<table border="1" cellspacing="0" cellpadding="8">
<tr>
<th>Issue</th>
<td>
<a href=https://github.com/llvm/llvm-project/issues/118452>118452</a>
</td>
</tr>
<tr>
<th>Summary</th>
<td>
[mlir] -tosa-optional-decompositions crashes
</td>
</tr>
<tr>
<th>Labels</th>
<td>
mlir
</td>
</tr>
<tr>
<th>Assignees</th>
<td>
</td>
</tr>
<tr>
<th>Reporter</th>
<td>
wwy6191
</td>
</tr>
</table>
<pre>
git version: d09707070c7460d0887eae8f7022e816510d5eb1
system: `Ubuntu 18.04.6 LTS`
reproduce with: `mlir-opt -tosa-optional-decompositions a.mlir`
a.mlir:
```
func.func @test_transpose_conv2D_pad_left(%arg0: tensor<1x32x 32x 16x f32>, %arg1: tensor<16x2x16x16xf32>, %arg2: tensor<16xf32>) -> tensor<1x32x 32x 16x f32> {
%0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {out_pad = array<i64: 0, 0, 8193, 0>, out_shape = array<i64: 1, 32, 8193, 16>, stride = array<i64: 1, 2>} :
(tensor<1x32x 32x 16x f32>, tensor<16x2x16x16xf32>, tensor<16xf32>) -> tensor<1x32x 32x 16x f32>
return %0 : tensor<1x32x 32x 16x f32>
}
```
stack trace:
```
<unknown>:0: error: invalid tensor dimension size
mlir-opt: /data/szy/MLIR/llvm-release/llvm-project/mlir/include/mlir/IR/StorageUniquerSupport.h:180: static ConcreteT mlir::detail::StorageUserBase<mlir::RankedTensorType, mlir::TensorType, mlir::detail::RankedTensorTypeStorage, mlir::detail::TypeUniquer, mlir::ShapedType::Trait, mlir::ValueSemantics>::get(MLIRContext *, Args &&...) [ConcreteT = mlir::RankedTensorType, BaseT = mlir::TensorType, StorageT = mlir::detail::RankedTensorTypeStorage, UniquerT = mlir::detail::TypeUniquer, Traits = <mlir::ShapedType::Trait, mlir::ValueSemantics>, Args = <llvm::ArrayRef<long> &, mlir::Type &, mlir::Attribute &>]: Assertion `succeeded( ConcreteT::verifyInvariants(getDefaultDiagnosticEmitFn(ctx), args...))' 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/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt -tosa-optional-decompositions /data/szy/MLIR/seed/seed4/tmp.xkcd0pMA92.mlir
#0 0x000055d5911b6f88 llvm::sys::PrintStackTrace(llvm::raw_ostream&, int) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x1185f88)
#1 0x000055d5911b4a9e llvm::sys::RunSignalHandlers() (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x1183a9e)
#2 0x000055d5911b791d SignalHandler(int) Signals.cpp:0:0
#3 0x00007f93bf621420 __restore_rt (/lib/x86_64-linux-gnu/libpthread.so.0+0x14420)
#4 0x00007f93bec5e00b raise /build/glibc-LcI20x/glibc-2.31/signal/../sysdeps/unix/sysv/linux/raise.c:51:1
#5 0x00007f93bec3d859 abort /build/glibc-LcI20x/glibc-2.31/stdlib/abort.c:81:7
#6 0x00007f93bec3d729 get_sysdep_segment_value /build/glibc-LcI20x/glibc-2.31/intl/loadmsgcat.c:509:8
#7 0x00007f93bec3d729 _nl_load_domain /build/glibc-LcI20x/glibc-2.31/intl/loadmsgcat.c:970:34
#8 0x00007f93bec4efd6 (/lib/x86_64-linux-gnu/libc.so.6+0x33fd6)
#9 0x000055d59471e703 (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x46ed703)
#10 0x000055d59471e628 mlir::RankedTensorType::get(llvm::ArrayRef<long>, mlir::Type, mlir::Attribute) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x46ed628)
