | /// {permutation_map = affine_map<(d0, d1, d2, d3) -> (d1, d2)>} : |
| 230 | /// vector<8x16xf32> |
| 231 | /// ``` |
| 232 | /// into: |
| 233 | /// ``` |
| 234 | /// %v1 = vector.broadcast %v : vector<8x16xf32> to vector<1x8x16xf32> |
| 235 | /// vector.transfer_write %v1 |
| 236 | /// {permutation_map = affine_map<(d0, d1, d2, d3) -> (d3, d1, d2)>} : |
| 237 | /// vector<1x8x16xf32> |
| 238 | /// ``` |
| 239 | struct TransferWriteNonPermutationLowering |
| 240 | : public MaskableOpRewritePattern<vector::TransferWriteOp> { |
| 241 | using MaskableOpRewritePattern::MaskableOpRewritePattern; |
| 242 | |
| 243 | FailureOr<mlir::Value> |
| 244 | matchAndRewriteMaskableOp(vector::TransferWriteOp op, |
| 245 | MaskingOpInterface maskOp, |
| 246 | PatternRewriter &rewriter) const override { |
| 247 | // TODO: support 0-d corner case. |
| 248 | if (op.getTransferRank() == 0) |
| 249 | return rewriter.notifyMatchFailure(arg&: op, msg: "0-d corner case not supported" ); |
| 250 | // TODO: Support transfer_write inside MaskOp case. |
| 251 | if (maskOp) |
| 252 | return rewriter.notifyMatchFailure(arg&: op, msg: "Masked case not supported" ); |
| 253 | |
| 254 | SmallVector<unsigned> permutation; |
| 255 | AffineMap map = op.getPermutationMap(); |
| 256 | if (map.isPermutationOfMinorIdentityWithBroadcasting(permutedDims&: permutation)) { |
| 257 | return rewriter.notifyMatchFailure( |
| 258 | arg&: op, |
| 259 | msg: "map is already permutable to minor identity, apply another pattern" ); |
| 260 | } |
| 261 | |
| 262 | // Missing outer dimensions are allowed, find the most outer existing |
| 263 | // dimension then deduce the missing inner dimensions. |
| 264 | SmallVector<bool> foundDim(map.getNumDims(), false); |
| 265 | for (AffineExpr exp : map.getResults()) |
| 266 | foundDim[cast<AffineDimExpr>(Val&: exp).getPosition()] = true; |
| 267 | SmallVector<AffineExpr> exprs; |
| 268 | bool foundFirstDim = false; |
| 269 | SmallVector<int64_t> missingInnerDim; |
| 270 | for (size_t i = 0; i < foundDim.size(); i++) { |
| 271 | if (foundDim[i]) { |
| 272 | foundFirstDim = true; |
| 273 | continue; |
| 274 | } |
| 275 | if (!foundFirstDim) |
| 276 | continue; |
| 277 | // Once we found one outer dimension existing in the map keep track of all |
| 278 | // the missing dimensions after that. |
| 279 | missingInnerDim.push_back(Elt: i); |
| 280 | exprs.push_back(Elt: rewriter.getAffineDimExpr(position: i)); |
| 281 | } |
| 282 | // Vector: add unit dims at the beginning of the shape. |
| 283 | Value newVec = extendVectorRank(builder&: rewriter, loc: op.getLoc(), vec: op.getVector(), |
| 284 | addedRank: missingInnerDim.size()); |
| 285 | // Mask: add unit dims at the end of the shape. |
| 286 | Value newMask; |
| 287 | if (op.getMask()) |
| 288 | newMask = extendMaskRank(builder&: rewriter, loc: op.getLoc(), vec: op.getMask(), |
| 289 | addedRank: missingInnerDim.size()); |
| 290 | exprs.append(in_start: map.getResults().begin(), in_end: map.getResults().end()); |
| 291 | AffineMap newMap = |
| 292 | AffineMap::get(dimCount: map.getNumDims(), symbolCount: 0, results: exprs, context: op.getContext()); |
| 293 | // All the new dimensions added are inbound. |
| 294 | SmallVector<bool> newInBoundsValues(missingInnerDim.size(), true); |
| 295 | for (int64_t i = 0, e = op.getVectorType().getRank(); i < e; ++i) { |
| 296 | newInBoundsValues.push_back(Elt: op.isDimInBounds(dim: i)); |
| 297 | } |
| 298 | ArrayAttr newInBoundsAttr = rewriter.getBoolArrayAttr(values: newInBoundsValues); |
| 299 | auto newWrite = rewriter.create<vector::TransferWriteOp>( |
| 300 | location: op.getLoc(), args&: newVec, args: op.getBase(), args: op.getIndices(), |
