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/Affine/IR/AffineOps.h" |
15 | #include "mlir/Dialect/MemRef/IR/MemRef.h" |
16 | #include "mlir/Dialect/Tensor/IR/Tensor.h" |
17 | #include "mlir/Dialect/Vector/Transforms/LoweringPatterns.h" |
18 | #include "mlir/Interfaces/VectorInterfaces.h" |
19 | |
20 | using namespace mlir; |
21 | using namespace mlir::vector; |
22 | |
23 | /// Transpose a vector transfer op's `in_bounds` attribute by applying reverse |
24 | /// permutation based on the given indices. |
25 | static ArrayAttr |
26 | inverseTransposeInBoundsAttr(OpBuilder &builder, ArrayAttr attr, |
27 | const SmallVector<unsigned> &permutation) { |
28 | SmallVector<bool> newInBoundsValues(permutation.size()); |
29 | size_t index = 0; |
30 | for (unsigned pos : permutation) |
31 | newInBoundsValues[pos] = |
32 | cast<BoolAttr>(attr.getValue()[index++]).getValue(); |
33 | return builder.getBoolArrayAttr(newInBoundsValues); |
34 | } |
35 | |
36 | /// Extend the rank of a vector Value by `addedRanks` by adding outer unit |
37 | /// dimensions. |
38 | static Value extendVectorRank(OpBuilder &builder, Location loc, Value vec, |
39 | int64_t addedRank) { |
40 | auto originalVecType = cast<VectorType>(vec.getType()); |
41 | SmallVector<int64_t> newShape(addedRank, 1); |
42 | newShape.append(originalVecType.getShape().begin(), |
43 | originalVecType.getShape().end()); |
44 | |
45 | SmallVector<bool> newScalableDims(addedRank, false); |
46 | newScalableDims.append(originalVecType.getScalableDims().begin(), |
47 | originalVecType.getScalableDims().end()); |
48 | VectorType newVecType = VectorType::get( |
49 | newShape, originalVecType.getElementType(), newScalableDims); |
50 | return builder.create<vector::BroadcastOp>(loc, newVecType, vec); |
51 | } |
52 | |
53 | /// Extend the rank of a vector Value by `addedRanks` by adding inner unit |
54 | /// dimensions. |
55 | static Value extendMaskRank(OpBuilder &builder, Location loc, Value vec, |
56 | int64_t addedRank) { |
57 | Value broadcasted = extendVectorRank(builder, loc, vec, addedRank); |
58 | SmallVector<int64_t> permutation; |
59 | for (int64_t i = addedRank, |
60 | e = cast<VectorType>(broadcasted.getType()).getRank(); |
61 | i < e; ++i) |
62 | permutation.push_back(Elt: i); |
63 | for (int64_t i = 0; i < addedRank; ++i) |
64 | permutation.push_back(Elt: i); |
65 | return builder.create<vector::TransposeOp>(loc, broadcasted, permutation); |
66 | } |
67 | |
68 | //===----------------------------------------------------------------------===// |
69 | // populateVectorTransferPermutationMapLoweringPatterns |
70 | //===----------------------------------------------------------------------===// |
71 | |
72 | namespace { |
73 | /// Lower transfer_read op with permutation into a transfer_read with a |
74 | /// permutation map composed of leading zeros followed by a minor identiy + |
75 | /// vector.transpose op. |
76 | /// Ex: |
77 | /// vector.transfer_read ... |
78 | /// permutation_map: (d0, d1, d2) -> (0, d1) |
79 | /// into: |
80 | /// %v = vector.transfer_read ... |
81 | /// permutation_map: (d0, d1, d2) -> (d1, 0) |
82 | /// vector.transpose %v, [1, 0] |
83 | /// |
84 | /// vector.transfer_read ... |
85 | /// permutation_map: (d0, d1, d2, d3) -> (0, 0, 0, d1, d3) |
86 | /// into: |
87 | /// %v = vector.transfer_read ... |
88 | /// permutation_map: (d0, d1, d2, d3) -> (0, 0, d1, 0, d3) |