#11 0x000055d5938425d5 mlir::tosa::SliceOp mlir::tosa::CreateOpAndInferShape<mlir::tosa::SliceOp, mlir::Value&, mlir::detail::DenseArrayAttrImpl<long>&, mlir::detail::DenseArrayAttrImpl<long>&>(mlir::ImplicitLocOpBuilder&, mlir::Type, mlir::Value&, mlir::detail::DenseArrayAttrImpl<long>&, mlir::detail::DenseArrayAttrImpl<long>&) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x38115d5)
#12 0x000055d59383dbe6 (anonymous namespace)::TransposeConvStridedConverter::matchAndRewrite(mlir::tosa::TransposeConv2DOp, mlir::PatternRewriter&) const TosaDecomposeTransposeConv.cpp:0:0
#13 0x000055d597110a21 void llvm::function_ref<void ()>::callback_fn<mlir::PatternApplicator::matchAndRewrite(mlir::Operation*, mlir::PatternRewriter&, llvm::function_ref<bool (mlir::Pattern const&)>, llvm::function_ref<void (mlir::Pattern const&)>, llvm::function_ref<llvm::LogicalResult (mlir::Pattern const&)>)::$_0>(long) PatternApplicator.cpp:0:0
#14 0x000055d59710d6eb mlir::PatternApplicator::matchAndRewrite(mlir::Operation*, mlir::PatternRewriter&, llvm::function_ref<bool (mlir::Pattern const&)>, llvm::function_ref<void (mlir::Pattern const&)>, llvm::function_ref<llvm::LogicalResult (mlir::Pattern const&)>) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x70dc6eb)
#15 0x000055d59466c11f (anonymous namespace)::GreedyPatternRewriteDriver::processWorklist() GreedyPatternRewriteDriver.cpp:0:0
#16 0x000055d594668aaf mlir::applyPatternsAndFoldGreedily(mlir::Region&, mlir::FrozenRewritePatternSet const&, mlir::GreedyRewriteConfig, bool*) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x4637aaf)
#17 0x000055d59382579b (anonymous namespace)::TosaOptionalDecompositions::runOnOperation() TosaOptionalDecompositions.cpp:0:0
#18 0x000055d5945f1936 mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x45c0936)
#19 0x000055d5945f2260 mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x45c1260)
#20 0x000055d5945f760e auto void mlir::parallelForEach<__gnu_cxx::__normal_iterator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo*, std::vector<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo, std::allocator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo>>>, mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::$_0>(mlir::MLIRContext*, __gnu_cxx::__normal_iterator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo*, std::vector<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo, std::allocator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo>>>, __gnu_cxx::__normal_iterator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo*, std::vector<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo, std::allocator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo>>>, mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::$_0&&)::'lambda'(__gnu_cxx::__normal_iterator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo*, std::vector<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo, std::allocator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo>>>&&)::operator()<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo&>(__gnu_cxx::__normal_iterator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo*, std::vector<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo, std::allocator<mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool)::OpPMInfo>>>&&) const Pass.cpp:0:0