| 301 | args: AffineMapAttr::get(value: newMap), args&: newMask, args&: newInBoundsAttr); |
| 302 | if (newWrite.hasPureTensorSemantics()) |
| 303 | return newWrite.getResult(); |
| 304 | // In the memref case there's no return value. Use empty value to signal |
| 305 | // success. |
| 306 | return Value(); |
| 307 | } |
| 308 | }; |
| 309 | |
| 310 | /// Lower transfer_read op with broadcast in the leading dimensions into |
| 311 | /// transfer_read of lower rank + vector.broadcast. |
| 312 | /// Ex: vector.transfer_read ... |
| 313 | /// permutation_map: (d0, d1, d2, d3) -> (0, d1, 0, d3) |
| 314 | /// into: |
| 315 | /// %v = vector.transfer_read ... |
| 316 | /// permutation_map: (d0, d1, d2, d3) -> (d1, 0, d3) |
| 317 | /// vector.broadcast %v |
| 318 | struct TransferOpReduceRank |
| 319 | : public MaskableOpRewritePattern<vector::TransferReadOp> { |
| 320 | using MaskableOpRewritePattern::MaskableOpRewritePattern; |
| 321 | |
| 322 | FailureOr<mlir::Value> |
| 323 | matchAndRewriteMaskableOp(vector::TransferReadOp op, |
| 324 | MaskingOpInterface maskOp, |
| 325 | PatternRewriter &rewriter) const override { |
| 326 | // TODO: support 0-d corner case. |
| 327 | if (op.getTransferRank() == 0) |
| 328 | return rewriter.notifyMatchFailure(arg&: op, msg: "0-d corner case not supported" ); |
| 329 | // TODO: support masked case. |
| 330 | if (maskOp) |
| 331 | return rewriter.notifyMatchFailure(arg&: op, msg: "Masked case not supported" ); |
| 332 | |
| 333 | AffineMap map = op.getPermutationMap(); |
| 334 | unsigned numLeadingBroadcast = 0; |
| 335 | for (auto expr : map.getResults()) { |
| 336 | auto dimExpr = dyn_cast<AffineConstantExpr>(Val&: expr); |
| 337 | if (!dimExpr || dimExpr.getValue() != 0) |
| 338 | break; |
| 339 | numLeadingBroadcast++; |
| 340 | } |
| 341 | // If there are no leading zeros in the map there is nothing to do. |
| 342 | if (numLeadingBroadcast == 0) |
| 343 | return rewriter.notifyMatchFailure(arg&: op, msg: "no leading broadcasts in map" ); |
| 344 | |
| 345 | VectorType originalVecType = op.getVectorType(); |
| 346 | unsigned reducedShapeRank = originalVecType.getRank() - numLeadingBroadcast; |
| 347 | // Calculate new map, vector type and masks without the leading zeros. |
| 348 | AffineMap newMap = AffineMap::get( |
| 349 | dimCount: map.getNumDims(), symbolCount: 0, results: map.getResults().take_back(N: reducedShapeRank), |
| 350 | context: op.getContext()); |
| 351 | // Only remove the leading zeros if the rest of the map is a minor identity |
| 352 | // with broadasting. Otherwise we first want to permute the map. |
| 353 | if (!newMap.isMinorIdentityWithBroadcasting()) { |
| 354 | return rewriter.notifyMatchFailure( |
| 355 | arg&: op, msg: "map is not a minor identity with broadcasting" ); |
| 356 | } |
| 357 | |
| 358 | SmallVector<int64_t> newShape( |
| 359 | originalVecType.getShape().take_back(N: reducedShapeRank)); |
| 360 | SmallVector<bool> newScalableDims( |
| 361 | originalVecType.getScalableDims().take_back(N: reducedShapeRank)); |
| 362 | |
| 363 | VectorType newReadType = VectorType::get( |
| 364 | shape: newShape, elementType: originalVecType.getElementType(), scalableDims: newScalableDims); |
| 365 | ArrayAttr newInBoundsAttr = |
| 366 | op.getInBounds() |
| 367 | ? rewriter.getArrayAttr( |
| 368 | value: op.getInBoundsAttr().getValue().take_back(N: reducedShapeRank)) |
| 369 | : ArrayAttr(); |
| 370 | Value newRead = rewriter.create<vector::TransferReadOp>( |
| 371 | location: op.getLoc(), args&: newReadType, args: op.getBase(), args: op.getIndices(), |
| 372 | args: AffineMapAttr::get(value: newMap), args: op.getPadding(), args: op.getMask(), |
| 373 | args&: newInBoundsAttr); |
| 374 | return rewriter |