89 | /// vector.transpose %v, [0, 1, 3, 2, 4] |
90 | /// Note that an alternative is to transform it to linalg.transpose + |
91 | /// vector.transfer_read to do the transpose in memory instead. |
92 | struct TransferReadPermutationLowering |
93 | : public OpRewritePattern<vector::TransferReadOp> { |
94 | using OpRewritePattern::OpRewritePattern; |
95 | |
96 | LogicalResult matchAndRewrite(vector::TransferReadOp op, |
97 | PatternRewriter &rewriter) const override { |
98 | // TODO: support 0-d corner case. |
99 | if (op.getTransferRank() == 0) |
100 | return rewriter.notifyMatchFailure(op, "0-d corner case not supported" ); |
101 | |
102 | SmallVector<unsigned> permutation; |
103 | AffineMap map = op.getPermutationMap(); |
104 | if (map.getNumResults() == 0) |
105 | return rewriter.notifyMatchFailure(op, "0 result permutation map" ); |
106 | if (!map.isPermutationOfMinorIdentityWithBroadcasting(permutedDims&: permutation)) { |
107 | return rewriter.notifyMatchFailure( |
108 | op, "map is not permutable to minor identity, apply another pattern" ); |
109 | } |
110 | AffineMap permutationMap = |
111 | map.getPermutationMap(permutation, op.getContext()); |
112 | if (permutationMap.isIdentity()) |
113 | return rewriter.notifyMatchFailure(op, "map is not identity" ); |
114 | |
115 | permutationMap = map.getPermutationMap(permutation, op.getContext()); |
116 | // Caluclate the map of the new read by applying the inverse permutation. |
117 | permutationMap = inversePermutation(map: permutationMap); |
118 | AffineMap newMap = permutationMap.compose(map); |
119 | // Apply the reverse transpose to deduce the type of the transfer_read. |
120 | ArrayRef<int64_t> originalShape = op.getVectorType().getShape(); |
121 | SmallVector<int64_t> newVectorShape(originalShape.size()); |
122 | ArrayRef<bool> originalScalableDims = op.getVectorType().getScalableDims(); |
123 | SmallVector<bool> newScalableDims(originalShape.size()); |
124 | for (const auto &pos : llvm::enumerate(First&: permutation)) { |
125 | newVectorShape[pos.value()] = originalShape[pos.index()]; |
126 | newScalableDims[pos.value()] = originalScalableDims[pos.index()]; |
127 | } |
128 | |
129 | // Transpose in_bounds attribute. |
130 | ArrayAttr newInBoundsAttr = |
131 | op.getInBounds() ? inverseTransposeInBoundsAttr( |
132 | rewriter, op.getInBounds().value(), permutation) |
133 | : ArrayAttr(); |
134 | |
135 | // Generate new transfer_read operation. |
136 | VectorType newReadType = VectorType::get( |
137 | newVectorShape, op.getVectorType().getElementType(), newScalableDims); |
138 | Value newRead = rewriter.create<vector::TransferReadOp>( |
139 | op.getLoc(), newReadType, op.getSource(), op.getIndices(), |
140 | AffineMapAttr::get(newMap), op.getPadding(), op.getMask(), |
141 | newInBoundsAttr); |
142 | |
143 | // Transpose result of transfer_read. |
144 | SmallVector<int64_t> transposePerm(permutation.begin(), permutation.end()); |
145 | rewriter.replaceOpWithNewOp<vector::TransposeOp>(op, newRead, |
146 | transposePerm); |
147 | return success(); |
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 OpRewritePattern<vector::TransferWriteOp> { |
169 | using OpRewritePattern::OpRewritePattern; |
170 | |
171 | LogicalResult matchAndRewrite(vector::TransferWriteOp op, |
172 | PatternRewriter &rewriter) const override { |
173 | // TODO: support 0-d corner case. |
174 | if (op.getTransferRank() == 0) |
