<table border="1" cellspacing="0" cellpadding="8">
<tr>
<th>Issue</th>
<td>
<a href=https://github.com/llvm/llvm-project/issues/59929>59929</a>
</td>
</tr>
<tr>
<th>Summary</th>
<td>
[MLIR] Crash when using -lower-affine
</td>
</tr>
<tr>
<th>Labels</th>
<td>
new issue
</td>
</tr>
<tr>
<th>Assignees</th>
<td>
</td>
</tr>
<tr>
<th>Reporter</th>
<td>
BealZephyr
</td>
</tr>
</table>
<pre>
I am trying to lower mlir, but the compiler crashes.
I think this bug is caused by specific optimization sequences ```-affine-loop-coalescing "-affine-data-copy-generate=generate-dma=false fast-mem-space=0 skip-non-unit-stride-loops" -affine-parallelize```.
The execution crashes with following backtrace:
```
mlir-opt: /home/data/mlir/lib/Conversion/AffineToStandard/AffineToStandard.cpp:49: mlir::Value buildMinMaxReductionSeq(mlir::Location, mlir::arith::CmpIPredicate, mlir::ValueRange, mlir::OpBuilder&): Assertion `!values.empty() && "empty min/max chain"' failed.
PLEASE submit a bug report to https://github.com/llvm/llvm-project/issues/ and include the crash backtrace.
Stack dump:
0. Program arguments: ./mlir-opt /home/ty/affine_test.mlir -lower-affine
#0 0x00005627c14b26ea llvm::sys::PrintStackTrace(llvm::raw_ostream&, int) (./mlir-opt+0x1a76ea)
#1 0x00005627c14afcfc SignalHandler(int) Signals.cpp:0:0
#2 0x00007f79a88a7980 __restore_rt (/lib/x86_64-linux-gnu/libpthread.so.0+0x12980)
#3 0x00007f79a799fe87 raise /build/glibc-CVJwZb/glibc-2.27/signal/../sysdeps/unix/sysv/linux/raise.c:51:0
#4 0x00007f79a79a17f1 abort /build/glibc-CVJwZb/glibc-2.27/stdlib/abort.c:81:0
#5 0x00007f79a79913fa __assert_fail_base /build/glibc-CVJwZb/glibc-2.27/assert/assert.c:89:0
#6 0x00007f79a7991472 (/lib/x86_64-linux-gnu/libc.so.6+0x30472)
#7 0x00005627c244f0e0 lowerAffineMapMin(mlir::OpBuilder&, mlir::Location, mlir::AffineMap, mlir::ValueRange) AffineToStandard.cpp:0:0
#8 0x00005627c244f38d lowerAffineMapMax(mlir::OpBuilder&, mlir::Location, mlir::AffineMap, mlir::ValueRange) AffineToStandard.cpp:0:0
#9 0x00005627c244fcf8 (anonymous namespace)::AffineParallelLowering::matchAndRewrite(mlir::AffineParallelOp, mlir::PatternRewriter&) const AffineToStandard.cpp:0:0
#10 0x00005627c244d516 mlir::detail::OpOrInterfaceRewritePatternBase<mlir::AffineParallelOp>::matchAndRewrite(mlir::Operation*, mlir::PatternRewriter&) const (./mlir-opt+0x1142516)
#11 0x00005627c2efb2cd 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&)>) (./mlir-opt+0x1bf02cd)
#12 0x00005627c2bb3d17 (anonymous namespace)::OperationLegalizer::legalize(mlir::Operation*, mlir::ConversionPatternRewriter&) DialectConversion.cpp:0:0
#13 0x00005627c2bb470f (anonymous namespace)::OperationConverter::convertOperations(llvm::ArrayRef<mlir::Operation*>, llvm::function_ref<void (mlir::Diagnostic&)>) DialectConversion.cpp:0:0
#14 0x00005627c2bb8270 mlir::applyPartialConversion(mlir::Operation*, mlir::ConversionTarget&, mlir::FrozenRewritePatternSet const&, llvm::DenseSet<mlir::Operation*, llvm::DenseMapInfo<mlir::Operation*, void>>*) (./mlir-opt+0x18ad270)
#15 0x00005627c2457f7d (anonymous namespace)::LowerAffinePass::runOnOperation() AffineToStandard.cpp:0:0
#16 0x00005627c2b3e319 mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) (./mlir-opt+0x1833319)
#17 0x00005627c2b3f0a9 mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) (.constprop.489) Pass.cpp:0:0
#18 0x00005627c2b3f7dd mlir::PassManager::run(mlir::Operation*) (./mlir-opt+0x18347dd)
#19 0x00005627c2b3158b performActions(llvm::raw_ostream&, bool, bool, std::shared_ptr<llvm::SourceMgr> const&, mlir::MLIRContext*, llvm::function_ref<mlir::LogicalResult (mlir::PassManager&)>, bool, bool) (.constprop.273) MlirOptMain.cpp:0:0
#20 0x00005627c2b31c88 processBuffer(llvm::raw_ostream&, std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, bool, bool, bool, bool, bool, bool, llvm::function_ref<mlir::LogicalResult (mlir::PassManager&)>, mlir::DialectRegistry&, llvm::ThreadPool*) MlirOptMain.cpp:0:0
#21 0x00005627c2b3208f 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>>, llvm::function_ref<mlir::LogicalResult (mlir::PassManager&)>, mlir::DialectRegistry&, bool, bool, bool, bool, bool, bool, bool)::'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
#22 0x00005627c2bf33b0 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) (./mlir-opt+0x18e83b0)
#23 0x00005627c2b30446 mlir::MlirOptMain(llvm::raw_ostream&, std::unique_ptr<llvm::MemoryBuffer, std::default_delete<llvm::MemoryBuffer>>, mlir::PassPipelineCLParser const&, mlir::DialectRegistry&, bool, bool, bool, bool, bool, bool, bool, bool) (./mlir-opt+0x1825446)
#24 0x00005627c2b324cb mlir::MlirOptMain(int, char**, llvm::StringRef, mlir::DialectRegistry&, bool) (./mlir-opt+0x18274cb)
#25 0x00005627c147f360 main (./mlir-opt+0x174360)
#26 0x00007f79a7982c87 __libc_start_main /build/glibc-CVJwZb/glibc-2.27/csu/../csu/libc-start.c:344:0
#27 0x00005627c1491dea _start (./mlir-opt+0x186dea)
Aborted (core dumped)
```
[Following IR](https://github.com/llvm/llvm-project/files/10392059/test.mlir.txt) is a function in [release/15.x/mlir/test/Dialect/Tosa/ops.mlir](https://github.com/llvm/llvm-project/blob/release/15.x/mlir/test/Dialect/Tosa/ops.mlir), you can use it to reproduce this bug:
```
func.func @test_bitwise_xor(%arg0: tensor<13x21x1xi32>, %arg1: tensor<13x21x3xi32>) -> tensor<13x21x3xi32> {
%0 = "tosa.bitwise_xor"(%arg0, %arg1) : (tensor<13x21x1xi32>, tensor<13x21x3xi32>) -> tensor<13x21x3xi32>
return %0 : tensor<13x21x3xi32>
}
```
Steps to reproduce :
```
mlir-opt test.mlir -pass-pipeline="builtin.module(func.func(tosa-to-linalg))" -o output.mlir
mlir-opt output.mlir -func-bufferize -linalg-bufferize -convert-linalg-to-affine-loops -affine-loop-coalescing -affine-data-copy-generate="generate-dma=false fast-mem-space=0 skip-non-unit-stride-loops" -affine-parallelize -lower-affine
```
</pre>
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