| 375 | .create<vector::BroadcastOp>(location: op.getLoc(), args&: originalVecType, args&: newRead) |
| 376 | .getVector(); |
| 377 | } |
| 378 | }; |
| 379 | |
| 380 | } // namespace |
| 381 | |
| 382 | void mlir::vector::populateVectorTransferPermutationMapLoweringPatterns( |
| 383 | RewritePatternSet &patterns, PatternBenefit benefit) { |
| 384 | patterns |
| 385 | .add<TransferReadPermutationLowering, TransferWritePermutationLowering, |
| 386 | TransferOpReduceRank, TransferWriteNonPermutationLowering>( |
| 387 | arg: patterns.getContext(), args&: benefit); |
| 388 | } |
| 389 | |
| 390 | //===----------------------------------------------------------------------===// |
| 391 | // populateVectorTransferLoweringPatterns |
| 392 | //===----------------------------------------------------------------------===// |
| 393 | |
| 394 | namespace { |
| 395 | /// Progressive lowering of transfer_read. This pattern supports lowering of |
| 396 | /// `vector.transfer_read` to a combination of `vector.load` and |
| 397 | /// `vector.broadcast` if all of the following hold: |
| 398 | /// - Stride of most minor memref dimension must be 1. |
| 399 | /// - Out-of-bounds masking is not required. |
| 400 | /// - If the memref's element type is a vector type then it coincides with the |
| 401 | /// result type. |
| 402 | /// - The permutation map doesn't perform permutation (broadcasting is allowed). |
| 403 | struct TransferReadToVectorLoadLowering |
| 404 | : public MaskableOpRewritePattern<vector::TransferReadOp> { |
| 405 | TransferReadToVectorLoadLowering(MLIRContext *context, |
| 406 | std::optional<unsigned> maxRank, |
| 407 | PatternBenefit benefit = 1) |
| 408 | : MaskableOpRewritePattern<vector::TransferReadOp>(context, benefit), |
| 409 | maxTransferRank(maxRank) {} |
| 410 | |
| 411 | FailureOr<mlir::Value> |
| 412 | matchAndRewriteMaskableOp(vector::TransferReadOp read, |
| 413 | MaskingOpInterface maskOp, |
| 414 | PatternRewriter &rewriter) const override { |
| 415 | if (maxTransferRank && read.getVectorType().getRank() > *maxTransferRank) { |
| 416 | return rewriter.notifyMatchFailure( |
| 417 | arg&: read, msg: "vector type is greater than max transfer rank" ); |
| 418 | } |
| 419 | |
| 420 | if (maskOp) |
| 421 | return rewriter.notifyMatchFailure(arg&: read, msg: "Masked case not supported" ); |
| 422 | SmallVector<unsigned> broadcastedDims; |
| 423 | // Permutations are handled by VectorToSCF or |
| 424 | // populateVectorTransferPermutationMapLoweringPatterns. |
| 425 | // We let the 0-d corner case pass-through as it is supported. |
| 426 | if (!read.getPermutationMap().isMinorIdentityWithBroadcasting( |
| 427 | broadcastedDims: &broadcastedDims)) |
| 428 | return rewriter.notifyMatchFailure(arg&: read, msg: "not minor identity + bcast" ); |
| 429 | |
| 430 | auto memRefType = dyn_cast<MemRefType>(Val: read.getShapedType()); |
| 431 | if (!memRefType) |
| 432 | return rewriter.notifyMatchFailure(arg&: read, msg: "not a memref source" ); |
| 433 | |
| 434 | // Non-unit strides are handled by VectorToSCF. |
| 435 | if (!memRefType.isLastDimUnitStride()) |
| 436 | return rewriter.notifyMatchFailure(arg&: read, msg: "!= 1 stride needs VectorToSCF" ); |
| 437 | |
| 438 | // If there is broadcasting involved then we first load the unbroadcasted |
| 439 | // vector, and then broadcast it with `vector.broadcast`. |
| 440 | ArrayRef<int64_t> vectorShape = read.getVectorType().getShape(); |
| 441 | SmallVector<int64_t> unbroadcastedVectorShape(vectorShape); |
| 442 | for (unsigned i : broadcastedDims) |
| 443 | unbroadcastedVectorShape[i] = 1; |
| 444 | VectorType unbroadcastedVectorType = read.getVectorType().cloneWith( |