175 | return rewriter.notifyMatchFailure(op, "0-d corner case not supported" ); |
176 | |
177 | SmallVector<unsigned> permutation; |
178 | AffineMap map = op.getPermutationMap(); |
179 | if (map.isMinorIdentity()) |
180 | return rewriter.notifyMatchFailure(op, "map is already minor identity" ); |
181 | |
182 | if (!map.isPermutationOfMinorIdentityWithBroadcasting(permutedDims&: permutation)) { |
183 | return rewriter.notifyMatchFailure( |
184 | op, "map is not permutable to minor identity, apply another pattern" ); |
185 | } |
186 | |
187 | // Remove unused dims from the permutation map. E.g.: |
188 | // E.g.: (d0, d1, d2, d3, d4, d5) -> (d5, d3, d4) |
189 | // comp = (d0, d1, d2) -> (d2, d0, d1) |
190 | auto comp = compressUnusedDims(map); |
191 | AffineMap permutationMap = inversePermutation(comp); |
192 | // Get positions of remaining result dims. |
193 | SmallVector<int64_t> indices; |
194 | llvm::transform(Range: permutationMap.getResults(), d_first: std::back_inserter(x&: indices), |
195 | F: [](AffineExpr expr) { |
196 | return dyn_cast<AffineDimExpr>(Val&: expr).getPosition(); |
197 | }); |
198 | |
199 | // Transpose in_bounds attribute. |
200 | ArrayAttr newInBoundsAttr = |
201 | op.getInBounds() ? inverseTransposeInBoundsAttr( |
202 | rewriter, op.getInBounds().value(), permutation) |
203 | : ArrayAttr(); |
204 | |
205 | // Generate new transfer_write operation. |
206 | Value newVec = rewriter.create<vector::TransposeOp>( |
207 | op.getLoc(), op.getVector(), indices); |
208 | auto newMap = AffineMap::getMinorIdentityMap( |
209 | dims: map.getNumDims(), results: map.getNumResults(), context: rewriter.getContext()); |
210 | rewriter.replaceOpWithNewOp<vector::TransferWriteOp>( |
211 | op, newVec, op.getSource(), op.getIndices(), AffineMapAttr::get(newMap), |
212 | op.getMask(), newInBoundsAttr); |
213 | |
214 | return success(); |
215 | } |
216 | }; |
217 | |
218 | /// Convert a transfer.write op with a map which isn't the permutation of a |
219 | /// minor identity into a vector.broadcast + transfer_write with permutation of |
220 | /// minor identity map by adding unit dim on inner dimension. Ex: |
221 | /// ``` |
222 | /// vector.transfer_write %v |
223 | /// {permutation_map = affine_map<(d0, d1, d2, d3) -> (d1, d2)>} : |
224 | /// vector<8x16xf32> |
225 | /// ``` |
226 | /// into: |
227 | /// ``` |
228 | /// %v1 = vector.broadcast %v : vector<8x16xf32> to vector<1x8x16xf32> |
229 | /// vector.transfer_write %v1 |
230 | /// {permutation_map = affine_map<(d0, d1, d2, d3) -> (d3, d1, d2)>} : |
231 | /// vector<1x8x16xf32> |
232 | /// ``` |
233 | struct TransferWriteNonPermutationLowering |
234 | : public OpRewritePattern<vector::TransferWriteOp> { |
235 | using OpRewritePattern::OpRewritePattern; |
236 | |
237 | LogicalResult matchAndRewrite(vector::TransferWriteOp op, |
238 | PatternRewriter &rewriter) const override { |
239 | // TODO: support 0-d corner case. |
240 | if (op.getTransferRank() == 0) |
241 | return rewriter.notifyMatchFailure(op, "0-d corner case not supported" ); |
242 | |
243 | SmallVector<unsigned> permutation; |
244 | AffineMap map = op.getPermutationMap(); |
245 | if (map.isPermutationOfMinorIdentityWithBroadcasting(permutedDims&: permutation)) { |
246 | return rewriter.notifyMatchFailure( |
247 | op, |
248 | "map is already permutable to minor identity, apply another pattern" ); |
249 | } |
250 | |
