<table border="1" cellspacing="0" cellpadding="8">
<tr>
<th>Issue</th>
<td>
<a href=https://github.com/llvm/llvm-project/issues/73547>73547</a>
</td>
</tr>
<tr>
<th>Summary</th>
<td>
[mlir] --canonicalize crashed with assertion failure "expected 'op' to have no uses"
</td>
</tr>
<tr>
<th>Labels</th>
<td>
mlir
</td>
</tr>
<tr>
<th>Assignees</th>
<td>
</td>
</tr>
<tr>
<th>Reporter</th>
<td>
anonymousMCS
</td>
</tr>
</table>
<pre>
git version: 5bd643e1456bd2acc53ac0bf594d285be89a44fe
system: Ubuntu 20.04.6 LTS (Focal Fossa)
reproduced with: ```mlir-opt --canonicalize a.mlir```
a.mlir:
```
#map = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
#map2 = affine_map<(d0, d1) -> (d0, d1)>
#map8 = affine_map<(d0, d1, d2) -> (d1)>
func.func @func2(%arg0: memref<?xf32>, %arg1: tensor<6xi32>) {
%c1_12 = arith.constant 1 : index
%c2 = arith.constant 2 : index
%c6 = arith.constant 6 : index
%c9 = arith.constant 9 : index
%c12 = arith.constant 12 : index
%c15 = arith.constant 15 : index
%c22_15 = arith.constant 22 : index
%c23 = arith.constant 23 : index
%c31 = arith.constant 31 : index
%alloc_25 = memref.alloc(%c6) {alignment = 64 : i64} : memref<?x6xf32>
%9 = bufferization.to_tensor %alloc_25 : memref<?x6xf32>
%18 = index.shru %c22_15, %c15
%20 = index.divs %18, %c31
%cst_63 = arith.constant 1.27479398E+18 : f32
%c1_68 = arith.constant 1 : index
%54 = tosa.reduce_sum %9 {axis = 0 : i32} : (tensor<?x6xf32>) -> tensor<1x6xf32>
%56 = linalg.generic {indexing_maps = [#map2, #map2], iterator_types = ["parallel", "parallel"]} ins(%54 : tensor<1x6xf32>) outs(%54 : tensor<1x6xf32>) {
^bb0(%in: f32, %out: f32):
%124 = math.log2 %in : f32
linalg.yield %124 : f32
} -> tensor<1x6xf32>
%alloc_71 = memref.alloc() : memref<14x27x4xf32>
%59 = memref.atomic_rmw assign %cst_63, %alloc_71[%20, %c9, %c1_12] : (f32, memref<14x27x4xf32>) -> f32
%78 = index.shru %c12, %20
%79 = index.ceildivu %c23, %c1_68
%83 = math.sqrt %59 : f32
%cst_83 = arith.constant 0x7F800000 : f32
%alloc_86 = memref.alloc(%79) {alignment = 64 : i64} : memref<14x?x4xf32>
%98 = bufferization.to_tensor %alloc_86 : memref<14x?x4xf32>
%alloc_87 = memref.alloc(%78) {alignment = 64 : i64} : memref<?xf32>
%99 = bufferization.to_tensor %alloc_87 : memref<?xf32>
%alloc_88 = memref.alloc(%20) : memref<?xf32>
%alloc_89 = memref.alloc(%c2) {alignment = 64 : i64} : memref<14x?x4xf32>
%100 = bufferization.to_tensor %alloc_89 : memref<14x?x4xf32>
%101 = linalg.generic {indexing_maps = [#map, #map8, #map8, #map], iterator_types = ["parallel", "parallel", "parallel"]} ins(%98, %99, %alloc_88 : tensor<14x?x4xf32>, tensor<?xf32>, memref<?xf32>) outs(%100 : tensor<14x?x4xf32>) {
^bb0(%in: f32, %in_100: f32, %in_101: f32, %out: f32):
linalg.yield %cst_83 : f32
} -> tensor<14x?x4xf32>
%111 = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel", "parallel", "parallel"]} ins(%98 : tensor<14x?x4xf32>) outs(%101 : tensor<14x?x4xf32>) {
^bb0(%in: f32, %out: f32):
%124 = math.absf %83 : f32
linalg.yield %124 : f32
} -> tensor<14x?x4xf32>
return
}
```
trace:
```
mlir-opt: /data/bin/llvm-project/mlir/lib/IR/PatternMatch.cpp:307: virtual void mlir::RewriterBase::eraseOp(mlir::Operation*): Assertion `op->use_empty() && "expected 'op' to have no uses"' failed.