#21 0x000055d5945f38bb mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x45c28bb)
#22 0x000055d5945f1a8f mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x45c0a8f)
#23 0x000055d5945f2260 mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x45c1260)
#24 0x000055d5945f4832 mlir::PassManager::run(mlir::Operation*) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x45c3832)
#25 0x000055d5945ed0da performActions(llvm::raw_ostream&, std::shared_ptr<llvm::SourceMgr> const&, mlir::MLIRContext*, mlir::MlirOptMainConfig const&) MlirOptMain.cpp:0:0
#26 0x000055d5945ecd2d llvm::LogicalResult llvm::function_ref<llvm::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&)::$_0>(long, std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&) MlirOptMain.cpp:0:0
#27 0x000055d594698fa5 mlir::splitAndProcessBuffer(std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, llvm::function_ref<llvm::LogicalResult (std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>, llvm::raw_ostream&, llvm::StringRef, llvm::StringRef) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x4667fa5)
#28 0x000055d5945e6d15 mlir::MlirOptMain(llvm::raw_ostream&, std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, mlir::DialectRegistry&, mlir::MlirOptMainConfig const&) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x45b5d15)
#29 0x000055d5945e6fbf mlir::MlirOptMain(int, char**, llvm::StringRef, llvm::StringRef, mlir::DialectRegistry&) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x45b5fbf)
#30 0x000055d5945e72ee mlir::MlirOptMain(int, char**, llvm::StringRef, mlir::DialectRegistry&) (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x45b62ee)
#31 0x000055d591197a77 main (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x1166a77)
#32 0x00007f93bec3f083 __libc_start_main /build/glibc-LcI20x/glibc-2.31/csu/../csu/libc-start.c:342:3
#33 0x000055d5911975ee _start (/data/szy/MLIR/llvm-release/llvm-project/build/bin/mlir-opt+0x11665ee)
```
</pre>
<img width="1px" height="1px" alt="" src="http://email.email.llvm.org/o/eJzsG1tT2zz215gXDxlZ8vWBB5eQ3c60AwP9dh89snUctHUkryTT5Pv1O5JNYhsC9JJ299u2IcT20bnfdCKo1nwtAC686J0XLc9oZ-6luvjyZRcHWXBWSra7WHPjP4DSXAqP5D5DWYLs_yoJY8RQmiZAIa0ThDGkQRwFiEVQBh7KPZTrnTawseu8GP1RdsJ0fpAuULiI_Q-f7rwY9XAKWiVZV4H_hZv7AX7TcHUuW-P750Zqaj9yKWhzzqCSm1Zqbq-1TxcWco_LQ_lwh-S-b2_EqH_Zi7oT1cK--V6IDGhTGEWFbqWGopLiAS-LlrKigdp4OPVwRNUaWUwGhJbKI5fBluCtb3-CeOvXBHvkysOXfg8bTGHjLd4GsX3NAfEc8BEg8889cvUyPd9L3nnIiocj5Htk6XsYWyUtZtIwD-ORHCM2R4zgzOKTnbGiO2xUKbrzyCWPQ8umW-je0iAj_UUvi12k72kLzy1zRAgerwviYaE2irPjq5wqkqXvkdzJOf7n4fRVY7xsgW9Vu2VFgemUeFT8a36Bci9ZDn45dkNtaPXZN4