251 | // Missing outer dimensions are allowed, find the most outer existing |
252 | // dimension then deduce the missing inner dimensions. |
253 | SmallVector<bool> foundDim(map.getNumDims(), false); |
254 | for (AffineExpr exp : map.getResults()) |
255 | foundDim[cast<AffineDimExpr>(exp).getPosition()] = true; |
256 | SmallVector<AffineExpr> exprs; |
257 | bool foundFirstDim = false; |
258 | SmallVector<int64_t> missingInnerDim; |
259 | for (size_t i = 0; i < foundDim.size(); i++) { |
260 | if (foundDim[i]) { |
261 | foundFirstDim = true; |
262 | continue; |
263 | } |
264 | if (!foundFirstDim) |
265 | continue; |
266 | // Once we found one outer dimension existing in the map keep track of all |
267 | // the missing dimensions after that. |
268 | missingInnerDim.push_back(Elt: i); |
269 | exprs.push_back(Elt: rewriter.getAffineDimExpr(position: i)); |
270 | } |
271 | // Vector: add unit dims at the beginning of the shape. |
272 | Value newVec = extendVectorRank(rewriter, op.getLoc(), op.getVector(), |
273 | missingInnerDim.size()); |
274 | // Mask: add unit dims at the end of the shape. |
275 | Value newMask; |
276 | if (op.getMask()) |
277 | newMask = extendMaskRank(rewriter, op.getLoc(), op.getMask(), |
278 | missingInnerDim.size()); |
279 | exprs.append(in_start: map.getResults().begin(), in_end: map.getResults().end()); |
280 | AffineMap newMap = |
281 | AffineMap::get(map.getNumDims(), 0, exprs, op.getContext()); |
282 | // All the new dimensions added are inbound. |
283 | SmallVector<bool> newInBoundsValues(missingInnerDim.size(), true); |
284 | for (int64_t i = 0, e = op.getVectorType().getRank(); i < e; ++i) { |
285 | newInBoundsValues.push_back(Elt: op.isDimInBounds(i)); |
286 | } |
287 | ArrayAttr newInBoundsAttr = rewriter.getBoolArrayAttr(newInBoundsValues); |
288 | rewriter.replaceOpWithNewOp<vector::TransferWriteOp>( |
289 | op, newVec, op.getSource(), op.getIndices(), AffineMapAttr::get(newMap), |
290 | newMask, newInBoundsAttr); |
291 | return success(); |
292 | } |
293 | }; |
294 | |
295 | /// Lower transfer_read op with broadcast in the leading dimensions into |
296 | /// transfer_read of lower rank + vector.broadcast. |
297 | /// Ex: vector.transfer_read ... |
298 | /// permutation_map: (d0, d1, d2, d3) -> (0, d1, 0, d3) |
299 | /// into: |
300 | /// %v = vector.transfer_read ... |
301 | /// permutation_map: (d0, d1, d2, d3) -> (d1, 0, d3) |
302 | /// vector.broadcast %v |
303 | struct TransferOpReduceRank : public OpRewritePattern<vector::TransferReadOp> { |
304 | using OpRewritePattern::OpRewritePattern; |
305 | |
306 | LogicalResult matchAndRewrite(vector::TransferReadOp op, |
307 | PatternRewriter &rewriter) const override { |
308 | // TODO: support 0-d corner case. |
309 | if (op.getTransferRank() == 0) |
310 | return rewriter.notifyMatchFailure(op, "0-d corner case not supported" ); |
311 | |
312 | AffineMap map = op.getPermutationMap(); |
313 | unsigned numLeadingBroadcast = 0; |
314 | for (auto expr : map.getResults()) { |
315 | auto dimExpr = dyn_cast<AffineConstantExpr>(expr); |
316 | if (!dimExpr || dimExpr.getValue() != 0) |
317 | break; |
318 | numLeadingBroadcast++; |
319 | } |
320 | // If there are no leading zeros in the map there is nothing to do. |
321 | if (numLeadingBroadcast == 0) |
322 | return rewriter.notifyMatchFailure(op, "no leading broadcasts in map" ); |
323 | |
324 | VectorType originalVecType = op.getVectorType(); |