PLEASE submit a bug report to https://github.com/llvm/llvm-project/issues/ and include the crash backtrace.
Stack dump:
0. Program arguments: /data/bin/llvm-project/build/bin/mlir-opt --canonicalize a.mlir
#0 0x000055644e81222f llvm::sys::PrintStackTrace(llvm::raw_ostream&, int) (/data/bin/llvm-project/build/bin/mlir-opt+0x161922f)
#1 0x000055644e80f284 SignalHandler(int) Signals.cpp:0:0
#2 0x00007f8324c36420 __restore_rt (/lib/x86_64-linux-gnu/libpthread.so.0+0x14420)
#3 0x00007f832472100b raise (/lib/x86_64-linux-gnu/libc.so.6+0x4300b)
#4 0x00007f8324700859 abort (/lib/x86_64-linux-gnu/libc.so.6+0x22859)
#5 0x00007f8324700729 (/lib/x86_64-linux-gnu/libc.so.6+0x22729)
#6 0x00007f8324711fd6 (/lib/x86_64-linux-gnu/libc.so.6+0x33fd6)
#7 0x0000556451644569 mlir::RewriterBase::eraseOp(mlir::Operation*) (/data/bin/llvm-project/build/bin/mlir-opt+0x444b569)
#8 0x000055644f01e307 (anonymous namespace)::EraseDeadLinalgOp::matchAndRewrite(mlir::linalg::LinalgOp, mlir::PatternRewriter&) const LinalgOps.cpp:0:0
#9 0x000055645414c7a8 mlir::PatternApplicator::matchAndRewrite(mlir::Operation*, mlir::PatternRewriter&, llvm::function_ref<bool (mlir::Pattern const&)>, llvm::function_ref<void (mlir::Pattern const&)>, llvm::function_ref<mlir::LogicalResult (mlir::Pattern const&)>) (/data/bin/llvm-project/build/bin/mlir-opt+0x6f537a8)
#10 0x00005564514db45c (anonymous namespace)::GreedyPatternRewriteDriver::processWorklist() GreedyPatternRewriteDriver.cpp:0:0
#11 0x00005564514df8cb mlir::applyPatternsAndFoldGreedily(mlir::Region&, mlir::FrozenRewritePatternSet const&, mlir::GreedyRewriteConfig, bool*) (/data/bin/llvm-project/build/bin/mlir-opt+0x42e68cb)
#12 0x0000556451444b9a (anonymous namespace)::Canonicalizer::runOnOperation() Canonicalizer.cpp:0:0
#13 0x0000556451425aee mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) (/data/bin/llvm-project/build/bin/mlir-opt+0x422caee)
#14 0x0000556451425fca mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) (/data/bin/llvm-project/build/bin/mlir-opt+0x422cfca)
#15 0x00005564514267f4 mlir::PassManager::run(mlir::Operation*) (/data/bin/llvm-project/build/bin/mlir-opt+0x422d7f4)
#16 0x0000556451417563 performActions(llvm::raw_ostream&, std::shared_ptr<llvm::SourceMgr> const&, mlir::MLIRContext*, mlir::MlirOptMainConfig const&) MlirOptMain.cpp:0:0
#17 0x0000556451418a34 processBuffer(llvm::raw_ostream&, std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, mlir::MlirOptMainConfig const&, mlir::DialectRegistry&, llvm::ThreadPool*) MlirOptMain.cpp:0:0