pW0Is4B_DIZSc-C_lFWDQkdz4ISknn1lw80IazgbjP-AaEjVBf8z_BQ_lj6LhIwitGDfXwSv-58_Dq44f3tx5eNc3D5lxBA1TD42Wr5L-gMh5eufjBKy6qpmNwuOGW3hmp6Br-EPzfHai7rm2lMgsbtkHq-NSGGl75l1JUCgx88odw9EjOwFDe9J8f8WhQ7ywX5PIAd0vFZ2CfnHyfdi1Ysx2eHrs_xj7HMFA7vsACDTJNge6sgzNHrQdUlJspyD9o08EdbKgwvNK9yTySr8FmEavxSykMbI3v4dyuzNVa-x6OPRwvFgsXgdG7g75sWLysC6uwOdwUYpB3DvRGFQ2KeGn1TF9OK7pPRmNLfpP29irqsVnv7EFzmyxuobY3pVi7XGjVOPGOnc1H87u5MYqXnekfkSsvWlpfzbUGZQuJLTm6qyoABszD6cF9-_UPoHi9ey8eqOJUGO3hdA1mCTXtGrPkdC2kNry62nCzEh5OK7P1cGZ5oGqteyu7V-LXlDfAFh7Kbz5c5XdXvu7KDTc-9ctu7Suw8eQb6d8b02pLHa88vFpzc9-Vi0puhnh9GrZc6w60h1c-Fcwfotc39-BXiup7v6TVZ5d0LO07l4NYt2n7FIQWfX69UXKt6May3W3ASvqtWaTseMPsby6GFOLq-cvl_AglDdYq7lfo4ZXZtIvt54qh9mOe4b7eI8smQT7aIoRQFLEoC4IyrtPUPziQ3un-w43iwjgdfHJpGKcHIEW_FFIbBXQz-BEXxkWpraU_TBMefoe2QZBGdZpa1-gFCGYChDSD5wS47cQdXwva_J0K1oDSjrlT8UhoBgce8YzHJAuYP-HGw-mgs_62XlRtOxQyNGAhA5akzkhZxzgIMfKLQoE2UkGhzCBLw0sPr7ZpXMThecNFtz1fi65_0Jp7BZQttFygntcwxOjAaTimAVUECJW-olzbPLCXed3wsjr_UL3HaLu_xAsSWBU6_j28siG80jvNoLUx1gm-7W88OFZEZy8d6kXlkTyyvWAwsBFN2SAsjTKfltLJ-DY2DOv14FY5CqmlkAwU4jmFBGf-GkzRc1xoWNtoLh5ssn0rUS6MlbyRlG30uqI93QhllvpAOHmOcCGawq4qmNxQLr6PXpZYryHhQDCdEgyhZvEbPKWyPhI7HyGkZvHBR7KxN4dJAAkipwijMAaWINITtpGO5oRjnL5U-EdNxUsl8Wk5PFIKT5QurJwxTg9yTlIaSUMcsWjEj60HQ7PQ8Aqu22efXSqgBq7bXLD3ogblGotJq_EEzzNtxpO-YNzSLEFocPq0Knq_aZuxUr9joX1PD0stAK-4-SCr6_adVaRNmM-0Mf81ApzGUUgaBBGLDo6Cp45CWAkutKmQYreRnfYF3YBuXcHO9g1lv-W9lOLhzu0rmf0IysAg6Yaa6j4X7Ba-KG7dPn3OaSaI8HLuPjfUGFBiwKEGrVRSaON_kpouhz4GJnhmZc8KScZCJkGAKA78B8nZqMrXnahsP1QoF9juaV_f95uLijaNbeiKWkyiYOAzb62PUSPfoIPrFhS15IbtyctCXx7ns5Sy8SeoBwS9nnqdDRnqVWG_C8nhwQe55hVtbkF3jXkb3sGzPBwW_aQjdaGAM_-Jcp-xbzi1L2IxlE9V-ts-32GfUySjBLEqhvKQjKJJdY7jKgjq15LR3xQA202tslT84TETtUpWoPU_pfrccG2Glv34qmfcK56xlVJajzyCtm3ziErngq1kwxx-3uwmyr2FtfOoWVVYKfknPDIx4LkDM7LBGLrnfIC-lKLmawtg_cz56on6C5JQWh8slUzLBo6SrHy1bEhNr4c96HKyBR32gJ24FqPAc4Y6vugZQ6UTQ0V1kJH4SPm9bj_J6_aGap0z2u5zgurELB60fpICjieHXNBmp7n-SAVd91Oa3jCXfifc6J-dcGMbRhXKSHywUjbTB8Yx-mp93PAWGi7m-dGC7sWMf7iCpilX6_dCG-WmI1I9k5PHAD3l_sHA-w1VIMx7UcvHqDpZpERVgGO0twFGMxskMQKfdkb2DchBiJYq2jTQrKS6otW9Ry6LYi26otpue4CiEFJtaFPYutOXscuvNeYowHK9E5XrO3Ha2yDb2_ajVdWgZm3Y4zyu-hlERxRp08jqZ0hqO7yrJ_u4H0do1Ncc0I-m1IOqfxv8Vxj8t9b_WmHmvuQZ3UsauikZ9XDi4fS3sX--sSf2kO2g6GFvfWLJh0nQb7P_MrMPAxuL-GnLjoNZe0TSsvzBueFEbR5Oy8PWFeP51oOm9f_Z1oOmhw0iJr-3Hr986xHObBCmBM9Yf1TGsx441eWpeCYpwQeepyOgCBhi1G9B1VJt8qqfFrz8xfE-5el7qoAVrVGT6ded7FQFH9fKI1dHZixPO_PRs4ar69Z8pFz005fxrMwfPX0m2cUz4SqGxyPo6VzuWwZ5e9k7d0zkiewfYSPV7l1X130A7OFZf6qiYNCAgeNr9u3bcQu8Pi8fKemttjy5PAfulpw2UJlbWHNt1O6pc7zkAE-2e_0Y-2dK8oJlXnHPZDrnzNKajr801G3DTS7YTT9RfeT1lzjd_2BIvAgxfnZnFBfrW6iP3j7RjDdOanr4ahDPpqkQsyB6Pg7-alF8mkpXRiwYqTebq7cu66PqHRqT6p72LUj-tS7zmm5OJnNdHrpCMhuGQoIBfojMv0a4GAMchJsdI8sSmiT-cBbnBAfE4pgmyYE6nh0KqlFK_KJoeFkV2lBliq85FlTp7vH8Vf_RPXR43AEhEmL7PtAmc8kjAL-neirZo73m94e4z9gFYRnJ6BlcBAkhOEgygs7uLwjNqhrjLI3SGpc4DKu6iuo6plGWBHEanfELjHAYYERQhiOCFmFV1mVWkYDWjGRp6IUINpQ3C8vkQqr1mTv4eREEaRjhs4aW0Gj3Rx0Y9we3sRctz9SFE6rs1toLUcO10QcMhpvG_SGIWxAtXzml6c6Tgj7rVHPx7cdUB4YfLvB_AgAA___TSLfY">