| 445 | shape: unbroadcastedVectorShape, elementType: read.getVectorType().getElementType()); |
| 446 | |
| 447 | // `vector.load` supports vector types as memref's elements only when the |
| 448 | // resulting vector type is the same as the element type. |
| 449 | auto memrefElTy = memRefType.getElementType(); |
| 450 | if (isa<VectorType>(Val: memrefElTy) && memrefElTy != unbroadcastedVectorType) |
| 451 | return rewriter.notifyMatchFailure(arg&: read, msg: "incompatible element type" ); |
| 452 | |
| 453 | // Otherwise, element types of the memref and the vector must match. |
| 454 | if (!isa<VectorType>(Val: memrefElTy) && |
| 455 | memrefElTy != read.getVectorType().getElementType()) |
| 456 | return rewriter.notifyMatchFailure(arg&: read, msg: "non-matching element type" ); |
| 457 | |
| 458 | // Out-of-bounds dims are handled by MaterializeTransferMask. |
| 459 | if (read.hasOutOfBoundsDim()) |
| 460 | return rewriter.notifyMatchFailure(arg&: read, msg: "out-of-bounds needs mask" ); |
| 461 | |
| 462 | // Create vector load op. |
| 463 | Operation *res; |
| 464 | if (read.getMask()) { |
| 465 | if (read.getVectorType().getRank() != 1) |
| 466 | // vector.maskedload operates on 1-D vectors. |
| 467 | return rewriter.notifyMatchFailure( |
| 468 | arg&: read, msg: "vector type is not rank 1, can't create masked load, needs " |
| 469 | "VectorToSCF" ); |
| 470 | |
| 471 | Value fill = rewriter.create<vector::SplatOp>( |
| 472 | location: read.getLoc(), args&: unbroadcastedVectorType, args: read.getPadding()); |
| 473 | res = rewriter.create<vector::MaskedLoadOp>( |
| 474 | location: read.getLoc(), args&: unbroadcastedVectorType, args: read.getBase(), |
| 475 | args: read.getIndices(), args: read.getMask(), args&: fill); |
| 476 | } else { |
| 477 | res = rewriter.create<vector::LoadOp>(location: read.getLoc(), |
| 478 | args&: unbroadcastedVectorType, |
| 479 | args: read.getBase(), args: read.getIndices()); |
| 480 | } |
| 481 | |
| 482 | // Insert a broadcasting op if required. |
| 483 | if (!broadcastedDims.empty()) |
| 484 | res = rewriter.create<vector::BroadcastOp>( |
| 485 | location: read.getLoc(), args: read.getVectorType(), args: res->getResult(idx: 0)); |
| 486 | return res->getResult(idx: 0); |
| 487 | } |
| 488 | |
| 489 | std::optional<unsigned> maxTransferRank; |
| 490 | }; |
| 491 | |
| 492 | /// Progressive lowering of transfer_write. This pattern supports lowering of |
| 493 | /// `vector.transfer_write` to `vector.store` if all of the following hold: |
| 494 | /// - Stride of most minor memref dimension must be 1. |
| 495 | /// - Out-of-bounds masking is not required. |
| 496 | /// - If the memref's element type is a vector type then it coincides with the |
| 497 | /// type of the written value. |
| 498 | /// - The permutation map is the minor identity map (neither permutation nor |
| 499 | /// broadcasting is allowed). |
| 500 | struct TransferWriteToVectorStoreLowering |
| 501 | : public MaskableOpRewritePattern<vector::TransferWriteOp> { |
| 502 | TransferWriteToVectorStoreLowering(MLIRContext *context, |
| 503 | std::optional<unsigned> maxRank, |
| 504 | PatternBenefit benefit = 1) |
| 505 | : MaskableOpRewritePattern<vector::TransferWriteOp>(context, benefit), |
| 506 | maxTransferRank(maxRank) {} |
| 507 | |
| 508 | FailureOr<mlir::Value> |
| 509 | matchAndRewriteMaskableOp(vector::TransferWriteOp write, |
| 510 | MaskingOpInterface maskOp, |
| 511 | PatternRewriter &rewriter) const override { |
| 512 | if (maxTransferRank && write.getVectorType().getRank() > *maxTransferRank) { |
| 513 | return rewriter.notifyMatchFailure( |
| 514 | arg&: write, msg: "vector type is greater than max transfer rank" ); |
| 515 | } |
| 516 | if (maskOp) |