325 | unsigned reducedShapeRank = originalVecType.getRank() - numLeadingBroadcast; |
326 | // Calculate new map, vector type and masks without the leading zeros. |
327 | AffineMap newMap = AffineMap::get( |
328 | map.getNumDims(), 0, map.getResults().take_back(N: reducedShapeRank), |
329 | op.getContext()); |
330 | // Only remove the leading zeros if the rest of the map is a minor identity |
331 | // with broadasting. Otherwise we first want to permute the map. |
332 | if (!newMap.isMinorIdentityWithBroadcasting()) { |
333 | return rewriter.notifyMatchFailure( |
334 | op, "map is not a minor identity with broadcasting" ); |
335 | } |
336 | |
337 | // TODO: support zero-dimension vectors natively. See: |
338 | // https://llvm.discourse.group/t/should-we-have-0-d-vectors/3097. |
339 | // In the meantime, lower these to a scalar load when they pop up. |
340 | if (reducedShapeRank == 0) { |
341 | Value newRead; |
342 | if (isa<TensorType>(op.getShapedType())) { |
343 | newRead = rewriter.create<tensor::ExtractOp>( |
344 | op.getLoc(), op.getSource(), op.getIndices()); |
345 | } else { |
346 | newRead = rewriter.create<memref::LoadOp>( |
347 | op.getLoc(), originalVecType.getElementType(), op.getSource(), |
348 | op.getIndices()); |
349 | } |
350 | rewriter.replaceOpWithNewOp<vector::BroadcastOp>(op, originalVecType, |
351 | newRead); |
352 | return success(); |
353 | } |
354 | |
355 | SmallVector<int64_t> newShape( |
356 | originalVecType.getShape().take_back(reducedShapeRank)); |
357 | SmallVector<bool> newScalableDims( |
358 | originalVecType.getScalableDims().take_back(reducedShapeRank)); |
359 | // Vector rank cannot be zero. Handled by TransferReadToVectorLoadLowering. |
360 | if (newShape.empty()) |
361 | return rewriter.notifyMatchFailure(op, "rank-reduced vector is 0-d" ); |
362 | |
363 | VectorType newReadType = VectorType::get( |
364 | newShape, originalVecType.getElementType(), newScalableDims); |
365 | ArrayAttr newInBoundsAttr = |
366 | op.getInBounds() |
367 | ? rewriter.getArrayAttr( |
368 | op.getInBoundsAttr().getValue().take_back(reducedShapeRank)) |
369 | : ArrayAttr(); |
370 | Value newRead = rewriter.create<vector::TransferReadOp>( |
371 | op.getLoc(), newReadType, op.getSource(), op.getIndices(), |
372 | AffineMapAttr::get(newMap), op.getPadding(), op.getMask(), |
373 | newInBoundsAttr); |
374 | rewriter.replaceOpWithNewOp<vector::BroadcastOp>(op, originalVecType, |
375 | newRead); |
376 | return success(); |
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 OpRewritePattern<vector::TransferReadOp> { |
405 | TransferReadToVectorLoadLowering(MLIRContext *context, |
406 | std::optional<unsigned> maxRank, |
407 | PatternBenefit benefit = 1) |
408 | : OpRewritePattern<vector::TransferReadOp>(context, benefit), |
409 | maxTransferRank(maxRank) {} |
410 | |
411 | LogicalResult matchAndRewrite(vector::TransferReadOp read, |
412 | PatternRewriter &rewriter) const override { |
413 | if (maxTransferRank && read.getVectorType().getRank() > *maxTransferRank) { |
414 | return rewriter.notifyMatchFailure( |
415 | read, "vector type is greater than max transfer rank" ); |
416 | } |
417 | |
418 | SmallVector<unsigned> broadcastedDims; |
419 | // Permutations are handled by VectorToSCF or |
420 | // populateVectorTransferPermutationMapLoweringPatterns. |
421 | // We let the 0-d corner case pass-through as it is supported. |