#18 0x0000556451418be4 mlir::LogicalResult llvm::function_ref<mlir::LogicalResult (std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>::callback_fn<mlir::MlirOptMain(llvm::raw_ostream&, std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, mlir::DialectRegistry&, mlir::MlirOptMainConfig const&)::'lambda'(std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>(long, std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&) MlirOptMain.cpp:0:0
#19 0x0000556451517ed4 mlir::splitAndProcessBuffer(std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, llvm::function_ref<mlir::LogicalResult (std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>, llvm::raw_ostream&, bool, bool) (/data/bin/llvm-project/build/bin/mlir-opt+0x431eed4)
#20 0x0000556451411447 mlir::MlirOptMain(llvm::raw_ostream&, std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, mlir::DialectRegistry&, mlir::MlirOptMainConfig const&) (/data/bin/llvm-project/build/bin/mlir-opt+0x4218447)
#21 0x0000556451418d31 mlir::MlirOptMain(int, char**, llvm::StringRef, llvm::StringRef, mlir::DialectRegistry&) (/data/bin/llvm-project/build/bin/mlir-opt+0x421fd31)
#22 0x0000556451419196 mlir::MlirOptMain(int, char**, llvm::StringRef, mlir::DialectRegistry&) (/data/bin/llvm-project/build/bin/mlir-opt+0x4220196)
#23 0x000055644e74997b main (/data/bin/llvm-project/build/bin/mlir-opt+0x155097b)
#24 0x00007f8324702083 __libc_start_main (/lib/x86_64-linux-gnu/libc.so.6+0x24083)
#25 0x000055644e7e258e _start (/data/bin/llvm-project/build/bin/mlir-opt+0x15e958e)
Aborted (core dumped)
```
</pre>
<img width="1px" height="1px" alt="" src="http://email.email.llvm.org/o/eJzcWl1v2zjW_jXKDRGDX_q6yIUTx-9boEGDpou9NCiJsrkjkxqSSp359QuKki3Zcu02mdnZLWYcRzx8eD6ecw5JhRkj1pLzuyC8D8LFDWvsRuk7JpV826rGPD283GSqeLtbCwteuTZCyYDMQZgVESUc0TDKCszyPCQsh1kZprTASZjxJGWUljyAiwDO_ad5M5Zv3ex_ZI20DcBwBuksAp-_vYAAJ0uVswoslTEswOlwpua1VkWT8wJ8F3bjIIII-v-2ldC3qrbg9jZ3aoucVeIPDtjMjezFhnDdEOl-PZbBZMtqEJAFYGUpJF9tWR2QhwAnBQzwAyhQ-4kDnILbgDyCqZGAPA7h8AW8KaRjjORndRphlI3MZ-4DBBS6nzjASYBDptfQOXTLt5qXDpMsdyXBbiJ-AF4COQnLpVE6IA_RTnTjKQjie48PnGiOVqgzVQu7meVKGsukBQg4BCELvhuKT8riadloSjaalk2nZNNp2TMKn9EChZPS4Rn78Gp6Aj4Dj8mkNJmWJmhKmpw620WxqlS-wl4bH-xZ-8zTII-6aLJKrOWWS9sKRtRjRTSIF-CEJ1HPlP0y3vNZU5Zciz-YFUrOrFp57hzp8WMwJ4w851tTZmajm4NXO3LmKBzIYziQL8Sr8SC9LEFD7xm7iibdjWY4pnFK0uQxwPetDnPgdBsRPUquJ3pIW1mrDJtp7irZyjTbzl_xPdsJ0wpAP5vg3tsBTvZpN_JRn-f7UTTlv9AnTSUkq9azNZdci9yt2Coo5NrVEb-0awC-VHlv-a_hwv0mLNfMKr2ybzUfiOOaaVZVvApwN2v0JFw4M4Q0nmKh59KUxjgFqrFXyQ0LTviYZdBPErIPko-1auz-Qbov9QB4WmEfjy2zm1ml1hi0CMdxBr3j3gSvisPEMRnixTWR8LSP0XT6peNsQHSH4x09Sa4uu_rpVm1FvtLb78C38QOr-8rdLdoGK8Swz4N0nzwr5MLUU61z3zk9es6NUyGezFHUBwLDoWw6kM25qArx2uU0OegUJYMpCTmEyvyu7d4PJylp7CqZzGe4i5cJdP8mpnkfJdGZuhinP1sXEd25TKWnHEiT64pjEl2L2MnH55RPfqWon-p9ZVFv9bgE1okmZ1R2JE0vwBxQ0nPdDH9M1FzKQ3il9adJfCZqCKKfL8uHqpxMfn1fqb5YvNO-iabpqLgkyVGxPrIaP4BRAzs8ntxwDvsA6vL1PPbV3UDIFYJw4hm6tmscd4J9tbnUDM7yCr2LBH96uC-6fhgo9FGBur5ts8yU-_7wIW17MlKa20bL7hgWL6ZPjINPq1nOzx0t-7Oqb7fLglkW4GUmZICXVfW6va21-hfPbYCX7QkVLyuRBXj56WuAl8_MWq7lE7P5ZpbXdUDmBMYO6lVo27AKvCpRgP5oS-Zf-Xft-HHPDPdPuGaGf6kDnBykvtSOQe5Yj-fe52BuDNfukTtlq9q5qTF8xbe1feu3KzgKcORIxHc1zy13fo5VHeAYWAU27JUDqUBjuGn5FoOSiYoXM--I58-P85dHYJpsKyxgIGvWQPNaadvOtrY2Tju8DPByLeymyWa52nZeOnWWMKZxCy0BkwUQMq-aggO74SDXzGxAxvLf2sB0y79Ylv8GimZb7yMFZ6D996zVWrMtYHrduL5hrohV1oiq2A9euJDoCwCBAO7cniQMI0p5gjDGJWjta-Ni3oz_8qyFtK3G31pu4eQgpNn3lTJWc7ZtI_IAhLQ-PskvKR3ge7hDEUoxLveXME5bNNYWljih4EWsJav-n8mi4jrASbe4f2w6ksL2_z0Q7oDiMiGY5iSiGILVSnNjleardoOX7Jm_S6JVRG8rIZvd7Vo2fqC2G81ZMTNqBr3GlLYbh8MyZLRMjBGEGdBMGH4Ffu6QoxaZEgizETIdI0OYhClgmbpK8wEyxkmYjpDDY-R4H8mrMWM8xozGmAiVRfRzmISURTTCjAdcCFFEaRil760772MspTQLo7HlyZCxJUScwNitsr_bBJJtuanbnEq9Uo9O0QVnxee2g3yp_eOtq7lzWXSWjezwvcZ_389y25u9RFe4e7e0iZqC9nQC-hlnkiUdepoimscsOUWe13UlcrcNuKzu2O2X1HwYFKSykbmbuPK7tkypCoygOwBvmbey2-qdBWk71ntBDpM_q7Wrtl-5aSp7He47iReVIYlZcrivxgTBUXrQIqNhfol4_6c5L97GIVho8co79Wutcm7MP5X-rRLOgLYLn591SienGTrSrEzybMAAVtdVj2bmsliqqmiXENXbyJlf-bplUDRm0FKrP3ivR4fzwu3A50Npr3wn_aBkKdZOwPHqQ0oC5lGSZ6PI4LH9lGYpuxSZh0EP7zTXjfwiB4nUxmIkN-1-Ml4eh4zzgUMKbpmo-jT9pr7Uz8yYecHqfWbrRh6x2piTRD6f4nPJqjcjzBOTbO1SvHf3A2hk-yKo-JANBMU4Z5yPfE-PjS9z9tPGP4uaV0IelzQnurcp-nBvjKukMZ-ksbrdHSo9UUaHAn5lP9Dp_sw0l_aTLFWfGB9BdpyXORs5PDxyeBSX9EjP3vJJbn1sg8a4iEs6UjAaK4jiMCKg5rpUejtvC7y5sNk1tug2yxumebGqrTvIHWa8qEbn_Gmt3UFvugo9ff709UFJy3f2JJRPldBfavvEhPT1adg9wGB0Ot3jI_sSRijoCvl9e5t0rXmNFL83_MS8J75V-q2HGsgXvGRNZVcFr7jl5-eQx_4u5iqbh3ILwSqeW9cJjNVvJ7uFb-0O_flQzC-6Kzl2V8aHfB339l_ZDPx17jwf1HbT0Y7krKrcuXRVypHaAz_9DekxHfYrU8aLBDiu2DYrWIDjv1NUcFIpuf5rHfsDlS4nzOhwgEIU82KYMKauhJ3L4vmo4vwnrPsvTNIfShx2Cv7ne7sjQZwXo-6Ij04RCFEaTyfa_1qZeO9OAyWUxiNfouPWUhB01pfdli_fML-5m4-p8GK1kOuvvPzB4x874v0GlgVBIwOPDjYoRWn0IQb-yZZgiNJoZAkZ3TPGNE3jDGyZkO-80gxDmMaj0yA-vsjDMCFgtapElq-MZdquButeewFHYUJGq4RjgzgOEw48_ntN4mmYHA5Z80xpfw-f5Erz9nqbFwdd-lcRN8UdKVKSsht-h2KIEKRxEt9s7ookTnHBWRElnCRhRklGIggjxPKoxHl8I-4wxAQhHKMYRjiapSkjMMZJlJMcoYgEFPItE9XMWTFTen3T3szfxSSk8U3FMl6ZO_9-yr_fwEG4uNF3rdFZszYBhZUw1hwArLBV-9eJ7YRwcXyr3l7wd38XCNj-xUXJRNVofu0LiptGV3e__tqhte_fAQAA__-AJRdB">