| 517 | return rewriter.notifyMatchFailure(arg&: write, msg: "Masked case not supported" ); |
| 518 | |
| 519 | // Permutations are handled by VectorToSCF or |
| 520 | // populateVectorTransferPermutationMapLoweringPatterns. |
| 521 | if ( // pass-through for the 0-d corner case. |
| 522 | !write.getPermutationMap().isMinorIdentity()) |
| 523 | return rewriter.notifyMatchFailure(loc: write.getLoc(), reasonCallback: [=](Diagnostic &diag) { |
| 524 | diag << "permutation map is not minor identity: " << write; |
| 525 | }); |
| 526 | |
| 527 | auto memRefType = dyn_cast<MemRefType>(Val: write.getShapedType()); |
| 528 | if (!memRefType) |
| 529 | return rewriter.notifyMatchFailure(loc: write.getLoc(), reasonCallback: [=](Diagnostic &diag) { |
| 530 | diag << "not a memref type: " << write; |
| 531 | }); |
| 532 | |
| 533 | // Non-unit strides are handled by VectorToSCF. |
| 534 | if (!memRefType.isLastDimUnitStride()) |
| 535 | return rewriter.notifyMatchFailure(loc: write.getLoc(), reasonCallback: [=](Diagnostic &diag) { |
| 536 | diag << "most minor stride is not 1: " << write; |
| 537 | }); |
| 538 | |
| 539 | // `vector.store` supports vector types as memref's elements only when the |
| 540 | // type of the vector value being written is the same as the element type. |
| 541 | auto memrefElTy = memRefType.getElementType(); |
| 542 | if (isa<VectorType>(Val: memrefElTy) && memrefElTy != write.getVectorType()) |
| 543 | return rewriter.notifyMatchFailure(loc: write.getLoc(), reasonCallback: [=](Diagnostic &diag) { |
| 544 | diag << "elemental type mismatch: " << write; |
| 545 | }); |
| 546 | |
| 547 | // Otherwise, element types of the memref and the vector must match. |
| 548 | if (!isa<VectorType>(Val: memrefElTy) && |
| 549 | memrefElTy != write.getVectorType().getElementType()) |
| 550 | return rewriter.notifyMatchFailure(loc: write.getLoc(), reasonCallback: [=](Diagnostic &diag) { |
| 551 | diag << "elemental type mismatch: " << write; |
| 552 | }); |
| 553 | |
| 554 | // Out-of-bounds dims are handled by MaterializeTransferMask. |
| 555 | if (write.hasOutOfBoundsDim()) |
| 556 | return rewriter.notifyMatchFailure(loc: write.getLoc(), reasonCallback: [=](Diagnostic &diag) { |
| 557 | diag << "out of bounds dim: " << write; |
| 558 | }); |
| 559 | if (write.getMask()) { |
| 560 | if (write.getVectorType().getRank() != 1) |
| 561 | // vector.maskedstore operates on 1-D vectors. |
| 562 | return rewriter.notifyMatchFailure( |
| 563 | loc: write.getLoc(), reasonCallback: [=](Diagnostic &diag) { |
| 564 | diag << "vector type is not rank 1, can't create masked store, " |
| 565 | "needs VectorToSCF: " |
| 566 | << write; |
| 567 | }); |
| 568 | |
| 569 | rewriter.create<vector::MaskedStoreOp>( |
| 570 | location: write.getLoc(), args: write.getBase(), args: write.getIndices(), args: write.getMask(), |
| 571 | args: write.getVector()); |
| 572 | } else { |
| 573 | rewriter.create<vector::StoreOp>(location: write.getLoc(), args: write.getVector(), |
| 574 | args: write.getBase(), args: write.getIndices()); |
| 575 | } |
| 576 | // There's no return value for StoreOps. Use Value() to signal success to |
| 577 | // matchAndRewrite. |
| 578 | return Value(); |
| 579 | } |
| 580 | |
| 581 | std::optional<unsigned> maxTransferRank; |
| 582 | }; |
| 583 | } // namespace |
| 584 | |
| 585 | void mlir::vector::populateVectorTransferLoweringPatterns( |
| 586 | RewritePatternSet &patterns, std::optional<unsigned> maxTransferRank, |
| 587 | PatternBenefit benefit) { |
| 588 | patterns.add<TransferReadToVectorLoadLowering, |
| 589 | TransferWriteToVectorStoreLowering>(arg: patterns.getContext(), |
| 590 | args&: maxTransferRank, args&: benefit); |
| 591 | } |
| 592 | |