422 | if (!read.getPermutationMap().isMinorIdentityWithBroadcasting( |
423 | &broadcastedDims)) |
424 | return rewriter.notifyMatchFailure(read, "not minor identity + bcast" ); |
425 | |
426 | auto memRefType = dyn_cast<MemRefType>(read.getShapedType()); |
427 | if (!memRefType) |
428 | return rewriter.notifyMatchFailure(read, "not a memref source" ); |
429 | |
430 | // Non-unit strides are handled by VectorToSCF. |
431 | if (!isLastMemrefDimUnitStride(memRefType)) |
432 | return rewriter.notifyMatchFailure(read, "!= 1 stride needs VectorToSCF" ); |
433 | |
434 | // If there is broadcasting involved then we first load the unbroadcasted |
435 | // vector, and then broadcast it with `vector.broadcast`. |
436 | ArrayRef<int64_t> vectorShape = read.getVectorType().getShape(); |
437 | SmallVector<int64_t> unbroadcastedVectorShape(vectorShape.begin(), |
438 | vectorShape.end()); |
439 | for (unsigned i : broadcastedDims) |
440 | unbroadcastedVectorShape[i] = 1; |
441 | VectorType unbroadcastedVectorType = read.getVectorType().cloneWith( |
442 | unbroadcastedVectorShape, read.getVectorType().getElementType()); |
443 | |
444 | // `vector.load` supports vector types as memref's elements only when the |
445 | // resulting vector type is the same as the element type. |
446 | auto memrefElTy = memRefType.getElementType(); |
447 | if (isa<VectorType>(memrefElTy) && memrefElTy != unbroadcastedVectorType) |
448 | return rewriter.notifyMatchFailure(read, "incompatible element type" ); |
449 | |
450 | // Otherwise, element types of the memref and the vector must match. |
451 | if (!isa<VectorType>(memrefElTy) && |
452 | memrefElTy != read.getVectorType().getElementType()) |
453 | return rewriter.notifyMatchFailure(read, "non-matching element type" ); |
454 | |
455 | // Out-of-bounds dims are handled by MaterializeTransferMask. |
456 | if (read.hasOutOfBoundsDim()) |
457 | return rewriter.notifyMatchFailure(read, "out-of-bounds needs mask" ); |
458 | |
459 | // Create vector load op. |
460 | Operation *loadOp; |
461 | if (read.getMask()) { |
462 | if (read.getVectorType().getRank() != 1) |
463 | // vector.maskedload operates on 1-D vectors. |
464 | return rewriter.notifyMatchFailure( |
465 | read, "vector type is not rank 1, can't create masked load, needs " |
466 | "VectorToSCF" ); |
467 | |
468 | Value fill = rewriter.create<vector::SplatOp>( |
469 | read.getLoc(), unbroadcastedVectorType, read.getPadding()); |
470 | loadOp = rewriter.create<vector::MaskedLoadOp>( |
471 | read.getLoc(), unbroadcastedVectorType, read.getSource(), |
472 | read.getIndices(), read.getMask(), fill); |
473 | } else { |
474 | loadOp = rewriter.create<vector::LoadOp>( |
475 | read.getLoc(), unbroadcastedVectorType, read.getSource(), |
476 | read.getIndices()); |
477 | } |
478 | |
479 | // Insert a broadcasting op if required. |
480 | if (!broadcastedDims.empty()) { |
481 | rewriter.replaceOpWithNewOp<vector::BroadcastOp>( |
482 | read, read.getVectorType(), loadOp->getResult(0)); |
483 | } else { |
484 | rewriter.replaceOp(read, loadOp->getResult(idx: 0)); |
485 | } |
486 | |
487 | return success(); |
488 | } |
489 | |
490 | std::optional<unsigned> maxTransferRank; |
491 | }; |
492 | |
493 | /// Replace a 0-d vector.load with a memref.load + vector.broadcast. |
494 | // TODO: we shouldn't cross the vector/scalar domains just for this |
495 | // but atm we lack the infra to avoid it. Possible solutions include: |
496 | // - go directly to LLVM + bitcast |
497 | // - introduce a bitcast op and likely a new pointer dialect |
498 | // - let memref.load/store additionally support the 0-d vector case |
499 | // There are still deeper data layout issues lingering even in this |
500 | // trivial case (for architectures for which this matters). |
501 | struct VectorLoadToMemrefLoadLowering |
502 | : public OpRewritePattern<vector::LoadOp> { |
503 | using OpRewritePattern::OpRewritePattern; |
504 | |
505 | LogicalResult matchAndRewrite(vector::LoadOp loadOp, |
506 | PatternRewriter &rewriter) const override { |
507 | auto vecType = loadOp.getVectorType(); |
508 | if (vecType.getNumElements() != 1) |
509 | return rewriter.notifyMatchFailure(loadOp, "not a single element vector" ); |
510 | |
511 | auto memrefLoad = rewriter.create<memref::LoadOp>( |
512 | loadOp.getLoc(), loadOp.getBase(), loadOp.getIndices()); |
513 | rewriter.replaceOpWithNewOp<vector::BroadcastOp>(loadOp, vecType, |
514 | memrefLoad); |
515 | return success(); |
516 | } |
517 | }; |
518 | |
519 | /// Replace a 0-d vector.store with a vector.extractelement + memref.store. |
520 | struct VectorStoreToMemrefStoreLowering |
521 | : public OpRewritePattern<vector::StoreOp> { |
522 | using OpRewritePattern::OpRewritePattern; |
523 | |
524 | LogicalResult matchAndRewrite(vector::StoreOp storeOp, |
525 | PatternRewriter &rewriter) const override { |
526 | auto vecType = storeOp.getVectorType(); |
527 | if (vecType.getNumElements() != 1) |
528 | return rewriter.notifyMatchFailure(storeOp, "not single element vector" ); |
529 | |
530 | Value ; |
531 | if (vecType.getRank() == 0) { |
532 | // TODO: Unifiy once ExtractOp supports 0-d vectors. |
533 | extracted = rewriter.create<vector::ExtractElementOp>( |
534 | storeOp.getLoc(), storeOp.getValueToStore()); |
535 | } else { |
536 | SmallVector<int64_t> indices(vecType.getRank(), 0); |
537 | extracted = rewriter.create<vector::ExtractOp>( |
538 | storeOp.getLoc(), storeOp.getValueToStore(), indices); |
539 | } |
540 | |
541 | rewriter.replaceOpWithNewOp<memref::StoreOp>( |
542 | storeOp, extracted, storeOp.getBase(), storeOp.getIndices()); |
543 | return success(); |
544 | } |
545 | }; |
546 | |
547 | /// Progressive lowering of transfer_write. This pattern supports lowering of |
548 | /// `vector.transfer_write` to `vector.store` if all of the following hold: |
549 | /// - Stride of most minor memref dimension must be 1. |
550 | /// - Out-of-bounds masking is not required. |
551 | /// - If the memref's element type is a vector type then it coincides with the |
552 | /// type of the written value. |
553 | /// - The permutation map is the minor identity map (neither permutation nor |
554 | /// broadcasting is allowed). |
555 | struct TransferWriteToVectorStoreLowering |
556 | : public OpRewritePattern<vector::TransferWriteOp> { |
557 | TransferWriteToVectorStoreLowering(MLIRContext *context, |
558 | std::optional<unsigned> maxRank, |
559 | PatternBenefit benefit = 1) |
560 | : OpRewritePattern<vector::TransferWriteOp>(context, benefit), |
561 | maxTransferRank(maxRank) {} |
562 | |
563 | LogicalResult matchAndRewrite(vector::TransferWriteOp write, |
564 | PatternRewriter &rewriter) const override { |
565 | if (maxTransferRank && write.getVectorType().getRank() > *maxTransferRank) { |
566 | return rewriter.notifyMatchFailure( |
567 | write, "vector type is greater than max transfer rank" ); |
568 | } |
569 | |
570 | // Permutations are handled by VectorToSCF or |
571 | // populateVectorTransferPermutationMapLoweringPatterns. |
572 | if ( // pass-through for the 0-d corner case. |
573 | !write.getPermutationMap().isMinorIdentity()) |
574 | return rewriter.notifyMatchFailure(write.getLoc(), [=](Diagnostic &diag) { |
575 | diag << "permutation map is not minor identity: " << write; |
576 | }); |
577 | |
578 | auto memRefType = dyn_cast<MemRefType>(write.getShapedType()); |
579 | if (!memRefType) |
580 | return rewriter.notifyMatchFailure(write.getLoc(), [=](Diagnostic &diag) { |
581 | diag << "not a memref type: " << write; |
582 | }); |
583 | |
584 | // Non-unit strides are handled by VectorToSCF. |
585 | if (!isLastMemrefDimUnitStride(memRefType)) |
586 | return rewriter.notifyMatchFailure(write.getLoc(), [=](Diagnostic &diag) { |
587 | diag << "most minor stride is not 1: " << write; |
588 | }); |
589 | |
590 | // `vector.store` supports vector types as memref's elements only when the |
591 | // type of the vector value being written is the same as the element type. |
592 | auto memrefElTy = memRefType.getElementType(); |
593 | if (isa<VectorType>(memrefElTy) && memrefElTy != write.getVectorType()) |
594 | return rewriter.notifyMatchFailure(write.getLoc(), [=](Diagnostic &diag) { |
595 | diag << "elemental type mismatch: " << write; |
596 | }); |
597 | |
598 | // Otherwise, element types of the memref and the vector must match. |
599 | if (!isa<VectorType>(memrefElTy) && |
600 | memrefElTy != write.getVectorType().getElementType()) |
601 | return rewriter.notifyMatchFailure(write.getLoc(), [=](Diagnostic &diag) { |
602 | diag << "elemental type mismatch: " << write; |
603 | }); |
604 | |
605 | // Out-of-bounds dims are handled by MaterializeTransferMask. |
606 | if (write.hasOutOfBoundsDim()) |
607 | return rewriter.notifyMatchFailure(write.getLoc(), [=](Diagnostic &diag) { |
608 | diag << "out of bounds dim: " << write; |
609 | }); |
610 | if (write.getMask()) { |
611 | if (write.getVectorType().getRank() != 1) |
612 | // vector.maskedstore operates on 1-D vectors. |
613 | return rewriter.notifyMatchFailure( |
614 | write.getLoc(), [=](Diagnostic &diag) { |
615 | diag << "vector type is not rank 1, can't create masked store, " |
616 | "needs VectorToSCF: " |
617 | << write; |
618 | }); |
619 | |
620 | rewriter.replaceOpWithNewOp<vector::MaskedStoreOp>( |
621 | write, write.getSource(), write.getIndices(), write.getMask(), |
622 | write.getVector()); |
623 | } else { |
624 | rewriter.replaceOpWithNewOp<vector::StoreOp>( |
625 | write, write.getVector(), write.getSource(), write.getIndices()); |
626 | } |
627 | return success(); |
628 | } |
629 | |
630 | std::optional<unsigned> maxTransferRank; |
631 | }; |
632 | } // namespace |
633 | |
634 | void mlir::vector::populateVectorTransferLoweringPatterns( |
635 | RewritePatternSet &patterns, std::optional<unsigned> maxTransferRank, |
636 | PatternBenefit benefit) { |
637 | patterns.add<TransferReadToVectorLoadLowering, |
638 | TransferWriteToVectorStoreLowering>(arg: patterns.getContext(), |
639 | args&: maxTransferRank, args&: benefit); |
640 | patterns |
641 | .add<VectorLoadToMemrefLoadLowering, VectorStoreToMemrefStoreLowering>( |
642 | arg: patterns.getContext(), args&: benefit); |
643 | } |
644 | |